摘要
提出了一种在船舶齿轮传动装置振动噪声分析中准确有效计入基础结构导纳特性的方法,并以单级人字齿轮传动装置为对象进行了说明。首先以二自由度系统为例验证了运用骨架线法进行物理参数识别的准确性;接着根据基础结构在与齿轮箱连接点处的自导纳曲线,将基础结构在每个连接点处等效为3个二自由度系统,并运用骨架线法对其物理参数进行了识别;然后用质量和弹簧单元模拟每个二自由度系统建立了振动噪声分析模型,并以通过求解齿轮系统动力学模型获得的轴承载荷为激励进行了振动噪声分析;最后通过试验验证了相关模型和方法的准确性。结果表明:计入基础结构导纳特性后的振动噪声分析结果更为准确,结构噪声和辐射噪声仿真值与试验值间的差值均未超过4.5 dB。
A method which can include the base admittance characteristics accurately and effectively in vibration and noise analysis of marine gear transmission is proposed in this paper. This method is introduced by taking a sing- stage double helical gear transmission as an example. The accuracy of physical parameter identification method based on skeleton line is verified by taking a two degree of freedom system as an the self-admittance curve of base at the connection points to gearbox dom systems at each connection point. The physical parameter of eac example firstly. Then according to , the base is taken as three two degree of free- h system is identified using skeleton line meth- od. And then the vibration and noise analysis model is constructed by simulating each two degree of freedom system using mass elements and spring elements. Based on this model, the vibration and noise is analyzed by taking the bearing dynamic loads which are obtained by solving gear dynamic formulations as excitation. Finally, the experi- ment is conducted to validate the accuracy of the method proposed in this paper. The results show the vibration and noise analysis results become more accurate after including the base admittance characteristics. The difference between simulated and measured structural noise and radiated noise does not exceed 4.5 dB.
作者
王晋鹏
常山
王鑫
刘更
刘岚
赵松涛
吴立言
Wang Jinpeng Chang Shan Wang Xin Liu Geng Liu Lan Zhao Songtao Wu Liyan(Shaanxi Engineering Laboratory for Transmissions and Controls, Northwestern Polytechnical University, Xi'an 710072, China China Shipbuilding Industry Corporation 703 Institute, Harbin 150078, China)
出处
《西北工业大学学报》
EI
CAS
CSCD
北大核心
2017年第1期90-97,共8页
Journal of Northwestern Polytechnical University
基金
国家自然科学基金重点项目(51535009)
高等学校学科创新引智计划(B13044)资助