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The paper used the AML method to compute transmission loss of aircraft panels and verifies correctness of the numerical simulation model by experimental test. Finally, this paper used an improved genetic algorithm to conduct a multi-objective optimization for the cabin noise. When the analyzed frequency is less than 250 Hz, transmission loss decreased rapidly with the increased analysis frequency, and decreased from the maximum 63.2 dB to 18.5 dB. Within 250 Hz-4000 Hz, the transmission loss gradually increased with the increased analysis frequency. At 250 Hz, the transmission loss had an obvious valley value. Sound radiation power was then computed based on boundary element method, and panel contribution analysis was conducted to find those panels which had an obvious impact on the cabin noise. Therefore, a multi-objective optimization was conducted on these panels and reinforced ribs. In order to further verify effectiveness of the MPP-NSGA method, it was compared with the traditional GA model and NSGA model. Optimization accuracy using MPP-NSGA model is increased, and optimization time is reduced. Through optimization with traditional GA method, the maximum sound power level decreased by 15.4 %, and the total sound power level decreased by 21.9 %. Through optimization with the NSGA method, the maximum sound power level decreased by 21.7 %, and the total sound power level decreased by 29.0 %. Through optimization with the MPP-NSGA method, the maximum sound power level decreased by 46.3 %, and the total sound power level decreased by 36.0 %. Therefore, compared with other two kinds of genetic algorithms, the MPP-NSGA method is obviously superior in noise optimization in the cabin. In the whole analysis frequency band, noise of the optimized cabin panel at each frequency point was smaller than that of the original structure, fully verifying feasibility of the optimization algorithm proposed in the paper. In addition, in the optimized structure, no panel made obvious contributions to the cabin noise, and each panel showed an equivalent contribution level. Transmission loss of the optimized cabin panel was obviously improved. However, the sound insulation valley still appeared at 250 Hz, but it was not so obvious like the original structure. After optimization, the sound insulation valley was 31.6 dB. The sound insulation valley of the original structure was 18.5 dB. Obviously, the sound insulation valley value of the optimized structure was increased by double compared with the original structure. This paper provided a valuable reference for noise reduction in the aircraft cabin.

A novel MPP-NSGA algorithm and its application in optimization for radiated noises in the aircraft cabin