About the project

  

Title: Induction Motor - Stator Inter-turn Fault Diagnosis 

Introductory Notes.

  • Modern industry uses Induction Machines (IM) the most because of its affordability, durability, and cost-effective maintenance. However, IM do also encounter certain faults such as bearing related faults, stator winding faults, rotor faults and others. 
  • This project will be focusing on the diagnosis of Stator Inter-turn Fault (SITF) of an IM. The diagnosis of the SITF will be online, analyzing the given dataset for the healthy and faulty IM which utilizes the parameters of a 2.2kW four-pole squirrel cage.
  • SITF severity levels are: 0.3%, 0.7%, 1.05%, and 2.1%.

Objectives.

  • Data acquisition (simulation).
  • Perform frequency analysis on the simulation data set.
  • Perform Principal Component Analysis (PCA), and Independent Component Analysis (ICA) - Explore the data and Dimensionality Reduction (DR).
  • Classification of the severity levels using shallow neural network and non-neural technique.


Dataset discussion:

  • IM model containing the SITF simulation data.
  • Data sample at 5kHz, with 30,000 samples obtained for the three phase current signatures.
  • Different load condition at 0%, 75% and 100%.
The SITF severity percentage was found using the equation: 

SITF% = (No. of coil turns shorted (Ncc) / (No- of turns in a phase (Ns) x 3 phase)) x 100


Table 1: Class labels

Fault Class

Fault Severity

Inter-turn shorted

1

Healthy

0

2

0.3%

1

3

0.7%

2

4

1.05%

3

5

2.1%

6









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