基于改进峭度图法的滚动轴承故障诊断
张海峰1陈丙炎2宋冬利2
Bogie Bearing Fault Diagnosis Based on Improved Kurtogram
ZHANG HaifengCHEN BingyanSONG Dongli
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作者信息:1.中车长春轨道客车股份有限公司国家轨道客车工程研究中心检修研发部，130062，长春；
2.西南交通大学牵引动力国家重点实验室，610031，成都
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Affiliation:CRRC Changchun Railway Vehicles Co., Ltd., 130062, Changchun, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2019.02.010
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中图分类号/CLCN:U270.331+.2
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栏目/Col:研究报告
摘要:
针对在强烈背景噪声和随机脉冲干扰下滚动轴承故障信号难以提取的问题，提出了一种改进的峭度图方法进行滚动轴承的故障诊断。该方法先通过计算特定频带信号包络的功率谱幅值的峭度，再按照峭度最大原则确定最优解调频带，然后根据最优解调频带获得带通滤波后的解调信号，通过对解调信号进行频谱分析来识别滚动轴承的故障及其类型。通过仿真和试验两种方式，对比分析了改进峭度图法和快速峭度图法诊断滚动轴承故障的效果，验证了改进峭度图法的有效性。分析结果表明：改进峭度图法比快速峭度图法能够更加准确地确定共振频带，并且在强烈背景噪声干扰下也能准确识别轴承故障。
Abstracts:
According to the difficulties in extracting fault signals of the rolling element bearings with the interference of intense background noise and random impulses, an improved Kurtogram method for fault diagnosis of rolling bearings is presented. By calculating the kurtosis of power spectrum of the envelope signal in specific frequency bands, this method uses the maximal kurtosis norm to determine the optimal demodulation frequency band. Thus, the bearing fault types can be identified from the envelope spectrum of filtered signal obtained from the optimal demodulation frequency band. In order to illustrate the effectiveness of the proposed method in rolling bearing fault detection, the simulated and experimental signals of the rolling bearing faults are analyzed, the performance of the improved Kurtogram and the fast Kurtogram is compared. The analysis results indicate that the improved Kurtogram method can accurately determine the resonant frequency band, and effectively detect the bearing faults under the influence of intense background noise compared with the fast Kurtogram method.
引文 / Ref:
张海峰，陈丙炎，宋冬利.基于改进峭度图法的滚动轴承故障诊断[J].城市轨道交通研究，2019，22（2）：41.
ZHANG Haifeng，CHEN Bingyan，SONG Dongli.Bogie Bearing Fault Diagnosis Based on Improved Kurtogram[J].Urban mass transit，2019，22（2）：41.
ZHANG Haifeng，CHEN Bingyan，SONG Dongli.Bogie Bearing Fault Diagnosis Based on Improved Kurtogram[J].Urban mass transit，2019，22（2）：41.
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