@inProceedings{
 title = {A new approach based on boundary analysis of reconstructed phase space for fault diagnosis},
 type = {inProceedings},
 year = {2013},
 identifiers = {[object Object]},
 keywords = {Fault diagnosis,boundary detection,image processing,induction motors,neural networks},
 id = {28286572-390e-32a7-a68b-6e13723db105},
 created = {2017-04-04T11:31:00.511Z},
 file_attached = {false},
 profile_id = {87d5a801-8629-3fa3-a3f9-81001241fe90},
 last_modified = {2017-04-04T11:31:00.511Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {This paper presents a new fault diagnosis approach based on boundary analysis of phase space. The proposed approach requires the measurement of one phase current signal to construct the phase space representation. Each phase space is converted to an image and the boundary of each image is extracted by boundary detection algorithm, helping to construct a characteristic image for each motor condition. The change in boundary of phase space appears to be a useful for diagnosing different motor operating conditions. A pattern recognition algorithm based on neural network is implemented to classify the faults. We will study one and two broken rotor bars faults. Extensive experimental results were carried out to validate the proposed approach, and good results were obtained. © 2013 IEEE.},
 bibtype = {inProceedings},
 author = {Aydin, I. and Karakose, M. and Akin, E.},
 booktitle = {2013 9th Asian Control Conference, ASCC 2013}
}

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