Abstract: In order to effectively control cabin noise and improve noise quality, combined techniques of ensemble empirical mode decomposition (EEMD) and an improvement of independent component analysis (ICA) were applied to analysze cabin noise. Intrinsic mode functions resulting from EEMD analysis were used as the virtual channels of ICA, which solved an undetermined problem of blind source identification from single sampling signal. The feasibility of EEMD-ICA method for complex non-stationary signals was verified by analyzing the simulated signals. With the experiment and coherence analysis for cabin interior and outside noise and vibration signals of a bulldozer, the technique of EEMD-ICA was effective on the noise source separation and identification. Meanwhile, techniques of coherence analysis and time-frequency analysis were used for accurate noise sources identification. The results showed that the main cabin noise source was combustion noise of diesel engine and mechanical radiation noise of cabin parts caused by 1／2 order and 1 order rotation frequency of the diesel engine. And generation details of noise source, transmission paths of air-borne or structure-borne noise were well analyzed in order to control the interior noise and identify faults by the techniques of coherence analysis and time-frequency analysis.

Key words: cabin noise, ensemble empirical mode decomposition, independent component analysis, noise source identification, time-frequency analysis