基于振动信号的带式运输机轴承故障诊断

Fault Diagnosis of Belt Conveyor Bearing Based on Vibration Signal

针对带式运输机轴承故障,提出一种基于振动信号的轴承故障诊断方法。首先,通过位移传感器采集轴承振动信号;其次,采用小波变换对振动信号进行时频域特征提取,以捕捉信号在不同频率和时间尺度下的局部特征;最后,利用决策树方法分类提取的特征向量,实现对不同轴承故障类型的识别。基于凯斯西储大学轴承数据集进行实验验证,基于多项指标验证该方法的有效性和健壮性。

In this paper,a bearing fault diagnosis method based on vibration signal for belt conveyor is proposed.Firstly,bearing vibration signal is collected by displacement sensor.Secondly,wavelet transform is used to extract the features of vibration signals in time-frequency domain to capture the local features of signals at different frequencies and time scales.Finally,decision tree method is used to classify the extracted feature vectors to realize the identification of different bearing fault types.Based on Case Western Reserve University bearing data set,the validity and robustness of the proposed method are verified by experiments.