Air gap Eccentricity Analysis in Induction Motor using Decision tree Algorithm
Rama Mishra1, E. Vijay Kumar2

1Rama Mishra, Sarvepalli Radhakrishnan University, Bhopal (M.P), India. 
2Dr. E Vijay Kumar, Department of Electrical & Electronics Engineering, Sarvepalli Radhakrishnan University, Bhopal (M.P), India.
Manuscript received on January 12, 2022. | Revised Manuscript received on February 12, 2022. | Manuscript published on February 28, 2022. | PP: 85-88 | Volume-11, Issue-3, January 2022 | Retrieval Number: 100.1/ijitee.C97210111322 | DOI: 10.35940/ijitee.C9721.0111322
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Abstract: This paper presents yeah the eccentricity Fault in the induction motor. the decision tree and Power spectrum Analysis methods are used to analyze the spectrum. Induction motor is very much like in the industry. It is also used a lot due to its easy control quality. All three-phase induction motors have mismatch eccentricity. Due to this eccentricity problem we got speed pulsation, vibration acoustic noise, and friction problem between stator and rotor. The proposed methodology is useful on Real-time data and achieves 90% true Value. The installation of various Sensors in order to maintain the Good condition of the induction motor is very costly. In the small industry, I would like to avoid this cost. The Status current contains unique fault spectrum components find fault with using a decision tree algorithm .We can easily analyze the air gap eccentricity faults. 
Keywords: Induction Motor, Spectrum Analysis, Decision Tree Algorithm, Air Gap Eccentricity, Pattern Recognition
Scope of the Article: Pattern Recognition