Monitoring and Fault Diagnosis of Induction Motors Mechanical Faults Using a Modified Auto-regressive Approach
| Autor: | Ameur Fethi Aimer, Noureddine Benouzza, Mohamed El Amine Khodja, Ahmed Hamida Boudinar, Azeddine Bendiabdellah |
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| Rok vydání: | 2018 |
| Předmět: |
Electric motor
0209 industrial biotechnology Bearing (mechanical) Computer science Stator 020208 electrical & electronic engineering Process (computing) Control engineering 02 engineering and technology Fault (power engineering) law.invention Identification (information) 020901 industrial engineering & automation Autoregressive model law 0202 electrical engineering electronic engineering information engineering Induction motor |
| Zdroj: | Advanced Control Engineering Methods in Electrical Engineering Systems ISBN: 9783319978154 |
| DOI: | 10.1007/978-3-319-97816-1_30 |
| Popis: | Electric motors failure remains a very serious issue in the industrial world. This problem may not only result in the paralysis of the production but may also influence the operator safety. To resolve this problem, several methods have been developed for the monitoring and the diagnosis of faults from their appearances to avoid the industrial process interruption. With this objective in mind, this paper proposes a new diagnosis technique used in the identification of these faults based on stator current Auto-Regressive modeling. The proposed approach presents several advantages compared to the classical stator current spectral analysis using the conventional Periodogram technique. In fact, the proposed approach offers a very good frequency resolution for a very short acquisition time, which is impossible to achieve with the classical technique of the Periodogram. Simulation and experimental tests will be carried out later in this paper to verify the proposed method in bearing faults diagnosis. |
| Databáze: | OpenAIRE |
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