基于振动信号的低压万能式断路器分合闸故障程度评估方法的研究

发布时间：2019-02-24 11:34

【摘要】：目前设备的机械故障诊断技术的研究多限于定性诊断,而故障诊断中故障程度的定量评估更能有效的指导设备维护。该文提出了一种低压万能式断路器分合闸故障程度定量评估的方法。首先对断路器工作模式进行识别,即利用局部均值分解(local mean decomposition,LMD)将采集到的分合闸振动信号自适应分解,求取主要乘积函数(product function,PF)的改进多尺度排列熵(multi-scale permutation entropy,MMPE)构成特征向量,再经过降维后,作为改进支持向量机(support vector machine,SVM)的输入量,实现断路器工作模式的识别;当断路器处于故障模式时,对采集的振动信号求取多尺度排列熵偏均值(partial mean of multi-scale permutation entropy,PMMPE),作为故障程度定量评估指标,并参照所求得的不同故障模式的故障程度特性曲线,可实现分合闸故障程度的定量评估。经实测数据验证表明,所提方法可以完成断路器工作模式的有效识别,且PMMPE指标相较于峭度、能量和多尺度排列熵平均值指标,能够更加有效的完成低压万能式断路器分合闸故障程度的定量评估。
[Abstract]:At present, the research of mechanical fault diagnosis of equipment is limited to qualitative diagnosis, and the quantitative evaluation of fault degree in fault diagnosis is more effective to guide the maintenance of equipment. In this paper, a quantitative method for evaluating the fault degree of low voltage universal circuit breaker is presented. First of all, the operating mode of circuit breaker is identified, that is, the local mean decomposition (local mean decomposition,LMD) is used to decompose the vibration signal of the switch and the main product function (product function, is obtained. The improved multi-scale permutation entropy (multi-scale permutation entropy,MMPE) of PF is used as the input of the improved support vector machine (support vector machine,SVM) after dimension reduction to realize the working pattern recognition of circuit breakers. When the circuit breaker is in the fault mode, the multi-scale permutation entropy mean value (partial mean of multi-scale permutation entropy,PMMPE) is obtained for the vibration signal collected, which is used as the quantitative evaluation index of the fault degree. According to the obtained characteristic curve of fault degree of different fault modes, the quantitative evaluation of fault degree can be realized. The experimental results show that the proposed method can effectively identify the operating patterns of circuit breakers, and the PMMPE index is compared with the average values of kurtosis, energy and multi-scale permutation entropy. Can more effectively complete the low-voltage circuit breaker open-off fault degree quantitative evaluation.
【作者单位】：河北工业大学;天津市百利电气有限公司;
【基金】：河北省教育厅资助科研项目(ZD2016108) 天津市科技特派员项目(16JCTPJC51700)~~
【分类号】：TM561

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