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Thermal image defect detection method of pressure vessel based on line variable step size segmentation

A defect detection and variable step size technology, applied in the field of defect detection, can solve problems such as low efficiency, poor safety, and long cycle

Active Publication Date: 2018-11-16
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

It does not damage the body, is fast and efficient, and can effectively solve the problems of traditional nondestructive testing methods such as high labor intensity, long cycle, low efficiency, and poor safety, and realize large-area rapid detection and save a lot of manpower and material resources.

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  • Thermal image defect detection method of pressure vessel based on line variable step size segmentation
  • Thermal image defect detection method of pressure vessel based on line variable step size segmentation
  • Thermal image defect detection method of pressure vessel based on line variable step size segmentation

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Embodiment

[0071] figure 1 It is a flow chart of the thermal image defect detection method of the pressure vessel based on the row and column variable step length division of the present invention.

[0072] In this embodiment, a thermal image defect detection method of a pressure vessel based on row-column variable-step segmentation of the present invention includes the following steps:

[0073] S1. The eddy current pulse thermal image is represented by a three-dimensional matrix S, where S(i,j,:) represents the ith row and the jth column of the three-dimensional matrix S, and the third dimension represents time;

[0074] S2. Select the point S(I) with the largest pixel value from the three-dimensional matrix S zz , J zz ,T zz ), where I zz , J zz and T zz Respectively represent the row corresponding value, column corresponding value and time corresponding value of the maximum pixel value point;

[0075] S3. Set K temperature thresholds T(m) from large to small, m=1, 2,...,K, set ...

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Abstract

The invention discloses a thermal image defect detection method of a pressure vessel based on line variable step size segmentation. The method comprises the following steps: selecting a maximum pixelvalue point from eddy current pulse thermal image, computing a related coefficient by utilizing a Pearson correlation coefficient method according to the maximum pixel value point, and then obtainingthe conversion step size; computing the transient thermal response of each pixel point by combining the conversion step size, and performing classification processing; and performing defuzzfication onall pixel points by utilizing the membership maximization principle to obtain the category of each pixel point; and finally performing feature extraction by adopting a Canny operator algorithm afterperforming dimension-reduction processing, thereby extracting the defect feature in the eddy current pulse thermal image.

Description

technical field [0001] The invention belongs to the technical field of defect detection, and more particularly relates to a thermal image defect detection method of a pressure vessel based on row-column variable-step division division. Background technique [0002] The manufacture of high-pressure vessels involves the cooperation of disciplinary knowledge and expertise in multiple industries, including: metallurgy, rot and protection, machining, safety protection, chemical industry, and testing. With the continuous advancement of technology in various industries in recent years, especially the development of metallurgy, machining, welding and non-destructive testing driven by the rapid development of computer technology, pressure vessel manufacturing technology has made great progress. [0003] Gas compression technology is widely used in natural gas vehicle charging stations and compressed air powered vehicle charging stations, while natural gas vehicle charging stations an...

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Application Information

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IPC IPC(8): G06T7/00G06T7/136G06T7/155
Inventor 程玉华殷春张博黄雪刚陈晓辉张昊楠薛婷
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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