A Noise Prediction Of Complex Coupled System Based On Statistical Energy Analysis

Noise produced by industrial machinery often has a large impact on physical and mental health of workers.An effective prediction and control of the noise in industrial enviroments is becoming a pressing issue.Because the actual industrial environment is often rather complex in nature,there is no existing universial technique which can be effectively applied to accurately predict the sound and vibration characteristics in the surrounding of a machine.Statistical energy analysis(SEA)is astatistical method for the prediction of energy flow between subsystems in coupled systems,paricularly when the detailed information of a system is not readily available and when there are a large uncertainty on determining the system parameters.To enable a nosie and vibration prediction and control of complex industrial systems,statistical energy analysis(SEA)is utilized in this thesis for the study of noise and vibration of a experimental room,and a large industrial chamber of a water injection pumping station in an oil field.Firstly,the theoretical background of statistical energy analysis and the research on noise control of pumping stations are briefly reviewed.The principles of susbsystem division of a coupled system,the establishment of the energy balance equations of statistical energy analysis model and the estimation of the main parameters such as modal density,internal loss factor,coupling loss factor and input power are then introduced.After the SEA model is established,the model is then utilized for the noise and vibration prediction of a small experimental room in our laboratory.The calculated results based on the energy balance equations are then compared with the simulation results using the SEA software-VA One and results from actual measurements.Influences of sound assorption of each wall on the averaged sound pressure level of the enclosed acoustic cavity are studied by adding sound absorbing materials on each wall and the results are discussed.Results obtained from the statistical energy analysis of the small experimental room is then used to guide the SEA of a practical industrial chamber of a water injection pumping station in an oilfield.Different configurations of the SEA model are also simulated to understand the sensitive influenctial factors affecting the noise level inside the chamber.Results obtained from the analysis can be used to guide the noise control design in practical industry applications.Main findings from this thesis work are summarized in the conclusion,a number of future research areas are identified and put forward.