Abstrato

Embedded System Development for Multiple Fault Diagnosis of Induction Motor

S.M. Shashidhara, Dr.P. Sangameswara Raju

With the proliferation of advanced technologies in signal processing, spectrum estimation of AC machines has lead to the accurate and precise identification of different faults. The popular machine in most of the industrial applications is a squirrel cage induction motor and failures of such significant motors may have severe consequences such as product quality, ageing, safety, and costs. Most of the condition monitoring techniques in induction motors generally involve with single and specific fault identification. This paper proposes a novel investigation technique for optimized identification of two or more combined faults of an induction motor. The contribution of this paper is a methodology that suits for hardware development, which integrates induction motor data with cRIO system to identify the faults such as broken rotor bars, vibration effects (eccentricities), leakage flux condition and stator current status. To ensure the performance response of proposed methodology, tests are conducted on a 2 kW induction motor in a laboratory, which show highly satisfactory results that prove its suitability for on-line detection of single and multiple combined faults in a flexible way through its hardware implementation in a field programmable gate array (FPGA) environment.