Power equipment surface defect detection method and device based on machine learning
A technology for electric equipment and defect detection, applied to instruments, computer components, image data processing, etc., can solve problems such as low efficiency and heavy workload, and achieve the effect of improving efficiency and recognition accuracy
Pending Publication Date: 2022-03-08
北京中拓新源科技有限公司
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Problems solved by technology
[0003] The present invention provides a method and device for detecting surface defects of electric equipment based on machine learning to solve the problem that surface defects of existing electric equipment are often monitored by video and manually identified by relevant personnel through video, which has low efficiency and heavy workload. big problem
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[0028] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention. The technical solutions provided by various embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.
[0029] To overcome the deficiencies of the prior art, the present invention uses smoke videos captured by low-cost cameras in the visual domain, and improves smoke detection by implementing a powerful cla...
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The invention discloses a method and a device for detecting surface defects of power equipment based on machine learning. The invention provides an electrical equipment surface defect detection method and device based on machine learning, and the method comprises the steps: obtaining an electrical equipment surface normal image and an electrical equipment surface defect image, and forming an electrical equipment surface image data set; according to the surface image data of the power equipment, training a Tiny-YOLO-v2 power equipment surface defect detection model; the architecture of the Tiny-YOLO-v2 power equipment surface defect detection model comprises a convolutional layer, an activation function and a plurality of pooling layers; receiving a real-time monitoring image of the surface of the power equipment; the surface of the power equipment is input into the Tiny-YOLO-v2 power equipment surface defect detection model; and outputting a detection result of the Tiny-YOLO-v2 electrical equipment surface defect detection model. Related personnel do not need to carry out manual recognition through videos, the efficiency is remarkably improved, and the recognition accuracy is remarkably improved.
Description
technical field [0001] The invention relates to the technical field of defect detection, in particular to a method and device for detecting surface defects of electrical equipment based on machine learning. Background technique [0002] The insulation health of power equipment is the basis for ensuring the reliability of power supply and the fundamental guarantee for safe production of power. With the continuous improvement of power transmission and transformation, the voltage level is also increasing, and the reliable operation and fault diagnosis of electrical equipment are becoming more and more important. Judging from the statistics of on-site faults, the surface defects of electrical equipment are irreversible and cumulative, and the probability of eventually causing breakdown or flashover faults is much higher than that of other types of defects. Especially the surface discharge of solid insulation will damage the insulation in a short time and cause serious damage to...
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IPC IPC(8): G06T7/00G06N3/04G06V10/774G06V10/82
CPCG06T7/0004G06T2207/20081G06T2207/20084G06N3/045G06F18/214
Inventor 李庆光张文杰兰彩霞魏东华王纯月
Owner 北京中拓新源科技有限公司