基于CPN神经网络的柴油机故障诊断(论文15000字,外文翻译)
摘要：近年来，大容量柴油机组作为人们日常生活中的重要动力源，一旦其运行处于异常状态，会造成严重的事故和经济损失。为了确定故障位置，及早采取措施，建立一套完善的状态监测与故障诊断系统是十分必要的。本文将CPN神经网络应用于柴油机组的故障诊断方法中，克服传统的人工诊断精度低，步骤繁琐，诊断时间长等缺点，增强泛化能力，提高收敛速度和精度，从而能够实现获得比一般诊断方法更加优异的诊断效果。通过本文的方法能够使得柴油机组更加高效地运行，出现问题后能够及时的解决，使得运营成本大大降低，经济效益得到提高，同时避免引发更大的事故，这也是国内外动力行业所面临的重要研究课题，具有重要的工程意义。
关键词：柴油机；状态监测；故障诊断；神经网络
Fault diagnosis of diesel engine based on CPN neural network
Abstract：In recent years, large capacity diesel engine set is an important power source in people's daily life.Once the operation is abnormal, it will cause serious accidents and economic losses. So it is necessary to establish a set of condition monitoring and fault diagnosis system in order to determine the fault location.In this paper, the fault diagnosis method of CPN neural network is applied to diesel engine unit, overcome the artificial diagnosis accuracy of the traditional low, cumbersome steps, disadvantages of long diagnosis time, enhance the generalization ability, improve the convergence speed and accuracy, which can achieve the diagnosis effect more excellent than the general diagnostic method.Through this method can make the engine more efficient operation, timely solve problems, make operation cost is greatly reduced, the economic benefit is improved, at the same time to avoid more accidents, the important research topic of power industry which is facing at home and abroad, has an important engineering significance.
Key words: diesel engine; condition monitoring; fault diagnosis; neural network
目录
摘要 1
Abstract 2
1绪论 3
1.1研究背景和意义 3
1.2国内外研究现状及趋势 5
2柴油机组简介 9
2.1柴油机系统结构 9
2.2柴油机工作原理 9
2.3柴油机常见故障类型 9
3柴油机组诊断原理 10
3.1数据预处理与特征提取 10
3.2故障诊断的时域分析法 10
3.3故障诊断的频域分析法 11
4对偶神经网络 12
4.1神经网络简介 12
4.2对偶传播神经网络（CPN）组成结构 13
4.3对偶神经网络的学习算法 14
5故障诊断实例研究 16
5.1诊断流程 16
5.2特征选择 17
5.3神经网络建模 17
5.4故障诊断的实现 21
6结论与展望 26
参考文献 27
附录 29
致谢 32
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