Noise Source Identification Applied in Electric Power Industry Using Microphone Arrays

Abstract

<span>The noise source identification</span><span> is an </span><span>important issue in</span><span> noise reduction</span><span> and </span><span>condition monitoring(CM) for machines in- site using microphone arrays</span><span>. In this paper, </span><span>we propose </span><span>a new approach to optimize array configuration</span><span> </span><span>based on particles swarm optimization algorithm </span><span>in order </span><span>to improve </span><span>noise source identification and condition monitoring performance</span><span>. </span><span>Two distinct optimized array configurations are designed under the certain conditions. </span><span>Furthermore,</span><span> an acoustic imaging equipment is developed to carry out </span><span>experiments</span><span> on transformer substation equipment and wind turbine generator, which </span><span>demonstrate that the </span><span>acoustic imaging system </span><span>allows a high resolution in </span><span>identifying main noise sources for noise reduction and abnormal noise sources for condition monitoring</span><span>.</span