基于人工智能的汽油车发动机故障诊断研究

Research on Engine Fault Diagnosis of Gasoline Vehicle Based on Artificial Intelligence

近些年来,伴随着我国经济发展速度的不断加快,在科学技术领域也有了全新的突破,现如今人工智能技术已经能够应用到各个领域当中,并取得了不错的成果。本文中,笔者就结合人工智能视角下的汽油车发动机故障诊断进行分析,提出了多信息融合、基于RBF神经网络的数据层、基于支持向量机的特征层以及基于D_S证据理论的决策层这四种故障诊断方法,希望能够提高汽油车发动机的故障诊断能力。

In recent years,with the continuous acceleration of China's economic development,there have been new breakthroughs in the field of science and technology.Now artificial intelligence technology has been able to be applied to various fields,and achieved good results.In this article,the author is combined with artificial intelligence under the perspective of gasoline car engine fault diagnosis were analyzed,and puts forward the multiple information fusion based on RBF neural network,the data layer,feature layer based on support vector machine(SVM)and policy makers based on the theory of the D_S evidence that four kinds of fault diagnosis methods,hoping to improve gasoline car engine fault diagnosis ability.