智能制造系统中关键部件故障模式分析 -机械设计制造及其自动化专业

摘要

随着工业4.0和智能制造的快速发展，关键部件的故障模式分析成为保障系统稳定性和生产效率的重要课题。本文聚焦于智能制造系统中核心部件的故障模式，旨在通过多层次、多维度的分析方法，揭示其潜在的故障机制并提出有效的预防策略。研究基于大数据分析和机器学习技术，结合实际生产环境中的传感器数据和历史故障记录，构建了高精度的故障预测模型。通过对某大型制造企业的实际案例分析，研究发现温度、振动和电流等参数的变化与关键部件的故障密切相关。此外，本文首次提出了基于深度学习的故障模式识别框架，能够有效区分不同类型的故障并提前预警。实验结果表明，该框架在故障预测准确率和响应时间上均优于传统方法，显著提升了系统的可靠性和维护效率。本文的研究不仅为智能制造系统的故障诊断提供了新的理论支持，还为实际生产中的设备维护和管理提供了可操作的解决方案。

关键词：智能制造；故障模式分析；深度学习；故障预测模型

FAILURE MODE ANALYSIS OF KEY COMPONENTS IN INTELLIGENT MANUFACTURING SYSTEM

ABSTRACT

With the rapid development of Industry 4.0 and intelligent manufacturing, fault mode analysis of key components has become an important topic to ensure system stability and production efficiency. This paper focuses on the failure mode of core components in intelligent manufacturing system, aiming to reveal the potential failure mechanism and propose effective prevention strategies through multi-level and multi-dimensional analysis. Based on big data analysis and machine learning technology, a high-precision fault prediction model is constructed by combining sensor data and historical fault records in actual production environment. Through the case study of a large manufacturing enterprise, it is found that the change of parameters such as temperature, vibration and current is closely related to the failure of key components. In addition, this paper proposes for the first time a fault pattern recognition fr amework based on deep learning, which can effectively distinguish different types of faults and give early warning. The experimental results show that the proposed fr amework is superior to the traditional methods in both fault prediction accuracy and response time, and significantly improves the reliability and maintenance efficiency of the system. The research in this paper not only provides a new theoretical support for fault diagnosis of intelligent manufacturing system, but also provides an operable solution for equipment maintenance and management in actual production.

KEY WORDS：Intelligent Manufacturing; Failure Mode Analysis; Deep Learning; Fault Prediction Model

摘要 I

ABSTRACT II

第1章绪论 2

1.1 研究背景及意义 2

1.2 智能制造系统中关键部件故障模式分析的研究现状 2

第2章智能制造系统关键部件故障模式的分类与识别 4

2.1 关键部件故障模式的分类方法 4

2.2 基于数据驱动的故障模式识别技术 4

2.3 典型智能制造系统中的故障模式案例分析 5

第3章智能制造系统关键部件故障模式的影响因素分析 6

3.1 环境因素对关键部件故障模式的影响 6