摘 要
本研究针对自动化生产线中的故障诊断与处理展开深入探讨。随着工业自动化水平的不断提升，生产线故障的快速准确诊断与处理显得尤为重要。本研究旨在通过综合运用先进的传感技术、数据分析及机器学习算法，实现对自动化生产线故障的高效识别与定位，进而优化故障处理流程，提高生产线的稳定性和运行效率。研究方法上，我们采用了多种传感器对生产线进行实时监控，收集了大量故障数据与非故障数据，并利用机器学习算法构建故障诊断模型。实验结果表明，该模型能够准确识别并预警潜在的故障点，有效缩短了故障排查时间，提高了维修效率。本研究的创新点在于结合了传统的故障诊断技术与现代数据分析方法，实现了对生产线故障的精准预测与快速响应。主要贡献在于提供了一种智能化、自动化的故障诊断与处理方案，为工业自动化领域的发展提供了新的思路和方法。通过本研究，我们期望能为相关企业提供更加智能、高效的故障诊断技术支持，推动工业自动化技术的进一步发展。
关键词：自动化生产线；故障诊断；机器学习算法
Abstract
In this paper, fault diagnosis and treatment in automatic production line are discussed in depth. With the continuous improvement of the level of industrial automation, the rapid and accurate diagnosis and treatment of production line faults is particularly important. This study aims to realize efficient fault identification and location of automated production lines through comprehensive application of advanced sensing technology, data analysis and machine learning algorithms, so as to optimize the fault handling process and improve the stability and operation efficiency of the production line. In terms of research methods, we use a variety of sensors to monitor the production line in real time, collect a lot of fault data and non-fault data, and use machine learning algorithms to build fault diagnosis models. The experimental results show that the model can accurately identify and warn potential fault points, effectively shorten the troubleshooting time and improve the maintenance efficiency. The innovation of this research is that the traditional fault diagnosis technology and modern data analysis method are combined to achieve accurate prediction and rapid response to production line faults. The main contribution is to provide an intelligent and automatic fault diagnosis and treatment scheme, which provides a new idea and method for the development of industrial automation field. Through this research, we hope to provide more intelligent and efficient fault diagnosis technical support for related enterprises, and promote the further development of industrial automation technology.
Key Words: Automatic production line; Fault diagnosis; Machine learning algorithm
目 录
第一章 绪 论 1
1.1 研究背景和意义 1
1.2 国内外研究现状 1
第二章 自动化生产线故障诊断技术 3
2.1 故障诊断技术概述 3
2.2 基于模型的故障诊断方法 3
2.3 基于数据驱动的故障诊断方法 4
第三章 自动化生产线故障处理策略 6
3.1 故障处理策略概述 6
3.2 预防性故障处理措施 6
3.3 响应性故障处理流程 7
第四章 自动化生产线故障诊断与处理系统实现 8
4.1 系统设计原则与目标 8
4.2 故障诊断模块设计与实现 8
4.3 故障处理模块设计与实现 9
结论 11
致 谢 12
参考文献 13
