Open research questions in Machine Fault Diagnosis Techniques

What the literature leaves open

• Further research can be done to improve the convergence speed and accuracy of the snake optimization algorithm, - The application of the proposed method to other types of power generation units can be explored, - The integration of the proposed method with other optimization algorithms can be investigated

  Intelligent Diagnosis Method for Constrained Primary Frequency Regulation Capacity of Coal-Fired Units Based on ISO-MLRF · 2026 · DOI

• The low diagnostic accuracy of constrained primary frequency regulating capacity due to complex and strongly coupled restricting factors. The need for an intelligent diagnosis method that can enable online diagnosis of PFR capacity limitations.

  Intelligent Diagnosis Method for Constrained Primary Frequency Regulation Capacity of Coal-Fired Units Based on ISO-MLRF · 2026 · DOI

• The study does not mention any specific limitations. The methodology depended heavily on handcrafted features and lacked end-to-end learning capability in previous efforts. The population/sample and dataset are not fully described.

  Polymer Gear Pitting Severity Diagnosis Using Vibration-Based Deep Learning Architectures · 2026 · DOI

• Further research could investigate the application of the proposed framework to other types of gear faults. The use of other deep learning architectures, such as recurrent neural networks, could be explored. The development of more advanced signal processing techniques could improve the accuracy of the framework.

  Polymer Gear Pitting Severity Diagnosis Using Vibration-Based Deep Learning Architectures · 2026 · DOI

• The study does not provide a comprehensive comparison with all existing methods, - The proposed approach may not be effective for all types of bearing faults, - The study uses a limited number of test rigs and simulation data, - The proposed approach may require additional computational resources, - The study does not provide a detailed analysis of the computational complexity of the proposed approach

  Advanced spatial processing of the cyclic spectral coherence map and its application to bearing fault detection in electric motors · 2026 · DOI

• Investigating the application of the proposed approach to other types of machinery, - Developing a more comprehensive comparison with existing methods, - Analyzing the computational complexity of the proposed approach, - Exploring the use of other statistical measures to improve the proposed approach

  Advanced spatial processing of the cyclic spectral coherence map and its application to bearing fault detection in electric motors · 2026 · DOI

• Systematic verification of the applicability of LoRA in audio cross-modal tasks, - Evaluation of the proposed framework on more public datasets, - Exploration of the use of other parameter-efficient fine-tuning methods

  Domain-Adaptive Audio Large Language Model for Acoustic Fault Diagnosis and Semantic Description of Coal Mine Equipment · 2026 · DOI

• Integrating multiple sensors to improve the robustness and discriminability of the learned representations. Achieving superior performance under both full and scarce data conditions. Reducing the computational complexity and improving the inference speed of the model.

  MSFF-Net: Multi-Sensor Frequency-Domain Feature Fusion Network with Lightweight 1D CNN for Bearing Fault Diagnosis · 2025 · DOI

• Investigating the application of the proposed method to other industrial environments, - Exploring the use of other sensor modalities, - Evaluating the proposed method under various operational conditions

  MSFF-Net: Multi-Sensor Frequency-Domain Feature Fusion Network with Lightweight 1D CNN for Bearing Fault Diagnosis · 2025 · DOI

• the multicomponent and non-stationary nature of signals, - a high level of noise, - requirements for sensor placement, - communication channel limitations, - the need for on-site processing

  Vibration-Based Condition Monitoring of Diesel Engines in Industrial Energy Applications: A Scoping Review · 2025 · DOI

• field validations of vibroacoustic data, - the use of multimodal sensor platforms, - noise-immune algorithms, - model adaptation to the specific environment

  Vibration-Based Condition Monitoring of Diesel Engines in Industrial Energy Applications: A Scoping Review · 2025 · DOI

• Accurately modeling complex multi-stress scenarios, where interactions between stresses may complicate the identification of failure mechanisms. Dealing with complex failure mechanisms that are not well understood. The lack of interpretability of data-driven models, which can make it challenging to understand the underlying degradation mechanisms.

  A Review of Reliability Assessment and Lifetime Prediction Methods for Electrical Machine Insulation Under Thermal Aging · 2025 · DOI

• The complex aging mechanisms of insulation systems under thermal aging make it challenging to evaluate and predict their lifetime. Current methods for reliability assessment and lifetime prediction have limitations, such as the inability to accurately model complex multi-stress scenarios.

  A Review of Reliability Assessment and Lifetime Prediction Methods for Electrical Machine Insulation Under Thermal Aging · 2025 · DOI

• There is a lack of comprehensive reviews on RUL estimation approaches for rotating machinery. The paper identifies the need for a detailed investigation of HI design using mechanical-signal-based, model-based, and AI-based techniques. The study highlights the challenges of acquiring run-to-failure data in industrial environments.

  A Comprehensive Review of Remaining Useful Life Estimation Approaches for Rotating Machinery · 2024 · DOI

• Data scarcity is a significant challenge in wind turbine operation, making it difficult to estimate RUL. Overfitting is a challenge when using machine learning models, which can be addressed using a cross-validation strategy. The lack of detailed information about the turbines due to confidentiality reasons is another challenge.

  Remaining Useful Life Estimation Framework for the Main Bearing of Wind Turbines Operating in Real Time · 2024 · DOI

• Further research is needed to improve the accuracy of RUL estimation, - The use of more advanced machine learning models could be explored, - The application of the proposed framework to other types of wind turbines or equipment could be investigated

  Remaining Useful Life Estimation Framework for the Main Bearing of Wind Turbines Operating in Real Time · 2024 · DOI

• Further research is needed to improve the accuracy of GPR models for wind turbine health and reliability assessment

  Wind Turbine Damage Equivalent Load Assessment Using Gaussian Process Regression Combining Measurement and Synthetic Data · 2024 · DOI

• optimizing condition-monitoring strategies, - enhancing the reliability of rotating machinery technologies

  A Comprehensive Review of Remaining Useful Life Estimation Approaches for Rotating Machinery · 2024 · DOI

• Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges.

  A federated learning–driven data fusion strategy for the hardenability prediction of gear steel · 2026 · DOI

• Three unresolved challenges remain: (i) motor whine, material-collision impacts, and ventilation-fan roar compound into a low-SNR soundscape where conventional models lose noise robustness; (ii) acoustic signatures vary widely across equipment types and fault-development stages; and (iii) existing supervised classifiers, trained on imbalanced data, exhibit limited generalization and output only binary judgments, lacking the semantic descriptions that maintenance crews actually need.

  Domain-Adaptive Audio Large Language Model for Acoustic Fault Diagnosis and Semantic Description of Coal Mine Equipment · 2026 · DOI

• The proposed data-model fusion approach incorporates physics-informed knowledge of the spalling process to improve interpretability and robustness under limited data conditions.

  Physics-informed prognostic model for rolling element bearing using auxiliary particle filter with resample-move and inline oil debris data · 2026 · DOI

• The novelty of the proposed model lies in the fusion of entropy-based statistical features with energy-based wavelet features, a combination that remains underexplored in the context of RUL estimation.

  Remaining useful life prediction of rolling bearings via wavelet feature fusion and LSTM networks · 2026 · DOI

• Aiming at the traditional single sensor vibration signal cannot fully express the bearing running state, and in the high noise background, the traditional algorithm is insufficient for fault feature extraction.

  Hybrid Multimodal Feature Fusion with Multi-Sensor for Bearing Fault Diagnosis · 2024 · DOI

• However, this is hindered by the lack of data in commercial machines and accurate models based on manufacturers’ proprietary design data.

  Wind Turbine Damage Equivalent Load Assessment Using Gaussian Process Regression Combining Measurement and Synthetic Data · 2024 · DOI

• The development of a reliable and automated fault diagnosis method for rotating machinery. The need to generalize beyond the conditions represented in the training data. The suppression of low-frequency rotational components and the isolation of the resonance band excited by bearing impacts.

  Fault Diagnosis of Rotating Machinery Using Supervised Machine Learning Algorithms with Integrated Data-Driven and Physics-Informed Feature Sets · 2026 · DOI

Most-cited papers in Machine Fault Diagnosis Techniques

• Feature Mode Decomposition: New Decomposition Theory for Rotating Machinery Fault Diagnosis · IEEE Transactions on Industrial Electronics · 2022 · 477 citations
• Data-Driven Fault Diagnosis for Traction Systems in High-Speed Trains: A Survey, Challenges, and Perspectives · IEEE Transactions on Intelligent Transportation Systems · 2022 · 455 citations
• CNN parameter design based on fault signal analysis and its application in bearing fault diagnosis · Advanced Engineering Informatics · 2023 · 427 citations
• Domain generalization for cross-domain fault diagnosis: An application-oriented perspective and a benchmark study · Reliability Engineering & System Safety · 2024 · 399 citations
• Prediction of remaining useful life based on bidirectional gated recurrent unit with temporal self-attention mechanism · Reliability Engineering & System Safety · 2022 · 369 citations
• Digital twin-driven partial domain adaptation network for intelligent fault diagnosis of rolling bearing · Reliability Engineering & System Safety · 2023 · 361 citations
• Artificial Intelligence for Predictive Maintenance Applications: Key Components, Trustworthiness, and Future Trends · Applied Sciences · 2024 · 351 citations
• Multi-mode data augmentation and fault diagnosis of rotating machinery using modified ACGAN designed with new framework · Advanced Engineering Informatics · 2022 · 326 citations
• A Review on Vibration-Based Condition Monitoring of Rotating Machinery · Applied Sciences · 2022 · 295 citations
• Aircraft engine remaining useful life estimation via a double attention-based data-driven architecture · Reliability Engineering & System Safety · 2022 · 288 citations

Most recent work

• Spatial-channel collaborative multi-scale graph interaction deep transfer learning for unsupervised rotating machinery fault diagnosis · Engineering Applications of Artificial Intelligence · 2026
• Synergistic operation and maintenance enabling lifecycle-aware opportunistic management of offshore wind energy · Applied Energy · 2026
• A novel interpretable dynamic weighted domain adaptation network for cross-domain fault diagnosis of bearings under time-varying speeds · Engineering Applications of Artificial Intelligence · 2026
• An interpretable causal invariant graph neural network for unseen domain gear fault diagnosis · Engineering Applications of Artificial Intelligence · 2026
• A Review of Fault Diagnosis Methods: From Traditional Machine Learning to Large Language Model Fusion Paradigm · Sensors · 2026
• A fault evolution knowledge-driven adversarial meta-learning method for few-shot tool state recognition under variable working conditions · Engineering Applications of Artificial Intelligence · 2026
• SCADA data-driven failure rate and reliability prediction for offshore wind turbines · Reliability Engineering & System Safety · 2026
• Remaining useful life prediction of rolling bearings via wavelet feature fusion and LSTM networks · The International Journal of Advanced Manufacturing Technology · 2026
• Temporal causal graph-based attention gated recurrent unit for interpretable fault diagnosis in nuclear power plants · Reliability Engineering & System Safety · 2026
• Conformer-PhyFaultNet: Physics-Informed Spectral Attention Conformer for Generalizable Bearing Fault Diagnosis · IEEE Internet of Things Journal · 2026

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