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作 者:李海英 孙越 张笑 宋建成[2] LI Haiying;SUN Yue;ZHANG Xiao;SONG Jiancheng(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China;College of Electrical and Power Engineering,Taiyuan University of Technology,Taiyuan 030024,China)
机构地区:[1]上海理工大学机械工程学院,上海200093 [2]太原理工大学电气与动力工程学院,太原030024
出 处:《高电压技术》2023年第5期1831-1840,共10页High Voltage Engineering
基 金:山西省重点研发计划(202003D111008)。
摘 要:针对时频方法用于真空接触器故障诊断存在特征遗漏的局限性,提出一种利用模态时频图描述振动信号特征,并融合ResNet50的故障辨识方法。首先设置故障模拟方案,并采用下采样处理方法,丰富样本数据库。其次采用灰狼优化算法,搜寻变分模态分解(variational mode decomposition,VMD)算法的最佳参数,将复杂振动信号分解成最佳中心频率、有限带宽的固有模态分量。最后,提出一种模态时频图提取特征方法,利用小波变换将模态分量生成模态时频图,充分提取特征,并融合ResNet50辨识故障类型。以ZKTJ–400/1140型真空接触器作为实验对象,故障识别率达到99.38%。通过与其他时频图故障诊断方法对比,所提方法准确率明显提升,为精确感知一次设备状态提供了参考。The feature omission problem may occur when the time-frequency method is applied in the fault diagnosis for the vacuum contactor.Therefore,the modal time-frequency diagram(MTFD)is adopted to describe the characteristics of vibration signals,and an integrated method of MTFD and ResNet50 is proposed to identify the fault.First,the fault simulation schemes are set up and the down sampling method is introduced to enrich the sample database.Then,the Gray Wolf optimization method is employed to optimize the parameters of the variational mode decomposition(VMD)algorithm,which guarantees the VMD to decompose the complex vibration signal into the intrinsic mode functions(IMFs)with certain bandwidth and center frequency.Finally,a feature extraction method called modal time-frequency diagram is introduced,which is generated from the IMFs by the Wavelet Transform.The features of vibration signal are fully extracted and regarded as the input of the ResNet50 to identify the faults.ZKTJ–400/1140 vacuum contactor is tested with 99.38%recognition rate.Compared with other methods,the proposed method can be employed to achieve higher accuracy and provide reference for the accurate situational awareness of the primary equipment.
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