Detection Of Inter-turn Short Circuits Research Articles

Detection of inter-turn short-circuit in induction motors using Park–Hilbert method

In this paper, a new method, called Park–Hilbert (P–H), is presented and used to detect inter-turn short circuit in three-phase induction motors. This technique is based on spectral analysis, via the FFT, of a new generated signal called PVMP–H which represents the Park’s vector modulus computed starting from the analytical signals obtained from the three-phase current by the Hilbert transform. A theoretical analysis is performed in order to show how the proposed method works. Various experimental tests carried out on a 3 kW three-phase induction motor, illustrate the efficiency of this new method and show that some spectral components of the PVMP–H are extremely sensitive to the occurrence of shorted turns. However, it is shown that the information about the motor state is distributed on many spectral components and in order to gather these useful information, the present paper suggests the monitoring of a new fault indicators computed starting from the most sensitive harmonics (basing on the multiple signature processing). This technique is applied on the proposed signal PVMP–H; and the experimental tests confirm that a small number of shorted turns can be effectively detected using these new fault indicators even under low load. A comparative study with the conventional MCSA and EPVA methods is also performed. The obtained results show the superiority of the P–H method and prove the effectiveness of the proposed fault indicators for extracting useful information from any motor signal.

WAVELET ANALYSIS FOR STATOR FAULT DETECTION IN INDUCTION MACHINES

The main objective of the proposed analysis is the detection of inter-turn short circuits in the stator windings of an induction machine. The analysis of the space vector current modulus of an induction motor is presented in this paper. This analysis is based on Daubechies 8 wavelet with seven decomposition levels. The 5th decomposition-level detail signal for a 4 kHz sampling frequency is chosen as a fault indicator, based on simulation results that show different behaviors of the energy contained in the detail signals independent of the percentage of load and fault levels. Experimental results that validate the proposed strategy are also presented. These results also show that the strategy is in addition immune to load variations as well as to feeding voltage unbalances.

Detection of stator winding faults in induction motors using three-phase current monitoring

The objective of this paper is to propose a new method for the detection of inter-turn short circuits in the stator windings of induction motors. In the previous reported methods, the supply voltage unbalance was the major difficulty, and this was solved mostly based on the sequence component impedance or current which are difficult to implement. Some other methods essentially are included in the offline methods. The proposed method is based on the motor current signature analysis and utilizes three phase current spectra to overcome the mentioned problem. Simulation results indicate that under healthy conditions, the rotor slot harmonics have the same magnitude in three phase currents, while under even 1 turn (0.3%) short circuit condition they differ from each other. Although the magnitude of these harmonics depends on the level of unbalanced voltage, they have the same magnitude in three phases in these conditions. Experiments performed under various load, fault, and supply voltage conditions validate the simulation results and demonstrate the effectiveness of the proposed technique. It is shown that the detection of resistive slight short circuits, without sensitivity to supply voltage unbalance is possible.

A current monitoring system for diagnosing electrical failures in induction motors

Induction motors are critical components in industrial processes. A motor failure may yield an unexpected interruption at the industrial plant, with consequences in costs, product quality, and safety. Many of these faulty situations in three phase induction motors have an electrical reason. Among different detection approaches proposed in the literature, those based on stator current monitoring are advantageous due to its non-invasive properties. One of these techniques resorts to spectrum analysis of machine line current. Another non-invasive technique is the Extended Park's Vector Approach, which allows the detection of inter-turn short circuits in the stator winding. This article presents the development of an on-line current monitoring system that uses both techniques for fault detection and diagnosis in the stator and in the rotor. Based on experimental observations and on the knowledge of the electrical machine, a knowledge-based system was constructed in order to carry out the diagnosis task from these estimated data.

The detection of inter-turn short circuits in the stator windings of operating motors

This paper develops a winding-function-based method for modeling polyphase cage induction motors with inter-turn short circuits in the machine stator winding. Analytical consideration which sheds light on some components of the stator current spectra of both healthy and faulty machines is developed. It is shown that, as a result of the nature of the cage rotor, no new frequency components of the line current spectra can appear as a consequence of the fault. Only a rise in some of the frequency components which already exist in the line current spectra of a healthy machine can be observed. An experimental setup comprising a 3 kW delta-connected motor loaded by a generator was used to validate this approach. The experimental results obtained clearly validate the analytical and simulation results.