Abstract: Signal processing methods are commonly used to analyze the structure of signals according to the criteria of spectral distribution. However, the causal relationship between components and sources are not revealed. Under the condition that only observed signals are known, the mixed signals can be separated into several components by denoising source separation (DSS) method according to statistical feature. The sources of observed signals are revealed by these independent components, thus it provides a direct reference to condition monitoring and active control of vibration and noise. The basic theory of DSS and denoising functions based on different criterion are studied, and the separation performance of four types of denoising function such as energy function, slope function, kurtosis function and tangent function are quantitatively compared by means of simulation of typical mechanical signals. The results show that the correlation coefficients between independent components, which are separated from nonlinear mixed signals by DSS based on tangent function, and related sources are more than 0.89. Thus the algorithm based on tangent function is more suitable for extracting nonlinear coupling information of mechanical equipment. The DSS method based on tangent function is used to extract running information feature of a warship, and the quantitative analysis results show that the running information of each equipment is well extracted from mixed vibration signals of the bulkhead.

Key words: Active control, Condition monitoring, Denoising function, Denoising source separation, Feature extraction, Nonlinear coupling, Vibration and noise