Time-Frequency Analysis Of Engine Vibration And Noise Signals And Research On The Blind Separation Technology For Source Signals

The vibration and noise signal of internal combustion (I.C.) engine is typically non-stationary and time-varying with complicated frequency components. Traditional spectral analysis methods can neither analyze this signal in local time domain nor reflect the time-varying characteristics of the frequency components. The time-frequency analysis method is characterized by time-frequency localization. It can simultaneously describe the energy density or intensity of signal in time and frequency. Therefore, this method can reveal the frequency components included in signal and the related variation with time. In recent years, with the development of digital signal processing technologies, the time-frequency analysis method suitable for processing non-stationary signals, has gradually been introduced and brought on some achievements in processing the vibration and noise signal of I.C. engine.This research is mainly originated from the project "Diagnosis of combustion noise source based on independent component analysis and wavelet transform of engine sound signal"(National Natural Science Foundation Project, No:50575203) and "Diagnosis of combustion performance and noise source based on wavelet analysis of engine radiation noise"(ph.D. Programs Foundation Project of Ministry of Education, No: 20030335092). The basic principles and algorithms of wavelet transform, S transform, Hilbert-Huang transform together with independent component analysis were investigated deeply and thoroughly. Taking several engines for example, the time-frequency analysis method and blind source separation technique were employed to study on the time and frequency characteristics of engine vibration and noise signals as well as to identify the vibration and noise sources. The research results are of great significance to the vibration and noise control of engine. The research details were as follows:1. Starting with the severity and harmfulness of noise, the importance of controlling engine vibration and noise was then expatiated. After investigating the development and applications of wavelet transform, S transform, Hilbert-Huang transform, and independent component analysis, the feasibility of these techniques used for analyzing the time and frequency characteristics and identifying vibration and noise sources of engine was explored.2.The basic concepts of time-frequency analysis were firstly defined and differentiated. Then the basic principles and characteristics of time-frequency analysis were summarized.3. Based on an in-depth study of the basic principles of wavelet transform, continuous wavelet transform was adopted to analyze the vibration and noise signals in time-frequency domain when engine was under steady and transient workload. The energy distribution of signals recorded in different conditions and variance of their predominant frequency components with time or engine speed were subsequently investigated. Afterwards, the cause of engine vibration and noise was analyzed according to the previous results together with the engine structural characteristics and working mechanism.4. Based on the wavelet packet decomposition and coefficient reconstruction of engine noise signal, the subband signals relevant to engine combustion process were combined and reconstructed, and noise signals resulted from the combustion excitation were obtained. Moreover, continuous complex wavelet transform was adopted to analyze the reconstructed signal. The three-dimensional wavelet power spectrum was also calculated to investigate the combustion condition of each cylinder and extract the related information.5. Based on an in-depth study of the basic principles and relevant algorithms of S transform, the research on the application of S transform in analysis of engine vibration and noise signals was conducted. Taking several engines for example, S transform was employed to process vibration and noise signals in time-frequency domain when engine was under steady and transient workload. Then the energy distribution law of signals was studied. Furthermore, variation of prominent frequency components with time was analyzed. Finally, the cause of vibration and noise was deduced according to engine structural characteristics.6. Based on an in-depth study of the basic principles and relevant algorithms of Hilbert-Huang transform, the research on its application in analysis of engine vibration and noise signals was conducted. Taking a six cylinder engine for example, the vibration and noise signals were decomposed into a collection of intrinsic mode functions (IMFs) with different frequencies by the method of EMD. Then Hilbert transform was adopted to analyze the amplitude and frequency of each IMF varying with time. In terms of the mechanism of the engine structural vibration and noise, the origination of each IMF was deduced. The vibration and noise sources were identified as well.7. Based on an in-depth study of the basic principles and relevant algorithms of independent component analysis, the research on its application in analysis of engine vibration and noise signals was conducted. The independence and gaussianity of vibration and noise signals was firstly investigated to demonstrate the feasibility of this method used for analyzing the vibration and noise signals of engine. Taking a six cylinder engine for example, the technology of independent component analysis and wavelet transform was adopted to separate the vibration and noise signals of engine and identify its vibration and noise sources.