摘 要
随着汽车工业的快速发展和车辆保有量的持续增长，制动系统作为保障行车安全的核心部件，其故障诊断与高效维修策略的研究显得尤为重要。本研究旨在针对汽车制动系统常见故障类型及成因，提出一种基于多源数据融合与智能算法的故障诊断方法，并结合实际维修需求设计高效的维修策略。通过采集制动系统的运行数据并引入机器学习模型进行特征提取与分类预测，实现了对制动失效、制动力不足等问题的精准识别。同时，研究开发了一套模块化维修方案，显著缩短了维修周期并降低了成本。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，且维修效率提高约30%。本研究的创新点在于将智能化技术与传统维修经验有机结合，为汽车行业提供了更为科学、高效的制动系统维护手段，对提升车辆安全性及降低运维成本具有重要实践意义。
关键词：汽车制动系统；故障诊断；多源数据融合；智能算法；维修策略
Abstract
With the rapid development of the automotive industry and the continuous growth in vehicle ownership, the braking system, as a core component ensuring driving safety, has drawn significant attention regarding its fault diagnosis and efficient maintenance strategies. This study focuses on common fault types and causes in automotive braking systems, proposing a fault diagnosis method based on multi-source data fusion and intelligent algorithms while designing an efficient maintenance strategy tailored to practical repair needs. By collecting operational data from the braking system and incorporating machine learning models for feature extraction and classification prediction, precise identification of issues such as brake failure and insufficient braking force is achieved. Additionally, a modular maintenance scheme was developed, substantially reducing repair cycles and lowering costs. Experimental results demonstrate that this approach can increase fault diagnosis accuracy to over 95% and improve maintenance efficiency by approximately 30%. The innovation of this study lies in the integration of intelligent technologies with traditional maintenance experience, providing the automotive industry with a more scientific and efficient means of maintaining braking systems, which holds important practical significance for enhancing vehicle safety and reducing operation and maintenance costs.
Keywords: Automobile Brake System；Fault Diagnosis；Multi-Source Data Fusion；Intelligent Algorithm；Maintenance Strategy
目 录
引言 1
一、汽车制动系统故障分析 1
（一）制动系统常见故障类型 1
（二）故障形成机理研究 2
（三）故障影响因素评估 2
二、故障诊断技术与方法 2
（一）传统诊断技术应用 2
（二）现代诊断工具开发 3
（三）数据驱动诊断策略 3
三、高效维修策略设计 4
（一）维修流程优化方案 4
（二）关键零部件更换标准 4
（三）预防性维护措施研究 5
四、实际应用与案例分析 5
（一）典型故障案例解析 5
（二）维修效果评估方法 5
（三）改进措施与经验总结 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，制动系统作为保障行车安全的核心部件，其故障诊断与高效维修策略的研究显得尤为重要。本研究旨在针对汽车制动系统常见故障类型及成因，提出一种基于多源数据融合与智能算法的故障诊断方法，并结合实际维修需求设计高效的维修策略。通过采集制动系统的运行数据并引入机器学习模型进行特征提取与分类预测，实现了对制动失效、制动力不足等问题的精准识别。同时，研究开发了一套模块化维修方案，显著缩短了维修周期并降低了成本。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，且维修效率提高约30%。本研究的创新点在于将智能化技术与传统维修经验有机结合，为汽车行业提供了更为科学、高效的制动系统维护手段，对提升车辆安全性及降低运维成本具有重要实践意义。
关键词：汽车制动系统；故障诊断；多源数据融合；智能算法；维修策略
Abstract
With the rapid development of the automotive industry and the continuous growth in vehicle ownership, the braking system, as a core component ensuring driving safety, has drawn significant attention regarding its fault diagnosis and efficient maintenance strategies. This study focuses on common fault types and causes in automotive braking systems, proposing a fault diagnosis method based on multi-source data fusion and intelligent algorithms while designing an efficient maintenance strategy tailored to practical repair needs. By collecting operational data from the braking system and incorporating machine learning models for feature extraction and classification prediction, precise identification of issues such as brake failure and insufficient braking force is achieved. Additionally, a modular maintenance scheme was developed, substantially reducing repair cycles and lowering costs. Experimental results demonstrate that this approach can increase fault diagnosis accuracy to over 95% and improve maintenance efficiency by approximately 30%. The innovation of this study lies in the integration of intelligent technologies with traditional maintenance experience, providing the automotive industry with a more scientific and efficient means of maintaining braking systems, which holds important practical significance for enhancing vehicle safety and reducing operation and maintenance costs.
Keywords: Automobile Brake System；Fault Diagnosis；Multi-Source Data Fusion；Intelligent Algorithm；Maintenance Strategy
目 录
引言 1
一、汽车制动系统故障分析 1
（一）制动系统常见故障类型 1
（二）故障形成机理研究 2
（三）故障影响因素评估 2
二、故障诊断技术与方法 2
（一）传统诊断技术应用 2
（二）现代诊断工具开发 3
（三）数据驱动诊断策略 3
三、高效维修策略设计 4
（一）维修流程优化方案 4
（二）关键零部件更换标准 4
（三）预防性维护措施研究 5
四、实际应用与案例分析 5
（一）典型故障案例解析 5
（二）维修效果评估方法 5
（三）改进措施与经验总结 6
结 论 6
致 谢 8
参考文献 9
