# Machine Fault Diagnosis Techniques

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/machine-fault-diagnosis-techniques/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on machine fault diagnosis and prognostics using methods such as Empirical Mode Decomposition, wavelet transform, and deep learning. It covers topics like condition monitoring, vibration analysis, and remaining useful life estimation for rotating machinery. The research explores the application of machine learning techniques, neural networks, and signal processing in fault detection and health management of various mechanical systems. |
| Domain | Physical Sciences |
| Field | Engineering |
| OpenAlex ID | t10220 |
| Works | 96 |

## Topic papers all

Showing 15 of 96.

- [Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications](https://scholariq.org/papers/prognostics-and-health-management-design-for-rotary-machinery-systems-reviews/)
- [Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics](https://scholariq.org/papers/wavelet-filter-based-weak-signature-detection-method-and-its-application-on/)
- [Rotating machinery prognostics: State of the art, challenges and opportunities](https://scholariq.org/papers/rotating-machinery-prognostics-state-of-the-art-challenges-and-opportunities/)
- [Intelligent prognostics tools and e-maintenance](https://scholariq.org/papers/intelligent-prognostics-tools-and-e-maintenance/)
- [Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review](https://scholariq.org/papers/vibration-based-condition-monitoring-and-fault-diagnosis-of-wind-turbine/)
- [Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings](https://scholariq.org/papers/deep-learning-enabled-fault-diagnosis-using-time-frequency-image-analysis-of/)
- [Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms](https://scholariq.org/papers/fault-detection-and-diagnosis-for-rotating-machinery-a-model-based-on/)
- [A Data-Level Fusion Model for Developing Composite Health Indices for Degradation Modeling and Prognostic Analysis](https://scholariq.org/papers/a-data-level-fusion-model-for-developing-composite-health-indices-for/)
- [A time varying filter approach for empirical mode decomposition](https://scholariq.org/papers/a-time-varying-filter-approach-for-empirical-mode-decomposition/)
- [Fault diagnosis of low speed bearing based on relevance vector machine and support vector machine](https://scholariq.org/papers/fault-diagnosis-of-low-speed-bearing-based-on-relevance-vector-machine-and/)
- [Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach : A review of two decades of research](https://scholariq.org/papers/multi-fault-diagnosis-of-industrial-rotating-machines-using-data-driven-approach/)
- [Machine Learning approach for Predictive Maintenance in Industry 4.0](https://scholariq.org/papers/machine-learning-approach-for-predictive-maintenance-in-industry-4-0/)
- [Remaining Useful Life Prediction using Deep Learning Approaches: A Review](https://scholariq.org/papers/remaining-useful-life-prediction-using-deep-learning-approaches-a-review/)
- [Model-Based Prognostic Techniques Applied to a Suspension System](https://scholariq.org/papers/model-based-prognostic-techniques-applied-to-a-suspension-system/)
- [Recent advances and trends of predictive maintenance from data-driven machine prognostics perspective](https://scholariq.org/papers/recent-advances-and-trends-of-predictive-maintenance-from-data-driven-machine/)

## Topic primary papers

Showing 15 of 51.

- [Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications](https://scholariq.org/papers/prognostics-and-health-management-design-for-rotary-machinery-systems-reviews/)
- [Rotating machinery prognostics: State of the art, challenges and opportunities](https://scholariq.org/papers/rotating-machinery-prognostics-state-of-the-art-challenges-and-opportunities/)
- [Intelligent prognostics tools and e-maintenance](https://scholariq.org/papers/intelligent-prognostics-tools-and-e-maintenance/)
- [Vibration based condition monitoring and fault diagnosis of wind turbine planetary gearbox: A review](https://scholariq.org/papers/vibration-based-condition-monitoring-and-fault-diagnosis-of-wind-turbine/)
- [Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings](https://scholariq.org/papers/deep-learning-enabled-fault-diagnosis-using-time-frequency-image-analysis-of/)
- [Fault detection and diagnosis for rotating machinery: A model based on convolutional LSTM, Fast Fourier and continuous wavelet transforms](https://scholariq.org/papers/fault-detection-and-diagnosis-for-rotating-machinery-a-model-based-on/)
- [A time varying filter approach for empirical mode decomposition](https://scholariq.org/papers/a-time-varying-filter-approach-for-empirical-mode-decomposition/)
- [Fault diagnosis of low speed bearing based on relevance vector machine and support vector machine](https://scholariq.org/papers/fault-diagnosis-of-low-speed-bearing-based-on-relevance-vector-machine-and/)
- [Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach : A review of two decades of research](https://scholariq.org/papers/multi-fault-diagnosis-of-industrial-rotating-machines-using-data-driven-approach/)
- [Remaining Useful Life Prediction using Deep Learning Approaches: A Review](https://scholariq.org/papers/remaining-useful-life-prediction-using-deep-learning-approaches-a-review/)
- [Model-Based Prognostic Techniques Applied to a Suspension System](https://scholariq.org/papers/model-based-prognostic-techniques-applied-to-a-suspension-system/)
- [Recent advances and trends of predictive maintenance from data-driven machine prognostics perspective](https://scholariq.org/papers/recent-advances-and-trends-of-predictive-maintenance-from-data-driven-machine/)
- [Scaling-Basis Chirplet Transform](https://scholariq.org/papers/scaling-basis-chirplet-transform/)
- [Multilevel Information Fusion for Induction Motor Fault Diagnosis](https://scholariq.org/papers/multilevel-information-fusion-for-induction-motor-fault-diagnosis/)
- [Intelligent condition-based prediction of machinery reliability](https://scholariq.org/papers/intelligent-condition-based-prediction-of-machinery-reliability/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.