The poor diagnosis performance of abnormal vibration fault of variable speed running gear will increase the vehicle maintenance cost and shorten the service life of the gear.In order to identify the gear fault in time and ensure that the vehicle transmission assembly has good vibration characteristics,a method for diagnosing abnormal vibration fault of variable speed running gear based on multi-sensor data fusion was proposed.The multi-sensor data fusion technology was analyzed,the theoretical framework of abnormal vibration fault diagnosis of variable speed running gear was grasped.On this basis,referring to the sensor fusion module,feature level parallel multi neural network local diagnosis module and terminal classification module,and combining the variational mode decomposition,multi-channel weighted fusion and single hidden layer feedforward neural network training algorithm,the fault diagnosis of abnormal vibration of variable speed running gear was realized from signal acquisition,signal feature extraction and signal feature classification.The experimental results show that when the gear is slightly worn,the amplitude of wear vibration signal is from 20 mV to 40 mV,and the frequency of wear vibration signal is from 0 to 4 000 Hz; in case of moderate wear,the signal amplitude is from 30 mV to 55 mV and the signal frequency is from 3 000 Hz to 7 000 Hz; in case of severe wear,the signal amplitude is from 50 mV to 70 mV,the signal frequency is from 6 000 Hz to 12 000 Hz,and the diagnosis results at each stage are consistent with the actual turning point of the fault degree.It can be seen that in the case of the same number of samples,the predicted value and the true value of the proposed fault diagnosis method are the same,and the diagnosis performance to fault degree and fault type is good.