摘要
为解决盲源分离在分析旋转机械故障信号时的欠定问题,提出一种基于固有时间尺度分解(ITD)和盖尔圆(GDE)的欠定去噪源分离(DSS)方法,即为ITD-GDE-DSS。通过ITD求出信号的旋转分量,进而重组固有旋转分量和原观测信号作为满足盲源分离要求的新观测信号,使盲源分离中维数不足的问题得到解决。通过GDE估计观察信号的组成源数,为DSS方法分离出源信号提供先决条件。将ITD-GDE-DSS方法应用于某转子的实测故障信号分析中,诊断出转子在升速过程中不平衡故障特征,分离出转子突加不平衡的一阶临界转速和二阶临界转速的信号。
Combining the features of Intrinsic Time-scale Decomposition( ITD) and Denoising Source Separation( DSS),we propose an underdetermined DSS method based on ITD. This method is used to deal with the blind source separation problem of rotating machinery in the case of the number of observed mixtures being less than that of contributing sources. The observed signals are decomposed into some proper rotation component with the ITD,which is an effective way to solve the problem of the dimension insufficient in underdetermined blind source separation. As the same time,the Gerschgorin Disk Estimator( GDE) is used to estimate the number of the types of observed signals,and the mixed sources are separated by DSS algorithm. Applying ITD-GDE-DSS method to the rotor fault detection,we have diagnosed the sudden unbalance phenomenon through the measured fault signals of the rotor. The first critical speed signals and the second critical speed signals are separated by this method.
出处
《机械科学与技术》
CSCD
北大核心
2015年第6期863-866,共4页
Mechanical Science and Technology for Aerospace Engineering
基金
国家自然科学基金项目(11272257)
陕西省自然科学基础研究(2011JQ1011)
航空科学基金项目(20112108001)
西北工业大学基础研究基金项目(JC201242)资助
关键词
盖尔圆
固有时间尺度分解
旋转机械
信号处理
去噪源分离
blind source separation
computer simulation
denoising source separation(DSS)
efficiency
fault detection
gerschgorin disk estimator
identification(control systems)
intrinsic time-scale decomposition
measurements
power spectrum
rotating machinery
signal processing
waveform analysis
