Search Results for fault

...Mellit, A. and Kalogirou, S. A., “Monitoring, fault detection and operations of photovoltaic systems,” in Toward Better Photovoltaic Systems: Design, Simulation, Optimization, Analysis, and Operations, edited by J. Ren, C. He, and L. Dong (AIP Publishing, Melville, New York, 2023), pp. 6-1...

...Wang, H., Qian, G., Cao, W., and Lu, S., “A two-step online fault detection method for high-resistance connection faults in a vehicular BLDC motor,” in Advanced Sensors and Sensing Technologies for Electric Vehicles, edited by W. Cao and S. Lu (AIP Publishing, Melville, New York, 2022), pp...

...The added generating units in the electrical distribution network would affect the currents and voltages during fault conditions. Subsequently, these fault currents and voltages will influence the operation of relay protection units, circuit breakers, and safety measures at the inter-connection...

... for a healthy condition, and six neurons for six different fault conditions. The network is trained using the Levenberg–Marquardt (LM) function, which is a backpropagation algorithm to update weights and biases. The input vectors are divided into three datasets (training has 70%, test has 15%, and validation...

... plots of SVM classification (WPT, db4). FIG. 8.5 Hyper-plane plots of SVM classification (WPT, rbio1.5). References References Al Tobi , M. , Bevan , G. , Wallace , P. , Harrison , D. , and Okedu , K. E. , “ Faults diagnosis of a centrifugal pump using multilayer perceptron...

... for the optimization and selection of the hidden layers and neurons numbers. There are seven neurons output layers; one for each tested pump condition; one neuron for a healthy condition, and six neurons for six different fault conditions. The training of the network was done using the Levenberg–Marquardt (LM...

...Introduction Another method based on the hybrid Neuro-Fuzzy approach of fault detection and diagnosis applying the Norm-test was reported in Bonsignore et al. (2014) . This work comprises mainly the development of a Neuro-Fuzzy model of PV modules, the analysis and extraction of six...

... Alam , M. K. , Khan , F. , Johnson , J. , and Flicker , J. , “ A comprehensive review of catastrophic faults in PV arrays: Types, detection, and mitigation techniques ,” IEEE J. Photovoltaics   5 ( 3 ), 982 – 997 ( 2015 ). 10.1109/JPHOTOV.2015.2397599 Ball , G. , Brooks...

...., 2021 ), fault prognosis ( Bhadriraju et al., 2021 ; and Bhadriraju et al., 2022 ), digital twin modeling ( Wang et al., 2022 ), and COVID-19 transmission dynamics modeling ( Jiang et al., 2021 ). Furthermore, SINDy has been extended as an adaptive modeling algorithm...

.... , Bangi , M. S. F. , Narasingam , A. , and Kwon , J. S. I. , “ Operable adaptive sparse identification of systems (OASIS): Application to chemical processes ,” AIChE J.   66 , e16980 ( 2020 ). Bhadriraju , B. , Kwon , J. S. I. , and Khan , F. , “ Risk-based fault prediction...

..., the reliability of a PV power generation system is lower than that of a traditional power generation system. Reliability analyses of PV power generation systems can help to mitigate certain risks and faults. For example, a high penetration of the PV systems can adversely affect the electricity distribution...

... for energy systems optimization: Challenges and opportunities ,” Energy   179 , 76 – 89 ( 2019 ). 10.1016/j.energy.2019.04.186 Ajagekar , A. and You , F. , “ Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems ,” Appl. Energy   303 , 117628...

... ). 10.35940/ijrte.B1014.0882S819 Chao , H. , Ho , H. , and Wang , H. , “ Modeling and fault diagnosis of a PV system ,” Electr. Power Syst. Res.   78 ( 1 ), 97 – 105 ( 2008 ). 10.1016/j.epsr.2006.12.012 Chel , A. , Tiwari , N. , and Chandra , A. , “ Simplified method...

... and You, 2019 ) in areas such as artificial intelligence and optimization, or being employed for fault diagnosis for electrical power systems using quantum annealing-assisted deep learning ( Ajagekar and You, 2021 ). It has also been explored for control [e.g., with model predictive control using quantum...