Abnormal movement states for a mobile robot were identified by four multi-layer perceptron. In the presence ot abnormality, avoidance strategies were designed to guarantee the safety of the robot. Firstly, the kinemat...Abnormal movement states for a mobile robot were identified by four multi-layer perceptron. In the presence ot abnormality, avoidance strategies were designed to guarantee the safety of the robot. Firstly, the kinematics of the normal and abnormal movement states were exploited, 8 kinds of features were extracted. Secondly, 4 multi-layer pereeptrons were employed to classify the features for four 4-driving wheels into 4 kinds of states, i.e. normal, blocked, deadly blocked, and slipping. Finally, avoidance strategies were designed based on this. Experiment results show that the methods can identify most abnormal movement states and avoid the abnormality correctly and timely.展开更多
The subsea anchor piles of offshore wind power floating platform structures are mainly subjected to uplift and horizontal loads, and this paper focuses on the case of horizontal loads. A three-dimensional numerical si...The subsea anchor piles of offshore wind power floating platform structures are mainly subjected to uplift and horizontal loads, and this paper focuses on the case of horizontal loads. A three-dimensional numerical simulation study of the horizontal pullout characteristics of wind power suction anchor piles in clay layers was carried out to reveal the horizontal movement state of the anchor piles during horizontal pile pullout, the range of pile depth at the pullout point where the horizontal movement is achieved (referred to as the horizontal movement range), the relationship between the pullout load and the ultimate load during the horizontal movement, and the optimal location of the pullout point for the horizontal movement. The results show that at certain pull-out points, the anchor pile produces an overall horizontal movement state under suitable horizontal pull-out loads. The depth of the pile pull-out point for horizontal movement is in the middle and lower part of the pile, i.e. 14.2 m to 14.5 m. The horizontal pull-out load of 24,000 kN at a depth of 14.5 m within the pile horizontal movement range of 14.2m to 14.5 m is the maximum ultimate horizontal pull-out load;the optimum pull-out point depth is 14.5 m at 0.275 L (L is the pile length). For each pull-out point of the anchor pile in horizontal movement, the horizontal pull-out load in horizontal movement and the horizontal ultimate pull-out load existed and it was found that the two values were not exactly the same, the values were compared and it was found that at the optimum pull-out point the value of the ultimate horizontal pull-out load/horizontal pull-out load in horizontal movement tended to 1.展开更多
The monitoring of related hourly and accumulated rainfall index requires that critical thresholds of accumulated 72 hours rainfall are updated frequently according with the factors and local conditions (natural and an...The monitoring of related hourly and accumulated rainfall index requires that critical thresholds of accumulated 72 hours rainfall are updated frequently according with the factors and local conditions (natural and anthropic) of each specific risk area. The importance of empirical methods is fundamental to confirm the relationship between rainfall intensity and accumulated rainfall with the mass movement events, in order to establish the critical threshold values. The present work performs an evaluation of the record data of mass movement events occurred in Sao Paulo State North coast region for a 4-year period (2014 to 2018) considering different mass movement characteristics (slope type, magnitude and impact level). Some rainfall values were obtained to show that within these parameters an event related to natural and anthropic features was triggered. A database was created, sorting source of information and municipalities monitored, to implement the correlation between the mass movement events and the rainfall values. To elaborate the event’s map, reliable record data of localization of the mass movement events was selected, as well as the nearest possible raingauges of CEMADEN (National Center for Monitoring and Early Warning of Natural Disasters);also the exact event triggering time, selection by the slope type, the magnitude and the impact level of the mass movement event. The rainfall values of these raingauges allowed the calculation of the accumulated rainfall index for 1, 3, 6, 24, 48, 72 and 96 hours, with the adoption of the 72 hours index for this work. The correlation graphics are divided by the slope type, the magnitude and the impact level of the mass movement event. Different critical thresholds appear, classifying such event by the influence level of triggering factors, natural and/or anthropic.展开更多
Compared with the study of single point motion of landslides,studying landslide block movement based on data from multiple monitoring points is of great significance for improving the accurate identification of landsl...Compared with the study of single point motion of landslides,studying landslide block movement based on data from multiple monitoring points is of great significance for improving the accurate identification of landslide deformation.Based on the study of landslide block,this paper regarded the landslide block as a rigid body in particle swarm optimization algorithm.The monitoring data were organized to achieve the optimal state of landslide block,and the 6-degree of freedom pose of the landslide block was calculated after the regularization.Based on the characteristics of data from multiple monitoring points of landslide blocks,a prediction equation for the motion state of landslide blocks was established.By using Kalman filtering data assimilation method,the parameters of prediction equation for landslide block motion state were adjusted to achieve the optimal prediction.This paper took the Baishuihe landslide in the Three Gorges reservoir area as the research object.Based on the block segmentation of the landslide,the monitoring data of the Baishuihe landslide block were organized,6-degree of freedom pose of block B was calculated,and the Kalman filtering data assimilation method was used to predict the landslide block movement.The research results showed that the proposed prediction method of the landslide movement state has good prediction accuracy and meets the expected goal.This paper provides a new research method and thinking angle to study the motion state of landslide block.展开更多
基金Project (60234030) supported by the National Natural Science Foundation of China
文摘Abnormal movement states for a mobile robot were identified by four multi-layer perceptron. In the presence ot abnormality, avoidance strategies were designed to guarantee the safety of the robot. Firstly, the kinematics of the normal and abnormal movement states were exploited, 8 kinds of features were extracted. Secondly, 4 multi-layer pereeptrons were employed to classify the features for four 4-driving wheels into 4 kinds of states, i.e. normal, blocked, deadly blocked, and slipping. Finally, avoidance strategies were designed based on this. Experiment results show that the methods can identify most abnormal movement states and avoid the abnormality correctly and timely.
文摘The subsea anchor piles of offshore wind power floating platform structures are mainly subjected to uplift and horizontal loads, and this paper focuses on the case of horizontal loads. A three-dimensional numerical simulation study of the horizontal pullout characteristics of wind power suction anchor piles in clay layers was carried out to reveal the horizontal movement state of the anchor piles during horizontal pile pullout, the range of pile depth at the pullout point where the horizontal movement is achieved (referred to as the horizontal movement range), the relationship between the pullout load and the ultimate load during the horizontal movement, and the optimal location of the pullout point for the horizontal movement. The results show that at certain pull-out points, the anchor pile produces an overall horizontal movement state under suitable horizontal pull-out loads. The depth of the pile pull-out point for horizontal movement is in the middle and lower part of the pile, i.e. 14.2 m to 14.5 m. The horizontal pull-out load of 24,000 kN at a depth of 14.5 m within the pile horizontal movement range of 14.2m to 14.5 m is the maximum ultimate horizontal pull-out load;the optimum pull-out point depth is 14.5 m at 0.275 L (L is the pile length). For each pull-out point of the anchor pile in horizontal movement, the horizontal pull-out load in horizontal movement and the horizontal ultimate pull-out load existed and it was found that the two values were not exactly the same, the values were compared and it was found that at the optimum pull-out point the value of the ultimate horizontal pull-out load/horizontal pull-out load in horizontal movement tended to 1.
文摘The monitoring of related hourly and accumulated rainfall index requires that critical thresholds of accumulated 72 hours rainfall are updated frequently according with the factors and local conditions (natural and anthropic) of each specific risk area. The importance of empirical methods is fundamental to confirm the relationship between rainfall intensity and accumulated rainfall with the mass movement events, in order to establish the critical threshold values. The present work performs an evaluation of the record data of mass movement events occurred in Sao Paulo State North coast region for a 4-year period (2014 to 2018) considering different mass movement characteristics (slope type, magnitude and impact level). Some rainfall values were obtained to show that within these parameters an event related to natural and anthropic features was triggered. A database was created, sorting source of information and municipalities monitored, to implement the correlation between the mass movement events and the rainfall values. To elaborate the event’s map, reliable record data of localization of the mass movement events was selected, as well as the nearest possible raingauges of CEMADEN (National Center for Monitoring and Early Warning of Natural Disasters);also the exact event triggering time, selection by the slope type, the magnitude and the impact level of the mass movement event. The rainfall values of these raingauges allowed the calculation of the accumulated rainfall index for 1, 3, 6, 24, 48, 72 and 96 hours, with the adoption of the 72 hours index for this work. The correlation graphics are divided by the slope type, the magnitude and the impact level of the mass movement event. Different critical thresholds appear, classifying such event by the influence level of triggering factors, natural and/or anthropic.
基金supported by National Natural Science Foundation of China(Grant Nos.42090054,52027814 and 41772376)the Open Fund of the Technology Innovation Center for Automated Geological Disaster Monitoring,Ministry of Natural Resources(Grant No.2022058014)。
文摘Compared with the study of single point motion of landslides,studying landslide block movement based on data from multiple monitoring points is of great significance for improving the accurate identification of landslide deformation.Based on the study of landslide block,this paper regarded the landslide block as a rigid body in particle swarm optimization algorithm.The monitoring data were organized to achieve the optimal state of landslide block,and the 6-degree of freedom pose of the landslide block was calculated after the regularization.Based on the characteristics of data from multiple monitoring points of landslide blocks,a prediction equation for the motion state of landslide blocks was established.By using Kalman filtering data assimilation method,the parameters of prediction equation for landslide block motion state were adjusted to achieve the optimal prediction.This paper took the Baishuihe landslide in the Three Gorges reservoir area as the research object.Based on the block segmentation of the landslide,the monitoring data of the Baishuihe landslide block were organized,6-degree of freedom pose of block B was calculated,and the Kalman filtering data assimilation method was used to predict the landslide block movement.The research results showed that the proposed prediction method of the landslide movement state has good prediction accuracy and meets the expected goal.This paper provides a new research method and thinking angle to study the motion state of landslide block.
文摘目的快速眼动睡眠行为障碍(rapid eye movement sleep behavior disorder,RBD)是帕金森病(Parkinson's disease,PD)常见的非运动症状且是重要预后因素。本研究通过静息态功能磁共振成像,利用度中心度(degreecentrality,DC)和低频振幅(amplitudes of low-frequency fluctuation,ALFF)分析PD伴RBD和不伴有RBD患者组以及健康对照组三组间DC值和ALFF值,探索PD伴RBD患者脑功能活动特征及RBD特异性脑区,探究RBD发生的病理机制。材料与方法招募20例伴有RBD的PD患者(PD-RBD组)、40例无RBD的PD患者(PD-nonRBD组)和44例年龄性别匹配的健康对照(健康对照组),三组被试均接受磁共振扫描。利用静息态数据计算DC值和ALFF值,探测脑功能特征。结果方差分析结果显示三组间DC值主效应脑区为右侧中央前回、颞上回、小脑、额中回(P<0.05,FDR校正);ALFF值主效应脑区为左侧海马旁回、楔叶、舌回(P<0.05,FDR校正)。进一步分析发现相比于PD-nonRBD组,PD-RBD患者表现为右侧额中回DC值升高(t=4.02;P=0.007,FDR校正);左侧楔前叶DC值降低(t=5.30;P=0.009,FDR校正)。相比于健康对照组,PD-RBD患者表现为左侧额上回、小脑、右侧颞上回、左侧颞中回、额中回的DC值升高(P<0.05,FDR校正);左侧中央前回、颞上回和颞中回的DC值降低(P<0.05,FDR校正);右侧楔叶ALFF值降低(P<0.05,FDR校正)。结论PD-RBD在DC和ALFF上有独特的影像学特征,特别是右侧额中回、左侧楔前叶的功能异常可能与PD患者RBD的发生密切相关。
