Full-Amplitude Probability Distribution Analysis-Based Information Entropy Signal Processing Method for Sodium Bubble Detector

Under conditions of high temperature and high pressure, the sodium-cooled fast reactor’s steam generator will leak and cause sodium-water reaction, which may lead to explosion in severe cases. Therefore, timely detection and warning are required at the leakage early stage. Electromagnetic vortex flowmeter (EVFM) can be used for leakage detection of steam generators in sodium-cooled fast reactor. To achieve reliable leak detection, EVFM needs to have fast response time and small leakage detection capabilities. This paper analyzes the full amplitude probability distribution of EVFM signals with or without leakage, and finds the distribution differences of single-peak and double-peak. Considering the randomness of bubble noise, an information entropy based signal processing method for EVFM is proposed, and information entropy is used to measure the uncertainty of signal amplitude waveform. By comparing the information entropy difference at different amplitude segment numbers, the optimal segment number is determined. Finally, a DSP based sodium bubble detection system is developed, and offline and online verification tests were carried out. Results show that the developed system and can detect steam generator leakage as low as 0.1 g/s with a response time less than 1 s.