基于深度学习的数控机床故障知识图谱构建探索

中图分类号：G424

文献标识码：A DOI：10.16400/j.cnki.kjdk.2025.20.023

Exploration on the Construction of Fault Knowledge Graph for CNC Machine Tools Based on Deep Learning

SHENGJunfei

（Yixing Higher Vocational School， Yixing， Jiangsu ）

AbstractRapid diagnosis and repair ofCNC machine tool faultsare crucial for ensuring production effciency and reducing maintenance costs.However，the scatered and heterogeneous nature of machine tool fault knowledge poses challenges to fault diagnosis.This paper explores a method ofconstructing a fault knowledge graph for CNC machine tools by integratingdeep learningtechnology，expounds on the important roleofknowledge graphs in integrating CNC machinetol fault knowledge and asisting intelligent diagnostic decision-making，and proposes a systematic technical route for knowledge graph construction. Taking the faults ofthe feed axis of CNC machine tools as an example， the application process of the proposed method is demonstrated.

KeywordsCNC machine tools; fault diagnosis; knowledge graph; deep learning; intelligent manufacturing

随着智能制造的快速发展，数控机床作为离散制造业的关键装备，其可靠性和智能化水平备受关注，然而，由于数控机床结构日益复杂，工况多变，故障问题频发，严重影响生产效率和产品质量。（剩余4803字）