自动化装配系统的故障诊断技术研究 -电气工程及其自动化专业

摘要

随着现代制造业的快速发展，自动化装配系统在提高生产效率和产品质量方面发挥着重要作用，但其复杂性也导致故障频发，严重影响生产稳定性。为此，本文聚焦于自动化装配系统的故障诊断技术研究，旨在建立一套高效、精准的故障诊断方法，以保障系统稳定运行。研究基于多源数据融合技术，整合传感器数据、工艺参数及历史故障信息，构建了包含特征提取、状态识别与故障定位的完整诊断框架。创新性地引入深度学习算法，通过卷积神经网络对图像类故障进行识别，利用长短期记忆网络实现时序数据的故障预测，显著提升了诊断精度与时效性。实验结果表明，该方法能够准确识别95%以上的常见故障类型，并将故障定位误差控制在5%以内。此外，开发的在线监测平台可实时反馈系统健康状态，为预防性维护提供决策支持。本研究不仅为自动化装配系统的故障诊断提供了新思路，也为智能制造领域的设备健康管理奠定了理论基础，具有重要的工程应用价值。

关键词：自动化装配系统故障诊断技术多源数据融合

Abstract

With the rapid development of modern manufacturing, automated assembly systems play a crucial role in enhancing production efficiency and product quality; however, their complexity leads to frequent faults, severely impacting production stability. This study focuses on fault diagnosis technology for automated assembly systems, aiming to establish an efficient and accurate fault diagnosis method to ensure stable system operation. Based on multi-source data fusion technology, this research integrates sensor data, process parameters, and historical fault information to construct a comprehensive diagnostic fr amework encompassing feature extraction, state recognition, and fault localization. Innovatively, deep learning algorithms are introduced, employing convolutional neural networks for image-based fault identification and long short-term memory networks for time-series data-based fault prediction, significantly improving diagnostic accuracy and timeliness. Experimental results demonstrate that this method can accurately identify over 95% of common fault types and control fault localization errors within 5%. Additionally, the developed online monitoring platform provides real-time feedback on system health status, offering decision support for preventive maintenance. This research not only offers new insights into fault diagnosis for automated assembly systems but also lays a theoretical foundation for equipment health management in the field of smart manufacturing, demonstrating significant engineering application value.

Keyword:Automation Assembly System Fault Diagnosis Technology Multi-source Data Fusion

1绪论 1

1.1自动化装配系统故障诊断的背景与意义 1

1.2国内外研究现状综述 1

1.3本文研究方法概述 2

2故障诊断技术基础理论 2

2.1故障诊断的基本概念 2

2.2常见故障模式分析 3

2.3故障诊断技术分类 3

3关键传感器与数据采集 4

3.1传感器选型原则 4

3.2数据采集系统设计 5