某柴油机油底壳异响问题分析与改进

针对某柴油机进行整车长里程耐久试验时油底壳发生"嗡嗡"异响的问题,通过噪声实测并结合有限元分析,对油底壳异响的原因进行了分析.分析结果表明,在加满机油状态下的油底壳系统一阶模态不满足油底壳的噪声设计要求,油底壳的共振带被激励起,产生了振动噪音.针对该问题,提出了几种油底壳设计优化措施,如加厚油底壳、在内部或外侧增加肋板等优化措施.通过样件在整车实测,结合工艺可行性,最终选择在油底壳内部增加肋板作为优化方案,解决了该柴油机油底壳异响问题.     

柴油机常见异响的判断与排除

本文论述了几种柴油机常见异响,分析产生的原因,指出了排除措施,以避免事故发生.     

8．9L柴油机用高压油管的设计与研究

为了验证直列泵8．9L柴油机用高压油管的设计，采用模拟计算和发动机整机试验相结合的方法进行了研究开发。首先使用Pro／E完成高压油管结构设计、3D模型和整机布置，然后运用ANSYS对高压油管进行FEA模态分析，最后进行了发动机性能试验、油管应力测试和发动机耐久性试验。同时还建立了高压油管设计的标准化工作流程。结果表明：高压油管设计满足发动机欧-Ⅱ排放、整机性能、可靠性及整机布置等所有要求。     

8.9 L柴油机用高压油管的设计与研究

为了验证直列泵8．9L柴油机用高压油管的设计,采用模拟计算和发动机整机试验相结合的方法进行了研究开发。首先使用Pro／E完成高压油管结构设计、3D模型和整机布置,然后运用ANSYS对高压油管进行FEA模态分析,最后进行了发动机性能试验、油管应力测试和发动机耐久性试验。同时还建立了高压油管设计的标准化工作流程。结果表明:高压油管设计满足发动机欧-Ⅱ排放、整机性能、可靠性及整机布置等所有要求。     

某发动机共振异响诊断与消除

测试了某异响发动机工作时的声压和振动加速度,通过异响工况下的加速度功率谱密度曲线结合曲轴自由模态分析结果诊断出了异响问题的原因-曲轴共振。对引起共振的激励源-发电机及点火系统进行改进,使激励能量足够小从而消除了该发动机的异响。该共振异响问题的解决,对类似问题具有参考和指导意义。     

某发动机前端轮系张紧器异响分析及改进

针对某发动机前端轮系张紧器在特定转速下的异响问题,通过仿真与试验,分析异响产生原因并进行结构优化.对张紧器进行模态仿真分析,发现张紧器螺旋弹簧的一阶轴向伸缩变形模态频率为347 Hz,与理论计算的异响转速相关频率(344 Hz)非常接近.拆解发生异响的张紧器,发现张紧器第二圈弹簧与壳体底部卡槽凸台发生干涉,产生摩擦噪声...     

柴油机机体模态分析与试验验证

建立某直列四缸柴油机机体三维模型,对其进行自由模态有限元分析,并提取前5阶机体的固有频率及对应的振型,分析机体各频率范围内的振动规律和抗振薄弱区。为了验证有限元分析模型的准确性,对机体进行自由悬挂试验模态分析。对比结果表明,计算和试验的低阶振型基本一致,固有频率最大相对误差为6.3%,说明有限元模型具有较高的精度,可以作为后续优化和动力学分析之用。     

基于模态分析的船用柴油机油底壳结构优化

以某船用柴油机油底壳为研究对象,采用有限模态分析方法,研究单因素结构变化对比分析不同结构布置及参数对动态特性的影响,为结构优化提供参考,证明并利用了模态振型的正交性,完成了油底壳的优化设计。针对优化后油底壳开展了有限元与试验模态分析方法,相应模态振型的模态频率偏差较小,装机状态油底壳具有良好的动态特性,模态频率能完全避开柴油机最高转速的激励频率,避免了发动机运行时共振的可能。     

用示波器对发动机异响进行检测与诊断

阐述了如何利用示波器检测发动机重要部位振动波形,并对检测到的波形进行分析,以此对发动机异响做出正确的诊断。     

发动机驱动盘总成异响原因分析及解决措施

某发动机在进行整车道路试验时出现了发动机驱动盘总成处出现异响的现象,我们详细分析了造成驱动盘总成异响的原因。结果表明:造成异响的原因是曲轴箱与气缸体的定位销孔为通孔,发动机运转时产生振动导致曲轴箱定位销脱落到驱动盘总成处,在回转力的作用下与驱动盘接触,进而产生异响,通过把曲轴箱定位孔由通孔改成阶梯孔,避免定位销从曲轴箱脱落,解决了驱动盘总成异响的问题。     

280型柴油机噪声的测量

介绍了依据国家标准GB T1859 2000对柴油机辐射的空气噪声进行测量和计算的过程,并得出280型柴油机样机的噪声A计权表面声压级和声功率级的计算值。     

某柴油机气缸盖垫片密封失效故障分析及改进

针对某柴油机耐久试验过程中出现的多次漏气故障,结合仿真分析方法,系统分析缸盖垫片漏气故障产生的原因,提出改进进气侧气缸盖和气缸体结构模型、填充材料增大进气侧的刚度和优化缸盖螺栓拧紧工艺等改进措施。经1000 h全负荷耐久试验及3000次热冲击试验验证,改进后的柴油机未发现任何泄漏及密封带部位异常磨损情况,为今后的设计提供了参考依据。     

运用中柴油机油的分析及化验意义

分析了柴油机油在使用过程中的污染变质问题,说明运用中柴油机油化验分析的意义,并提出实际应用中存在的问题及建议。     

不同大气压力和生物柴油/柴油掺混比对柴油机噪声的影响

使用大气模拟试验台进行了直喷式柴油机在高原环境不同大气压下燃用不同体积掺混比生物柴油/柴油混合燃料的噪声测量对比试验研究。结果表明：噪声声功率随着大气压力和生物柴油掺混比的增加而减小;怠速工况时,在101kPa和81kPa大气压下分别燃用掺混比为70%和80%的混合燃料噪声值最小;在630～2000Hz噪声主要贡献频带上,各个测试点燃用B100油时声压级较B0油小;在高原环境下使用生物柴油可有效地降低柴油机整机噪声。     

Experimental study of combustion noise radiation during transient turbocharged diesel engine operation

Diesel engine noise radiation has drawn increased attention in recent years since it is associated with the passengers’ and pedestrians’ discomfort, a fact that has been acknowledged by the manufacturers and the legislation in many countries. In the current study, experimental tests were conducted on a truck, turbocharged diesel engine in order to investigate the mechanism of combustion noise emission under various transient schedules experienced during daily driving conditions, namely acceleration and load increase. To this aim, a fully instrumented test bed was set up in order to capture the development of key engine and turbocharger variables during the transient events. Analytical diagrams are provided to explain the behavior of combustion noise radiation in conjunction with cylinder pressure (spectrum), turbocharger and governor/fuel pump response. Turbocharger lag was found to be the main cause for the noise spikes during all test cases examined, with the engine injection timing calibration and the slow adjustment of cylinder wall temperature to the new fueling conditions playing a vital role. The analysis was extended with a quasi-steady approximation of transient combustion noise using steady-state maps, in order to better highlight the effect of dynamic engine operation on combustion noise emissions.     

柴油电站的降噪方案分析

对柴油机组的降噪方法、降噪结构及其效果进行了分析；分析了降噪特性曲线对消音器参数选择的指导作用。     

某小型汽油机正时链条异响的分析及改进

在某小型汽油机的生产线上出现了异响,主观判断为正时系统的异常噪声,该噪声具有明显的间歇性。通过现场振动测试,结合调制分析确定其调制频率,确定了影响该噪声的关键因素,进而通过对相关零部件尺寸外形测量及生产工艺的分析,找到了问题的根源,确定了最终的解决方案,取得了消除异响的效果。     

Suitability analysis of advanced diesel combustion concepts for emissions and noise control

During the last years, the preservation of the atmospheric environment has played an increasingly important role in society. The Diesel engine can be considered an environmentally friendly engine because of its low consumption and the subsequent carbon dioxide (CO₂) emissions reduction. However, in the near future it will face strong restrictive emission standards, which demand that the current nitrogen oxides (NO_x) and soot emissions are halved. To comply with these restrictions new combustion concepts are emerging, such as PCCI (premixed charge compression ignition), in which the fuel burns in premixed conditions. Combustion noise is thus deteriorated and consequently end-users could be reluctant to drive vehicles powered with Diesel engines and their potential for environment preservation could be missed. In this paper, Diesel combustion is addressed through the analysis of performance, emissions and combustion noise in order to evaluate the suitability of PCCI engines for automotive applications. The results show that PCCI combustion offers great possibilities to fulfill future emission restrictions, but the engine noise is strongly deteriorated. The great sensitivity of users to this factor requires vehicle manufacturers to focus their efforts on the optimization of passive solutions for implementing the PCCI concept in passenger car and light-duty engines, even with the subsequent increase in the cost of vehicle. This aspect is less restrictive in heavy-duty engines, since the great benefits in emissions reduction compensate the deterioration of engine noise.     

Artificial intelligence techniques for the vibration,noise, and emission characteristics of a hydrogen-enriched diesel engine

The present paper investigates the prediction of vibration, noise level, and emission characteristics of a four-stroke, four-cylinder diesel engine fueled with sunflower, canola, and corn biodiesel blends while H₂ injected through inlet manifold using two different artificial intelligence methods: artificial neural network (ANN) and support vector machines (SVM). The aim of using these methods is to predict vibration, noise, carbon monoxide (CO), CO₂, and NO_x based on the initial experimental study by varying engine speed, blends of biodiesel, and H₂ energy substitution ratio. Experimental data were gathered from the literature. For the ANN method, LevenbergMarquardt backpropagation training algorithm with logarithmic sigmoid and linear transfer function for hidden and output layers, respectively, gives the best results for prediction of vibration, noise, and emission characteristics. For SVM, a regression model is implemented with Gaussian kernel function. Results show that the ANN performs better than SVM, and the best mean average percent error and R² for the models developed are 2.03 and 0.988 for vibration acceleration, 0.39 and 0.9615 for noise, 7.27 and 0.8549 for CO, 5.09 and 0.9398 for NO_x, and 2.21 and 0.993 for CO₂ values, respectively. Eventually, it is found that the ANN method is a good choice for simulation and prediction of dual fueled hydrogen sunflower, canola, and corn biodiesel blends.