Self-diagnosis method of acceleration sensors for locomotive bogie detection

The invention discloses a self-diagnosis method of acceleration sensors for locomotive bogie detection. The method comprises the following sequential steps: firstly, dividing bogie detection points into a plurality of monitoring arrays, wherein each monitoring array detects one type of bearings correspondingly, and each detection point in each monitoring array corresponds to one bearing needing to be detected; secondly, installing one acceleration sensor on each bearing needing to be detected; thirdly, establishing RBF neural network predictors of the acceleration sensors of K detection points in each monitoring array respectively; fourthly, setting the mean value threshold value and the variance threshold value of shock signals of the acceleration sensors during the open-circuit fault, the mean value threshold value and the variance threshold value of the shock signals of the acceleration sensors during the short-circuit fault, and the distance error threshold value of the acceleration sensors; fifthly, completing routing inspection of the multiple monitoring arrays and carrying out fault diagnosis when a locomotive bogie works. By means of the method, the short-circuit fault, the open-circuit fault and other faults of the acceleration sensors can be quickly detected, and the method is of great significance on the safety of locomotive bogie detection.