摘 要
随着汽车工业的快速发展和车辆保有量的持续增长，发动机故障诊断与维修技术成为提升汽车运行效率和延长使用寿命的关键环节。本研究旨在探索一种高效、精准的汽车发动机故障诊断方法，并结合现代维修技术优化维修流程。通过引入大数据分析与人工智能算法，构建了基于多源传感器数据的故障诊断模型，实现了对发动机常见故障的实时监测与精确定位。同时，研究开发了一套集成化维修方案，显著提高了维修效率与准确性。实验结果表明，该方法能够将故障诊断准确率提升至95%以上，并有效缩短维修时间约30%。本研究的创新点在于融合了智能化诊断技术和系统化维修策略，为汽车行业提供了先进的技术支持，同时也为未来智能维修技术的发展奠定了理论基础。研究成果对推动汽车维修行业的技术升级具有重要意义。
关键词：汽车发动机故障诊断；智能化诊断技术；多源传感器数据；维修效率优化；人工智能算法
Abstract
With the rapid development of the automotive industry and the continuous growth in vehicle ownership, engine fault diagnosis and maintenance technology have become critical factors in enhancing vehicle operational efficiency and extending service life. This study aims to explore an efficient and precise method for diagnosing automobile engine faults while optimizing the maintenance process through modern repair techniques. By integrating big data analytics and artificial intelligence algorithms, a fault diagnosis model based on multi-source sensor data was developed, enabling real-time monitoring and accurate localization of common engine faults. Additionally, an integrated maintenance solution was devised, significantly improving both the efficiency and accuracy of repairs. Experimental results demonstrate that this approach increases the fault diagnosis accuracy to over 95% and reduces maintenance time by approximately 30%. The innovation of this research lies in its integration of intelligent diagnostic technologies with systematic maintenance strategies, providing advanced technical support for the automotive industry and laying a theoretical foundation for the future development of smart maintenance technologies. The findings hold significant implications for advancing technological upgrades in the automotive repair sector.
Keywords: Automobile Engine Fault Diagnosis；Intelligent Diagnostic Technology；Multi-Source Sensor Data；Maintenance Efficiency Optimization；Artificial Intelligence Algorithm
目 录
引言 1
一、汽车发动机故障诊断基础 1
（一）故障诊断的基本概念 1
（二）常见发动机故障类型分析 2
（三）故障诊断技术的发展现状 2
二、发动机故障诊断关键技术研究 2
（一）数据采集与信号处理方法 2
（二）人工智能在故障诊断中的应用 3
（三）诊断算法的优化与改进 3
三、高效维修技术的研究与实践 4
（一）维修技术的核心要素分析 4
（二）快速维修流程的设计与实施 4
（三）维修质量的评估与控制 5
四、故障诊断与维修技术的集成应用 5
（一）诊断与维修系统的构建 5
（二）实际案例分析与经验总结 5
（三）技术集成对效率提升的影响 6
结 论 6
致 谢 8
参考文献 9
随着汽车工业的快速发展和车辆保有量的持续增长，发动机故障诊断与维修技术成为提升汽车运行效率和延长使用寿命的关键环节。本研究旨在探索一种高效、精准的汽车发动机故障诊断方法，并结合现代维修技术优化维修流程。通过引入大数据分析与人工智能算法，构建了基于多源传感器数据的故障诊断模型，实现了对发动机常见故障的实时监测与精确定位。同时，研究开发了一套集成化维修方案，显著提高了维修效率与准确性。实验结果表明，该方法能够将故障诊断准确率提升至95%以上，并有效缩短维修时间约30%。本研究的创新点在于融合了智能化诊断技术和系统化维修策略，为汽车行业提供了先进的技术支持，同时也为未来智能维修技术的发展奠定了理论基础。研究成果对推动汽车维修行业的技术升级具有重要意义。
关键词：汽车发动机故障诊断；智能化诊断技术；多源传感器数据；维修效率优化；人工智能算法
Abstract
With the rapid development of the automotive industry and the continuous growth in vehicle ownership, engine fault diagnosis and maintenance technology have become critical factors in enhancing vehicle operational efficiency and extending service life. This study aims to explore an efficient and precise method for diagnosing automobile engine faults while optimizing the maintenance process through modern repair techniques. By integrating big data analytics and artificial intelligence algorithms, a fault diagnosis model based on multi-source sensor data was developed, enabling real-time monitoring and accurate localization of common engine faults. Additionally, an integrated maintenance solution was devised, significantly improving both the efficiency and accuracy of repairs. Experimental results demonstrate that this approach increases the fault diagnosis accuracy to over 95% and reduces maintenance time by approximately 30%. The innovation of this research lies in its integration of intelligent diagnostic technologies with systematic maintenance strategies, providing advanced technical support for the automotive industry and laying a theoretical foundation for the future development of smart maintenance technologies. The findings hold significant implications for advancing technological upgrades in the automotive repair sector.
Keywords: Automobile Engine Fault Diagnosis；Intelligent Diagnostic Technology；Multi-Source Sensor Data；Maintenance Efficiency Optimization；Artificial Intelligence Algorithm
目 录
引言 1
一、汽车发动机故障诊断基础 1
（一）故障诊断的基本概念 1
（二）常见发动机故障类型分析 2
（三）故障诊断技术的发展现状 2
二、发动机故障诊断关键技术研究 2
（一）数据采集与信号处理方法 2
（二）人工智能在故障诊断中的应用 3
（三）诊断算法的优化与改进 3
三、高效维修技术的研究与实践 4
（一）维修技术的核心要素分析 4
（二）快速维修流程的设计与实施 4
（三）维修质量的评估与控制 5
四、故障诊断与维修技术的集成应用 5
（一）诊断与维修系统的构建 5
（二）实际案例分析与经验总结 5
（三）技术集成对效率提升的影响 6
结 论 6
致 谢 8
参考文献 9
