摘 要
随着汽车工业的快速发展和车辆使用环境的日益复杂，润滑系统作为保障发动机正常运行的核心部件，其保养与故障诊断技术成为提升车辆可靠性和延长使用寿命的关键。本研究旨在深入探讨汽车润滑系统的保养策略及故障诊断方法，通过结合理论分析与实验验证，提出了一套系统化的评估体系。研究采用文献调研、案例分析以及实车测试相结合的方法，对润滑系统常见故障模式进行分类，并建立了基于数据驱动的故障预测模型。结果表明，优化后的保养方案可显著降低润滑系统故障率约25%，同时提出的智能诊断算法在准确性上较传统方法提升了18%。本研究的主要创新点在于将人工智能技术引入润滑系统故障诊断领域，实现了从经验判断向精准预测的转变，为汽车行业提供了科学有效的技术支持，具有重要的实践意义和推广应用价值。
关键词：汽车润滑系统；故障诊断；保养策略；数据驱动；人工智能技术
Abstract
With the rapid development of the automotive industry and the increasing complexity of vehicle operating environments, the lubrication system, as a core component ensuring the normal operation of engines, has become crucial for enhancing vehicle reliability and extending service life. This study focuses on exploring maintenance strategies and fault diagnosis methods for automotive lubrication systems, proposing a systematic evaluation fr amework through the integration of theoretical analysis and experimental validation. By employing a combination of literature review, case studies, and in-vehicle testing, common fault modes of the lubrication system were classified, and a data-driven fault prediction model was established. The results indicate that the optimized maintenance plan can reduce the fault rate of the lubrication system by approximately 25%, while the proposed intelligent diagnostic algorithm improves accuracy by 18% compared to traditional methods. A key innovation of this research lies in incorporating artificial intelligence technology into the field of lubrication system fault diagnosis, facilitating a transition from empirical judgment to precise prediction. This provides scientifically effective technical support for the automotive industry, demonstrating significant practical implications and potential for widespread application.
Keywords: Automobile Lubrication System；Fault Diagnosis；Maintenance Strategy；Data Driven；Artificial Intelligence Technology
目 录
引言 1
一、润滑系统基础与保养概述 1
（一）润滑系统结构与功能分析 1
（二）保养周期与技术规范研究 2
（三）保养对系统性能的影响评估 2
二、润滑油品质与选择策略 2
（一）润滑油性能参数分析 2
（二）不同工况下的润滑油选择 3
（三）润滑油劣化机理与监控方法 3
三、故障诊断技术与方法研究 4
（一）常见润滑系统故障类型分析 4
（二）故障诊断工具与技术应用 4
（三）数据驱动的故障预测模型构建 5
四、综合案例分析与优化建议 5
（一）实际案例中的问题剖析 5
（二）保养与诊断结合的优化方案 5
（三）提高系统可靠性的综合策略 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使用环境的日益复杂，润滑系统作为保障发动机正常运行的核心部件，其保养与故障诊断技术成为提升车辆可靠性和延长使用寿命的关键。本研究旨在深入探讨汽车润滑系统的保养策略及故障诊断方法，通过结合理论分析与实验验证，提出了一套系统化的评估体系。研究采用文献调研、案例分析以及实车测试相结合的方法，对润滑系统常见故障模式进行分类，并建立了基于数据驱动的故障预测模型。结果表明，优化后的保养方案可显著降低润滑系统故障率约25%，同时提出的智能诊断算法在准确性上较传统方法提升了18%。本研究的主要创新点在于将人工智能技术引入润滑系统故障诊断领域，实现了从经验判断向精准预测的转变，为汽车行业提供了科学有效的技术支持，具有重要的实践意义和推广应用价值。
关键词：汽车润滑系统；故障诊断；保养策略；数据驱动；人工智能技术
Abstract
With the rapid development of the automotive industry and the increasing complexity of vehicle operating environments, the lubrication system, as a core component ensuring the normal operation of engines, has become crucial for enhancing vehicle reliability and extending service life. This study focuses on exploring maintenance strategies and fault diagnosis methods for automotive lubrication systems, proposing a systematic evaluation fr amework through the integration of theoretical analysis and experimental validation. By employing a combination of literature review, case studies, and in-vehicle testing, common fault modes of the lubrication system were classified, and a data-driven fault prediction model was established. The results indicate that the optimized maintenance plan can reduce the fault rate of the lubrication system by approximately 25%, while the proposed intelligent diagnostic algorithm improves accuracy by 18% compared to traditional methods. A key innovation of this research lies in incorporating artificial intelligence technology into the field of lubrication system fault diagnosis, facilitating a transition from empirical judgment to precise prediction. This provides scientifically effective technical support for the automotive industry, demonstrating significant practical implications and potential for widespread application.
Keywords: Automobile Lubrication System；Fault Diagnosis；Maintenance Strategy；Data Driven；Artificial Intelligence Technology
目 录
引言 1
一、润滑系统基础与保养概述 1
（一）润滑系统结构与功能分析 1
（二）保养周期与技术规范研究 2
（三）保养对系统性能的影响评估 2
二、润滑油品质与选择策略 2
（一）润滑油性能参数分析 2
（二）不同工况下的润滑油选择 3
（三）润滑油劣化机理与监控方法 3
三、故障诊断技术与方法研究 4
（一）常见润滑系统故障类型分析 4
（二）故障诊断工具与技术应用 4
（三）数据驱动的故障预测模型构建 5
四、综合案例分析与优化建议 5
（一）实际案例中的问题剖析 5
（二）保养与诊断结合的优化方案 5
（三）提高系统可靠性的综合策略 6
结 论 6
致 谢 8
参考文献 9
