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has been cited by the following article:

• TITLE: Noise Source Identification Applied in Electric Power Industry Using Microphone Arrays

  AUTHORS: Pengxiao Teng, Rilin Chen, Yichun Yang

  KEYWORDS: Noise Source Identification; Condition Monitoring; Noise Reduction; Microphone Array; Particle Swarm Optimization

  JOURNAL NAME: Engineering, Vol.5 No.1B, January 16, 2013

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