小波变换应用于水轮机空化信号检测  

Wavelet transforms applied to cavitation noise analysis for hydro-turbine

作　　者：王佳俊[1] 潘罗平[2] 曹树良[1] 

机构地区：[1]清华大学水沙科学与水利水电工程国家重点实验室热能工程系,北京100084 [2]中国水利水电科学研究院,北京100084

出　　处：《水力发电学报》2013年第4期215-220,共6页Journal of Hydroelectric Engineering

基　　金：国家自然科学基金项目(51176088);水沙科学与水利水电工程国家重点实验室开放研究基金资助课题(sklhse-20012-E-02);中国博士后科学基金面上资助项目(2011M500315)

摘　　要：水轮机中的空化现象成因复杂,影响水轮机性能和使用寿命,危害很大。通过测量空化噪声信号监测空化发展程度是防止机组在空化状态下运行的一个重要方法。空化噪声信号是典型的突变信号,单纯依靠频谱分析难以确定不同空化程度下对应的噪声信号特点。小波变换良好的时频局部化特性使其能够很好地处理信号突变点。本文尝试应用小波变换处理空化噪声信号,通过小波变换的模极大值来描述空化噪声信号的奇异性,提出了2个新的参数用以描述不同空化程度下噪声信号的特点。将该方法应用于实测数据分析的结果表明:该方法能够提供更多噪声信号中的突变信息,可以更好的帮助判断空化发展的程度,对于监测空化状态是非常有效的。Cavitation in hydro-turbine is a complicated and harmful problem, which can affect its performances and shorten its life, and cavitation noise measurement is an important way to monitor cavitation. Typical cavitation noises are abrupt signal and their features are difficult to identify by traditional spectrum analysis. Wavelet transform has a nice local characteristic both in time and frequency domains, and provides an excellent tool for processing of abrupt signal. This paper applies wavelet transform to cavitation noise evaluation, and describes the singular features of cavitation noises using the extreme amplitude values in the transformed domain. Two new parameters are suggested to describe the characteristics of cavitation noises under different cavitation degrees. Application to real data analysis shows that this new method provides more information on abrupt changes in cavitation noises signals, and is useful in identification of cavitation development stage.

关 键 词：水力机械 奇异性检测 小波变换 空化噪声 

分 类 号：TV136.1[水利工程—水力学及河流动力学]