An approach based on wavelets and machine learning to build a prediction model for SF6 filling pressure of high-voltage circuit breakers

[1]  Kaveh Niayesh,et al.  Condition Monitoring of High Voltage Circuit Breakers: Past to Future , 2020, IEEE Transactions on Power Delivery.

[2]  Serkan Ayvaz,et al.  Predictive maintenance system for production lines in manufacturing: A machine learning approach using IoT data in real-time , 2021, Expert Syst. Appl..

[3]  Wei Zhang,et al.  Fault Diagnosis of Conventional Circuit Breaker Contact System Based on Time–Frequency Analysis and Improved AlexNet , 2021, IEEE Transactions on Instrumentation and Measurement.

[4]  Sujie Geng,et al.  Research on data-driven method for circuit breaker condition assessment based on back propagation neural network , 2020, Comput. Electr. Eng..

[5]  Gilberto Francisco Martha de Souza,et al.  Wavelet-Like Transform to Optimize the Order of an Autoregressive Neural Network Model to Predict the Dissolved Gas Concentration in Power Transformer Oil from Sensor Data , 2020, Sensors.

[6]  Nantian Huang,et al.  Mechanical Fault Diagnosis of a High Voltage Circuit Breaker Based on High-Efficiency Time-Domain Feature Extraction with Entropy Features , 2020, Entropy.

[7]  Xiaoyong Li,et al.  Particle Swarm Optimization-Support Vector Machine Model for Machinery Fault Diagnoses in High-Voltage Circuit Breakers , 2020 .

[8]  Sheng Lei,et al.  Mechanical Condition Identification and Prediction of Spring Operating Mechanism of High Voltage Circuit Breaker , 2020, IEEE Access.

[9]  Yuhao Wang,et al.  High-Voltage Circuit Breaker Fault Diagnosis Using a Hybrid Feature Transformation Approach Based on Random Forest and Stacked Autoencoder , 2019, IEEE Transactions on Industrial Electronics.

[10]  Mileta Žarković,et al.  Artificial intelligence SF6 circuit breaker health assessment , 2019, Electric Power Systems Research.

[11]  Stanislav A. Eroshenko,et al.  High-Voltage Circuit Breakers Technical State Patterns Recognition Based on Machine Learning Methods , 2019, IEEE Transactions on Power Delivery.

[12]  Ali Asghar Razi-Kazemi,et al.  Fault Analysis of High-Voltage Circuit Breakers Based on Coil Current and Contact Travel Waveforms Through Modified SVM Classifier , 2019, IEEE Transactions on Power Delivery.

[13]  Ali A. Razi-Kazemi,et al.  A New Approach on Prioritization of the Circuit Breakers for Installation of Online Monitoring Systems , 2019, IEEE Transactions on Power Delivery.

[14]  Lei Chen,et al.  Fault Diagnosis of High-Voltage Circuit Breakers Using Mechanism Action Time and Hybrid Classifier , 2019, IEEE Access.

[15]  Yi Pan,et al.  An Approach for HVCB Mechanical Fault Diagnosis Based on a Deep Belief Network and a Transfer Learning Strategy , 2019, Journal of Electrical Engineering & Technology.

[16]  Abderrahmane Haddad,et al.  Evaluation of SF6 Leakage from Gas Insulated Equipment on Electricity Networks in Great Britain , 2018, Energies.

[17]  Wenyuan Li,et al.  A RankBoost-Based Data-Driven Method to Determine Maintenance Priority of Circuit Breakers , 2018, IEEE Transactions on Power Delivery.

[18]  Fábio Henrique Pereira,et al.  Disease spreading in complex networks: A numerical study with Principal Component Analysis , 2017, Expert Systems with Applications.

[19]  Abderrahmane Beroual,et al.  Recent Advances in the Quest for a New Insulation Gas with a Low Impact on the Environment to Replace Sulfur Hexafluoride (SF6) Gas in High-Voltage Power Network Applications , 2017 .

[20]  Vladimiro Miranda,et al.  Substations SF6 circuit breakers: Reliability evaluation based on equipment condition , 2017 .

[21]  Dianguo Xu,et al.  Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Wavelet Time-Frequency Entropy and One-Class Support Vector Machine , 2015, Entropy.

[22]  Ali Asghar Razi-Kazemi,et al.  Applicability of auxiliary contacts in circuit breaker online condition assessment , 2015 .

[23]  Gian Antonio Susto,et al.  Machine Learning for Predictive Maintenance: A Multiple Classifier Approach , 2015, IEEE Transactions on Industrial Informatics.

[24]  M. Seeger.  Perspectives on Research on High Voltage Gas Circuit Breakers , 2015, Plasma Chemistry and Plasma Processing.

[25]  Geoffrey E. Hinton,et al.  Neighbourhood Components Analysis , 2004, NIPS.

[26]  J. Friedman.  Greedy function approximation: A gradient boosting machine. , 2001 .