Locomotive running gear fault detection method and device based on time sequence images and storage medium

A technology for fault detection and running parts, which is applied in image analysis, image data processing, graphics and image conversion, etc.

Pending Publication Date: 2020-12-04
CENT SOUTH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the deficiencies of the above-mentioned prior art, the present invention aims at the characteristic that the locomotive shape changes little in a short period of time but changes greatly in a long time, and provides a time-series image-based l

Method used

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  • Locomotive running gear fault detection method and device based on time sequence images and storage medium
  • Locomotive running gear fault detection method and device based on time sequence images and storage medium
  • Locomotive running gear fault detection method and device based on time sequence images and storage medium

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Experimental program
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Embodiment 1

[0063] This embodiment provides a time-series image-based fault detection method for running parts of a locomotive, including:

[0064] S01: Obtain a time-series image dataset of the running part of the locomotive;

[0065] During implementation, the position of the high-definition camera is fixed, and the same running part of the locomotive is photographed at a fixed time interval to obtain z normal image data sets {x 1 , x 2 ,...,x z}, where x i Indicates the image collected for the i-th time.

[0066] S02: Perform unified size preprocessing on the acquired time-series image data set of the running part of the locomotive;

[0067] Since the positions of the locomotives cannot be exactly the same every time they stop, there are problems of geometric changes and inconsistencies in the size of the intercepted key part data set pictures. In order to unify the size of the image, based on the acquired time series image data set of the running part of the locomotive, the inter...

Embodiment 2

[0099] This embodiment provides a time-series image-based fault detection device for running parts of a locomotive, including:

[0100] The image acquisition module is used to acquire the time-series image data set of the running part of the locomotive, and perform unified size preprocessing;

[0101] The time series residual data set acquisition module is used to select a number of normal and fault-free sequence images based on the preprocessed locomotive running part time series image data set, and perform the gray level difference between two time series adjacent images in order to obtain the time series Residual dataset;

[0102] The standard template acquisition module is used to calculate the gray average value of the image in the time series residual data set to obtain the standard template;

[0103] The similarity acquisition module is used to randomly extract a preset number of images from the time series residual data set, and calculate its structural similarity with ...

Embodiment 3

[0122] In a third aspect, a computer-readable storage medium is provided, which stores a computer program, and the computer program is adapted to be loaded by a processor and execute the time-series image-based fault detection method for running parts of a locomotive as described in Embodiment 1.

[0123] Those skilled in the art should understand that the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

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Abstract

The invention discloses a locomotive running gear fault detection method and device based on time sequence images and a storage medium, and the method comprises the steps: obtaining a locomotive running gear time sequence image data set, and unifying the size; selecting a plurality of normal fault-free sequence images, and performing gray scale difference of two adjacent images in a time sequenceto obtain a time sequence residual data set; calculating an image gray average value in the time sequence residual data set to obtain a standard template; extracting a plurality of images from the time sequence residual data set, and calculating the structural similarity between the images and a standard template based on an image structural similarity algorithm to obtain a similarity matrix; calculating parameters [theta] and [epsilon] based on the similarity matrix; for the to-be-detected image M, calculating the gray difference M' between the to-be-detected image M and the image adjacent tothe to-be-detected image M in time sequence; and calculating the structural similarity MS between M'and the standard module, if MS theta is less than epsilon, determining that M is a normal image, and otherwise, determining that M is a fault image. The method can solve a problem that a single standard template cannot effectively detect a fault when the shape of a to-be-detected object changes with time.

Description

technical field [0001] The invention relates to the field of locomotive fault detection, in particular to a fault detection method, device and storage medium for a running part of a locomotive based on time-series images. Background technique [0002] The railway is an important infrastructure of the country, which undertakes the main tasks of passenger transportation and commodity circulation. At the same time, the railway transportation industry is also a pillar industry of the national economy. With the rapid development of my country's national economy, the demand for passenger and freight transportation is increasing year by year, and the operating mileage of railway transportation is also increasing year by year. [0003] The continuous growth of railway demand for rolling stock has made the society put forward higher requirements for railway traffic safety. The automatic detection of train faults is a field closely related to the safety of railway traffic. The tradit...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T3/40G06F17/11
CPCG06T3/4007G06F17/11G06T7/0002
Inventor 齐倩倩龙军章成源钟思伟
Owner CENT SOUTH UNIV
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