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Shockproof hammer defect detection method, device and equipment and storage medium

A defect detection and anti-vibration hammer technology, applied in character and pattern recognition, image data processing, instruments, etc., can solve problems such as low detection accuracy, inability to meet the needs of transmission line inspection, meet accuracy requirements, and improve richness. , the effect of improving the accuracy

Pending Publication Date: 2022-04-12
BEIJIG YUPONT ELECTRIC POWER TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the current mainstream target detection model has low detection accuracy and cannot meet the inspection requirements of transmission lines.

Method used

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  • Shockproof hammer defect detection method, device and equipment and storage medium
  • Shockproof hammer defect detection method, device and equipment and storage medium
  • Shockproof hammer defect detection method, device and equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0032] figure 1 It is a flow chart of a method for detecting a defect in an anti-vibration hammer provided in Embodiment 1 of the present application. The embodiments of the present application are applicable to the detection of anti-vibration hammers of power transmission lines. The method can be implemented by a device for detecting vibration-proof hammer defects. The device can be implemented by software and / or hardware, and is specifically configured in electronic equipment.

[0033] refer to figure 1 A method for detecting a defect of a shockproof hammer specifically includes the following steps:

[0034] S110. Acquire a zoomed image in at least one scale obtained after feature extraction of the image to be detected; wherein, the image to be detected includes an anti-vibration hammer to be detected.

[0035] Wherein, the image to be detected is an image in which defect detection needs to be performed on the anti-vibration hammer to be detected. Feature extraction can b...

Embodiment 2

[0054] figure 2 It is a flow chart of a method for detecting a defect of an anti-vibration hammer provided in Embodiment 2 of the present application. The embodiment of the present application refines the acquisition operation of the residual enhancement map on the basis of the technical solutions of the foregoing embodiments, so as to improve the accuracy of the defect detection of the anti-vibration hammer.

[0055] refer to figure 2 A method for detecting a defect of a shockproof hammer specifically includes the following steps:

[0056] S210. Acquire a scaled image of at least one scale of the image to be detected after feature extraction; wherein, the image to be detected includes an anti-vibration hammer to be detected.

[0057] S220. Process each scaled image to obtain a scaled feature map in at least one scale.

[0058] S230. Use the scaled image in at least one scale as the current feature map.

[0059] The scaled feature map at least one scale is used as the cu...

Embodiment 3

[0078] Figure 3A It is a flowchart of defect detection of anti-vibration hammer provided in Embodiment 3 of the present application. The embodiment of the present application is a preferred embodiment provided on the basis of the foregoing embodiments, and is applied to an electronic device. refer to Figure 3A , the method specifically includes:

[0079] S310. Use unmanned to collect image data.

[0080] The anti-vibration hammer of the field transmission line is captured by a remote-controlled drone.

[0081] S320. Mark the image data and create an image data set.

[0082] Using the method of manual labeling to classify and label the collected images of anti-vibration hammers, two classifications can be performed first, that is, the collected images are marked as "with anti-vibration hammers" and "without anti-vibration hammers", and then from "with anti-vibration hammers" For example, it can be divided into: anti-vibration hammer is normal, anti-vibration hammer is da...

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Abstract

The embodiment of the invention discloses a stockbridge damper defect detection method and device, equipment and a storage medium. The method comprises the following steps: acquiring a scaled image of a to-be-detected image under at least one scale after feature extraction; wherein the to-be-detected image comprises the to-be-detected shockproof hammer; processing each scaled image to obtain a scaled feature map under at least one scale; performing feature enhancement on the at least one zoomed image to obtain a residual enhancement image; fusing the residual enhancement image and the scaled feature images under each scale to obtain a fused feature image; and determining the defect condition of the to-be-detected shockproof hammer in the to-be-detected image according to the fused feature map. The method has the advantages that the feature information lost in calculation of the scaled feature graph can be supplemented by generating the residual enhancement graph, the richness of the feature information in the fused image is improved, the defect detection precision is further improved, and the accuracy requirement in line inspection is met.

Description

technical field [0001] The embodiments of the present application relate to the technical field of machine learning, and in particular, to a method, device, device and storage medium for detecting a defect of a vibration-proof hammer. Background technique [0002] In the overhead transmission line, due to the influence of environmental factors, all kinds of electrical equipment are prone to damage and other conditions, resulting in the failure of the normal operation of the transmission line. Therefore, in the inspection process of transmission lines, detecting the use status of various electrical equipment is one of the important tasks of inspection. [0003] The traditional inspection of transmission lines requires manual visual inspection, which consumes a lot of manpower and material resources. At this stage, technicians use drones to take aerial photos of power transmission lines, and process the captured images to detect the use status of various electrical equipment....

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06V10/40G06K9/62G06T3/40G06V10/80
Inventor 夏春磊魏威杨奎刚
Owner BEIJIG YUPONT ELECTRIC POWER TECH
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