Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A Visual Inspection Method for Defect Detection of Anti-vibration Hammer

A defect detection and visual inspection technology, used in image analysis, image enhancement, instruments, etc., can solve the problems of research on the defect detection of anti-vibration hammer, it cannot be used well, and it is not universal and accurate.

Active Publication Date: 2018-07-06
GUIZHOU POWER GRID CO LTD
View PDF5 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The above methods are not universal and accurate, and cannot be well applied to actual systems
At the same time, these methods failed to make a study on the defect detection of anti-vibration hammer

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Visual Inspection Method for Defect Detection of Anti-vibration Hammer
  • A Visual Inspection Method for Defect Detection of Anti-vibration Hammer
  • A Visual Inspection Method for Defect Detection of Anti-vibration Hammer

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0066] Example: such as Figure 1-4 Shown, a kind of visual detection method of antivibration hammer defect detection, this method comprises the following steps:

[0067] Step 1. Preprocess the transmission line images collected by the UAV, detect whether there are quality problems in the captured images, and perform denoising and anti-shake operations on the data;

[0068] Step 2, data expansion, before sample collection, first perform data expansion on the preprocessed data in step 1 to generate similar images;

[0069] Step 3, collect samples: Use the method of collecting one side of the anti-vibration hammer to sample the image sample expanded in step 2. During the sample collection process, ensure that there are more than 500 different types of anti-vibration hammers and more than 500 different anti-vibration hammer bodies. The total number is not less than 4000;

[0070] Step 4, determine the area selection to be trained, use the information of the image segmentation t...

Embodiment 2

[0111] Embodiment 2: a kind of visual detection method of antivibration hammer defect detection, this method comprises the following steps:

[0112] Step 1: First, preprocess the aerial images of the UAV. Since the aerial image collection by aircraft inspection is carried out in the natural environment in the field, the image is very seriously affected by noise and motion blur during the acquisition process, resulting in serious image degradation, that is, distortion, blur, distortion or distortion in the imaging process. The noise is mixed in, resulting in a decline in image quality. At the same time, due to the limitation of lighting conditions, poor exposure (under or over) and uneven brightness of the image screen are caused during photography. Therefore, it is important to analyze and detect the collected aerial images. The most important link is the preprocessing of aerial images. The purpose of aerial image preprocessing is to use a series of technical means to improve...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a visual detection method of shockproof hammer defect detection. The visual detection method comprises the steps that denoising and anti-shaking preprocessing is performed on an aerial photographing image so as to obtain an original image to be detected; the existing original image is expanded by using the method of geometric transformation, scale change and contrast transformation so as to generate more data similar to the original image; samples are acquired, a shockproof hammer in the aerial photographing image is acquired and the size of the shockproof hammer is mainly acquired; a network model to be trained is determined, and the sample data are inputted to perform forward propagation and reverse propagation to adjust the weight so as to obtain the optimized detection network model parameters; the image to be detected is identified by using the trained model and the position of the hammer of the shockproof hammer is determined; and the lead in which the hammer is located is determined, and shockproof hammer defect discrimination is performed according to the relative position of the lead and the shockproof hammer and the constraints of respective directions.

Description

technical field [0001] The invention relates to a visual detection method for anti-vibration hammer defect detection, and belongs to the technical field of anti-vibration hammer defect detection for transmission line UAV images. Background technique [0002] Since the transmission line is exposed to the outdoors for a long time, it is subject to wind and rain, it is greatly affected by the natural environment, and the frequency of failures is relatively high. The line inspection method is actively adopted, and the prior inspection and repair of various defects of each component has become the focus of research. When the wire is subjected to wind force, it will vibrate. When the conductor vibrates, the working conditions are the most unfavorable where the conductor is suspended. Due to multiple vibrations, the wire will be fatigued and damaged due to periodic bending. Therefore, the anti-vibration hammer can reduce the vibration of the wire due to the wind. Once the anti-...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00G06T7/73
CPCG06T7/0004G06T7/73G06T2207/20084G06T2207/30164G06T2207/30181
Inventor 虢韬杨恒王伟时磊陈凤翔沈平杨渊刘晓伟李德洋田丁
Owner GUIZHOU POWER GRID CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com