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基于多尺度形态滤波和递归求差的冲击特征自适应分离方法

Adaptive separation method for impact features based on multiscale morphological filtering and recursive subtraction
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摘要 针对故障诊断中的耦合冲击特征提取和分离难题,提出了一种基于多尺度形态滤波(multiscale morphological filtering, MMF)和递归求差的冲击特征自适应提取与分离方法。首先,利用能量幅值(energy amplitude, EA)指标和频响特性分析,从典型组合算子中筛选出适合冲击特征分离的组合形态滤波-帽变换(combination morphological filter-hat transform, CMFH)算子;其次,利用CMFH形态学算子和加权谐噪比(weighted harmonic to noise ratio, WHNR)指标实现周期性冲击特征提取;然后,利用求差增强技术(strengthen operate subtract operate, SOSO)抑制谐波干扰和白噪声,进一步增强周期性冲击特征;最后,通过迭代求差思想构造循环滤波器,对周期性冲击特征进行多尺度提取与分离。仿真数据和牵引电机轴承故障数据分析结果表明,该方法在随机冲击、谐波干扰下的周期性冲击提取能力优于最大二阶循环平稳盲解卷积(maximum second order cyclostationary blind deconvolution, CYCBD)方法和经典谱峭度方法。 Here,aiming at the difficult problem of extraction and separation of coupled impact features in fault diagnosis,an adaptive impact feature extraction and separation method based on multiscale morphological filtering(MMF)and recursive subtraction was proposed.Firstly,using energy amplitude(EA)indexes and frequency response analysis,combination morphological filter-hat transform(CMFH)morphological operators suitable for impact feature separation were selected from typical combination operators.Secondly,periodic impact feature extraction was realized using CMFH morphological operators and weighted harmonic to noise ratio(WHNR)indexes.Then,the strengthen operate subtract operate(SOSO)technology was used to suppress harmonic interference and white noise,and further enhance periodic impact features.Finally,a cyclic filter was constructed using the iterative subtraction idea to perform multiscale extraction and separation for periodic impact features.The analysis results of simulation data and traction motor bearing fault data showed that the proposed method can have better ability to extract periodic impacts under random impacts and harmonic interference than maximum second order cyclostationary blind deconvolution(CYCBD)method and classical spectral kurtosis method can.
作者 和丹 权伟 汤明军 刘晖 HE Dan;QUAN Wei;TANG Mingjun;LIU Hui(College of Mechanical Engineering,Xi’an Polytechnic University,Xi’an 710048,China;Xi’an Municipal Key Lab of Modern Intelligent Textile Equipment,Xi’an 710600,China;School of Mechanical Engineering,Xi’an Jiaotong University,Xi’an 710049,China)
出处 《振动与冲击》 EI CSCD 北大核心 2024年第5期149-158,共10页 Journal of Vibration and Shock
基金 陕西省自然科学基础研究计划(2022JM-362) 陕西省教育厅服务地方专项计划项目(19JC019)。
关键词 多尺度形态滤波(MMF) 冲击特征 加权谐噪比(WHNR) 复合故障 multiscale morphological filtering(MMF) impact feature weighted harmonic to noise ratio(WHNR) compound faults
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