Shannon Entropy and K-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals
For industry, the induction motors are essential elements in production chains. Despite the robustness of induction motors, they are susceptible to failures. The broken rotor bar (BRB) fault in induction motors has received special attention since one of its characteristics is that the motor can con...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2016/4860309 |
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| author | David Camarena-Martinez Martin Valtierra-Rodriguez Juan P. Amezquita-Sanchez David Granados-Lieberman Rene J. Romero-Troncoso Arturo Garcia-Perez |
| author_facet | David Camarena-Martinez Martin Valtierra-Rodriguez Juan P. Amezquita-Sanchez David Granados-Lieberman Rene J. Romero-Troncoso Arturo Garcia-Perez |
| author_sort | David Camarena-Martinez |
| collection | DOAJ |
| description | For industry, the induction motors are essential elements in production chains. Despite the robustness of induction motors, they are susceptible to failures. The broken rotor bar (BRB) fault in induction motors has received special attention since one of its characteristics is that the motor can continue operating with apparent normality; however, at certain point the fault may cause severe damage to the motor. In this work, a methodology to detect BRBs using vibration signals is proposed. The methodology uses the Shannon entropy to quantify the amount of information provided by the vibration signals, which changes due to the presence of new frequency components associated with the fault. For automatic diagnosis, the K-means cluster algorithm and a decision-making unit that looks for the nearest cluster through the Euclidian distance are applied. Unlike other reported works, the proposal can diagnose the BRB condition during startup transient and steady state regimes of operation. Additionally, the proposal is also implemented into a field programmable gate array in order to offer a low-cost and low-complex online monitoring system. The obtained results demonstrate the proposal effectiveness to diagnose half, one, and two BRBs. |
| format | Article |
| id | doaj-art-00a68b2a111046a99697731f093bae22 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-00a68b2a111046a99697731f093bae222025-02-03T01:26:04ZengWileyShock and Vibration1070-96221875-92032016-01-01201610.1155/2016/48603094860309Shannon Entropy and K-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration SignalsDavid Camarena-Martinez0Martin Valtierra-Rodriguez1Juan P. Amezquita-Sanchez2David Granados-Lieberman3Rene J. Romero-Troncoso4Arturo Garcia-Perez5División de Ingenierías, Universidad de Guanajuato, Campus Irapuato-Salamanca, Carretera Salamanca-Valle de Santiago Km 3.5 + 1.8, Comunidad de Palo Blanco, 36885 Salamanca, GTO, MexicoFacultad de Ingeniería, Universidad Autónoma de Querétaro, Campus San Juan del Río, Río Moctezuma 249, Col. San Cayetano, 76807 San Juan del Río, QRO, MexicoFacultad de Ingeniería, Universidad Autónoma de Querétaro, Campus San Juan del Río, Río Moctezuma 249, Col. San Cayetano, 76807 San Juan del Río, QRO, MexicoDepartamento de Ingeniería Electromecánica, Instituto Tecnológico Superior de Irapuato, Carretera Irapuato-Silao Km 12.5, Colonia El Copal, 36821 Irapuato, GTO, MexicoDivisión de Ingenierías, Universidad de Guanajuato, Campus Irapuato-Salamanca, Carretera Salamanca-Valle de Santiago Km 3.5 + 1.8, Comunidad de Palo Blanco, 36885 Salamanca, GTO, MexicoDivisión de Ingenierías, Universidad de Guanajuato, Campus Irapuato-Salamanca, Carretera Salamanca-Valle de Santiago Km 3.5 + 1.8, Comunidad de Palo Blanco, 36885 Salamanca, GTO, MexicoFor industry, the induction motors are essential elements in production chains. Despite the robustness of induction motors, they are susceptible to failures. The broken rotor bar (BRB) fault in induction motors has received special attention since one of its characteristics is that the motor can continue operating with apparent normality; however, at certain point the fault may cause severe damage to the motor. In this work, a methodology to detect BRBs using vibration signals is proposed. The methodology uses the Shannon entropy to quantify the amount of information provided by the vibration signals, which changes due to the presence of new frequency components associated with the fault. For automatic diagnosis, the K-means cluster algorithm and a decision-making unit that looks for the nearest cluster through the Euclidian distance are applied. Unlike other reported works, the proposal can diagnose the BRB condition during startup transient and steady state regimes of operation. Additionally, the proposal is also implemented into a field programmable gate array in order to offer a low-cost and low-complex online monitoring system. The obtained results demonstrate the proposal effectiveness to diagnose half, one, and two BRBs.http://dx.doi.org/10.1155/2016/4860309 |
| spellingShingle | David Camarena-Martinez Martin Valtierra-Rodriguez Juan P. Amezquita-Sanchez David Granados-Lieberman Rene J. Romero-Troncoso Arturo Garcia-Perez Shannon Entropy and K-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals Shock and Vibration |
| title | Shannon Entropy and K-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals |
| title_full | Shannon Entropy and K-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals |
| title_fullStr | Shannon Entropy and K-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals |
| title_full_unstemmed | Shannon Entropy and K-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals |
| title_short | Shannon Entropy and K-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals |
| title_sort | shannon entropy and k means method for automatic diagnosis of broken rotor bars in induction motors using vibration signals |
| url | http://dx.doi.org/10.1155/2016/4860309 |
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