Feature Analysis Mechanical Fault Signals Based on Correlation Dimension and Complexity

Abstract

In connection with the nonlinear dynamic characteristics shown from the performance of fault rotating mechanical system, based on the research and analysis, correlation dimension and complexity can be used to characterize the system state of motion. The authors propose the analysis method of correlation dimension and complexity to the signal feature of mechanical fault. Using theory of phase space reconstruction, simulating fault signal of rotating machine is reconstructed. In order to reconstruct the phase space which can be adequately reflect the movement characteristics of the system, the time delay and embedding dimension are discussed emphatically, on this basis, the correlation dimension are calculated. From the analysis and calculation on simulation of different fault signals, it shows that under different rotating machinery fault conditions, its correlation dimension, and complexity are significantly different, which verifies that the these nonlinear feature quantities are effective parameters for fault information and they are excellent parameters in terms of extraction and recognition of fault feature. Studies have shown that, these nonlinear feature quantities can reflect the nonlinearity of the system. If combine these parameters, supplemented mutually, verifies mutually, it will be more conducive to recognize and analyze fault signal recognition, enhance the reliability, and thus to study the fault diagnosis of complexity rotating machinery in a more effective way.