High Reliable Operational Transfer Path Analysis Method And Its Application On Noise Reduction Of Construction Machinery’s Cab

The unsatisfying driving comfort is an important issue that currently restricts the market share of domestic construction machinery.An effective way to resolve this issue is to identify the sources of noise and reduce the dominant one inside construction machinery’s cab.Transfer Path Analysis(TPA)is one of such methods that are useful in source identification,and Operational Transfer Path Analysis(OTPA),because of its convenience and high efficiency,is particularly suitable for the analysis of construction machinery with complicated structure and difficulty to dismantling,such as compacter.However,in current OTPA methods,no uncertainty coming with random noise is taken into consideration.As a consequence,severe errors may appear in the result and may even lead to identifying the totally wrong dominant path.Therefore,developing an improved OTPA method with consideration of uncertainty and providing an effective analysis tool for noise reduction of construction machinery is urgent.In this thesis,some double-drum compacter is selected as the object to research.According to the noise reduction requirements of the compacter’s cab,an uncertain SVR-OTPA method is proposed with the combination of Support Vector Regression(SVR),OTPA theory and uncertain analysis as foundations.The proposed method is applied to conduct transfer path analysis of the compacter’s cab,and the effectiveness of the analyzing outcome is validated by vehicle test.The details of this thesis are as follows:Firstly,the basic principles,application processes and key problems of the OTPA method are deduced and expounded.Three common deterministic solutions to solve key problems,as Truncated Singular Value Decomposition(TSVD)method,Tikhonov Regularization method and Illconditioned function method,are introduced and explained in detail.The basic principles of the proposed method,uncertain SVR-OTPA method,is also extensively deduced in this part.And then,an “emitter-receiver” numerical spatial acoustic model is built and the analytic solution of path contribution is accessed through spectral method.The proposed uncertain SVR-OTPA method and other OTPA methods are applied to the numerical model,and the accuracy of each method can be derived by the comparison between the outcomes and the analytic solution.The effectiveness and high efficiency of the proposed method is further verified by an acoustic experiment.After that,the proposed uncertain SVR-OTPA method is applied to a double-drum compacter to conduct transfer path analysis.Acoustic imagining technology is used to identify the sources of the whole machine,and operational data is collected to build the OTPA model.The dominant airborne sound transfer path and structure-borne sound transfer path is identified by the model under two testing operational conditions.The analysis outcome is proved to be correct through vehicle test.The outcome of this research shows that in comparison with current OTPA methods,the proposed uncertainty SVR-OTPA method can not only identify the dominant transfer path and predict path contribution correctly,but also quantify the uncertain of path contribution caused by random noise,decreasing the influence of noise and increasing the precision of path contribution prediction.The proposed method is validated to be higher precise,higher reliable and more informative than previous ones by experiments,providing a powerful analysis tool for the noise reduction design of construction machinery.