摘要
介绍适用于大型机械设备变工况非平稳在线和离线动态分析与监测诊断的关键技术:小波包频带能量监测、小波包自回归谱分析、谐波小波分析、小波分形分析、广义自适应小波分析、主分量自回归谱模糊识别、小波包模糊聚类网络分类、机械设备监测诊断装置与系统等。举例说明了这些技术在工程中的应用,成功地诊断出松动、喘振、轴承缺陷、摩擦、不对中、失衡等多种机械故障。
This paper introduces key technologies on dynamic analysis and monitoring-diagnosis of varying operation and nonstationarity, which are suitable for large mechanical equipment under on-line and off-line conditions. They are frequency band energy monitoring via wavelet packets, spectral analysis of wavelet-autoregressive, harmonic wavelet analysis, wavelet fractal analysis, generalized adaptive wavelet analysis, fuzzy identification using principal component and autoregressive spectrum, fuzzy cluster neural network based on wavelet packets, monitoring- diagnosis device and systems for mechanical equipment etc. Engineering applications are illustrated with examples. Mechanical faults like looseness, surge, bearing defect, friction, misalignment, unbalance and so on were diagnosed successfully.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
1999年第9期978-981,共4页
China Mechanical Engineering
基金
国家自然科学基金
关键词
机械设备
变工况
非平稳
动态分析
监测诊断
mechanical equipment varying operation nonstationarity dynamic analysis monitoring-diagnosis