.png){kind=icon}
Return
A method to detect broken boars in induction machine using pattern recognition techniques
.png){kind=icon}
OA
AI
DOI：10.1109/TIA.2006.876071.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, a pattern recognition (PR) method is used to provide the tracking and the diagnosis of a system. First of all, from measurements carried out on the system, features are extracted from current and voltage measurements without any other sensors. These features are used to build up a pattern vector, which is considered as the system signature. Then, a feature selection method is applied in order to select the most relevant features, which define the representation space. The decision phase is based on the k-nearest neighbors (knn) rule, associated with an evolution tracking of system using trajectory allowing a diagnosis not only of states defined in the training set, but also of the intermediate states. The appearance of a new operating mode is taken into account in order to enrich the initial knowledge base and thus to improve the diagnosis. This approach is illustrated on asynchronous motor of 5.5 kW with squirrel cage, in order to detect broken bars under any load level. The experimental results prove the efficiency of PR methods in condition monitoring of electrical machines.
Keywords:
fault detection and diagnosis
features selection
induction motor
k-nearest neighbors (knn) rule
pattern recognition (PR)
Journal
IF:
4.5
Papers:
1.1W
Citations:
3.5W
Organization
No organization information available
Cited Papers
ShareSaveQuantitative evaluation of induction motor broken bars by means of electrical signature analysis
PREAI
ShareSaveDose-Dense Chemotherapy in Metastatic Breast Cancer: Shortening the Time Interval for a Better Therapeutic Index.png)
Breast Care
OAAI
Breast CareIF0
OAAIShareSaveShareSaveShareSaveFactors affecting tetramer dissociation of rabbit muscle lactate dehydrogenase and reactivity of its sulfhydryl groupsBiochemistry
BiochemistryIF0
PREAI
ShareSaveShareSave
View more