摘要翻译：
近十年来，随着工业机械和电气系统的发展，故障诊断已成为一个非常重要的研究领域。汽车是故障诊断的一个重要领域。由于车辆的复杂性和新增加的特征，必须进行全面的研究，以获得一个合适的诊断模型。诊断系统能够通过调查可观察到的影响（或症状）来识别系统的故障。系统将故障分类为诊断类，并根据提供的故障征兆识别可能的原因。采用相似匹配技术进行故障分类和识别。诊断类的开发是通过利用应用领域内以前的经验、知识或信息来完成的。所使用的必要信息可能来自几个知识来源，例如来自系统分析。本文讨论了汽车信息娱乐应用中的相似匹配故障诊断技术。
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英文标题：
《Similarity Matching Techniques for Fault Diagnosis in Automotive
  Infotainment Electronics》
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作者：
Mashud Kabir
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最新提交年份：
2009
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  Fault diagnosis has become a very important area of research during the last decade due to the advancement of mechanical and electrical systems in industries. The automobile is a crucial field where fault diagnosis is given a special attention. Due to the increasing complexity and newly added features in vehicles, a comprehensive study has to be performed in order to achieve an appropriate diagnosis model. A diagnosis system is capable of identifying the faults of a system by investigating the observable effects (or symptoms). The system categorizes the fault into a diagnosis class and identifies a probable cause based on the supplied fault symptoms. Fault categorization and identification are done using similarity matching techniques. The development of diagnosis classes is done by making use of previous experience, knowledge or information within an application area. The necessary information used may come from several sources of knowledge, such as from system analysis. In this paper similarity matching techniques for fault diagnosis in automotive infotainment applications are discussed.
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PDF链接：
https://arxiv.org/pdf/0909.2375