# Fault Detection and Control Systems

**Type:** Topics  
**Canonical URL:** https://scholariq.org/topics/fault-detection-and-control-systems/

## Facts

| Field | Value |
| --- | --- |
| Description | This cluster of papers focuses on the application of various data-driven and statistical techniques for process fault detection and diagnosis in industrial settings. It covers topics such as process monitoring, fault isolation, soft sensors, model-based diagnosis, and the use of machine learning in analyzing and improving industrial processes. |
| Domain | Physical Sciences |
| Field | Engineering |
| OpenAlex ID | t10876 |
| Works | 193 |

## Topic papers all

Showing 15 of 193.

- [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/)
- [A review on prognostics and health monitoring of Li-ion battery](https://scholariq.org/papers/a-review-on-prognostics-and-health-monitoring-of-li-ion-battery/)
- [Intelligent prognostics tools and e-maintenance](https://scholariq.org/papers/intelligent-prognostics-tools-and-e-maintenance/)
- [An overview of control performance assessment technology and industrial applications](https://scholariq.org/papers/an-overview-of-control-performance-assessment-technology-and-industrial/)
- [A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes](https://scholariq.org/papers/a-convolutional-neural-network-for-fault-classification-and-diagnosis-in/)
- [On the estimation of transfer functions, regularizations and Gaussian processes—Revisited](https://scholariq.org/papers/on-the-estimation-of-transfer-functions-regularizations-and-gaussian-processes/)
- [Revision of the Tennessee Eastman Process Model](https://scholariq.org/papers/revision-of-the-tennessee-eastman-process-model/)
- [A generalized S-D assignment algorithm for multisensor-multitarget state estimation](https://scholariq.org/papers/a-generalized-s-d-assignment-algorithm-for-multisensor-multitarget-state/)
- [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/)
- [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/)
- [Quantitative measures of robustness for multivariable systems](https://scholariq.org/papers/quantitative-measures-of-robustness-for-multivariable-systems/)
- [Physical Safety and Cyber Security Analysis of Multi-Agent Systems: A Survey of Recent Advances](https://scholariq.org/papers/physical-safety-and-cyber-security-analysis-of-multi-agent-systems-a-survey-of/)
- [Stabilization for Markovian jump systems with partial information on transition probability based on free-connection weighting matrices](https://scholariq.org/papers/stabilization-for-markovian-jump-systems-with-partial-information-on-transition/)
- [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/)

## Topic primary papers

Showing 15 of 79.

- [An overview of control performance assessment technology and industrial applications](https://scholariq.org/papers/an-overview-of-control-performance-assessment-technology-and-industrial/)
- [Revision of the Tennessee Eastman Process Model](https://scholariq.org/papers/revision-of-the-tennessee-eastman-process-model/)
- [Industrial Process Monitoring in the Big Data/Industry 4.0 Era: from Detection, to Diagnosis, to Prognosis](https://scholariq.org/papers/industrial-process-monitoring-in-the-big-data-industry-4-0-era-from-detection-to/)
- [Machine Learning approach for Predictive Maintenance in Industry 4.0](https://scholariq.org/papers/machine-learning-approach-for-predictive-maintenance-in-industry-4-0/)
- [Recent trends on hybrid modeling for Industry 4.0](https://scholariq.org/papers/recent-trends-on-hybrid-modeling-for-industry-4-0/)
- [Evolving an artificial neural network classifier for condition monitoring of rotating mechanical systems](https://scholariq.org/papers/evolving-an-artificial-neural-network-classifier-for-condition-monitoring-of/)
- [Data-Driven Soft Sensor Approach for Quality Prediction in a Refining Process](https://scholariq.org/papers/data-driven-soft-sensor-approach-for-quality-prediction-in-a-refining-process/)
- [Automatic feature extraction of waveform signals for in-process diagnostic performance improvement](https://scholariq.org/papers/automatic-feature-extraction-of-waveform-signals-for-in-process-diagnostic/)
- [Supervised Variational Autoencoders for Soft Sensor Modeling With Missing Data](https://scholariq.org/papers/supervised-variational-autoencoders-for-soft-sensor-modeling-with-missing-data/)
- [Fault detection in the Tennessee Eastman benchmark process using dynamic principal components analysis based on decorrelated residuals (DPCA-DR)](https://scholariq.org/papers/fault-detection-in-the-tennessee-eastman-benchmark-process-using-dynamic/)
- [The current state of control loop performance monitoring – A survey of application in industry](https://scholariq.org/papers/the-current-state-of-control-loop-performance-monitoring-a-survey-of-application/)
- [Feature selection for manufacturing process monitoring using cross-validation](https://scholariq.org/papers/feature-selection-for-manufacturing-process-monitoring-using-cross-validation/)
- [On cross-domain feature fusion in gearbox fault diagnosis under various operating conditions based on Transfer Component Analysis](https://scholariq.org/papers/on-cross-domain-feature-fusion-in-gearbox-fault-diagnosis-under-various/)
- [Detection and Diagnosis of Stiction in Control Loops](https://scholariq.org/papers/detection-and-diagnosis-of-stiction-in-control-loops/)
- [Machine learning for anomaly detection and process phase classification to improve safety and maintenance activities](https://scholariq.org/papers/machine-learning-for-anomaly-detection-and-process-phase-classification-to/)

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