Prabhakar Neti

Stator Inter-Turn Fault Detection of Doubly-Fed Induction Generators Using Rotor Current and Search Coil Voltage Signature Analysis

A novel technique for detecting stator inter-turn faults in a doubly fed induction generator (DFIG) is proposed by analyzing its rotor current and search coil voltage. So far, fault diagnostic techniques proposed for stator inter-turn fault detection in DFIG are based on analysis of stator current or vibration of generator. Results from these methods are ambiguous because either they fail to account for condition when DFIG is operating under unbalanced load or these methods are based on experimental results alone. Our recent observations suggested that harmonics induced in the rotor circuit are very promising in detecting stator inter-turn faults in DFIGs. Hence, in this study, an in-depth investigation was conducted to determine the origin of various harmonic components in the rotor currents and their feasibility to detect inter-turn stator faults unambiguously. Detailed analysis is presented that explains the induction of stator inter-turn fault related harmonics in the rotor circuit. The theory is verified with simulation and extensive experimental results.

Stator Interturn Fault Detection of Synchronous Machines Using Field Current and Rotor Search-Coil Voltage Signature Analysis

Our recent observations suggested that harmonics in the field current are very promising to detect stator interturn faults in synchronous machines. So far, an increase in some of the even harmonics in the field current has been reported to detect such faults. However, no explanation has been provided for the cause of these harmonics. Moreover, the even harmonics can significantly increase with supply unbalance as well as time harmonics, which can lead to a serious confusion. Hence, in this study, an in-depth investigation was conducted to determine the origin of various harmonic components in the field current and their feasibility to detect stator faults. It was found that, owing to structural asymmetries of the field winding, some of these components clearly increased with stator interturn fault. The findings are helpful to detect faults involving few turns without ambiguity, in spite of the presence of supply unbalance and time harmonics. Both simulation and experimental results are presented in this paper. The diagnosis results have also been verified using a rotor-mounted search coil, which can also be used to detect even a one-turn stator fault very effectively.

On-line capacitance and dissipation factor monitoring of AC stator insulation

A new on-line technique for monitoring the insulation condition of ac motor and generator stator windings is proposed. The approach uses a newly developed High-Sensitivity Current Transformer (HSCT) to precisely and non-invasively measure the differential current (e.g., the insulation current) of each phase winding from the motor junction box. Conventional differential current transformers (CT) used for fault protection can be replaced with the new HSCT to measure the winding insulation current with higher sensitivity and accuracy. The HSCT can serve both motor health monitoring and motor protection functions. Presently, indicators for insulation condition such as capacitance (C), dissipation factor (DF), or insulation power factor (PF) are only obtainable off-line. The new approach can provide a low-cost solution for on-line motor insulation condition assessment. Validation of the new HSCT technology was carried out during an accelerated life testing of a 460 V, 100 HP, 1200 RPM form wound induction motor. The motor discussed in this paper was aged at high temperature (255 °C) as the load cycled between 0 % and 200 % every 5 minutes. Although this highly accelerated life test does not represent how a motor ages in service under real operating conditions precisely, the principal goal was to prove the capability of the new HSCT to accurately detect the insulation current and quantitatively monitor motor insulation gradual aging and health. On-line data from the HSCT correlated well with off-line data from a commercial capacitance and DF bridge. It is hoped that the benefits of the on-line motor health monitoring are fully realized and the method extended to other electrical assets as well.

Development and Validation of a Comprehensive Synchronous Machine Model for a Real-Time Environment

A comprehensive model of a salient-pole synchronous machine is developed for a real-time environment. By obtaining the effective specific permeance of the machine from simple experimental measurements and the exact geometry of the rotor pole arc, a model is developed that includes the exact distribution of windings and operating-point-dependent saturation. This model offers a superior simulated response of the machine for fault transients, as well as for steady-state harmonic behavior, and is suitable for the closed-loop testing of relays and controls. The inductances of the machine are computed using the modified winding function approach and validated using finite-element analysis. Finally, the performance of the model is validated under healthy and faulted conditions by comparison with tests on an actual machine.

Electrical signature analysis based online monitoring of drive-trains for doubly-fed wind generators

Drive train failures are one of the common failure modes of wind turbines. Their early detection, including the generator bearing and gearbox defects, is considered difficult using the state-of-the-art monitoring techniques. In this paper, a novel electrical signature analysis-based drivetrain monitoring technique is proposed for wind turbines. A novel electrical signature tool, electrical multi-phase imbalance separation technique (eMIST), is proposed to improve the signal-to-noise ratio in electrical signature analysis. The theoretical basis of drivetrain defect detection is also presented in detail. The proposed approach is validated by experimental results obtained from a 25 HP wind drivetrain simulator, designed to simulate 1.5 MW wind turbines. The experimental results show that the proposed approach is capable of providing accurate detection of drivetrain defects at an early stage. The proposed approach is cost effective with high probability of detection (PoD) of drivetrain defects compared to existing techniques.

A New Robust Method To Detect Rotor Faults in Salient-Pole Synchronous Machines Using Structural Asymmetries

This paper presents a novel method to detect rotor faults in salient-pole synchronous machines by exploiting small constructional asymmetries in the machine. In order to unambiguously detect the faults, it is very important to identify a signal that is minimally sensitive to the abnormal operating conditions of the machine but highly sensitive to the fault. This paper shows that certain frequency components such as the 30, 90 Hz in the stator current of a 4-pole 60 Hz salient-pole synchronous machine (SM) are good candidates for detecting rotor faults. The paper presents the physical explanation behind these observed frequency components and shows them to be suitable candidates to detect broken damper bars and inter-turn faults in the field winding.

Detection of Gearbox Bearing Defects Using Electrical Signature Analysis for Doubly Fed Wind Generators

Drivetrain failures may cause severe damage to the wind turbines. In the previous work, detection of failures in generator bearing and gearbox gears using electrical signature analysis (ESA) has been investigated. However, the detection of defects of bearings in the gearboxes has been a major gap. Bearings defects in gearboxes are believed to be one of the root causes of wind drivetrain failures. In this paper, a novel electrical signature analysis-based monitoring technique is proposed for monitoring gearbox bearing defects in wind turbines, which is the first ESA technique reported capable of detecting bearing defects in gearboxes. A novel electrical signature tool, i.e., electrical multi-phase imbalance separation technique, has been used to improve the signal-to-noise ratio in electrical signature analysis. The principle of gearbox bearing defect detection is presented in detail. The proposed approach is validated by experimental results obtained from a 25 HP wind drivetrain simulator, which is designed to simulate 1.5 MW wind turbines as well as in the field on 1.5MW wind turbines. The experimental results show that the proposed approach is capable of providing accurate detection of gearbox bearing failures at early stage. The proposed approach is cost effective with reliable detection of defects compared to existing techniques.

Online detection of endwinding contamination in industrial motors

This paper discusses a novel online technique to detect moisture and surface tracking of stator end-winding insulation in medium/high voltage AC motors. A novel high sensitivity differential current transformer is used as a sensor for monitoring insulation capacitance and dissipation factor of motors online. A 100 hp, 4160V, 3-phase form-wound induction motor is tested with different contaminants sprayed on its end winding. Partial discharge couplers are also used to monitor partial discharge activity during insulation contamination tests. A comparison of both techniques to detect pre-cursors of motor failure due to end-winding tracking is presented in this paper.

Motor current signature analysis during accelerated life testing of form wound induction motors

The work presented in this paper describes motor accelerated thermo-mechanical aging and helps set the stage for on-line monitoring/data analysis as an effective means to detect a fault as electrical machine develops it and identify its type in real time. As a first step towards this goal, Motor Current Signature Analysis (MCSA) is applied to the data collected during accelerated thermo-mechanical aging of a formed wound induction motor tested to failure. The characteristic frequencies corresponding to detecting broken bars, stator inter-turn shorts, static/dynamic eccentricities and gradual degradation of the machine insulation are identified and sought from the collected data. To accomplish this accelerated aging, the motor was started/stopped frequently and subjected to overload in a steady state manner to subject it to severe thermo-mechanical stresses. Detailed analysis of experimental data is presented. It is hoped that this effort would pave the way for future work where on-line monitoring and diagnostics become a standard tool for life extension, lower maintenance cost, condition based loading, etc. for electrical assets.

A novel online stator ground-wall insulation monitoring scheme for inverter-fed AC motors

Insulation failures are one of the most common failure modes of ac motors, especially high-voltage motors. Online monitoring of insulation health of ac motors is important for preventing unexpected outages and minimizing the associated financial losses particularly in critical applications. Previously, an online ground-wall insulation monitoring technique has already been proposed for 6-lead ac motors. In this paper, a novel online ground-wall insulation monitoring scheme is proposed for inverter-fed ac motors. This approach is based on measurement of common-mode insulation leakage current for online C/DF (capacitance and dissipation factor) monitoring. The proposed technique can be applied to both 3-lead and 6-lead ac motors and can also be extended to monitor the insulation health of the cable connecting the inverter and the motor. The proposed technique is demonstrated in the lab environment, and correlated with standard offline C/DF measurements.