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Enhancing the accuracy of machinery fault diagnosis through fault source isolation of complex mixture of industrial sound signals
Machinery health monitoring techniques provide valuable insights into the performance and condition of machines. Acoustic sensor-based monitoring has...
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Fault Prediction in Induction Motor Using Artificial Neural Network Algorithms
The paper reflects on the investigation of current signals and vibration signals monitoring for induction motor (IM) effective fault prediction using...
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An effective torque-based method for automatic turn fault detection and turn fault severity classification in permanent magnet synchronous motor
This article presents a novel approach based on the electromechanical torque signal for the inter-turn short-circuit fault (ISCF) detection and the...
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Smart machine fault diagnostics based on fault specified discrete wavelet transform
This study examines the impact of the mother wavelet, sensor selection, and machine learning (ML) models for smart fault diagnosis of rotating...
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Fault Diagnosis of Wastewater Treatment Processes Based on CPSO-DKPCA
The wastewater treatment process (WWTP) is one of the most common links in chemical plants. However, the testing for diagnosing faults in wastewater...
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Systematic Review on Fault Diagnosis on Rolling-Element Bearing
PurposeTo maintain machinery operations smoothly, Rolling-Element Bearings (REBs) are utilized so that the entire equipment’s safety is ensured....
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Fault Analysis Approach of Physical Machines in Cloud Infrastructure
The large-scale cloud computing environment has raised great challenges for fault analysis in infrastructure. The openness of cloud computing makes...
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Unsupervised Manufacturing Fault Detection Based on Self-labeled Training of Fingerprint Image Constructed from Time-Series Data
The acquisition of properly labeled datasets is challenging, which hampers the implementation of industrial deep learning technology in actual...
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Linear and non-linear bayesian regression methods for software fault prediction
Faults are most likely to occur during the coding phase of software development. If, before the testing process, we can predict parts of code that...
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Robust fault diagnosis of a high-voltage circuit breaker via an ensemble echo state network with evidence fusion
Reliable mechanical fault diagnosis of high-voltage circuit breakers is important to ensure the safety of electric power systems. Recent fault...
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Analytic hierarchy process-based regression test case prioritization technique enhancing the fault detection rate
Regression testing is a testing method conducted to ensure that improvements do not affect the software’s current behavior. Test cases play a...
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Design and Hardware Implementation of an Intelligent Industrial IoT Edge Device for Bearing Monitoring and Fault Diagnosis
Manufacturers have traditionally relied on regular maintenance and inspections to ensure the proper functioning of all technical devices, machines,...
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Few-shot transfer learning with attention for intelligent fault diagnosis of bearing
The bearing is one of the key components in modern industrial equipment. In the past few years, many studies have been carried out on bearing...
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Fault detection model for a variable speed heat pump
The impact of the COVID pandemic has resulted in many people cultivating a remote working culture and increasing building energy use. A reduction in...
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Fault Detection Exploiting Artificial Intelligence in Satellite Systems
Mission control and fault management are fundamental in safety-critical scenarios such as space applications. To this extent, fault detection...
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Comparison of ML Algorithms and Neural Networks on Fault Diagnosis of a Worm Gear
PurposeOur main aim is to examine worm gearbox vibration analysis in order to find flaws. To do the vibration study, an experimental setup was...
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Spectral proper orthogonal decomposition and machine learning algorithms for bearing fault diagnosis
Vibration analysis has been extensively exploited for bearing fault diagnosis. However, signal acquisition is quite expensive since external hardware...
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Manifold Learning Based Intelligent Fault Diagnosis and Prognosis
Manifold learning, also known as nonlinear dimensionality reduction or nonlinear embedding, is a set of techniques in machine learning and data...
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Machine Learning Support for Board-Level Functional Fault Diagnosis
The ever-increasing integration density and design complexity of printed-circuit boards are making functional fault diagnosis extremely challenging....
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Non Invasive Fault Detection of Offshore Wind Turbines Using Deep Network-Based Thermogram Features
The offshore regions typically experience greater wind speeds, which makes offshore Wind Turbines (WTs) more efficient. This enhanced output comes...
