Visual detection method of shockproof hammer defect detection

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-...

Examples

Embodiment

[0067] Example: as Figure 1-4 As shown, a visual inspection method for the defect detection of shock-proof hammer, the method includes the following steps:

[0068] Step 1: Preprocess the transmission line image collected by the UAV to detect whether there is a quality problem in the captured image, and perform denoising and anti-shake operation on the data;

[0069] Step 2, data expansion, before sample collection, first perform data expansion on the preprocessed data in step 1 to generate similar images;

[0070] Step 3, collect samples: use the method of collecting anti-vibration hammers unilaterally to collect samples of the image samples expanded in step 2. During the sample collection process, ensure that different anti-vibration hammer types and more than 500 anti-vibration hammer bodies each, and the samples are collected. The total number is not less than 4000;

[0071] Step 4: Determine the selection of the region to be trained, use the information introduced into...

Embodiment 2

[0112] Embodiment 2: a visual detection method for the detection of shock-proof hammer defects, the method comprises the following steps:

[0113] Step 1: First, preprocess the UAV aerial image. Since the aerial images collected by the aircraft inspection are carried out in the wild natural environment, the images are seriously affected by noise and motion blur during the collection process, resulting in serious degradation of the images, that is, distortion, blur, distortion or distortion during the imaging process. Mixed with noise, the image quality is degraded. At the same time, due to the limitation of lighting conditions, the exposure is poor (under or over) and the image is uneven. Therefore, it is important to analyze and detect the collected aerial images. The most important part is the preprocessing of aerial images. The purpose of aerial image preprocessing is to use a series of technical means to improve the quality of the image, suppress various interference sign...

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-...

Examples

Embodiment

[0067] Example: as Figure 1-4 As shown, a visual inspection method for the defect detection of shock-proof hammer, the method includes the following steps:

[0068] Step 1: Preprocess the transmission line image collected by the UAV to detect whether there is a quality problem in the captured image, and perform denoising and anti-shake operation on the data;

[0069] Step 2, data expansion, before sample collection, first perform data expansion on the preprocessed data in step 1 to generate similar images;

[0070] Step 3, collect samples: use the method of collecting anti-vibration hammers unilaterally to collect samples of the image samples expanded in step 2. During the sample collection process, ensure that different anti-vibration hammer types and more than 500 anti-vibration hammer bodies each, and the samples are collected. The total number is not less than 4000;

[0071] Step 4: Determine the selection of the region to be trained, use the information introduced into...

Embodiment 2

[0112] Embodiment 2: a visual detection method for the detection of shock-proof hammer defects, the method comprises the following steps:

[0113] Step 1: First, preprocess the UAV aerial image. Since the aerial images collected by the aircraft inspection are carried out in the wild natural environment, the images are seriously affected by noise and motion blur during the collection process, resulting in serious degradation of the images, that is, distortion, blur, distortion or distortion during the imaging process. Mixed with noise, the image quality is degraded. At the same time, due to the limitation of lighting conditions, the exposure is poor (under or over) and the image is uneven. Therefore, it is important to analyze and detect the collected aerial images. The most important part is the preprocessing of aerial images. The purpose of aerial image preprocessing is to use a series of technical means to improve the quality of the image, suppress various interference sign...

Images