Large-scale train shift fault detection method and system based on deep learning

Abstract

The invention provides a large-scale train shift fault detection method and system based on deep learning. The detection method comprises the steps that of collecting and transmitting a train part shifting image is collected and transmitted into a deep learning framework to train a train part classification model, and obtaining a part shear map is obtained; marking the shear map and transmitting the shear map into a deep learning framework to train a component contour segmentation model; collecting a to-be-detected image, transmitting the to-be-detected image into the train part classification model for prediction, automatically detecting parts according to classification and positioning, and shearing; transmitting the shear map into a component contour segmentation model to segment inner and outer contours of a component, and obtaining relative position information; and setting a threshold value of the relative position information, carrying out logic judgment according to the inner and outer contour relative position information, and judging whether the train part has a displacement fault. Compared with the prior art, automatic detection of mass train part data is effectively achieved, the detection efficiency and accuracy are improved, and the manpower and material resource cost is reduced.

Description

[0001] 【Technical field】 [0002] The invention relates to the field of automatic fault detection, in particular to the field of large-scale train displacement fault detection. [0003] 【Background technique】 [0004] The safe and efficient operation of high-speed trains has always been a major issue. The long-term continuous running of the train for thousands of kilometers, the accelerated wear of the train, the intensified vibration, and the rapid deterioration of performance parameters, etc., these factors seriously threaten the safe operation of the train, reduce the safety factor of the train, and cause safety accidents during the operation of the train. Because these factors are unavoidable, only by timely overhauling the key parts of the train and finding faults can the safe operation of the train and the safety of passengers be guaranteed. [0005] The faults of the key parts of the train mainly include displacement, loss, corrosion, deformation, damage, etc. As one of...

AI Technical Summary

Problems solved by technology

[0009] At present, the signal processing method and image processing method of the existing technology have great limitations in the data volume and accuracy of processing train component faults, and the training and detection efficiency of massive data is low for model training and fault detection in big data scenarios. , the problem of poor tolerance, the present invention provides a method and system for automatically detecting displacement faults of large-scale train components

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