摘要
现代船舶的舱室需满足严格的噪声级限值要求,在设计阶段,对大型船舶进行舱室噪声预报和开展降噪设计具有实际工程意义。以6500吨油化船为研究对象,利用声学分析软件VA One建立声学模型,并基于统计能量分析法对重要舱室进行噪声预报。结果显示,全船重要舱室的噪声级均严重超标,故需进行降噪设计。首先,采用分离变量法分析噪声源,区分主要噪声源与次要噪声源,对主要噪声源进行隔振、隔声处理。其次,通过子系统能量分布云图明确船舶舱室噪声的主要传递路径,并据此进行进一步的降噪设计。采取降噪措施后,全船重要舱室噪声级均达到限值要求。研究结果可用于工程实际中6500吨油化船的降噪设计,同时可为其他类型船舶的降噪设计提供参考。
The cabin noise of modern ships need to meet the requirements of a strict noise limitation standard.Therefore,it is of practical engineering significance to predict the cabin noise in the design stage for large modern ships and carry out noise reduction design.In this study,the cabin noise prediction model for a 6500-ton oil/chemical tanker is established using VA One acoustic analysis software.Based on statistical energy analysis method,the noises of the main cabins are predicted.The prediction results show that all the noises of the main cabins in the tanker are beyond the noise limitation standard which shows the urgency of carrying out the noise reduction design for the tanker.Firstly,the main noise sources and secondary noise sources are distinguished by using the method of variable separation.The main noise sources are then treated by vibration isolation and noise isolation.Secondly,the transmission paths of the noise are found by analyzing the energy contour diagram of the subsystem and the corresponding noise reduction schemes are made.After the noise reduction schemes are realized,the noise level of the main cabins of the whole tanker meets the noise limit requirements.The results of this research can be used for the noise reduction design for the 6500-ton oil/chemical tanker,and also provide a reference for the noise reduction design for other types of structures.
作者
林嘉欢
汤伟民
张俊
姚立纲
LIN Jiahuan;TANG Weimin;ZHANG Jun;YAO Ligang(School of Mechanical Engineering and Automation,Fuzhou University,Fuzhou 350116,China)
出处
《噪声与振动控制》
CSCD
2020年第4期142-148,共7页
Noise and Vibration Control
关键词
声学
舱室噪声预报
统计能量法
噪声控制
油化船
acoustics
cabin noise prediction
statistical energy analysis method
noise control
oil/chemical tanker
