Detecting Steam Leakage in Nuclear Power Systems Based on the Improved Background Subtraction Method

Author:

Liu Jie1,Huang Yanping1,Zhang Minglu1,Zhou Suting1,Nie Changhua1,Li Minggang1,Zhang Lin12

Affiliation:

1. Nuclear Power Institute of China, Chengdu 610213, China

2. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Abstract

As a key system in nuclear power plants, nuclear power systems contain high-temperature, high-pressure water media. A steam leak, if it occurs, can at minimum cause system functional loss and at worst lead to casualties. Therefore, it is urgent to carry out steam leakage detection work for high-temperature, high-pressure loop systems. Currently, steam leaks are primarily detected through visual monitoring and pressure gauges. However, if there is a minor leak under high system pressure, the slight decrease in pressure may not be enough to alert the operators, leading to a delay in detecting the steam leak. Thus, this detection method has certain drawbacks. In view of these issues, this paper introduces computer vision technology to monitor the high-temperature, high-pressure loop system and proposes the use of an improved background subtraction method to detect steam leaks in the loop system. The results show the following advantages of this method: (1) It can effectively identify steam leaks at an early stage; (2) it overcomes the difficulty of determining the threshold value for the binarization of grayscale images in traditional background subtraction methods; (3) it eliminates the noise impact brought by the binarization of grayscale images in existing improved background subtraction methods. The introduction of this method provides a new approach for detecting steam leaks in high-temperature, high-pressure loop systems and can be effectively applied in engineering fields. It also offers reference value for the detection of high-temperature, high-pressure media leaks in other fields.

Funder

Key Research Program of Sichuan Province

Publisher

MDPI AG

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