传递路径中声源串扰消除问题研究
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摘要
噪声控制一般从三方面着手,即声源控制、传播途径控制和接受者保护。其中最根本的方法是声源控制。实现声源控制最重要的是正确识别出主要噪声源,从而可以采取针对性的措施来控制声源。
     在实际结构中,在多个噪声源同时传播的情况下,声源间会彼此产生串扰,加大了求取主导噪声源的难度。
     目前,在振动噪声分析领域,传递路径分析方法(TPA)发展很快,它试图解决找出主要激励源的问题,然而传统的传递路径分析法不能很好的消除串扰,因此需要对传统传递路径分析法进行改良优化。
     本文在掌握传递路径分析理论原理的基础上,通过对传统传递路径分析步骤逐一拆解,在其中加入消除声源串扰的步骤。结合完全Cholesky分解预处理和最小二乘方法,对病态方程组进行有效求解,优化了传递路径分析法,更好的求出主要的噪声与振动激励源。通过对声源串扰消除计算过程进行Gui界面编程设计,使这个方法能方便、稳定、高效的运用到噪声振动工程实践中。
     在理论推导有效的情况下,再进行一系列的试验验证,结果显示,串扰消除方法作用明显,能解决声源串扰的问题,经过优化后的传递路径分析法比传统的传递路径分析法效果明显,更准确的找出主要噪声源。
Generally, We have three methods to control noise. They are sound source control, route of transmission control and receiver protection. The most fundamental method is source control. Identifying the main noise source correctly is the most important thing to achieve the goal of source control. So we can take targeted measures to control the sound source.
     In the actual structure, multiple noise sources spread at the same time, the sound source will produce crosstalk with each other. It will increase the difficulty of getting the dominant noise source.
     In the field of noise and vibration, transfer path analysis (TPA) has developed rapidly. It is trying to solve the problem of identifying the main excitation source. However, the traditional transfer path analysis method cannot eliminate the crosstalk. Therefore, we need to improve the traditional TPA.
     In this paper, with the mastering of TPA theory, I first decompose the traditional TPA process, and then add steps to eliminate the sound crosstalk. I combine the incomplete Cholesky decomposition pre-processing and least squares methods to solve pathological equations which can make TPA better to find the noise and vibration excitation source. After that, I start Gui interface programming to make convenient, stable and efficient use in noise and vibration engineering practice.
     Finding out that the theory very effective, I start a series of experimental verification, the results show that the method of crosstalk cancellation is effective and the optimized TPA is better than the traditional TPA. It can solve sound crosstalk problem and identify the main noise source.
引文
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