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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.