面向旋转机械装备的智能故障诊断通用基础模型研究
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关键词：智能故障诊断；通用基础模型；旋转机械；定制化适配中图分类号：TH17文献标志码：ADOI：10.7652/xjtuxb202507001 文章编号：0253-987X（2025）07-0001-12
Research on General Foundation Model for Intelligent Fault Diagnosis for Rotating Machinery
LI Xiang，XU Yixiao，LEI Yaguo，LI Xiwei，LI Naipeng，YANG Bin （KeyLaboratory of Education Ministry for Modern Design and Rotor-Bearing System， Xi'anJiaotongUniversity，Xi'an71oo49，China）
Abstract： Given that existing inteligent fault diagnosis methods for rotating machinery often lack generalizability and are typically limited to specific models， structures，operating conditions， measurement points，and load scenarios，a universal fundamental model for intelligent fault diagnosis tailored to rotating machinery is developed. By mining massve volumes of state monitoring data from various types of rotating machinery，a multi-source data structure with a multi-scale adaptive alignment method is proposed. A multi-level state fusion intelligent diagnosis model is constructed，and a universal fundamental model with strong applicability to typical rotating machinery is established. Additionally，a method for individualized customization and adaptation of the diagnosis model is introduced. The proposed method is validated on extensive state monitoring datasets for rotating machinery. Experimental results show that the universal intelligent diagnosis model can directly detect anomalies in unknown measured equipment，achieving an overall diagnosis accuracy of 88.5% without any supervised fine-tuning. With minor fine-tuning using a small amount of measured data，the model rapidly adapts to new equipment and achieves a diagnosis accuracy of up to 98.6% . Furthermore，the proposed data preprocessing method enables cross-equipment signal amplitude normalization while preserving the relative amplitude distribution between healthy and faulty states within the same equipment，effectively retaining key amplitude-based feature diferences.These findings demonstrate the strong engineering potential of the proposed method and its promise for widespread application in real-world industrial scenarios.
Keywords： intelligent fault diagnosis； general foundation model;rotating machine； customizedadaptation
近年来，随着人工智能技术的突飞猛进，大数据驱动的机械装备智能故障诊断方法取得了显著进步[1]。（剩余16593字）