Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained promine...Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis efficiency.Recently,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault diagnosis.However,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative model.This complexity results in high computational costs and limited industrial applicability.To tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault diagnosis.First,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration signals.Then,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global perspective.Finally,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and Transformer.This study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.展开更多
To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precis...To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precisely pinpointing misfire faults.In the experiment,we established a total of 11 distinct states,encompassing the engine’s normal state,single-cylinder misfire faults,and dual-cylinder misfire faults for different cylinders.Data collection was facilitated by a highly sensitive acceleration signal collector with a high sampling rate of 20,840Hz.The collected data were methodically divided into training and testing sets based on different experimental groups to ensure generalization and prevent overlap between the two sets.The results revealed that,with a vibration acceleration sequence of 1000 time steps(approximately 50 ms)as input,the SENET model achieved a misfire fault detection accuracy of 99.8%.For comparison,we also trained and tested several commonly used models,including Long Short-Term Memory(LSTM),Transformer,and Multi-Scale Residual Networks(MSRESNET),yielding accuracy rates of 84%,79%,and 95%,respectively.This underscores the superior accuracy of the SENET model in detecting engine misfire faults compared to other models.Furthermore,the F1 scores for each type of recognition in the SENET model surpassed 0.98,outperforming the baseline models.Our analysis indicated that the misclassified samples in the LSTM and Transformer models’predictions were primarily due to intra-class misidentifications between single-cylinder and dual-cylinder misfire scenarios.To delve deeper,we conducted a visual analysis of the features extracted by the LSTM and SENET models using T-distributed Stochastic Neighbor Embedding(T-SNE)technology.The findings revealed that,in the LSTMmodel,data points of the same type tended to cluster together with significant overlap.Conversely,in the SENET model,data points of various types were more widely and evenly dispersed,demonstrating its effectiveness in distinguishing between different fault types.展开更多
Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and ...Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.展开更多
The multi-terminal direct current(DC)grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy.Both the DC circuit breaker(DCCB)and the current flow ...The multi-terminal direct current(DC)grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy.Both the DC circuit breaker(DCCB)and the current flow controller(CFC)are demanded to ensure the multiterminal DC grid to operates reliably and flexibly.However,since the CFC and the DCCB are all based on fully controlled semiconductor switches(e.g.,insulated gate bipolar transistor,integrated gate commutated thyristor,etc.),their separation configuration in the multiterminal DC grid will lead to unaffordable implementation costs and conduction power losses.To solve these problems,integrated equipment with both current flow control and fault isolation abilities is proposed,which shares the expensive and duplicated components of CFCs and DCCBs among adjacent lines.In addition,the complicated coordination control of CFCs and DCCBs can be avoided by adopting the integrated equipment in themultiterminal DC grid.In order to examine the current flow control and fault isolation abilities of the integrated equipment,the simulation model of a specific meshed four-terminal DC grid is constructed in the PSCAD/EMTDC software.Finally,the comparison between the integrated equipment and the separate solution is presented a specific result or conclusion needs to be added to the abstract.展开更多
Large basins are currently the global focus for geothermal development,with their hydrothermal system being controlled by a variety of factors,such as basement relief and fracture development.Donglihu is located at th...Large basins are currently the global focus for geothermal development,with their hydrothermal system being controlled by a variety of factors,such as basement relief and fracture development.Donglihu is located at the north of the Cangxian uplift in the North China Basin,the concentrated geothermal resource development zone in North China.This study systematically collects temperature logging data and long-term dynamic monitoring of water level and water quality as well as group well tracer test data carried out in this area in recent years,on the basis of which the hydrothermal controlling role of the deep hidden faults is systematically analyzed.The results show that the Cangdong fault communicates with different geothermal reservoirs in the shallow part and plays a specific role in the water-heat channel of the local area.As a result,the high-value area of the geothermal temperature gradient in the sedimentary layer of the Donglihu area is distributed around the Cangdong fault.The geothermal reservoir temperature of the Minghuazhen Formation within the influence of the fault is also significantly higher than the regional average,the hydraulic head of different geothermal reservoirs showing a consistent and synergistic trend.However,the water quality has been stable for many years without any apparent changes.This understanding has a particular significance for further deepening understanding of the geothermal genesis mechanism in sedimentary basins and guiding future geothermal exploration and development in the Donglihu area.展开更多
Radiation detectors, such as survey meters, are essential for ensuring radiation safety in various sectors, including healthcare, industrial processing, emergency response, etc. However, regular calibration and proper...Radiation detectors, such as survey meters, are essential for ensuring radiation safety in various sectors, including healthcare, industrial processing, emergency response, etc. However, regular calibration and proper maintenance of survey meters are important in order to ascertain their accuracy and reliability. This study provides a comprehensive retrospective assessment of the calibration behaviour, durability, and fault trends of 160 survey meters, spanning ten different models. They were calibrated at the Secondary Standard Dosimetry Laboratory (SSDL) in Nigeria over a decade (2012-2023) using an X-Ray Beam Irradiator Model X80-225K and Cs-137 irradiator (OB6) with a PTW reference spherical chamber traceable to the IAEA SSDL in Seibersdorf, Austria. The calibration stability of each model was evaluated, revealing that models like Instrument A and Instrument B demonstrated high reliability with calibration factors close to the ideal value of 1, while models like Instrument C exhibited higher variability, suggesting less consistent performance for dose rate monitoring. Fault analysis showed that the most common issues were related to the battery compartment, indicating a need for improved handling practices. Correlation analysis reveals no statistically significant correlation between calibration factor and age of survey meter across the analysed models. The study concludes that regular calibration, proper handling, and user training are crucial for maintaining the accuracy and longevity of radiation detectors.展开更多
The Longmenshan(LMS) fault zone is located at the junction of the eastern Tibetan Plateau and the Sichuan Basin and is of great significance for studying regional tectonics and earthquake hazards. Although regional ve...The Longmenshan(LMS) fault zone is located at the junction of the eastern Tibetan Plateau and the Sichuan Basin and is of great significance for studying regional tectonics and earthquake hazards. Although regional velocity models are available for the LMS fault zone, high-resolution velocity models are lacking. Therefore, a dense array of 240 short-period seismometers was deployed around the central segment of the LMS fault zone for approximately 30 days to monitor earthquakes and characterize fine structures of the fault zone. Considering the large quantity of observed seismic data, the data processing workflow consisted of deep learning-based automatic earthquake detection, phase arrival picking, and association. Compared with the earthquake catalog released by the China Earthquake Administration, many more earthquakes were detected by the dense array. Double-difference seismic tomography was adopted to determine V_(p), V_(s), and V_(p)/V_(s) models as well as earthquake locations. The checkerboard test showed that the velocity models have spatial resolutions of approximately 5 km in the horizontal directions and 2 km at depth. To the west of the Yingxiu–Beichuan Fault(YBF), the Precambrian Pengguan complex, where most of earthquakes occurred, is characterized by high velocity and low V_(p)/V_(s) values. In comparison, to the east of the YBF, the Upper Paleozoic to Jurassic sediments, where few earthquakes occurred, show low velocity and high V_(p)/V_(s) values. Our results suggest that the earthquake activity in the LMS fault zone is controlled by the strength of the rock compositions. When the high-resolution velocity models were combined with the relocated earthquakes, we were also able to delineate the fault geometry for different faults in the LMS fault zone.展开更多
The complex Red River fault zone(RRFZ), which is situated in the southwestern region of China and separates the Indochina plate and South China blocks, has diverse seismic activities in different segments. To reveal t...The complex Red River fault zone(RRFZ), which is situated in the southwestern region of China and separates the Indochina plate and South China blocks, has diverse seismic activities in different segments. To reveal the detailed geometric characteristics of the RRFZ at different sections and to better understand the seismogenic environment, in 2022 and 2023 we deployed 7 seismic dense linear arrays, consisting of 574 nodal stations, across the RRFZ in the northern and southern segments near the towns Midu, Gasa, Zhega,Dazhai, Xinzhai, and Taoyuan. The linear arrays, which extend from 2.4 to 12.5 km in length with station intervals ranging between 40 and140 m, recorded seismic ambient noise for approximately one month. Using the extended range phase shift method, we extract the phase velocity dispersion curves of the Rayleigh waves between 0.9 and 10 Hz, which are then used to invert for the high resolution shearwave velocity structures across the RRFZ beneath the linear arrays. The key findings are:(1) the 7 imaged sections of the RRFZ exhibit quite similar structures, with higher velocities on the SW side and lower velocities on the NE side;the velocity variation is consistent with the surface geological structures along the RRFZ;(2) the shear-wave velocities on the SW side of the RRFZ at the northern Midu section and southern Gasa-Dazhai sections are generally higher than their counterparts in the southern Xinzhai-Taoyuan sections, which reflects lithological variations from the marble-dominated Paleoproterozoic Along basement to the gneiss dominated Paleoproterozoic Qingshuihe basement;(3) from the northern Midu section to the southern region where the RRFZ intersects with the Xiaojiang Fault, the major faults of the RRFZ exhibit a consistent high-angle, NE-dipping structure;(4) the low shear-wave velocities immediately to the NE of the velocity boundary may indicate a faulted zone due to long-term shearing, where excessive amplifications of ground motions could occur. This study provides new insights into the characteristics of the shallow structures of the RRFZ.展开更多
In order to solve the code debugging difficulties faced by students and relieve the pressure of manual personalized tutoring,this paper proposes a method for locating faults in student code,called SCFL(student code fa...In order to solve the code debugging difficulties faced by students and relieve the pressure of manual personalized tutoring,this paper proposes a method for locating faults in student code,called SCFL(student code fault location).This method utilizes a historical correct code repository composed of correct codes submitted by previous students in the same assignments.It standardizes the erroneous code and historical correct code variables simultaneously and calculates the abstract syntax change tree.Then,by establishing the mapping between the abstract syntax change tree and the student assignment code,the fault location results of the student assignment are calculated.The evaluation experiments show that the SCFL method has a result of 9.25 in the cumulative inspection statement count and 15.9%in the fault localization cost indicator.Both indicators are better than the three currently commonly used spectrum-based baseline methods.展开更多
Geodetic observations over the past several decades identify the Tien Shan as a prominent and active intracontinental mountain belt,characterized by a meridional shortening rate of up to 20 mm/a.The region has experie...Geodetic observations over the past several decades identify the Tien Shan as a prominent and active intracontinental mountain belt,characterized by a meridional shortening rate of up to 20 mm/a.The region has experienced significant seismic events,particularly along its northern boundary,highlighting the recurrent seismic activity in the Kyrgyz Republic.The Issyk-Ata fault,stretching 120 km from west to east in the northern Tien Shan,bounds from the north a young,growing anticline demarcating the foothills of the Kyrgyz Range and the Chui depression.This region is susceptible to strong earthquakes,posing a significant threat to the Chui region and Bishkek,the capital city with over a million residents.The youngest fault in the area is the Issyk-Ata fault,traversing the southern part of Bishkek,where modern construction has obscured its features.This study integrates remote sensing,detailed fieldwork,and paleoseismological investigations to map and analyze surface ruptures,quantify vertical displacements,and assess seismic hazards along the Issyk-Ata fault.Using optically stimulated luminescence and radiocarbon dating,we determined ages for documented paleoseismic events,placing two ancient earthquakes in the Holocene.Magnitude estimates suggest seismic events with magnitudes ranging from 6.6 to 7.1.In the Dzhal area,geological and geomorphological analysis yielded a longterm fault-slip rate of 1.15 mm/a.The Issyk-Ata fault shows variable rupture behavior,with distinct segments demonstrating different seismic characteristics and histories of activity.This variability necessitates comprehensive seismic hazard modeling to better understand and mitigate potential risks in the region.展开更多
Fractal geometry quantitatively analyzes the irregular distribution of geological features,highlighting the dynamic aspects of tectonics,seismic heterogeneity,and geological maturity.This study analyzed the active fau...Fractal geometry quantitatively analyzes the irregular distribution of geological features,highlighting the dynamic aspects of tectonics,seismic heterogeneity,and geological maturity.This study analyzed the active fault data along the Kuhbanan fault zone in southeastern Iran by applying the boxcounting method and observing the changes in Coulomb stress and tried to find the potential triggering parts.The entire region was divided into 16subzones with the box-counting method,and then the fractal dimension(D)in each zone was calculated.The analysis of the fractal dimension for active faults and earthquake epicenters along with the seismicity parameter(b)and their ratio in the Kuhbanan region indicates an imbalance between seismic fractals and faults.This finding suggests that the area may have the potential for future earthquakes or hidden faults.In conjunction with b-value and changes in Coulomb stress change,D-value analysis reveals intense tectonic activity and stress accumulation,particularly within the Ravar,Zarand,and Kianshahr sections.It may be considered a potential location for future earthquakes.The changes in Coulomb stress resulting from the 2005Dahuieh earthquake have also placed this region within the stress accumulation zone,potentially triggering the mentioned areas.This integrative approach,backed by historical earthquake data,highlights the impact of fault geometry and stress dynamics,offering an enhanced framework for earthquake forecasting and seismic risk mitigation applicable to other tectonically active areas within the Iranian plateau.展开更多
Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accu...Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.展开更多
The water conductivity of karst collapsed column is affected by multiple factors such as the characteristics of its own column filling,structure and mining disturbance.As a structural water-conducting channel,fault us...The water conductivity of karst collapsed column is affected by multiple factors such as the characteristics of its own column filling,structure and mining disturbance.As a structural water-conducting channel,fault usually plays a controlling role in hydrogeological structure.During the process of mine water hazard prevention and control,it was discovered that the lithology composition,compaction and cementation degree and water physical properties of karst collapsed column fillings were all non-conducting water,but due to the influence of combined development faults,some exploration drill holes showed concentrated water outflow.Based on this,the scientific hypothesis was proposed that fault cutting leads to water conduction in karst collapsed columns.The study comprehensively used methods like chronology,exploration data analysis,and hydrochemical testing to analyze the chronological relationship between faults and karst collapsed columns,their spatial relationship,outlet point distribution and water chemical properties,and the impact of faults on the water-conductivity of karst collapsed columns,which proved the effect of fault cutting on changing water conductivity of karst collapsed column.The research showed that later fault cutting through karst collapsed columns turned the originally non-conductive karst collapsed columns into water-conductive collapsed columns at the fault plane,creating a longitudinally connected water-conducting channel.A new model of fault cutting karst collapsed column to change the original water conductivity of karst collapsed column was proposed.The research results can provide a theoretical basis for the prediction of the water conductivity of the karst collapsed column.According to whether the karst collapsed column was cut by the fault,it was predicted theoretically,so as to determine the key areas of water conductivity detection and prevention and control,and has broad application prospects under the background of source control of mine water disaster.展开更多
A fault is a geological structure characterized by significant displacement of rock masses along a fault plane within the Earth's crust.The Yunnan Tabaiyi Tunnel intersects multiple fault zones,making tunnel const...A fault is a geological structure characterized by significant displacement of rock masses along a fault plane within the Earth's crust.The Yunnan Tabaiyi Tunnel intersects multiple fault zones,making tunnel construction in fault-prone areas particularly vulnerable to the effects of fault activity due to the complexities of the surrounding geological environment.To investigate the dynamic response characteristics of tunnel structures under varying surrounding rock conditions,a three-dimensional large-scale shaking table physical model test was conducted.This study also aimed to explore the damage mechanisms associated with the Tabaiyi Tunnel under seismic loading.The results demonstrate that poor quality surrounding rock enhances the seismic response of the tunnel.This effect is primarily attributed to the distribution characteristics of acceleration,dynamic strain,and dynamic soil pressure.A comparison between unidirectional and multi-directional(including vertical)seismic motions reveals that vertical seismic motion has a more significant impact on specific tunnel locations.Specifically,the maximum tensile stress is observed at the arch shoulder,with values ranging from 60 to 100 k Pa.Moreover,NPR(Non-Prestressed Reinforced)anchor cables exhibit a substantial constant resistance effect under low-amplitude seismic waves.However,when the input earthquake amplitude reaches 0.8g,local sliding occurs at the arch shoulder region of the NPR anchor cable.These findings underscore the importance of focusing on seismic mitigation measures in fault zones and reinforcing critical areas,such as the arch shoulders,in practical engineering applications.展开更多
Rolling bearings are important parts of industrial equipment,and their fault diagnosis is crucial to maintaining these equipment’s regular operations.With the goal of improving the fault diagnosis accuracy of rolling...Rolling bearings are important parts of industrial equipment,and their fault diagnosis is crucial to maintaining these equipment’s regular operations.With the goal of improving the fault diagnosis accuracy of rolling bearings under complex working conditions and noise,this study proposes a multiscale information fusion method for fault diagnosis of rolling bearings based on fast Fourier transform(FFT)and variational mode decomposition(VMD),as well as the Senet(SE)-TCNnet(TCN)model.FFT is used to transform the original one-dimensional time domain vibration signal into a frequency domain signal,while VMD is used to decompose the original signal into several inherent mode functions(IMFs)of different scales.The center frequency method also determines the number of mode decompositions.Then,the data obtained by the two methods are fused into data containing the bearing fault information of different scales.Finally,the fused data are sent to the SE-TCN model for training.Experimental tests are conducted to verify the performance of this method.The findings reveal that an average accuracy of 98.39%can be achieved when noise is added and can even reach 100%when the signal-to-noise ratio is 6 dB.When the load changes,the accuracy of the model can reach 97.45%.The proposed method has the characteristics of high accuracy and strong generalization ability in bearing fault diagnosis.Furthermore,it can effectively overcome the effects of noise and variable working conditions in actual industrial environments,thus providing some ideas for future practical applications of bearing fault diagnosis.展开更多
The Main Himalayan Thrust(MHT),where the 2015 MW7.8 Gorkha earthquake occurred,features the most seismicity of any structure in Nepal.The structural complexity of the MHT makes it difficult to obtain a definitive inte...The Main Himalayan Thrust(MHT),where the 2015 MW7.8 Gorkha earthquake occurred,features the most seismicity of any structure in Nepal.The structural complexity of the MHT makes it difficult to obtain a definitive interpretation of deep seismogenic structures.The application of new methods and data in this region is necessary to enhance local seismic hazard analyses.In this study,we used a well-designed machine learning-based earthquake location workflow(LOC-FLOW),which incorporates machine learning phase picking,phase association,absolute location,and double-difference relative location,to process seismic data collected by the Hi-CLIMB and NAMASTE seismic networks.We built a high-precision earthquake catalog of both the quiet-period and aftershock seismicity in this region.The seismicity distribution suggests that the quietperiod seismicity(388 events)was controlled by a mid-crustal ramp and the aftershock seismicity(12,669 events)was controlled by several geological structures of the MHT.The higher-level detail of the catalogs derived from this machine learning method reveal clearer structural characteristics,showing how the flat-ramp geometry and a possible duplex structure affect the depth distribution of the seismic events,and how a tear fault changes this distribution along strike.展开更多
Quantum circuit fidelity is a crucial metric for assessing the accuracy of quantum computation results and indicating the precision of quantum algorithm execution. The primary methods for assessing quantum circuit fid...Quantum circuit fidelity is a crucial metric for assessing the accuracy of quantum computation results and indicating the precision of quantum algorithm execution. The primary methods for assessing quantum circuit fidelity include direct fidelity estimation and mirror circuit fidelity estimation. The former is challenging to implement in practice, while the latter requires substantial classical computational resources and numerous experimental runs. In this paper, we propose a fidelity estimation method based on Layer Interleaved Randomized Benchmarking, which decomposes a complex quantum circuit into multiple sublayers. By independently evaluating the fidelity of each layer, one can comprehensively assess the performance of the entire quantum circuit. This layered evaluation strategy not only enhances accuracy but also effectively identifies and analyzes errors in specific quantum gates or qubits through independent layer evaluation. Simulation results demonstrate that the proposed method improves circuit fidelity by an average of 6.8% and 4.1% compared to Layer Randomized Benchmarking and Interleaved Randomized Benchmarking methods in a thermal relaxation noise environment, and by 40% compared to Layer RB in a bit-flip noise environment. Moreover, the method detects preset faulty quantum gates in circuits generated by the Munich Quantum Toolkit Benchmark, verifying the model’s validity and providing a new tool for faulty gate detection in quantum circuits.展开更多
Drainage divide migration refers to the shifting boundaries between adjacent drainage basins over time,driven by processes such as tectonic uplift,differential erosion,stream capture,and lithological variations.This p...Drainage divide migration refers to the shifting boundaries between adjacent drainage basins over time,driven by processes such as tectonic uplift,differential erosion,stream capture,and lithological variations.This phenomenon has a significant impact on water flow patterns and basin extents,serving as an indicator of the landscape's response to active tectonic forces.One of the key drivers of divide migration is asymmetric uplift,which causes divides to shift from areas of lower uplift to regions experiencing higher uplift.Drainage divides are inherently dynamic,evolving over time as drainage networks develop and adjust to changing conditions.This study focuses on the migration of the main drainage divide along Karιncalιda?,located between Bozdo?an and Karacasu.It employs geomorphic analyses using metrics such as the normalized steepness index(ksn),Chi(χ),and Gilbert metrics.The main divide is categorized into four segments(D1–D4),with the Karacasu Fault,situated along the mountain's north-eastern boundary,identified as the primary factor influencing divide dynamics.Secondary factors include the relatively low elevation of Karιncalιda?,uniform lithology,and consistent rainfall patterns across the region.The results indicate that the main divide is currently stable,suggesting a balance between uplift and erosion.However,higherχvalues in the D4 segment suggest that future erosion may dominate,potentially causing the divide to migrate toward the Bozdo?an Basin.These findings highlight the dynamic nature of drainage divides and the complex interplay of tectonic,erosional,and lithological processes that shape their evolution.Continued monitoring and advanced geomorphic analysis are essential for understanding the long-term stability of the divide and its response to future tectonic activity and erosional modifications.展开更多
The Anninghe–Zemuhe Fault and the Xiaojiang Fault are critical active faults along the middle-eastern boundary of the South Chuan–Dian Block. Many researchers have identified these faults as potential strong-earthqu...The Anninghe–Zemuhe Fault and the Xiaojiang Fault are critical active faults along the middle-eastern boundary of the South Chuan–Dian Block. Many researchers have identified these faults as potential strong-earthquake risk zones. In this study, we leveraged a dense seismic array to investigate the high-resolution shallow crust shear wave velocity(Vs) structure beneath the junction of the Zemuhe Fault Zone and the Xiaojiang Fault Zone, one of the most complex parts of the eastern boundary of the South Chuan–Dian Block. We analyzed the distribution of microseismic events detected between November 2022 and February 2023 based on the fine-scale Vs model obtained. The microseismicity in the study region was clustered into three groups, all spatially related to major faults in this region. These microseismic events indicate near-vertical fault planes, consistent with the fault geometry revealed by other researchers.Moreover, these microseismic events are influenced by the impoundment of the downstream Baihetan Reservoir and the complex tectonic stress near the junction of the Zemuhe Fault Zone and the Xiaojiang Fault Zone. The depths of these microseismic events are shallower in the junction zone, whereas moving south along the Xiaojiang Fault Zone, the microseismic events become deeper.Additionally, we compared our fine-scale local Vs model with velocity models obtained by other researchers and found that our model offers greater detail in characterizing subsurface heterogeneity while demonstrating improved reliability in delineating fault systems.展开更多
Robustness against measurement uncertainties is crucial for gas turbine engine diagnosis.While current research focuses mainly on measurement noise,measurement bias remains challenging.This study proposes a novel perf...Robustness against measurement uncertainties is crucial for gas turbine engine diagnosis.While current research focuses mainly on measurement noise,measurement bias remains challenging.This study proposes a novel performance-based fault detection and identification(FDI)strategy for twin-shaft turbofan gas turbine engines and addresses these uncertainties through a first-order Takagi-Sugeno-Kang fuzzy inference system.To handle ambient condition changes,we use parameter correction to preprocess the raw measurement data,which reduces the FDI’s system complexity.Additionally,the power-level angle is set as a scheduling parameter to reduce the number of rules in the TSK-based FDI system.The data for designing,training,and testing the proposed FDI strategy are generated using a component-level turbofan engine model.The antecedent and consequent parameters of the TSK-based FDI system are optimized using the particle swarm optimization algorithm and ridge regression.A robust structure combining a specialized fuzzy inference system with the TSK-based FDI system is proposed to handle measurement biases.The performance of the first-order TSK-based FDI system and robust FDI structure are evaluated through comprehensive simulation studies.Comparative studies confirm the superior accuracy of the first-order TSK-based FDI system in fault detection,isolation,and identification.The robust structure demonstrates a 2%-8%improvement in the success rate index under relatively large measurement bias conditions,thereby indicating excellent robustness.Accuracy against significant bias values and computation time are also evaluated,suggesting that the proposed robust structure has desirable online performance.This study proposes a novel FDI strategy that effectively addresses measurement uncertainties.展开更多
基金supported by the National Natural Science Foundation of China(No.52277055).
文摘Traditional data-driven fault diagnosis methods depend on expert experience to manually extract effective fault features of signals,which has certain limitations.Conversely,deep learning techniques have gained prominence as a central focus of research in the field of fault diagnosis by strong fault feature extraction ability and end-to-end fault diagnosis efficiency.Recently,utilizing the respective advantages of convolution neural network(CNN)and Transformer in local and global feature extraction,research on cooperating the two have demonstrated promise in the field of fault diagnosis.However,the cross-channel convolution mechanism in CNN and the self-attention calculations in Transformer contribute to excessive complexity in the cooperative model.This complexity results in high computational costs and limited industrial applicability.To tackle the above challenges,this paper proposes a lightweight CNN-Transformer named as SEFormer for rotating machinery fault diagnosis.First,a separable multiscale depthwise convolution block is designed to extract and integrate multiscale feature information from different channel dimensions of vibration signals.Then,an efficient self-attention block is developed to capture critical fine-grained features of the signal from a global perspective.Finally,experimental results on the planetary gearbox dataset and themotor roller bearing dataset prove that the proposed framework can balance the advantages of robustness,generalization and lightweight compared to recent state-of-the-art fault diagnosis models based on CNN and Transformer.This study presents a feasible strategy for developing a lightweight rotating machinery fault diagnosis framework aimed at economical deployment.
基金Yongxian Huang supported by Projects of Guangzhou Science and Technology Plan(2023A04J0409)。
文摘To accurately diagnosemisfire faults in automotive engines,we propose a Channel Attention Convolutional Model,specifically the Squeeze-and-Excitation Networks(SENET),for classifying engine vibration signals and precisely pinpointing misfire faults.In the experiment,we established a total of 11 distinct states,encompassing the engine’s normal state,single-cylinder misfire faults,and dual-cylinder misfire faults for different cylinders.Data collection was facilitated by a highly sensitive acceleration signal collector with a high sampling rate of 20,840Hz.The collected data were methodically divided into training and testing sets based on different experimental groups to ensure generalization and prevent overlap between the two sets.The results revealed that,with a vibration acceleration sequence of 1000 time steps(approximately 50 ms)as input,the SENET model achieved a misfire fault detection accuracy of 99.8%.For comparison,we also trained and tested several commonly used models,including Long Short-Term Memory(LSTM),Transformer,and Multi-Scale Residual Networks(MSRESNET),yielding accuracy rates of 84%,79%,and 95%,respectively.This underscores the superior accuracy of the SENET model in detecting engine misfire faults compared to other models.Furthermore,the F1 scores for each type of recognition in the SENET model surpassed 0.98,outperforming the baseline models.Our analysis indicated that the misclassified samples in the LSTM and Transformer models’predictions were primarily due to intra-class misidentifications between single-cylinder and dual-cylinder misfire scenarios.To delve deeper,we conducted a visual analysis of the features extracted by the LSTM and SENET models using T-distributed Stochastic Neighbor Embedding(T-SNE)technology.The findings revealed that,in the LSTMmodel,data points of the same type tended to cluster together with significant overlap.Conversely,in the SENET model,data points of various types were more widely and evenly dispersed,demonstrating its effectiveness in distinguishing between different fault types.
基金supported by the Deanship of Scientific Research and Graduate Studies at King Khalid University under research grant number(R.G.P.2/93/45).
文摘Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation systems.Fog computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end nodes.Consisting of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud computing.In smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system reliability.To address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog environments.This framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation systems.The FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud environments.Through simulation-based executions,tasks are allocated to the nearest available nodes with minimum latency.In the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of tasks.Upon successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.
基金supported in part by Natural Science Foundation of Jiangsu Province under Grant BK20230255Natural Science Foundation of Shandong Province under Grant ZR2023QE281.
文摘The multi-terminal direct current(DC)grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy.Both the DC circuit breaker(DCCB)and the current flow controller(CFC)are demanded to ensure the multiterminal DC grid to operates reliably and flexibly.However,since the CFC and the DCCB are all based on fully controlled semiconductor switches(e.g.,insulated gate bipolar transistor,integrated gate commutated thyristor,etc.),their separation configuration in the multiterminal DC grid will lead to unaffordable implementation costs and conduction power losses.To solve these problems,integrated equipment with both current flow control and fault isolation abilities is proposed,which shares the expensive and duplicated components of CFCs and DCCBs among adjacent lines.In addition,the complicated coordination control of CFCs and DCCBs can be avoided by adopting the integrated equipment in themultiterminal DC grid.In order to examine the current flow control and fault isolation abilities of the integrated equipment,the simulation model of a specific meshed four-terminal DC grid is constructed in the PSCAD/EMTDC software.Finally,the comparison between the integrated equipment and the separate solution is presented a specific result or conclusion needs to be added to the abstract.
基金funded by Public Interest Monitoring Project(No.XCSD-2024-317)of the Tianjin Municipal Bureau of Planning and Natural Resources。
文摘Large basins are currently the global focus for geothermal development,with their hydrothermal system being controlled by a variety of factors,such as basement relief and fracture development.Donglihu is located at the north of the Cangxian uplift in the North China Basin,the concentrated geothermal resource development zone in North China.This study systematically collects temperature logging data and long-term dynamic monitoring of water level and water quality as well as group well tracer test data carried out in this area in recent years,on the basis of which the hydrothermal controlling role of the deep hidden faults is systematically analyzed.The results show that the Cangdong fault communicates with different geothermal reservoirs in the shallow part and plays a specific role in the water-heat channel of the local area.As a result,the high-value area of the geothermal temperature gradient in the sedimentary layer of the Donglihu area is distributed around the Cangdong fault.The geothermal reservoir temperature of the Minghuazhen Formation within the influence of the fault is also significantly higher than the regional average,the hydraulic head of different geothermal reservoirs showing a consistent and synergistic trend.However,the water quality has been stable for many years without any apparent changes.This understanding has a particular significance for further deepening understanding of the geothermal genesis mechanism in sedimentary basins and guiding future geothermal exploration and development in the Donglihu area.
文摘Radiation detectors, such as survey meters, are essential for ensuring radiation safety in various sectors, including healthcare, industrial processing, emergency response, etc. However, regular calibration and proper maintenance of survey meters are important in order to ascertain their accuracy and reliability. This study provides a comprehensive retrospective assessment of the calibration behaviour, durability, and fault trends of 160 survey meters, spanning ten different models. They were calibrated at the Secondary Standard Dosimetry Laboratory (SSDL) in Nigeria over a decade (2012-2023) using an X-Ray Beam Irradiator Model X80-225K and Cs-137 irradiator (OB6) with a PTW reference spherical chamber traceable to the IAEA SSDL in Seibersdorf, Austria. The calibration stability of each model was evaluated, revealing that models like Instrument A and Instrument B demonstrated high reliability with calibration factors close to the ideal value of 1, while models like Instrument C exhibited higher variability, suggesting less consistent performance for dose rate monitoring. Fault analysis showed that the most common issues were related to the battery compartment, indicating a need for improved handling practices. Correlation analysis reveals no statistically significant correlation between calibration factor and age of survey meter across the analysed models. The study concludes that regular calibration, proper handling, and user training are crucial for maintaining the accuracy and longevity of radiation detectors.
基金supported by the Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology under Grant 2024yjrc64the National Key R&D Program of China under Grant 2018YFC1504102。
文摘The Longmenshan(LMS) fault zone is located at the junction of the eastern Tibetan Plateau and the Sichuan Basin and is of great significance for studying regional tectonics and earthquake hazards. Although regional velocity models are available for the LMS fault zone, high-resolution velocity models are lacking. Therefore, a dense array of 240 short-period seismometers was deployed around the central segment of the LMS fault zone for approximately 30 days to monitor earthquakes and characterize fine structures of the fault zone. Considering the large quantity of observed seismic data, the data processing workflow consisted of deep learning-based automatic earthquake detection, phase arrival picking, and association. Compared with the earthquake catalog released by the China Earthquake Administration, many more earthquakes were detected by the dense array. Double-difference seismic tomography was adopted to determine V_(p), V_(s), and V_(p)/V_(s) models as well as earthquake locations. The checkerboard test showed that the velocity models have spatial resolutions of approximately 5 km in the horizontal directions and 2 km at depth. To the west of the Yingxiu–Beichuan Fault(YBF), the Precambrian Pengguan complex, where most of earthquakes occurred, is characterized by high velocity and low V_(p)/V_(s) values. In comparison, to the east of the YBF, the Upper Paleozoic to Jurassic sediments, where few earthquakes occurred, show low velocity and high V_(p)/V_(s) values. Our results suggest that the earthquake activity in the LMS fault zone is controlled by the strength of the rock compositions. When the high-resolution velocity models were combined with the relocated earthquakes, we were also able to delineate the fault geometry for different faults in the LMS fault zone.
基金funded by the National Key Research and Development Project of China (Grant No. 2021YFC3000600)the China Earthquake Science Experiment Field-Cross-fault Observation Array-Red River Fault Scientific Drilling Project Geophysical Prospecting Site Selection Project+2 种基金Anhui Province Science and Technology Breakthrough Plan Project (Key Project,202423l10050030)the Earthquake Science and Technology Spark Program of the China Earthquake Administration (XH23020YA)the Anhui Mengcheng National Geophysical Observatory Joint Open Fund (MENGO-202307)。
文摘The complex Red River fault zone(RRFZ), which is situated in the southwestern region of China and separates the Indochina plate and South China blocks, has diverse seismic activities in different segments. To reveal the detailed geometric characteristics of the RRFZ at different sections and to better understand the seismogenic environment, in 2022 and 2023 we deployed 7 seismic dense linear arrays, consisting of 574 nodal stations, across the RRFZ in the northern and southern segments near the towns Midu, Gasa, Zhega,Dazhai, Xinzhai, and Taoyuan. The linear arrays, which extend from 2.4 to 12.5 km in length with station intervals ranging between 40 and140 m, recorded seismic ambient noise for approximately one month. Using the extended range phase shift method, we extract the phase velocity dispersion curves of the Rayleigh waves between 0.9 and 10 Hz, which are then used to invert for the high resolution shearwave velocity structures across the RRFZ beneath the linear arrays. The key findings are:(1) the 7 imaged sections of the RRFZ exhibit quite similar structures, with higher velocities on the SW side and lower velocities on the NE side;the velocity variation is consistent with the surface geological structures along the RRFZ;(2) the shear-wave velocities on the SW side of the RRFZ at the northern Midu section and southern Gasa-Dazhai sections are generally higher than their counterparts in the southern Xinzhai-Taoyuan sections, which reflects lithological variations from the marble-dominated Paleoproterozoic Along basement to the gneiss dominated Paleoproterozoic Qingshuihe basement;(3) from the northern Midu section to the southern region where the RRFZ intersects with the Xiaojiang Fault, the major faults of the RRFZ exhibit a consistent high-angle, NE-dipping structure;(4) the low shear-wave velocities immediately to the NE of the velocity boundary may indicate a faulted zone due to long-term shearing, where excessive amplifications of ground motions could occur. This study provides new insights into the characteristics of the shallow structures of the RRFZ.
基金supported by the National Natural Science Foundation of China(Grant No.62177003)the Fundamental Research Funds for the Central Universities of Ministry of Education of China(Grant No.JKF-20240213)。
文摘In order to solve the code debugging difficulties faced by students and relieve the pressure of manual personalized tutoring,this paper proposes a method for locating faults in student code,called SCFL(student code fault location).This method utilizes a historical correct code repository composed of correct codes submitted by previous students in the same assignments.It standardizes the erroneous code and historical correct code variables simultaneously and calculates the abstract syntax change tree.Then,by establishing the mapping between the abstract syntax change tree and the student assignment code,the fault location results of the student assignment are calculated.The evaluation experiments show that the SCFL method has a result of 9.25 in the cumulative inspection statement count and 15.9%in the fault localization cost indicator.Both indicators are better than the three currently commonly used spectrum-based baseline methods.
基金financial support of the Faculty Research Grant project of the American University of Central Asia(AUCA)supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2023S1A5B5A16080131)。
文摘Geodetic observations over the past several decades identify the Tien Shan as a prominent and active intracontinental mountain belt,characterized by a meridional shortening rate of up to 20 mm/a.The region has experienced significant seismic events,particularly along its northern boundary,highlighting the recurrent seismic activity in the Kyrgyz Republic.The Issyk-Ata fault,stretching 120 km from west to east in the northern Tien Shan,bounds from the north a young,growing anticline demarcating the foothills of the Kyrgyz Range and the Chui depression.This region is susceptible to strong earthquakes,posing a significant threat to the Chui region and Bishkek,the capital city with over a million residents.The youngest fault in the area is the Issyk-Ata fault,traversing the southern part of Bishkek,where modern construction has obscured its features.This study integrates remote sensing,detailed fieldwork,and paleoseismological investigations to map and analyze surface ruptures,quantify vertical displacements,and assess seismic hazards along the Issyk-Ata fault.Using optically stimulated luminescence and radiocarbon dating,we determined ages for documented paleoseismic events,placing two ancient earthquakes in the Holocene.Magnitude estimates suggest seismic events with magnitudes ranging from 6.6 to 7.1.In the Dzhal area,geological and geomorphological analysis yielded a longterm fault-slip rate of 1.15 mm/a.The Issyk-Ata fault shows variable rupture behavior,with distinct segments demonstrating different seismic characteristics and histories of activity.This variability necessitates comprehensive seismic hazard modeling to better understand and mitigate potential risks in the region.
基金financial support received through a grant from the Vice-President's Research Office at Bu-Ali Sina University,Iran(Grant Number 09.99)。
文摘Fractal geometry quantitatively analyzes the irregular distribution of geological features,highlighting the dynamic aspects of tectonics,seismic heterogeneity,and geological maturity.This study analyzed the active fault data along the Kuhbanan fault zone in southeastern Iran by applying the boxcounting method and observing the changes in Coulomb stress and tried to find the potential triggering parts.The entire region was divided into 16subzones with the box-counting method,and then the fractal dimension(D)in each zone was calculated.The analysis of the fractal dimension for active faults and earthquake epicenters along with the seismicity parameter(b)and their ratio in the Kuhbanan region indicates an imbalance between seismic fractals and faults.This finding suggests that the area may have the potential for future earthquakes or hidden faults.In conjunction with b-value and changes in Coulomb stress change,D-value analysis reveals intense tectonic activity and stress accumulation,particularly within the Ravar,Zarand,and Kianshahr sections.It may be considered a potential location for future earthquakes.The changes in Coulomb stress resulting from the 2005Dahuieh earthquake have also placed this region within the stress accumulation zone,potentially triggering the mentioned areas.This integrative approach,backed by historical earthquake data,highlights the impact of fault geometry and stress dynamics,offering an enhanced framework for earthquake forecasting and seismic risk mitigation applicable to other tectonically active areas within the Iranian plateau.
基金funded by the Youth Fund of the National Natural Science Foundation of China(Grant No.42261070).
文摘Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.
基金supported by the Postdoctoral Fellowship Program of CPSF(No.GZC20233005)the Fundamental Research Funds for the Central Universities(No.2024QN11025)+1 种基金the General Program of National Natural Science Foundation of China(No.52274243)the Hebei Province Natural Science Foundation Ecological Wisdom Mine Joint Fund Project(Nos.D2020402013 and D2022402040)。
文摘The water conductivity of karst collapsed column is affected by multiple factors such as the characteristics of its own column filling,structure and mining disturbance.As a structural water-conducting channel,fault usually plays a controlling role in hydrogeological structure.During the process of mine water hazard prevention and control,it was discovered that the lithology composition,compaction and cementation degree and water physical properties of karst collapsed column fillings were all non-conducting water,but due to the influence of combined development faults,some exploration drill holes showed concentrated water outflow.Based on this,the scientific hypothesis was proposed that fault cutting leads to water conduction in karst collapsed columns.The study comprehensively used methods like chronology,exploration data analysis,and hydrochemical testing to analyze the chronological relationship between faults and karst collapsed columns,their spatial relationship,outlet point distribution and water chemical properties,and the impact of faults on the water-conductivity of karst collapsed columns,which proved the effect of fault cutting on changing water conductivity of karst collapsed column.The research showed that later fault cutting through karst collapsed columns turned the originally non-conductive karst collapsed columns into water-conductive collapsed columns at the fault plane,creating a longitudinally connected water-conducting channel.A new model of fault cutting karst collapsed column to change the original water conductivity of karst collapsed column was proposed.The research results can provide a theoretical basis for the prediction of the water conductivity of the karst collapsed column.According to whether the karst collapsed column was cut by the fault,it was predicted theoretically,so as to determine the key areas of water conductivity detection and prevention and control,and has broad application prospects under the background of source control of mine water disaster.
基金funded by the National Natural Science Foundation of China(Grant No.42377195)。
文摘A fault is a geological structure characterized by significant displacement of rock masses along a fault plane within the Earth's crust.The Yunnan Tabaiyi Tunnel intersects multiple fault zones,making tunnel construction in fault-prone areas particularly vulnerable to the effects of fault activity due to the complexities of the surrounding geological environment.To investigate the dynamic response characteristics of tunnel structures under varying surrounding rock conditions,a three-dimensional large-scale shaking table physical model test was conducted.This study also aimed to explore the damage mechanisms associated with the Tabaiyi Tunnel under seismic loading.The results demonstrate that poor quality surrounding rock enhances the seismic response of the tunnel.This effect is primarily attributed to the distribution characteristics of acceleration,dynamic strain,and dynamic soil pressure.A comparison between unidirectional and multi-directional(including vertical)seismic motions reveals that vertical seismic motion has a more significant impact on specific tunnel locations.Specifically,the maximum tensile stress is observed at the arch shoulder,with values ranging from 60 to 100 k Pa.Moreover,NPR(Non-Prestressed Reinforced)anchor cables exhibit a substantial constant resistance effect under low-amplitude seismic waves.However,when the input earthquake amplitude reaches 0.8g,local sliding occurs at the arch shoulder region of the NPR anchor cable.These findings underscore the importance of focusing on seismic mitigation measures in fault zones and reinforcing critical areas,such as the arch shoulders,in practical engineering applications.
基金supported by Handan Science and Technology Research and Development Plan Project under Grant no.23422901031Key Laboratory of Intelligent Industrial Equipment Technology of Hebei Province(Hebei University of Engineering)under Grant no.202206.
文摘Rolling bearings are important parts of industrial equipment,and their fault diagnosis is crucial to maintaining these equipment’s regular operations.With the goal of improving the fault diagnosis accuracy of rolling bearings under complex working conditions and noise,this study proposes a multiscale information fusion method for fault diagnosis of rolling bearings based on fast Fourier transform(FFT)and variational mode decomposition(VMD),as well as the Senet(SE)-TCNnet(TCN)model.FFT is used to transform the original one-dimensional time domain vibration signal into a frequency domain signal,while VMD is used to decompose the original signal into several inherent mode functions(IMFs)of different scales.The center frequency method also determines the number of mode decompositions.Then,the data obtained by the two methods are fused into data containing the bearing fault information of different scales.Finally,the fused data are sent to the SE-TCN model for training.Experimental tests are conducted to verify the performance of this method.The findings reveal that an average accuracy of 98.39%can be achieved when noise is added and can even reach 100%when the signal-to-noise ratio is 6 dB.When the load changes,the accuracy of the model can reach 97.45%.The proposed method has the characteristics of high accuracy and strong generalization ability in bearing fault diagnosis.Furthermore,it can effectively overcome the effects of noise and variable working conditions in actual industrial environments,thus providing some ideas for future practical applications of bearing fault diagnosis.
基金funded by the National Key R&D Program of China(2022YFF0800601)National Natural Science Foundation of China(42174069,U1939204).
文摘The Main Himalayan Thrust(MHT),where the 2015 MW7.8 Gorkha earthquake occurred,features the most seismicity of any structure in Nepal.The structural complexity of the MHT makes it difficult to obtain a definitive interpretation of deep seismogenic structures.The application of new methods and data in this region is necessary to enhance local seismic hazard analyses.In this study,we used a well-designed machine learning-based earthquake location workflow(LOC-FLOW),which incorporates machine learning phase picking,phase association,absolute location,and double-difference relative location,to process seismic data collected by the Hi-CLIMB and NAMASTE seismic networks.We built a high-precision earthquake catalog of both the quiet-period and aftershock seismicity in this region.The seismicity distribution suggests that the quietperiod seismicity(388 events)was controlled by a mid-crustal ramp and the aftershock seismicity(12,669 events)was controlled by several geological structures of the MHT.The higher-level detail of the catalogs derived from this machine learning method reveal clearer structural characteristics,showing how the flat-ramp geometry and a possible duplex structure affect the depth distribution of the seismic events,and how a tear fault changes this distribution along strike.
文摘Quantum circuit fidelity is a crucial metric for assessing the accuracy of quantum computation results and indicating the precision of quantum algorithm execution. The primary methods for assessing quantum circuit fidelity include direct fidelity estimation and mirror circuit fidelity estimation. The former is challenging to implement in practice, while the latter requires substantial classical computational resources and numerous experimental runs. In this paper, we propose a fidelity estimation method based on Layer Interleaved Randomized Benchmarking, which decomposes a complex quantum circuit into multiple sublayers. By independently evaluating the fidelity of each layer, one can comprehensively assess the performance of the entire quantum circuit. This layered evaluation strategy not only enhances accuracy but also effectively identifies and analyzes errors in specific quantum gates or qubits through independent layer evaluation. Simulation results demonstrate that the proposed method improves circuit fidelity by an average of 6.8% and 4.1% compared to Layer Randomized Benchmarking and Interleaved Randomized Benchmarking methods in a thermal relaxation noise environment, and by 40% compared to Layer RB in a bit-flip noise environment. Moreover, the method detects preset faulty quantum gates in circuits generated by the Munich Quantum Toolkit Benchmark, verifying the model’s validity and providing a new tool for faulty gate detection in quantum circuits.
文摘Drainage divide migration refers to the shifting boundaries between adjacent drainage basins over time,driven by processes such as tectonic uplift,differential erosion,stream capture,and lithological variations.This phenomenon has a significant impact on water flow patterns and basin extents,serving as an indicator of the landscape's response to active tectonic forces.One of the key drivers of divide migration is asymmetric uplift,which causes divides to shift from areas of lower uplift to regions experiencing higher uplift.Drainage divides are inherently dynamic,evolving over time as drainage networks develop and adjust to changing conditions.This study focuses on the migration of the main drainage divide along Karιncalιda?,located between Bozdo?an and Karacasu.It employs geomorphic analyses using metrics such as the normalized steepness index(ksn),Chi(χ),and Gilbert metrics.The main divide is categorized into four segments(D1–D4),with the Karacasu Fault,situated along the mountain's north-eastern boundary,identified as the primary factor influencing divide dynamics.Secondary factors include the relatively low elevation of Karιncalιda?,uniform lithology,and consistent rainfall patterns across the region.The results indicate that the main divide is currently stable,suggesting a balance between uplift and erosion.However,higherχvalues in the D4 segment suggest that future erosion may dominate,potentially causing the divide to migrate toward the Bozdo?an Basin.These findings highlight the dynamic nature of drainage divides and the complex interplay of tectonic,erosional,and lithological processes that shape their evolution.Continued monitoring and advanced geomorphic analysis are essential for understanding the long-term stability of the divide and its response to future tectonic activity and erosional modifications.
基金funded by the National Key R&D Program of China (Grant No. 2021YFC3000704)the National Natural Science Foundation of China (Grant No. 42125401)the Central Public-interest Scientific Institution Basal Research Fund (Grant No. CEAIEF20240401)。
文摘The Anninghe–Zemuhe Fault and the Xiaojiang Fault are critical active faults along the middle-eastern boundary of the South Chuan–Dian Block. Many researchers have identified these faults as potential strong-earthquake risk zones. In this study, we leveraged a dense seismic array to investigate the high-resolution shallow crust shear wave velocity(Vs) structure beneath the junction of the Zemuhe Fault Zone and the Xiaojiang Fault Zone, one of the most complex parts of the eastern boundary of the South Chuan–Dian Block. We analyzed the distribution of microseismic events detected between November 2022 and February 2023 based on the fine-scale Vs model obtained. The microseismicity in the study region was clustered into three groups, all spatially related to major faults in this region. These microseismic events indicate near-vertical fault planes, consistent with the fault geometry revealed by other researchers.Moreover, these microseismic events are influenced by the impoundment of the downstream Baihetan Reservoir and the complex tectonic stress near the junction of the Zemuhe Fault Zone and the Xiaojiang Fault Zone. The depths of these microseismic events are shallower in the junction zone, whereas moving south along the Xiaojiang Fault Zone, the microseismic events become deeper.Additionally, we compared our fine-scale local Vs model with velocity models obtained by other researchers and found that our model offers greater detail in characterizing subsurface heterogeneity while demonstrating improved reliability in delineating fault systems.
文摘Robustness against measurement uncertainties is crucial for gas turbine engine diagnosis.While current research focuses mainly on measurement noise,measurement bias remains challenging.This study proposes a novel performance-based fault detection and identification(FDI)strategy for twin-shaft turbofan gas turbine engines and addresses these uncertainties through a first-order Takagi-Sugeno-Kang fuzzy inference system.To handle ambient condition changes,we use parameter correction to preprocess the raw measurement data,which reduces the FDI’s system complexity.Additionally,the power-level angle is set as a scheduling parameter to reduce the number of rules in the TSK-based FDI system.The data for designing,training,and testing the proposed FDI strategy are generated using a component-level turbofan engine model.The antecedent and consequent parameters of the TSK-based FDI system are optimized using the particle swarm optimization algorithm and ridge regression.A robust structure combining a specialized fuzzy inference system with the TSK-based FDI system is proposed to handle measurement biases.The performance of the first-order TSK-based FDI system and robust FDI structure are evaluated through comprehensive simulation studies.Comparative studies confirm the superior accuracy of the first-order TSK-based FDI system in fault detection,isolation,and identification.The robust structure demonstrates a 2%-8%improvement in the success rate index under relatively large measurement bias conditions,thereby indicating excellent robustness.Accuracy against significant bias values and computation time are also evaluated,suggesting that the proposed robust structure has desirable online performance.This study proposes a novel FDI strategy that effectively addresses measurement uncertainties.
