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Signal Processing based SVM Classifier for Mixed Fault Detection in Induction Motor

Dr. Saurabh Jadhao, Mr. Vijay Karale, Dr. A. U. Jawadekar, Dr. Sudhir Paraskar, Mr. P. R. Bharambe

Abstract


Use of induction motor is widespread in industry. Early detection of faults is crucial for reliable and economical operation of induction motor in industries. In this study fault diagnosis of induction motor under mixed fault including stator inter turn and broken rotor bar is introduced.  The base structure of study consists of current signature analysis, feature extraction, SVM and diagnosis algorithm. Motor current signals are recorded for healthy and faulty conditions of motor. To get sight of the effects of current signals that are in time domain is transformed into time frequency domain via discrete wavelet transform (DWT). Five types of wavelets are used for signal processing to demonstrate the superiority of Db4 over other standard wavelets for accurate fault classification. Features extracted using DWT are applied to SVM which is used as a fault classifier. Results obtained prove the suitability of proposed method.


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References


G.Didier ,E Ternisien ,O.caspary and H.Razik ,”A New Approach to Detect Broken Rotor Bars in Induction Machines by current Spectrum Analysis” Mechanical Systems and signal processing 21,2(2007) pp1127-1142.

J.J.Rangel-Magdaleno,R.J RomeroTroncoso,L.M.Contreras-Medina & A Garcia Perez,”Fpga implementation of novel algorithm for online bar breakage detection of induction motors” in proceddings of IMTC ,2008 IEEE 2008 pp 720-725.

A.J.M Cardosa , S,M.A Cruz, J.F.S Carvalho,E.S.Saraiva,”Rotor cage fault diagnosis in three phase induction motor by Parks Vector Approach “ IEEE industry application conference 1995 volume 1, 1995 ,pp642-646.

A.J.M Cardosa , S,M.A Cruz. D.S.B. Fonseca “Inte rturn Stator Winding Faults diagnosis in three phase Induction motor by Park’s Vector Approach ,”IEEE Transaction Energy Conversion ,vol 14 September 1999, , pp 595-598.

H.Nejjari,M.Benbouzid,”Monitoring and Diagnosis of Induction Motor Electrical Faults using Current Park’s Vector Pattern Learning Approach” ,IEEE Transaction Industry Application , volume 36, May/June 2000 ,pp 730-735.

Lazarevic .Z.Petrovic D ,”The Advanced method for rotor failure Detection in Induction Motor “ IEEE Transaction Energy Conversion 2000 ,pp493-509.

Combastel C, Lesecq S, Petropal S, Gentil S ,”Model based and wavelet approachesto Induction Motor online Fault detection “ Control Engineering Practice ,vol 2,No 5,pp493-509.

O Ondel, E.Boutleux and G.Clerc ,” A Method to detect Broken Bars in Induction Machines using Pattern ecognition Technique s” IEEE Transactions on Industry Application ,Vol 42, No 4, July?August 2006 , pp 916-923.

Adydin ,I; KARAKOSE, M; AKIN , E;”A Simple and Efficient Method for Fault Diagnosis using Time Series Data Mining “IEEE Machines and Drives Conference (IEMDC07)-2007 pp 597-600.

A.M.Daselva ,R.J. Poveneli ,N.A. Odemer Dash “,Induction Machine Broken bar and stator current short circuit fault diagnosis based on three phase stator current envelope “ IEEE transaction on Industrial Electronics ,2008 pp1310-1318.].


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