Abstract：Pressure pulsation during the operation of hydroelectric generating unit (HGU) is inevitable phenomenon. Diagnosing and assessing accurately pulsation state are of particular importance. In view of the pressure pulsation is closely related to the operating state of HGU, a novel diagnosis strategy based on working condition is proposed in this paper: Firstly, contribution rates based on mutual information analysis is computed to extract the superior condition parameters, and this superior condition parameters and time-frequency of pulsation signals are fused, the fusion information are considered to the eigenvectors of pressure pulsation. Then, support vector machine (SVM) and extreme learning machine (ELM) are been used to diagnose the pulsation state. Finally, in order to achieve a quantitative diagnosis for pressure pulsation, the degradation function is given with fuzzy evaluation theory. The results of a real example show that this diagnosis strategy is better than the traditional time-frequency diagnosis strategy, and it is of practical guiding significance to safety and stable operation of unit to quantify pulsation assessment.
朱文龙，周建中，夏鑫，李超顺. 基于水电机组运行工况的水轮机压力脉动诊断策略[J]. 振动与冲击, 2015, 34(8): 26-30.
ZHU Wenlong ZHOU Jianzhon XIA Xin LI Chaoshun. A novel diagnosis strategy for hydraulic turbine pressure pulsation based on operating state of hydroelectric generating unit. JOURNAL OF VIBRATION AND SHOCK, 2015, 34(8): 26-30.
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