Fault diagnosis of induction motors rotor using current signature with different signal processing techniques
Guezam Abdelhak, Sid Ahmed Bessedik, Rabah Djekidel
Abstract
The popularity of asynchronous machines, particularly squirrel cage machines, stems from their inexpensive production costs, resilience, and low maintenance requirements. Unfortunately, potential flaws in these devices might have a negative impact on the facility's profitability and service quality. As a result, diagnostic tools for detecting flaws in these types of devices must be developed. Asynchronous machine problems can be diagnosed using a variety of methods. Signal processing techniques based on extracting information from characteristic quantities of electrical machine operation can provide highly useful information about flaws.
Topics & Concepts
Signature (topology)Fault (geology)Induction motorRotor (electric)Signal processingComputer scienceElectrical engineeringArtificial intelligenceEngineeringDigital signal processingMathematicsSeismologyGeologyVoltageGeometryMachine Fault Diagnosis TechniquesEngineering Diagnostics and ReliabilityFault Detection and Control Systems