Empirical study on fine-tuning pre-trained large language models for fault diagnosis of complex systems

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Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

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Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice

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A review of the application of deep learning in intelligent fault diagnosis of rotating machinery

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Graph of Thoughts: Solving Elaborate Problems with Large Language Models

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Generative adversarial network in mechanical fault diagnosis under small sample: A systematic review on applications and future perspectives

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Towards trustworthy machine fault diagnosis: A probabilistic Bayesian deep learning framework

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Long short-term memory network with Bayesian optimization for health prognostics of lithium-ion batteries based on partial incremental capacity analysis

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Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting

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A rotating machinery fault diagnosis method based on multi-scale dimensionless indicators and random forests

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Rolling Bearing Fault Diagnosis Under Data Imbalance and Variable Speed Based on Adaptive Clustering Weighted Oversampling

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Explainability-driven model improvement for SOH estimation of lithium-ion battery

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TRA-ACGAN: A motor bearing fault diagnosis model based on an auxiliary classifier generative adversarial network and transformer network

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Frozen Pretrained Transformers as Universal Computation Engines

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From task structures to world models: what do LLMs know?

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Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions

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Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions

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PMSM Stator Winding Fault Detection and Classification Based on Bispectrum Analysis and Convolutional Neural Network

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Challenges and opportunities for battery health estimation: Bridging laboratory research and real-world applications

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A method for fault detection in multi-component systems based on sparse autoencoder-based deep neural networks

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XFDDC: eXplainable Fault Detection Diagnosis and Correction framework for chemical process systems

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A Local Adaptive Minority Selection and Oversampling Method for Class-Imbalanced Fault Diagnostics in Industrial Systems

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Water management fault diagnosis for proton-exchange membrane fuel cells based on deep learning methods

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Causal Graph Attention Network with Disentangled Representations for Complex Systems Fault Detection

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A SVM-based framework for fault detection in high-speed trains

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Fault detection in complex mechatronic systems by a hierarchical graph convolution attention network based on causal paths

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Weighted K-NN Classification Method of Bearings Fault Diagnosis With Multi-Dimensional Sensitive Features

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Physics-guided, data-refined fault root cause tracing framework for complex electromechanical system

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Multi-Class Support Vector Machine with Maximizing Minimum Margin

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A fault diagnosis method for building electrical systems based on the combination of variational modal decomposition and new mutual dimensionless

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Fault Detection in Industrial Systems Using Maximized Divergence Analysis Approach

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Mutual Information Alleviates Hallucinations in Abstractive SummarizationPreprint

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FD-LLM: Large language model for fault diagnosis of complex equipment

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Enhancing diagnostic capability with multi-agents conversational large language models

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IIoT-enabled digital twin for legacy and smart factory machines with LLM integration

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A Survey on Applications of Large Language Model-Driven Digital Twins for Intelligent Network Optimization

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A Review of Large Language Models for Energy Systems: Applications, Challenges, and Future Prospects

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Large scale foundation models for intelligent manufacturing applications: a survey

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Data-driven fault detection and diagnosis in industrial process systems: A systematic review and perspective

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The role of AI in detecting and mitigating human errors in safety-critical industries: A review

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A novel multiaxial fatigue life prediction method based on multi-scale physical neural network

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Deep digital twin-powered large vision-language model for multi-scenario industrial fault diagnosis

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Smart Fault Detection, Classification, and Localization in Distribution Networks: AI-Driven Approaches and Emerging Technologies

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Brain-Like Cognition-Driven Model Factory for IIoT Fault Diagnosis by Combining LLMs With Small Models

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Probing a novel machine tool fault reasoning and maintenance service recommendation approach through data-knowledge empowered LLMs integrated with AR-assisted maintenance guidance

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Large model for fault diagnosis of industrial equipment based on a knowledge graph construction

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AI Large Models for Power System: A Survey and Outlook

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LLMs in industrial domains: A systematic review of adaptation techniques and applications from the product lifecycle perspective

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Wind power prediction using foundation large time series models enhanced by time series prompt in exogenous and tuning forms

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Graph RAG-based fault diagnosis for train bogies using knowledge graphs and large language model

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Align knowledge with time-series: Cross-modal domain knowledge activation for LLM-enabled zero-shot fault diagnosis

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A4PS: Agentic AI-assisted advanced planning and scheduling with large language models for smart manufacturing

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An adaptive industrial large language model for mechanical fault diagnosis under variable operating conditions

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A MoE-LLM-based multisensor flexible fusion fault diagnosis method for rotating machinery

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Interpretable and robust fault diagnosis of rotating machinery in noisy environments via improved high-order spatial interactions network

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Large language models and AI agents in disaster-resilient infrastructure: concepts, applications, pathways, and challenges

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A new large model with multi-scale feature fusion for fault diagnosis based on unified time series model

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Comprehensive review of gas turbine fault diagnostic strategies

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Large language model to assist data augmentation in soft contrastive learning for few-shot machinery fault diagnosis

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A comprehensive review on generative artificial intelligence models for fault diagnostics and prognostics of rotating machineries

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New Era of AI in Chemical Process Safety: Foundation Models

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A unified rotating machinery health management framework leveraging large language models for diverse components, conditions, and tasks

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A systematic procedure for the analysis of maintenance reports based on a taxonomy and BERT attention mechanism

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Temporal causal graph-based attention gated recurrent unit for interpretable fault diagnosis in nuclear power plants

Liu, J., Pan, K., Zio, E., & Yao, Y. (2026) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2026.112332 · Cited by 9 · see citing works

A unified multimodal large language model for explainable tool wear state assessment and maintenance decision support

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DeFIANT: A degradation-aware large model paradigm for generalizable RUL prediction

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Large Language and Foundation Models for Machinery Health Monitoring: A Systematic Review

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A multi-task integrated question-answering framework for highly generalizable fault and RUL assessments based on LLMs with a post-training and fine-tuning strategy

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Dynamic risk-informed verification prioritization for Complex Product Systems: A tri-metric approach using a Multi-State Hierarchical Bayesian Network

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Deconfounding enhanced image-based knowledge distillation for fault diagnosis with an application in manufacturing process

Zhang, J., & Liu, J. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.112907 · Cited by 7 · see citing works

Joint state-of-charge and state-of-health estimation of lithium-ion batteries across varying operational stages on differing timescales with large language model: a multi-task prompting method

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Domain-specific large language model-driven risk analysis of battery energy storage systems

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VSLLaVA: A pipeline for Large Multimodal Foundation Models in industrial vibration signal analysis

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Causality-enhanced system reliability and safety analysis: An overview

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Fault inference diagnosis based on causal network and large language model-enhanced knowledge graph network

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Large models for machinery fault diagnosis: Current advances and future directions

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Knowledge-Enhanced Industrial Question-Answering Using Large Language Models

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Semi-Supervised Prefix Tuning of Large Language Models for Industrial Fault Diagnosis with Big Data

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Knowledge graph-driven fault diagnosis for aviation equipment: Integrating improved joint extraction with large language model

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Graph-constrained association rule mining-based energy efficiency diagnosis method for HVAC systems with knowledge-enhanced large language model

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From physics to machine learning and back: Part II - Learning and observational bias in prognostics and health management (PHM)

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Long causal chain-of-thought for compound fault diagnosis: enhancing hypergraph-based Causal-LLM intervention reasoning

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Using the Large Language Model ChatGPT to Support Decisions in Sustainable Transport

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Healthcare 4.0: A Large Language Model-Based Blockchain Framework for Medical Device Fault Detection and Diagnostics

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LLM-YOLOMS: Large Language Model-based Semantic Interpretation and Fault Diagnosis for Wind Turbine ComponentsPreprint

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An Innovative Foundation Model for Bearing Prognostics and Health Management Through Pre-Trained Large Language ModelsPreprint

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LAISA: Large-language Agent for Industrial State Assessment

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A Multi-stage Language Model Post-Training Framework for HVAC Fault Diagnosis in Urban Rail TransitPreprint

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DiagLLM: A CNN-Language Model Framework with LoRA for Fault Diagnosis of Cross Roller Bearings

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A LLM-Driven Agent System for Automotive Fault Diagnosis with Integrated Reasoning and Expertise Sharing

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Fault Detection for Time-variant Avionics Systems Based on A New Data-driven Time-varying ApproachPreprint

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A Multi-stage Post-Training Framework for Domain-Specific Language Models in Fault DiagnosisPreprint

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Power Ops Agent: A Knowledge and Data Dual-Driven Multi-Agent Framework for Substation Operation and MaintenancePreprint

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Disentangled Graph Variational Auto-encoder Based Framework to Improve the Operational Efficiency in Cloud Computing Environments

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A Multi-stage Post-Training Framework for Domain-Specific Language Models in Fault DiagnosisPreprint

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An Intelligent Triage System for Hospital Emergency Services Based on Large Language Models and Machine Learning

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Rotor Skidding Root-Cause Tracing and Regulation Based on Supervised Fine-Tuning of LLM

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Exploring LLM-based Frameworks for Fault DiagnosisPreprint

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The Interpretable Reasoning and Intelligent Decision-Making Based on Event Knowledge Graph With LLMs in Fault Diagnosis Scenarios

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A Multi-stage Post-Training Framework for Domain-Specific Language Models in Fault DiagnosisPreprint

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