机械设备滚珠轴承故障声发射信号诊断与监控

Fault diagnosis and monitoring of the acoustic emission signal on the rolling bearing of machanical equipment

滚动轴承受损时产生开放性裂纹,在受到交变循环载荷作用时会产生声发射信号。其信号与零部件形状、结构无关。本文以此为例建立神经网络故障分析诊断机制,在matlab中先做好程序调试,移植入labview中,利用小波分析重构算法,重构出滤波(除噪)后的信号,达到有用信号与噪音分离的目的,判别滚动轴承运行故障,确定检与修的人工处理模式,实现机械故障诊断处理智能化。

The rolling bearing is nondestructive to produce open the crack and under the condition of the alternating loading to produce acoustic emission signal. Regardless of the shape, structure and components of signal, making a neural network fault diagnosis mechanism to do the program debugging in MATLAB, transplanting into labview, using wavelet reconstruction algorithm to reconstruct filter（denoising） after the useful signal and noise signal, in order to achieve the purpose of separation, rolling bearing fault identification, determining the inspection and repairing of the pattern of artificial process.