内燃机结构噪声预测方法的研究/Research on the structural noise prediction of internal-combustio

2018-12-27 13:15:48

noise engine 12 内燃机 V230



内燃机结构噪声控制已经成为现代内燃机技术一个重要的研究方向,在设计阶段了解和掌握内燃机辐射水平,基于仿真模型进行整机声学优化,对确保内燃机产品满足日益严格的噪声要求,提高其产品的竞争力,具有十分重要的意义。本文以12V230柴油机为研究对象,采用有限元法(FEM)和边界元法(BEM)对内燃机结构噪声预测进行了比较系统的研究,实现了对12V230柴油机结构噪声的预测;此外通过对12V230柴油机进行振动噪声测试实验,验证了计算模型和方法的正确性。具体研究工作如下:
(1)查阅了相关文献资料,分析了国内外内燃机结构噪声预测的研究现状,研究了内燃机结构噪声预测的方法及技术路线。
(2)建立了内燃机主要零部件三维实体模型及整机有限元模型,并进行了模态分析。在没有模态实验的情况下,通过对不同单元尺寸有限元模型模态分析的对比,确定了油底壳、机体、机架、气缸盖和气门室罩的有限元模型;然后采用RBE2单元和节点耦合方式处理结合面,构成整机有限元模型,得出整机固有频率和振型,为整机的动态响应分析和结构声学优化奠定了基础。
(3)计算了气缸压力、主轴承作用力、配气机构作用力、活塞侧推力等内燃机主要载荷,并确定这些载荷的大小、相位以及作用区域;利用有限元分析软件MSC.Nastran进行了整机频域响应分析,得到整机动态响应;分析了配气机构作用力对内燃机各构件振动的影响,结果显示配气机构作用力对内燃机各构件振动影响较大。
(4)建立了内燃机边界元模型,并导入整机表面振动响应,利用噪声预测软件LMS.Sysnoise实现了整机噪声预测,获得了空间场点声压、声强以及整机辐射声功率、辐射效率等声学结果;并根据计算结果对辐射噪声较大的油底壳和气门室罩部件,采用模型重构方法进行结构灵敏度分析和结构声学优化,为整机结构辐射噪声的优化控制提供了指导方向。
(5)针对12V230柴油机进行了振动与噪声的测试,并把测试所得的表面振动加速度信号以及空间场点声强信号与理论计算值进行对比,验证了采用有限元和边界元法对内燃机结构噪声预测的合理性。



The structural noise prediction has been an important aspect in the field of internal-combustion engine research. Knowing the radiant level of engine noise at the stage of design and doing optimization of whole engine structural noise control based on simulative model have great significance to insure internal-combustion engine satisfing more and more strict requirements of engine noise and to promote the product competitive capability. Based on 12V230 diesel engine, the research of internal-combustion engine structural noise prediction is done systematically by using FEM and BEM, and the research on structural noise prediction of 12V230 diesel engine is achieved. Furthermore, the vibration and noise of 12V230 diesel engine are measured to validate the correctness of model and the theoretic method. In detail, the main work is as follows:
(1)The actuality of the research of internal-combustion engine structural noise prediction is reviewed firstly after referring to some literature, and then the method and technical path of this research is gived.
(2) The 3-D entity models and the finite element models of main construct of 12V230 diesel engine are established, and the modal analysis is done. Comparing the difference results of modal analysis which considered different element size without the modal experiment, the finite element models of the sump、block、cylinder heads and valve cover are constructed. The combined surface is dealed with the RBE2 and the coupling-node, and then the finite element model of whole engine is built to receive the natural frequencies and mode shapes, which establish the base to structure response analysis and noise optimization.
(3)The main loads of 12V230 diesel engine are calculated, such as cylinder pressure, main bearing force, valve train force, piston impact force and side push force. Then the values, phase angles and positions of these loads have been determined. The response of engine structure is calculated by software of MSC.Nastran. And the effect of valve train to the response of engine structure has been analyzed, which shows the valve train has a relative effect to the response of engine structure.
(4) The boundary element model of 12V230 diesel engine is built, and then the response of engine exterior is imported into the boundary element model. Afterward, we can predict 12V230 diesel engine structural noise and calculate the main acoustic result, such as sound pressure, sound intensity, radiation power and radiation efficiency by software of LMS.Sysnoise. The result shows that the sump and valve cover structural noise is the main part of whole engine radiant noise, so the structural sensitivity and noise optimization are done by the re-calculation method, and the result of optimization is evaluated, which provides the guide for development of low noise internal-combustion engine.
(5) The vibration and noise of 12V230 diesel engine were measured, then the experimental results and the theoretic results are compared to prove that the reliability of internal-combustion engine structural noise prediction by FEM and BEM.