面向旋轉(zhuǎn)機械裝備的智能故障診斷通用基礎(chǔ)模型研究

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關(guān)鍵詞：智能故障診斷；通用基礎(chǔ)模型；旋轉(zhuǎn)機械；定制化適配中圖分類號：TH17文獻標(biāo)志碼：ADOI：10.7652/xjtuxb202507001 文章編號：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

近年來，隨著人工智能技術(shù)的突飛猛進，大數(shù)據(jù)驅(qū)動的機械裝備智能故障診斷方法取得了顯著進步[1]。（剩余16593字）