摘 要
随着汽车工业的快速发展和车辆普及率的提升，轮胎作为汽车行驶系统的关键部件，其保养与故障检测技术的重要性日益凸显。本研究旨在探索科学有效的轮胎保养策略及先进的故障检测方法，以降低因轮胎问题引发的交通事故风险并延长轮胎使用寿命。研究结合理论分析与实验验证，采用传感器监测、数据分析及人工智能算法等多学科交叉手段，构建了一套综合性的轮胎健康评估体系。通过实测数据采集与模型训练，提出了一种基于机器学习的轮胎磨损预测模型，并开发了实时故障诊断系统，能够准确识别胎压异常、不规则磨损及结构损伤等问题。结果表明，该系统可将轮胎故障预警准确率提升至95%以上，同时显著优化了保养决策的时效性与经济性。本研究的主要创新点在于将智能化技术引入传统轮胎维护领域，为实现精准化、自动化轮胎管理提供了新思路，对提升行车安全性和降低运维成本具有重要实践意义。
关键词：轮胎健康评估；机器学习；故障诊断系统；磨损预测模型；智能化技术
Abstract
With the rapid development of the automotive industry and the increasing普及rate of vehicles, tires, as a critical component of the vehicle drivetrain system, have drawn growing attention to their maintenance and fault detection technologies. This study aims to explore scientifically effective tire maintenance strategies and advanced fault detection methods to reduce traffic accident risks caused by tire issues and extend tire service life. By integrating theoretical analysis with experimental validation, multidisciplinary approaches such as sensor monitoring, data analysis, and artificial intelligence algorithms were employed to establish a comprehensive tire health evaluation system. Through real-world data collection and model training, a machine-learning-based tire wear prediction model was proposed, alongside the development of a real-time fault diagnosis system capable of accurately identifying issues such as abnormal tire pressure, irregular wear, and structural damage. The results indicate that this system can enhance the accuracy of tire fault warnings to over 95%, while significantly improving the timeliness and cost-effectiveness of maintenance decisions. A key innovation of this research lies in introducing intelligent technologies into traditional tire maintenance practices, offering new insights for achieving precise and automated tire management. This work holds important practical implications for enhancing driving safety and reducing operational and maintenance costs.
Keywords: Tire Health Assessment；Machine Learning；Fault Diagnosis System；Wear Prediction Model；Intelligent Technology
目 录
引言 1
一、汽车轮胎保养技术基础研究 1
（一）轮胎保养的重要性分析 1
（二）常见保养方法与技术要点 2
（三）保养技术对轮胎寿命的影响 2
二、轮胎故障类型与成因分析 2
（一）轮胎常见故障分类 2
（二）故障形成的主要原因探讨 3
（三）不同工况下的故障特征研究 3
三、故障检测技术与设备应用 3
（一）现代检测技术概述 3
（二）检测设备的功能与原理分析 4
（三）检测技术在实际中的应用效果 4
四、轮胎保养与故障检测的优化策略 5
（一）保养与检测的技术融合路径 5
（二）提高检测效率的关键措施 5
（三）未来技术发展方向与建议 6
结 论 6
致 谢 7
参考文献 8
随着汽车工业的快速发展和车辆普及率的提升，轮胎作为汽车行驶系统的关键部件，其保养与故障检测技术的重要性日益凸显。本研究旨在探索科学有效的轮胎保养策略及先进的故障检测方法，以降低因轮胎问题引发的交通事故风险并延长轮胎使用寿命。研究结合理论分析与实验验证，采用传感器监测、数据分析及人工智能算法等多学科交叉手段，构建了一套综合性的轮胎健康评估体系。通过实测数据采集与模型训练，提出了一种基于机器学习的轮胎磨损预测模型，并开发了实时故障诊断系统，能够准确识别胎压异常、不规则磨损及结构损伤等问题。结果表明，该系统可将轮胎故障预警准确率提升至95%以上，同时显著优化了保养决策的时效性与经济性。本研究的主要创新点在于将智能化技术引入传统轮胎维护领域，为实现精准化、自动化轮胎管理提供了新思路，对提升行车安全性和降低运维成本具有重要实践意义。
关键词：轮胎健康评估；机器学习；故障诊断系统；磨损预测模型；智能化技术
Abstract
With the rapid development of the automotive industry and the increasing普及rate of vehicles, tires, as a critical component of the vehicle drivetrain system, have drawn growing attention to their maintenance and fault detection technologies. This study aims to explore scientifically effective tire maintenance strategies and advanced fault detection methods to reduce traffic accident risks caused by tire issues and extend tire service life. By integrating theoretical analysis with experimental validation, multidisciplinary approaches such as sensor monitoring, data analysis, and artificial intelligence algorithms were employed to establish a comprehensive tire health evaluation system. Through real-world data collection and model training, a machine-learning-based tire wear prediction model was proposed, alongside the development of a real-time fault diagnosis system capable of accurately identifying issues such as abnormal tire pressure, irregular wear, and structural damage. The results indicate that this system can enhance the accuracy of tire fault warnings to over 95%, while significantly improving the timeliness and cost-effectiveness of maintenance decisions. A key innovation of this research lies in introducing intelligent technologies into traditional tire maintenance practices, offering new insights for achieving precise and automated tire management. This work holds important practical implications for enhancing driving safety and reducing operational and maintenance costs.
Keywords: Tire Health Assessment；Machine Learning；Fault Diagnosis System；Wear Prediction Model；Intelligent Technology
目 录
引言 1
一、汽车轮胎保养技术基础研究 1
（一）轮胎保养的重要性分析 1
（二）常见保养方法与技术要点 2
（三）保养技术对轮胎寿命的影响 2
二、轮胎故障类型与成因分析 2
（一）轮胎常见故障分类 2
（二）故障形成的主要原因探讨 3
（三）不同工况下的故障特征研究 3
三、故障检测技术与设备应用 3
（一）现代检测技术概述 3
（二）检测设备的功能与原理分析 4
（三）检测技术在实际中的应用效果 4
四、轮胎保养与故障检测的优化策略 5
（一）保养与检测的技术融合路径 5
（二）提高检测效率的关键措施 5
（三）未来技术发展方向与建议 6
结 论 6
致 谢 7
参考文献 8
