Ventilation equipment blade quality detection method, device and system based on image processing

Abstract

The invention discloses a ventilation equipment blade quality detection method, device and system based on image processing, and relates to the field of artificial intelligence. The method mainly comprises the steps that a blade surface image of ventilation equipment to be detected is acquired and preprocessed to obtain a gray level image of a blade; obtaining an abnormal point in the gray level image according to the gradient magnitude of the pixel point in the gray level image and the gradient magnitude of the pixel point in the pixel point neighborhood; dividing the abnormal points in the sliding windows with the same preset size into the same category so as to obtain a plurality of categories after dividing all the abnormal points; carrying out mean shift clustering on intersection points of the gradient directions of the abnormal points contained in the category, and obtaining defect points in the grayscale image according to the proportion of pixel points contained in a clustering result in pixel points in the category; and obtaining the defect severity according to the dispersion degree of the defect points and the number of the defect points, and detecting the quality of the ventilation equipment blade by using the defect severity.

Description

technical field [0001] The present application relates to the field of artificial intelligence, in particular to an image processing-based quality detection method, device and system for ventilation equipment blades. Background technique [0002] The mine ventilation system occupies an extremely important position in all mine production unit systems. In order to ensure the safe production of the mine, the mine ventilation system, a dynamic system, must be able to maintain the best operating condition for a long time. However, in actual production practice, various factors are constantly affecting the normal operation and function of the mine ventilation system. Any slight external disturbance and internal factor changes will cause the ventilation system itself and its The possibility of failure of sub-units is greatly increased, the reliability and effectiveness of the ventilation system are greatly reduced, and even catastrophic accidents may be caused, resulting in serious...

AI Technical Summary

Problems solved by technology

However, in actual production practice, various factors are constantly affecting the normal operation and function of the mine ventilation system. Any slight external disturbance and internal factor changes will cause the ventilation system itself and its The possibility of failure of sub-units is greatly increased, the reliability and effectiveness of the ventilation system are greatly reduced, and even catastrophic accidents may be caused, resulting in serious social impact and huge economic losses

[0003] The quality problem of ventilation equipment is the key to affecting the normal operation and function of the ventilation system. The blades of the ventilation equipment are the key sub-components. If the quality defects of the blades cannot be dealt with in time, the local defects will continue to expand, and eventually cause serious quality problems of the blades. , may cause serious accidents in production practice

Blade quality problems are usually surface defects of blades. Due to poor quality control of the manufacturing process, surface defects such as sagging, whitening, scratches, and pinholes often occur. Such defects are local defects, and the traditional threshold segmentation method is used. Corresponding detection can be carried out, but the traditional threshold segmentation method is difficult to segment the paint bubble defects on the blade surface

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