Study On Incipient Fault Detection Technology Of Induction Motor

The incipient fault characteristic of the induction motor is usually very weak. Forspeed regulation and energy saving requirements, the induction motor is driven byfrequency converter. The soaring harmonic component in converter and the noiseproduced by peripheral equipment make it more difficult for the incipient fault detection.Aiming at the broken rotor bar, inter-turn short circuit, and bearing fault of the inductionmotor, this dissertation focuses on incipient fault characteristic extraction and detection inheavy noise.When induction motor has the incipient broken bar fault, the new added faultcharacteristic component is difficult to be discriminated in the spectrum analysis because ofbeing blanketed by fundamental component. The improved correlation algorithm isproposed to solve this problem. According to the truth that the voltage and the fundamentalcomponent of current have the same frequency, reference signals whose frequency areequal to the one of stator voltage are constructed. By the improved correlation algorithm,the amplitude and phase of the fundamental component in stator current can be obtained, sothe rotor broken bar fault signal will be emerged after the fundamental component isremoved accurately. When broken rotor bar fault occurs in induction motor with variablefrequency power, the fault characteristic centred on the carrier frequency is distributed inthe input-side current spectrum of inverter with specific frequency interval. But it is easy tobe covered with neighbouring components, and the condition gets worse as the inverterruns in low frequency or under light load. The reference signals are constructed accordingto input, output and carrier frequency of inverter. With improved correlation algorithm, thecomponents confusing the diagnosis result is removed，and the fault characteristic canemerge from the spectrum.Since there are a lot of harmonics and noise in the stator current signal, especiallywhen induction motor is fed with variable converter, the inter-turn short circuit faultdiagnosis should be greatly influenced. With the three-phase improved correlationalgorithm, the fundamental component in stator current can be got accurately. This paperpresents the detection method based on the anti-synchronous-speed coordinatetransformation. Via this transformation, the positive sequence component is turned into the second harmonic, and the negative one is transformed into DC component which can beextracted with the mean algorithm, then the amplitude of synthetic vector of the negativesequence component in new coordinate can be derived. A sensitivity factor is defined toevaluate the severity extension of the inter-turn-short-circuit faults, which takes intoaccount the manufactured asymmetry of the induction motor.The incipient bearing fault characteristic is so weak that it is very difficult to bediscriminated because of being obscured by noises of the peripheral equipment. A filterused to extract weak signal in heavy noise is presented to extract weak fault signal based onspectral kurtosis. Via short-time Fourier transform to the vibration signals, the estimation ofthe spectral kurtosis is given. According to the spectral kurtosis, a filter controlled bysignal-to-noise ratio is constructed automatically to remove the noises and harmoniccomponents. Then the incipient bearing fault characteristic information could be veryobvious by means of the envelope analysis.Taking32-bit S3C2440A microprocessor as a core of motor parameters collection，viathe Labview software platform for data analysis and fault diagnosis，an incipient faultdiagnosis system for the induction motor is constructed. Experiment results indicate that thesystem is feasible in the broken rotor bar, inter-turn short circuit, and bearing faultdiagnosis.