Abstract：If loose parts or remaining metal exist in the reactor, they will collide with the pressure boundary and endanger the safety of the reactor. In order to effectively solve the problem of inaccurate identification of reactor metal impact signals caused by insufficient features and unsuitable model, a recognition approach based on variational mode decomposition (VMD) and random forest (RF) was proposed in this paper. The original signal was decomposed into several component signals through the variational mode decomposition method, then the component features were extracted from each component signals to form the original signal eigenvector. To recognize reactor metal impact signal, the original signal eigenvector were used as inputs to build the VMD_RF model to classify impact signal, self-checking signal, pulse spike signal, noise fluctuation signal, channel break signal and noise signal. The feasibility and validity of the method were verified by the data collected by LPMS in nuclear power plant, and the results showed that good recognition results could be obtained by this method.
者娜,刘才学,杨泰波,何攀,简捷,王广金. VMD和随机森林在反应堆金属撞击信号识别中的应用研究[J]. 振动与冲击, 2021, 40(5): 102-107.
ZHE Na, LIU Caixue, YANG Taibo, HE Pan, JIAN Jie, WANG Guangjin. Application of VMD and random forest in reactor metal impact signal recognition. JOURNAL OF VIBRATION AND SHOCK, 2021, 40(5): 102-107.
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