Time- Frequency Techniques for Fault Identification of Induction Motor

Condition monitoring and fault diagnosis of engineering plant has increased recently because of the widespread use of automation and consequent reduction in direct human-machine interaction to supervise the motor drive system operation. With advances in digital technology in recent years, adequate data processing capability is now available on cost-effective hardware platforms, to monitor motors for a variety of abnormalities on a real time basis in addition to the normal motor protection functions. Such multifunction monitors are now starting to displace the multiplicity of electromechanical devices commonly applied for many years. For such reasons, this paper is devoted to a comparison of signal processing techniques for the detection of common faults of electric machines. These techniques show different pattern of stator current of motor for different types of fault. This paper also presents the features of these techniques which will help us to decide most appropriate technique for induction motor fault detection. STFT, Gabor Transform and WVD are some techniques that are discussed in this paper. Introduction Induction motors are one of the rotating electrical machines most widely used. Due to its low cost, reasonably small size, and operation with an easily available power supply, induction motor is widely used in industries such as automotive, aerospace, and industrial equipment. However, operational environment, duty, and installation issues may combine to accelerate induction motor failure far sooner than the designed motor lifetime. Faults can occur in the stator, rotor, bearing, or the external systems connected to the induction motor. It is well known that induction motors dominate the field of electromechanical energy conversion. These machines find a wide role in most industries in particular in the electric utility industry as auxiliary drives in central power plants of power systems, as well as a restricted role in low MVA power supply systems