Papers › HSE: A plug-and-play module for unified fault diagnosis foundation models
HSE: A plug-and-play module for unified fault diagnosis foundation models
Qi Li et al.
Intelligent Fault Diagnosis (IFD) plays a crucial role in industrial applications, where developing foundation models analogous to ChatGPT for comprehensive fault diagnosis remains a significant challenge. Current IFD methodologies are constrained by their inability to construct unified models capable of processing heterogeneous signal types, varying sampling rates, and diverse signal lengths across different equipment. To address these limitations, we propose a novel Heterogeneous Signal Embedding (HSE) module that projects heterogeneous signals into a unified signal space, offering seamless integration with existing IFD architectures as a plug-and-play solution. The HSE framework comprises two primary components: the Temporal-Aware Patching (TAP) module for embedding heterogeneous signals into a unified space, and the Cross-Dimensional Patch Fusion (CDPF) module for fusing embedded signals with temporal information into unified representations. We validate the efficacy of HSE through two comprehensive case studies: a simulation signal dataset and three distinct bearing datasets with heterogeneous features. Our experimental results demonstrate that HSE significantly enhances traditional fault diagnosis models, improving both diagnostic accuracy and generalization capability. While conventional approaches necessitate separate models for specific signal types, sampling frequencies, and signal lengths, HSE-enabled architectures successfully learn unified representations across diverse signal. The results from bearing fault diagnosis applications confirm substantial improvements in both diagnostic precision and cross-dataset generalization. As a pioneering contribution toward IFD foundation models, the proposed HSE framework establishes a fundamental architecture for advancing unified fault diagnosis systems.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Methods
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections