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Machine vision detection method and system of boiler pipeline surface defect

A machine vision detection and pipeline technology, applied in the direction of instruments, computer components, image data processing, etc., to achieve the effect of protecting edge features and eliminating salt and pepper noise

Active Publication Date: 2018-03-02
CENT SOUTH UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] The technical problem to be solved by the present invention is that: in view of the many disadvantages caused by the current pipeline surface defect detection mainly relying on the naked eye observation of workers, the present invention provides a machine vision detection method and system for boiler pipeline surface defects. High precision

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  • Machine vision detection method and system of boiler pipeline surface defect
  • Machine vision detection method and system of boiler pipeline surface defect
  • Machine vision detection method and system of boiler pipeline surface defect

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Embodiment Construction

[0076] The present invention will be further described below in conjunction with drawings and embodiments.

[0077] Such as figure 1 As shown, the machine vision detection system for boiler pipe surface defects disclosed in the present invention includes an image acquisition unit, an image transmission unit, an image processing unit, a fault judgment unit, and a fault alarm unit. Its specific structure is as figure 2 with 3 As shown, it includes an industrial camera 3, a two-degree-of-freedom platform 2, a lifting platform 1, an illumination system and a host computer; the industrial camera 3 and the illumination system are fixed on the lifting platform 1 through the two-degree-of-freedom platform 2, and the lifting platform 1 And the two-degree-of-freedom pan-tilt 2 drives the industrial camera 3 to move up and down, left and right, and is used to realize the continuous acquisition of boiler pipe surface images; the industrial camera 3 collects boiler pipe surface images ...

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Abstract

The invention discloses a machine vision detection method and a system of a boiler pipeline surface defect. The method comprises the following steps of firstly, collecting a certain number of boiler pipeline surface images and taking as sample images; carrying out preprocessing, dimension reduction and characteristic merging on the images; then, using a genetic algorithm and a SMO algorithm to solve a classification hyperplane with highest accuracy; using the optimal classification hyperplane to determine a decision function; and then, through the decision function, carrying out real-time detection on the boiler pipeline surface images to be detected collected by an industrial camera. In the invention, a classification model is simple and reliable, a correct rate of defect identification is high; and compared with manual boiler surface defect detection, detection efficiency of machine vision detection is greatly increased.

Description

technical field [0001] The invention relates to the technical field of machine vision, in particular to a machine vision detection method and system for surface defects of boiler pipes. Background technique [0002] Since my country's energy is mainly based on fossil fuels such as coal, thermal power will still occupy a dominant position in my country's power supply for a period of time in the future. According to statistics, as of February 2015, there are 1,241 thermal power plants currently in operation in my country, with a total power generation of 916 million kilowatts, accounting for about 67% of the total power generation. Thermal power generation is still the main power generation method of my country's electric energy industry at present. Among the various equipment of thermal power generation, boilers occupy an important position. Together with steam turbines and generators, they are called the "three main engines" of the power plant. They are the main components o...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T5/40G06T5/00G06T7/136G06K9/62G06K9/46
CPCG06T5/40G06T7/0004G06T7/136G06T2207/30168G06T2207/20032G06V10/40G06F18/2411G06T5/70
Inventor 谭建平李臻方宇
Owner CENT SOUTH UNIV
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