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

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。

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.