Noise Source Identification of the Carpet Tufting Machine Based on the Single Channel Blind Source Separation and Time-Frequency Signal Analysis

Abstract

Noise source identification is the first key step to reduce the noise pressure level of the carpet tufting machine. For identifying the main noise sources of the carpet tufting machine, the single channel blind source separation (SCBSS) method is proposed to separate the acquired single channel noise, and the time-frequency signal analysis is applied to identify separated noise components. The SCBSS includes ensemble empirical mode decomposition (EEMD), improved Akaike information criterion (AIC) source number estimation and fast independent component analysis (FastICA). The separation method based on EEMD-AIC-FastICA not only overcomes traditional blind source separation problems that require enough test channel numbers, but also solves the problem that the number of virtual multichannel signals is unknown. Four independent components (ICs) are obtained after using the SCBSS. Combining the time-frequency analysis of the four ICs and the acquired vibration signals of six main components, the specific four noise sources can be identified. The four ICs correspond to the noise of needles, noise of hooks, noise of hook driven shaft, and noise of motor spindle, respectively.