Noise Location And Visuilization Of Marine Power Plant Equipment

In the space of the ship and the marine platform,the sound field in the reverberation chamber is produced in the case of the operation of the power plant.The recognition of noise sources is an important research direction in the field of noise and vibration control for the reduction of the sound field in the cabin.The sound field is caused by one or more sound sources.Locating and identifying the location and amplitude of the source,can analyze the composition of noise sources in the cabin effectively,so that it can diagnose the normal operation of the power plant,and the abnormal sound field caused by various factors in the cabin effectively.Therefore,taking the sound field environment in the cabin as a prototype,this paper analyzes the characteristics of the sound field near the source of the microphone in the reverberation room,and carries out the theoretical algorithm research,simulation analysis,experimental measurement and experimental results analysis of the noise localization and imaging technology.In the theroretical algorithm research part,the advantages and disadvantages of the three acoustic source localization algorithms are analyzed,and the beamforming algorithm is used as the algorithm in this paper.Based on the assumption of plane wave,"scan vector" and "solving beamforming energy" are defined,which can be used to get the relationship between energy and azimuth.Using the use of "Y" type three to the array(microphone spacing 5cm),and the three spatial orientation of sound source and geometry calculation,can localize the sound source in the three-dimensional space.Focusing on the characteristics of the sound field of multi point sound source,the improved scan vector is introduced and the solution of the nonlinear equations in the domain is solved with the genetic algorithm.In the reverberation chamber,the wall reflection,and white noise in the cabin,can be recognized as "the falsetto source" in sound source identification.So using the improved DAMAS iterative algorithm,can strengthen the real sound source signal,weaken the falsetto signals,and suppress the reverberation effect.The simulation part,simulating a certain frequency band multi point sound source with one source and multi-source based on the theory of algorithms,respectively for anechoic and reverberant room environment.The traditional beamforming algorithm and the improved beamforming algorithm are used to carry out simulation calculation,and the acoustic imaging is obtained by the geometric calculation.Because the beamforming is based on the plane wave hypothesis,many ingredients can affect the complexity and accuracy of the algorithm such as the distance between the source and microphone,the frequency of the source,the number of sound sources,the reverberation effect and the reflection of the wall surface.Through calculating of anechoic environment simulation,according to SNR and relative error identification results,can verify that the proposed algorithm perform better than the traditional algorithm.The improved algorithm can obtains more effective recognition range on the frequency of the sound source.The simulation calculation of reverberation environment proves that the improved DAMAS algorithm combined with the improved beamforming algorithm has good recognition effect for the sound source recognition in reverberation environment.The experimental part,based on the results of simulation calculation,the sound source identification experiments under different conditions is carried out in the effective range of this algorithm in indoor in anechoic and reverberation environment.A lot of experimental data are processed.The experimental results verify the correctness of the simulation results,and then verify the effectiveness of the improve beamforming algorithm and the improved DAMAS iterative algorithm for the identification of multi-sources in the reverberation chamber.The results of simulation and experimental calculation show that the acoustic source recognition algorithm in this paper can be used in the application of acoustic source recognition in the cabin.