摘要
随着现代制造业的快速发展，数控机床作为关键生产设备，其运行可靠性与效率对生产质量及经济效益具有重要影响。然而，由于复杂的工作环境和高强度运行，数控机床故障频发，严重影响生产稳定性。为此，本研究旨在探索高效的数控机床故障诊断方法与维护保养技术，以提升设备的可靠性和使用寿命。研究基于大数据分析与人工智能算法，构建了一套集成化故障诊断模型，能够实时监测设备运行状态并精准定位故障源。同时，结合预防性维护理论，提出了针对性的维护保养策略，有效降低了故障发生率。实验结果表明，所提出的诊断模型在准确性、灵敏度和适应性方面均优于传统方法，且维护策略的应用显著延长了设备的平均无故障时间。本研究的创新点在于将智能化技术与传统维护手段有机结合，实现了从被动维修到主动预防的转变，为数控机床的高效运行提供了技术支持。研究成果不仅为相关领域提供了理论参考，还具备较强的工程应用价值，可广泛推广于各类智能制造场景。
关键词：数控机床故障诊断；智能化维护策略；大数据分析；人工智能算法；平均无故障时间
Abstract
With the rapid development of modern manufacturing, CNC machines, as critical production equipment, play a vital role in production quality and economic efficiency. However, due to complex working environments and high-intensity operations, frequent failures of CNC machines significantly impact production stability. This study aims to explore efficient fault diagnosis methods and maintenance techniques for CNC machines to enhance their reliability and service life. Based on big data analysis and artificial intelligence algorithms, an integrated fault diagnosis model has been developed, which can monitor the operational status of equipment in real-time and accurately pinpoint the source of faults. Additionally, by incorporating preventive maintenance theory, targeted maintenance strategies have been proposed, effectively reducing the failure rate. Experimental results demonstrate that the proposed diagnosis model outperforms traditional methods in terms of accuracy, sensitivity, and adaptability, while the application of maintenance strategies significantly extends the mean time between failures (MTBF). The innovation of this research lies in the organic combination of intelligent technologies with traditional maintenance approaches, achieving a shift from reactive repair to proactive prevention, thereby providing technical support for the efficient operation of CNC machines. The research findings not only offer theoretical references for related fields but also possess significant engineering application value, making them widely applicable in various smart manufacturing scenarios.
Keywords：Cnc Machine Tool Fault Diagnosis; Intelligent Maintenance Strategy; Big Data Analysis; Artificial Intelligence Algorithm; Mean Time Between Failures
目 录
摘要 I
Abstract II
引言 1
一、数控机床故障诊断技术概述 1
(一) 故障诊断的基本概念 1
(二) 数控机床常见故障类型分析 2
(三) 故障诊断技术的发展现状 2
二、数控机床故障诊断方法研究 3
(一) 基于传感器的故障检测技术 3
(二) 数据驱动的故障诊断模型构建 3
(三) 人工智能在故障诊断中的应用 4
三、数控机床维护保养技术分析 5
(一) 维护保养的基本原则与策略 5
(二) 定期维护的关键环节与实施方法 5
(三) 预防性维护的技术手段与效果评估 6
四、数控机床综合管理与优化方案 6
(一) 故障诊断与维护保养的协同机制 6
(二) 智能化管理系统的设计与实现 7
(三) 提高数控机床可靠性的综合措施 8
结 论 9
参考文献 10
