共查询到20条相似文献,搜索用时 171 毫秒
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在我国工业发展过程中,为了保障其自身得到有效成长,必须对工业领域进行全面优化。其中,在内燃机工与气缸敲击振动关系当中,可以通过建立相关的数学模型,完成有效测试,以根据其相关的计算模式,分析出其内部的相关比值。并通过有效的方程式,对其发动机转速、动力、扭矩等信息完成有效的平衡。因此,本文将就内燃机工况对气缸敲击振动的影响探究展开讨论,阐述内燃机的基本概述,分析内燃机的振动以及噪声,研究如何通过合理有效的方式对其进行有效优化。 相似文献
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《汽车零部件》2012,(5):27-27
当前使用的大部分内燃机都属于四冲程循环内燃机,由德国工程师奥托发明.虽然奥托发动机的使用长达一个多世纪,工作效率得到不断提升,但基本结构和原理仍保持不变.美国Scuderi集团基于前人的"一分为二式"发动机设计理念,以奥托循环发动机为基础对四冲程内燃机进行了大刀阔斧的改动,相比传统奥托内燃机拥有更低的油耗和排放.
"一分为二式"发动机将传统四冲程发动机的工作过程分为两部分,在普通气缸之外又配备了一个新的气缸,每个气缸负责完成两个冲程的动作,一个气缸(暂将其称为A气缸)用于进气和压缩,另一个(暂将其称为B气缸)用于作功和排气,曲轴只需旋转一周就能完成四个冲程. 相似文献
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连杆是内燃机组成的重要传动零件之一,其可靠性问题长期以来一直是人们在发动机研究和改进过程中关注的热点问题.用现代设计的方法和手段对连杆进行动态特性研究,已经成为连杆设计中的重要环节. 相似文献
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内燃机优化设计研究现状与展望 总被引:2,自引:0,他引:2
综述了内燃机优化设计理论的研究和应用现状、进展。着重讨论内燃机主要零部件、工作过程以及内燃机动力学、摩擦学等方面的优化设计研究工作,展望了内燃机优化设计理论和应用的发展动向及若干重要问题。 相似文献
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针对内燃机故障诊断中振动响应信号强耦合、弱故障特征的问题,提出一种基于内燃机振动谱图纹理特征提取的故障诊断方法。首先,为了清晰地刻画内燃机振动信号时频联合分布中的非平稳时变分量,将变分模态分解(VMD)与Rihaczek复能量密度分布方法有效结合,得到了时频聚集性好、无交叉项干扰的内燃机振动谱图像;针对VMD分解过程中的参数选取问题,提出将功率谱熵作为目标函数,对VMD的分解参数进行网格寻优,提高了VMD分解的自适应性。为了实现对内燃机振动谱图像的自动识别及故障诊断,提出了改进的局部二值模式(ILBP)方法,用来对振动谱图中蕴含的纹理信息进行分析,提取低维特征参量并采用最近邻分类器对内燃机不同工况的振动谱图像进行模式识别。将该方法应用于内燃机故障诊断实例中,结果表明该方法能有效提取内燃机振动信号中的微弱故障特征,实现内燃机故障的自动诊断。 相似文献
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内燃机属于重要的机械设备类型,具有很大的应用空间。然而,具体运用的过程当中,内燃机却碰到了很多不同类型的故障问题,如何科学分析,并且制定出合理的维修和维护措施可谓一项难题。本文通过说明汽车内燃机机械维修和控制工作开展的价值,分析了汽车内燃机机械维修过程当中显现出来的常见问题,并且提出了汽车内燃机机械维修当中的有效控制及维护对策,从而有效提升汽车内燃机机械维修和改造工作的总体水平。 相似文献
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通过分析内燃机噪声产生机理,阐述了内燃机噪声控制技术的特点,综述了近年来内燃机噪声控制技术的研究现状,提出了未来内燃机噪声控制技术的研究方向。 相似文献
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Tomasz Figlus Štefan Liščák Andrzej Wilk Bogusław Łazarz 《Journal of Mechanical Science and Technology》2014,28(5):1663-1671
A change in the technical condition of mechanical components of internal combustion engines may not be detected by on-board diagnostic systems installed in vehicles. In similar cases, measurements and analyses of vibroacoustic signals being recorded prove useful. Since there are certain limitations to vibration measurements, including those related to the vibration transmission and the engine’s high temperature at measurement points, the authors of this paper have proposed that measurements and analyses of acoustic signals should be applied for the sake of assessment of the internal combustion engine technical condition. However, such an assessment requires new acoustic signal processing methods to be developed, and so this subject has been elaborated in the paper. The article provides a discussion on the option of applying a wavelet packet decomposition while filtering the internal combustion engine’s acoustic signal in order to diagnose an excessive valve clearance. The authors prepared an algorithm enabling selection of the chosen details and approximation of the wavelet analysis to low-frequency components, which constitute the noise, as well as high-frequency components comprising information on the possible enlarged engine valve clearance. Next, based on the selected high-frequency acoustic signal components, a method for automatic detection of enlarged clearance valves was developed, assuming that energy participations of the acoustic signal being emitted were to be determined while opening and closing individual valves. Under the study discussed, identification tests were conducted using two 4-cylinder internal combustion engines featuring valves of different clearances to consequently confirm the efficiency of the algorithm developed for the acoustic signal filtration and automatic detection of enlarged clearance valves. 相似文献
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相对于一个工业经济来说,内燃机是汽车和工程机械的主要动力来源,内燃机的温度过高或者是在运行的过程中噪音过大,这样都会对运行产生影响,对于这两个问题,可能产生的原因有很多,所以需要进行具体的设计以用来提高内燃机的使用寿命,需要不断提高生产内燃机的质量,这将对于我国工业经济发展有着很大一部分的提升。这篇文章主要是论述了内燃机存在问题以及震动噪音问题,并对于目前这个情况,分别提出具体的噪音控制技术,以及温度过高控制技术。 相似文献
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Engine tests are both costly and time consuming in developing a new internal combustion engine.Therefore,it is of great importance to predict engine characteristics with high accuracy using artificial intelligence.Thus,it is pos-sible to reduce engine testing costs and speed up the engine development process.Deep Learning is an effective artificial intelligence method that shows high performance in many research areas through its ability to learn high-level hidden features in data samples.The present paper describes a method to predict the cylinder pressure of a Homogeneous Charge Compression Ignition(HCCI)engine for various excess air coefficients by using Deep Neural Network,which is one of the Deep Learning methods and is based on the Artificial Neural Network(ANN).The Deep Learning results were compared with the ANN and experimental results.The results show that the difference between experimental and the Deep Neural Network(DNN)results were less than 1%.The best results were obtained by Deep Learning method.The cylinder pressure was predicted with a maximum accuracy of 97.83% of the experimental value by using ANN.On the other hand,the accuracy value was increased up to 99.84% using DNN.These results show that the DNN method can be used effectively to predict cylinder pressures of internal combustion engines. 相似文献