Fault diagnostic method and diagnostic device of sensor

The invention embodiment discloses a fault diagnostic method and diagnostic device of a sensor. The method includes the following steps: receiving output signals of the sensor; utilizing a wavelet packet to analyze the output signals; screening the conversion coefficient of the wavelet packet with the maximum amplitude, so as to reserve the data capable of representing the fault features; performing feature extraction according to the change rate of the component energies of the frequencies of the sensor, so as to obtain feature vectors; and inputting the feature vectors into a specified neural network, so as to obtain the fault type of the sensor, wherein the node number of the input and output layers of the neural network are determined by the dimension numbers of the feature vectors and the fault type numbers of the sensor respectively, and the network weight and the threshold are determined by training through a training sample. The fault diagnostic method and diagnostic device adopt the wavelet packet to perform refinement partition of the dynamic signals of the sensor, and determine the fault type of the sensor according to the output of the neural network, so as to effectively diagnose the catastrophic fault of the sensor.