Vibration signal fault diagnosis method and device, equipment and storage medium

The invention discloses a vibration signal fault diagnosis method and device, equipment and a storage medium, and the method combines a continuous FRFT time-frequency spectrogram with a neural network, collects and builds an equipment vibration signal fault data set through the frequency-phase feature extraction capability of FRFT and the local feature analysis capability of the neural network, and achieves the fault diagnosis of a vibration signal. The data set is used for training an image classification neural network, the neural network obtained through training is used for reasoning, and fault judgment and classification are effectively carried out on the collected vibration signals. Fault diagnosis can be accurately carried out on the vibration signal, and the fault type and cause can be timely judged, so that the operation safety of mechanical equipment is improved. 本发明公开了一种振动信号故障诊断方法、装置、设备及存储介质，该方法将连续FRFT时频谱图和神经网络结合在一起，利用FRFT的频率-相位特征提取能力和神经网络的局部特征分析能力，采集和建立设备振动信号故障数据集，使用该数据集训练图像分类神经网络，使用训练得到的神经网络进行推理，