Numerical optimization of sound insulation performance for the new type glass window based on genetic algorithm and its application in high-speed trains

Transmission loss of a glass window was measured in this paper by means of sound pressure method and sound intensity method. Test results of two methods were consistent with each other, which could avoid some errors in experiment effectively. As a result, the verification of the subsequent acoustic simulation was thus guaranteed. Then, damping loss factor of the glass window was measured by pulse decay method and imported into an AML model to calculate transmission loss of simulation. The simulation result was consistent with the experimental one by comparison, which showed that AML method was feasible to predict transmission loss of the glass window. Then, influence factors on sound insulation performance for the glass window were analyzed from multiple aspects. Then, the laminated mid-hollow glass window filled with Argon which had better sound insulation performance was obtained. It was a new type glass window currently. However, each structural parameter of the new type glass window can’t be optimal currently. As a result, optimization design was conducted on it based on genetic algorithm. Finally, the new type glass window which had the optimal structural parameter and performance was obtained. This research can also provide certain guidance for design of the other type glass window