摘要
将改进的希尔伯特黄应用到泵阀的故障检测,通过对现场采集数据的分析,提出了一种新的识别故障泵阀的简易诊断方式。首先对6个泵阀信号都作EMD分解,用IMF分量数鉴别故障泵阀,故障泵阀含有IMF数量最多,然后再做出每个泵阀信号希尔伯特能量谱,通过故障泵阀具有高能量来进一步证实。结果表明了该方法能够准确有效的判断出故障泵阀。因此相对于可靠性低并对工作人员身体有害的传统方法而言该方法具有可靠性高,对工作人员无害等优点。
The Hilbert-Huang Transform （HHT） is more effective in processing nonlinear and non-stationary signals than traditional signal processing methods, but three problems need to be considered before it can be used in practice： over-decomposition, end effects and mode mixing. Previous work has indicated that these three defects can be overcome to some extent. This paper describes an improved HHT transform which fully overcomes these three problems and can be used to analyze data from tape recorders at the site of a drilling pump valve. Signals from good pump valves can usually be decomposed into 8 Intrinsic Mode Functions （IMFs）, whereas faulty pump valves usually show 10 IMFs. A novel method to identify faulty pump valves is presented, based on comparison of differences in IMFs from six pump valve signals. The accuracy of the method is supported by Hilbert power spectrum analysis. The results showed that this new method can, accurately and efficiently, distinguish between good and faulty pump valves during operation, and that it is an effective replacement for the traditional method of pump valve diagnosis which is harmful and of low efficiency.
出处
《北京化工大学学报（自然科学版）》
CAS
CSCD
北大核心
2008年第4期81-85,共5页
Journal of Beijing University of Chemical Technology(Natural Science Edition)
基金
国家自然科学基金(50575017)
