Belt conveyer key component automatic identification method based on infrared thermography

Abstract

The invention discloses a belt conveyer key component automatic identification method based on infrared thermography. An acquired belt conveyer infrared image is preprocessed by adopting bilateral filtering and a piecewise linear transform algorithm; image segmentation is performed by adopting an improved region growing method; a Zernike moment is extracted to act as a shape feature vector for belt conveyer key component target classification, and entropy and contrast are extracted to act as a texture feature vector for belt conveyer key component target classification; and a classifier based on a BP neural network is designed, and classification and identification of the belt conveyer key component infrared image are completed by utilizing the extracted shape features and texture features. The key components in the belt conveyer infrared monitoring image can be automatically identified through integration of an infrared thermal imaging technology, a computer technology and an image processing and identification technology so that the necessary technical support is provided for fault early warning of a belt conveyer of an underground coal mine, and the method has important meaning for guaranteeing safe operation of the belt conveyer.

Description

technical field [0001] The invention belongs to the field of mining equipment operation state monitoring, and in particular relates to an automatic identification method for key components of a belt conveyor based on infrared thermal images. Background technique [0002] The safe operation of the belt conveyor is a major issue related to the safe production of coal mines, so the monitoring of the running status of the belt conveyor is very necessary. Since many key faults of the belt conveyor are manifested by temperature abnormalities, using infrared thermal imaging technology, it is possible to diagnose and analyze the thermal faults of the belt conveyor without sampling, disassembly, or power failure, quickly and It is convenient to judge the thermal faults of key components such as belt conveyor motors, idlers, and rollers. Diagnostic rules for specific diagnoses. Therefore, the identification of the key components of the belt conveyor is the prerequisite for the fault...

AI Technical Summary

Problems solved by technology

The shape feature Zernike moment is effective for the obtained target contour as a complete closed contour, but if the parts obtained from the shooting angle are partially occluded, there is a great inaccuracy in identifying key parts only by using shape features. Compared with visible light images, Infrared images provide less texture information, but with the gradual maturity of infrared imaging technology, the accuracy of collected infrared images has been greatly improved, which provides the possibility for texture feature analysis of infrared images

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