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Fault identification of a chain conveyor based on functional data feature engineering and optimized multi-layer kernel extreme learning machine
The functional time series signals generated during the operation of electromechanical systems contain fault characteristic information. This study...
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An unsupervised mechanical fault classification method under the condition of unknown number of fault types
This paper proposes a novel unsupervised classification method to solve the problem of mechanical fault diagnosis under the condition of unknown...
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CNN-based fault classification considered fault location of vibration signals
Recently, with the development of the 4th industrial technology such as big data, cloud computing, and IoT, technologies that automatically perform...
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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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Implication of fault seal analysis method to evaluate the sealing conditions of major fault planes at Barapukuria basin, North-West Bangladesh
The Barapukuria coal basin stands as Bangladesh’s sole active underground coal mining site. The geological setting of this basin is marked by two...
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LSTM-based low-impedance fault and high-impedance fault detection and classification
In this article, a long short-term memory based protection scheme for power transmission lines is presented. A fault detection framework is developed...
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A 3-layered nonlinear process monitoring strategy with a novel fault diagnosis approach
The article proposes the development of a layered process monitoring strategy based on multi-block kernel principal component analysis (MBKPCA)....
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Microgrid Fault Diagnosis Based on Whale Algorithm Optimizing Extreme Learning Machine
A microgrid fault diagnosis method based on whale algorithm optimizing extreme learning machine (ELM) is proposed. Firstly, the three-phase fault...
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Automatic Fault Detection of Photovoltaic Modules Using Recurrent Neural Network
AbstractEverywhere in the globe, the total capacity of photovoltaic (PV) panels is expanding at an exponential rate. Arc faults, open-circuit (OC)...
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An End-to-End Mutually Exclusive Autoencoder Method for Analog Circuit Fault Diagnosis
Fault diagnosis of analog circuits is a classical problem, and its difficulty lies in the similarity between fault features. To address the issue, an...
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Rolling bearing fault diagnosis method based on improved residual shrinkage network
With strong feature extraction ability, neural networks can effectively realize rolling bearing fault diagnosis. However, due to the impact of noise...
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Fault Tolerant Architectures
Fault-tolerant computing has been the cornerstone of reliable computing using electronic systems. Traditionally, fault-tolerant system design has...
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A learning-based approach to fault detection and fault-tolerant control of permanent magnet DC motors
In the context of Industry 4.0, which prioritizes intelligent and efficient solutions for industrial systems, this paper introduces an innovative...
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An Improved Fault Diagnosis in Stand-Alone Photovoltaic System Using Artificial Neural Network
This paper proposes an improved fault diagnosis for stand-alone photovoltaic (SAPV) system using artificial neural network (ANN) and power loss...
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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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A new deep learning model combining CNN for engine fault diagnosis
Real-time condition monitoring of electric motors and early diagnosis is of great importance for ensuring safe and reliable operation, preventing...
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Attention-parallel multisource data fusion residual network-based open-circuit fault diagnosis of cascaded H-bridge inverters
Aiming to solve the problems of multiple internal power components, high fault probability, high similarity of the fault features of different power...
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Grid interlocking fault prevention and control method considering safety and network loss
The paper proposes a chain fault prevention and control method that takes into account safety and network loss to address chain fault accidents and...
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Lightweight fault diagnosis method in embedded system based on knowledge distillation
Deep learning (DL) has garnered attention in mechanical device health management for its ability to accurately identify faults and predict component...
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A Novel Incipient Fault Diagnosis Method for Analogue Circuits Based on an MLDLCN
Incipient faults in analogue circuits used in complex electrical systems are hard to diagnose due to weak fault features. To improve the reliability...
