摘 要
随着汽车电气化和智能化的快速发展，汽车电气系统复杂性显著提升，故障检测与维修成为保障车辆安全运行的关键环节。本研究旨在针对汽车电气系统故障检测与维修中的难点问题，提出一种基于多源数据融合的智能诊断方法。通过结合传感器数据、车载网络信息及历史维修记录，构建了故障特征提取模型，并引入机器学习算法优化故障分类与定位过程。研究结果表明，该方法能够有效提高故障检测的准确率和效率，同时降低误判率。此外，本文还设计了一套标准化的维修流程，为技术人员提供明确的操作指导。创新点在于首次将多源数据融合技术应用于汽车电气系统故障诊断，并实现了从检测到维修的全流程优化。本研究为提升汽车电气系统的可靠性和维护效率提供了重要参考，对现代汽车维修技术的发展具有积极意义。
关键词：汽车电气系统；多源数据融合；智能诊断；故障检测；维修流程优化
Abstract
With the rapid development of vehicle electrification and intelligence, the complexity of automotive electrical systems has significantly increased, making fault detection and maintenance critical to ensuring safe vehicle operation. This study focuses on addressing challenging issues in the fault detection and repair of automotive electrical systems by proposing an intelligent diagnostic method based on multi-source data fusion. By integrating sensor data, in-vehicle network information, and historical maintenance records, a fault feature extraction model was constructed, and machine learning algorithms were introduced to optimize the processes of fault classification and localization. The results demonstrate that this method effectively enhances the accuracy and efficiency of fault detection while reducing misjudgment rates. Additionally, a standardized maintenance procedure was designed to provide technicians with clear operational guidance. The innovation lies in the first application of multi-source data fusion technology to automotive electrical system fault diagnosis, achieving comprehensive optimization from detection to repair. This research provides significant reference for improving the reliability and maintenance efficiency of automotive electrical systems and contributes positively to the development of modern automotive repair technologies.
Keywords: Automobile Electrical System；Multi-Source Data Fusion；Intelligent Diagnosis；Fault Detection；Maintenance Process Optimization
目 录
引言 1
一、汽车电气系统故障概述 1
（一）故障类型与特点分析 1
（二）故障成因及其影响因素 1
（三）研究现状与发展趋势 2
二、故障检测技术与方法 2
（一）常用检测工具与设备 2
（二）数据采集与分析方法 3
（三）智能化检测技术应用 3
三、维修策略与实施路径 4
（一）维修原则与基本流程 4
（二）典型故障维修案例分析 4
（三）提高维修效率的关键措施 4
四、未来发展方向与优化建议 5
（一）新技术在检测中的应用前景 5
（二）维修标准化体系建设探讨 5
（三）行业发展对人才的要求 6
结 论 6
致 谢 7
参考文献 8
随着汽车电气化和智能化的快速发展，汽车电气系统复杂性显著提升，故障检测与维修成为保障车辆安全运行的关键环节。本研究旨在针对汽车电气系统故障检测与维修中的难点问题，提出一种基于多源数据融合的智能诊断方法。通过结合传感器数据、车载网络信息及历史维修记录，构建了故障特征提取模型，并引入机器学习算法优化故障分类与定位过程。研究结果表明，该方法能够有效提高故障检测的准确率和效率，同时降低误判率。此外，本文还设计了一套标准化的维修流程，为技术人员提供明确的操作指导。创新点在于首次将多源数据融合技术应用于汽车电气系统故障诊断，并实现了从检测到维修的全流程优化。本研究为提升汽车电气系统的可靠性和维护效率提供了重要参考，对现代汽车维修技术的发展具有积极意义。
关键词：汽车电气系统；多源数据融合；智能诊断；故障检测；维修流程优化
Abstract
With the rapid development of vehicle electrification and intelligence, the complexity of automotive electrical systems has significantly increased, making fault detection and maintenance critical to ensuring safe vehicle operation. This study focuses on addressing challenging issues in the fault detection and repair of automotive electrical systems by proposing an intelligent diagnostic method based on multi-source data fusion. By integrating sensor data, in-vehicle network information, and historical maintenance records, a fault feature extraction model was constructed, and machine learning algorithms were introduced to optimize the processes of fault classification and localization. The results demonstrate that this method effectively enhances the accuracy and efficiency of fault detection while reducing misjudgment rates. Additionally, a standardized maintenance procedure was designed to provide technicians with clear operational guidance. The innovation lies in the first application of multi-source data fusion technology to automotive electrical system fault diagnosis, achieving comprehensive optimization from detection to repair. This research provides significant reference for improving the reliability and maintenance efficiency of automotive electrical systems and contributes positively to the development of modern automotive repair technologies.
Keywords: Automobile Electrical System；Multi-Source Data Fusion；Intelligent Diagnosis；Fault Detection；Maintenance Process Optimization
目 录
引言 1
一、汽车电气系统故障概述 1
（一）故障类型与特点分析 1
（二）故障成因及其影响因素 1
（三）研究现状与发展趋势 2
二、故障检测技术与方法 2
（一）常用检测工具与设备 2
（二）数据采集与分析方法 3
（三）智能化检测技术应用 3
三、维修策略与实施路径 4
（一）维修原则与基本流程 4
（二）典型故障维修案例分析 4
（三）提高维修效率的关键措施 4
四、未来发展方向与优化建议 5
（一）新技术在检测中的应用前景 5
（二）维修标准化体系建设探讨 5
（三）行业发展对人才的要求 6
结 论 6
致 谢 7
参考文献 8
