Power plant high-temperature pipeline defect detection and segmentation method based on OTSU and region growing method

Abstract

The invention relates to a power plant high-temperature pipeline defect detection and segmentation method based on OTSU and a region growing method, and the method comprises the following steps: obtaining an original infrared image, carrying out the graying, and extracting a pipeline region through the improved two-dimensional OTSU pre-segmentation; finding out a gray scale range corresponding tothe normal temperature of the pipeline through the gray scale distribution histogram of the pipeline area; judging whether the maximum value of the neighborhood gray average value exceeds a normal gray range or not to finish automatic detection and positioning of the multi-defect seed points; and taking the self-adaptive threshold adjusted according to the gray average value and the standard deviation of the grown region as a growth criterion, and taking a gradient amplitude threshold calculated based on a Prewitt operator as an additional condition to realize growth and extraction of the defect region. Compared with the prior art, the system has the advantages of high reliability and accuracy and good real-time performance, and can meet application requirements.

Description

technical field [0001] The invention relates to the background image processing field of a power plant inspection robot, in particular to a defect detection and segmentation method for a high-temperature pipeline in a power plant based on OTSU and a region growing method. Background technique [0002] The safe production of electric power is related to the stability of all walks of life and society. There are a large number of high-temperature and high-pressure steam pipelines distributed in power plants. Once high-temperature and high-pressure steam leaks due to pipeline defects, the consequences will be disastrous. Electric power inspection is an important means to ensure the stable operation and safe production of power plants. It mainly uses hand-held infrared thermal imaging cameras and other equipment to detect "running, dripping, leaking" of pipelines and valves according to the prescribed inspection line. However, affected by subjective factors and environmental fac...

AI Technical Summary

Problems solved by technology

In recent years, experts and scholars at home and abroad have made corresponding improvements through watershed algorithms and edge detection algorithms for different application scenarios, but none of them can be directly applied to power plant inspection robots to complete the automatic detection of multiple defects in high-temperature and high-pressure pipelines.

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