Artificial Neural Network Application for Current Sensors Fault Detection in the Vector Controlled Induction Motor Drive
| Autor: | Kamil Klimkowski, Mateusz Dybkowski |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Stator
Computer science neural network 020209 energy 02 engineering and technology lcsh:Chemical technology Biochemistry Fault detection and isolation Article Analytical Chemistry law.invention law 0202 electrical engineering electronic engineering information engineering current sensor lcsh:TP1-1185 Current sensor Electrical and Electronic Engineering Instrumentation fault detector Vector control Artificial neural network Fault Tolerant Control (FTC) 020208 electrical & electronic engineering Fault tolerance Control engineering Atomic and Molecular Physics and Optics induction motor Direct Field Oriented Control (DFOC) Current (fluid) Induction motor |
| Zdroj: | Sensors (Basel, Switzerland) Sensors Volume 19 Issue 3 Sensors, Vol 19, Iss 3, p 571 (2019) |
| ISSN: | 1424-8220 |
| Popis: | This paper describes a Fault Tolerant Control structure for the Induction Motor (IM) drive. We analyzed the influence of current sensor faults on the properties of the vector-controlled IM drive system. As a control algorithm, the Direct Field Oriented Control structure was chosen. For the proper operation of this system and for other vector algorithms, information about the stator currents components is required. It is important to monitor and detect these sensor faults, especially in drives with an increased safety level. We discuss the possibility of the neural network application in detecting stator current sensor faults in the vector control algorithm. Simulation and experimental results for various drive conditions are presented. |
| Databáze: | OpenAIRE |
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