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Machine learning techniques applied to mechanical fault diagnosis and fault prognosis in the context of real industrial manufacturing use-cases: a systematic literature review
When put into practice in the real world, predictive maintenance presents a set of challenges for fault detection and prognosis that are often...
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On fault diagnosis using image-based deep learning networks based on vibration signals
With the development of complex and intelligent mechanical products, the reliability of rotating machinery equipment increasingly gains much...
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Incremental Learning with Maximum Dissimilarity Sampling Based Fault Diagnosis for Rolling Bearings
Traditional fault diagnosis methods for rolling bearings require retraining the model from scratch when faced with new fault signals, consuming...
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Fault diagnosis and prognosis of steer-by-wire system based on finite state machine and extreme learning machine
In this paper, an integrated condition monitoring method combining model-based fault diagnosis and data-driven prognosis is proposed for...
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Hybrid deep transfer learning architecture for industrial fault diagnosis using Hilbert transform and DCNN–LSTM
Early-stage fault detection has become an indispensable part of modern industry to prevent potential hazards or sudden hindrances to the production...
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Intelligent fault diagnosis of rolling bearings based on LSTM with large margin nearest neighbor algorithm
In industrial machinery, rolling bearings are often rated as the most likely to fail in mechanical systems due to excessive working stress....
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Machine learning-based techniques for fault diagnosis in the semiconductor manufacturing process: a comparative study
Industries are going through the fourth industrial revolution (Industry 4.0), where technologies like the Industrial Internet of things, big data...
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An Intelligent Fault Detection Framework for HVAC Systems with Alert Generation
The HVACs used in commercial buildings are one of the major electricity consumers. They undergo periodic inspections to prevent discomfort and...
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Hybrid optimization-enabled deep Q network for fault prediction in service-oriented architecture
Fault prediction in service-oriented architecture-based models has been recognized as one of the essential processes to reduce computational expenses...
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A review on fault detection and diagnosis techniques: basics and beyond
Safety and reliability are absolutely important for modern sophisticated systems and technologies. Therefore, malfunction monitoring capabilities are...
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Diagnosis Hepatitis B Using Machine and Deep Learning: Survey
Machine Learning (ML) improves healthcare systems by hel** to reach a proper diagnosis and reducing the diagnosis faults such as severe illness,...
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Fault Classification of Wind Turbine: A Comparison of Hyperparameter Optimization Methods
The last few years have been marked by the insertion of renewable technologies in the global energy matrix, such as wind and solar energy, which are...
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Machine Learning for PV System Operational Fault Analysis: Literature Review
This review paper aims to discover the research gap and assess the feasibility of a holistic approach for photovoltaic (PV) system operational fault...
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Which Components to Blame? Integrating Diagnosis into Monitoring of Technical Systems
System monitoring is essential for detecting failures during operation and ensuring reliability. A monitoring system obtains observations and checks...
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Framework to Evaluate Deep Learning Algorithms for Edge Inference and Training
Edge computing is a paradigm in which data is intelligently processed close to its source. Along with advancements in deep learning, there is a...
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A comprehensive assessment of artificial intelligence applications for cancer diagnosis
Artificial intelligence (AI) is being used increasingly to detect fatal diseases such as cancer. The potential reduction in human error, rapid...
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Fault diagnosis in service-oriented computing through partially observed stochastic Petri nets
Service composition, interoperability, loose coupling and distributed nature make service-oriented computing (SOC) enhanced for small-scale to large...
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A novel health state prediction approach based on artificial intelligence combination strategy for compensation capacitors in track circuit
The health management of railway signal equipment in the high-speed railway is a key link between intelligent operation and maintenance. Accurately...
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Deep Learning Methods for Chronic Myeloid Leukaemia Diagnosis
Chronic myeloid leukaemia (CML) is considered as the cancer of the blood or cancer of the bone marrow. Blood consists of three different cells, one...
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Data-driven exploratory models of an electric distribution network for fault prediction and diagnosis
Data-driven models are becoming of fundamental importance in electric distribution networks to enable predictive maintenance, to perform effective...
