Noise control is important and essential in a factory where the noise level is restricted by the occupational safety and health act. Before noise abatement is performed, the identification work in seeking the location and sound power level (SWL) of noise sources is an absolute prerequisite. Research on new techniques of single noise control has been addressed and developed; however, the research work on sound identification for existing multi-noise plants is rare and observably insufficient. If noises go unrecognized, noise control work will be expectedly expensive and fruitless; therefore, the numerical approach in distinguishing noises in a multi-noise plant becomes crucial and obligatory. In this paper, the novel technique of simulated annealing (SA) in conjunction with the method of minimized variation square is applied in the following numerical optimization. In addition, various sound monitoring systems for detecting the noise condition within a plant area are also introduced. Before noises are identified, one single noise is tested and compared with the experimental data for the purpose of accuracy with the mathematical model. Moreover, three kinds of multi-noise plants have been fully discussed and optimally recognized by the SA. The results reveal that the locations and sound power levels (SWLs) of noises can be precisely distinguished. Consequently, this paper may provide an efficient and rapid methodology in noise identification work for a multi-equipment plant.
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