적응형 파라미터 알고리즘을 이용한 개별 소음원의 음향파워 예측 연구
PURPOSES : We propose a parameter-setting-free harmony-search (PSF-HS) algorithm to determine the individual sound power levels of noise sources in the cases of industrial or road noise environment.
METHODS: In terms of using methods, we use PSF-HS algorithm because the optimization parameters cannot be fixed through finding the global minimum.
RESULTS: We found that the main advantage of the PSF-HS heuristic algorithm is its ability to find the best global solution of individual sound power levels through a nonlinear complex function, even though the parameters of the original harmony-search (HS) algorithm are not fixed. In an industrial and road environment, high noise exposure is harmful, and can cause nonauditory effects that endanger worker and passenger safety. This study proposes the PSF-HS algorithm for determining the PWL of an individual machine (or vehicle), which is a useful technique for industrial (or road) engineers to identify the dominant noise source in the workplace (or road field testing case).
CONCLUSIONS : This study focuses on providing an efficient method to determine sound power levels (PWLs) and the dominant noise source while multiple machines (or vehicles) are operating, for comparison with the results of previous research. This paper can extend the state-of-the-art in a heuristic search algorithm to determine the individual PWLs of machines as well as loud machines (or vehicles), based on the parameter-setting-free harmony-search (PSF-HS) algorithm. This algorithm can be applied into determining the dominant noise sources of several vehicles in the cases of road cross sections and congested housing complex.