基于改进VMD算法的电机轴承异音识别与定位
Recognition and location of abnormal sound of motor bearing based on improved VMD algorithm
摘 要
针对核电站电机异音人工定位成本高、效率低的问题,提出一种基于改进变分模态分解(VMD)的电机轴承异音识别与定位方法。该方法首先根据改进VMD算法对电机声音信号进行分解,计算最佳模式分量的有效值和峭度指标,初步实现电机异音的识别;其次,通过分析声音在空气中的传播特性,利用不同位置测试信号的有效值实现异音源的定位。最后,笔者设计了电机异音定位模拟试验,验证了所提方法的可行性和有效性。
自适应变分模态分解
异音识别
异音定位
abnormal sound of motor
adaptive variational modal decomposition
abnormal sound recognition
abnormal sound location
Abstract
Aiming at the problem of low efficiency and high cost of manual positioning of abnormal noises in nuclear power plants, this paper proposes a method based on improved variational mode decomposition (VMD) to identify and locate abnormal noises in motor bearings. Firstly, this method first decomposes the motor sound signal according to the improved VMD algorithm, calculates the effective value and kurtosis index of the best mode component, and initially realizes the recognition of the abnormal sound of the motor. Secondly, through the sound propagation characteristics in the air, using the size of the effective value of the test signal at different locations was used to achieve the location of the different sound source. The simulation experiment of the location of abnormal sound of the motor verifies the feasibility and effectiveness of the proposed method.
中图分类号 TG115.28 DOI 10.11973/wsjc202212009
所属栏目 试验研究
基金项目
收稿日期 2021/10/25
修改稿日期
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作者单位点击查看
备注杨磊(1987-),男,本科,工程师,主要从事高压电气设备的管理工作
引用该论文: YANG Lei,WANG Jingqi,LI Liang,GAO Fan,YU Xuan,TANG Guoyun. Recognition and location of abnormal sound of motor bearing based on improved VMD algorithm[J]. Nondestructive Testing, 2022, 44(12): 42～47
杨磊,王镜淇,李亮,高帆,于轩,唐国运. 基于改进VMD算法的电机轴承异音识别与定位[J]. 无损检测, 2022, 44(12): 42～47
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参考文献
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