Fault indicator

About: Fault indicator is a research topic. Over the lifetime, 10057 publications have been published within this topic receiving 143482 citations. The topic is also known as: FCI & power line fault indicator.

Fault section identification and location on a distribution feeder using travelling waves

Abstract: This paper describes how the fault generated travelling waves detected in the current signals at a single location on a distribution feeder can be used for fault section identification and location. The method identifies the fault section and the probable location of the fault by comparing the relative distance of each "peak" in the high frequency current signals to the known reflection points in the distribution feeder. The probable fault location is then used within a transient power system simulator that models the actual network. The resulting simulated current waveforms are then cross-correlated against the signal captured on the real network. If the estimated fault location is correct, the high frequency signatures in the simulated waveform will be similar to that of the measured waveforms and the cross-correlation value will be a high positive value. Simulation studies using PSCAD/EMTDC and analysis using cross-correlation technique suggest that the method described can accurately locate a fault on a distribution feeder using measurement at a single location.

Detection of faults of filter capacitors in a converter. Application to predictive maintenance

Abstract: One of the most frequent reasons of breakdown of static power converters, and in particular switch mode power supplies, is the failure of filter electrolytic capacitors. With the use of time-worn capacitors, or by modelling the faults artificially, the authors have developed a fault indicator. By comparing the latter with data representing the system during normal running, they have achieved an estimate of imminent failure. >

A Novel Solid-State Fault Current-Limiting Circuit Breaker for Medium-Voltage Network Applications

Abstract: In this paper, a novel solid-state fault current-limiting circuit breaker (SSFCLCB) based on a series resonance LC tank is proposed. Since the series configuration of the resonance structure (a capacitor and a reactor) of the SSFCLCB is invisible during normal operation mode, it shows negligible impedance in the line. In fault conditions, the SSFCLCB topology changes to a rectifier bridge and feeds the resonance structure with rectified ac voltage. With the rectified voltage, the series capacitor is charged and, as a result, the faulty line is opened and the fault current is seized. Hence, the suggested SSFCLCB cannot only limit the fault current but can also open the faulty line and acts as a circuit breaker. For confirmation of these aspects, simulations are performed using MATLAB software. Also, a prototype structure is designed and built for results confirmation. This experimental setup is established to prove that SSFCLCB has excellent performance in its startup, normal operation, and current-limiting/breaking conditions. The results show that the SSFCLCB has the ability to improve distribution network reliability and it can decrease the network fault current level successfully.

A Stray Magnetic Flux-Based Robust Diagnosis Method for Detection and Location of Interturn Short Circuit Fault in PMSM

Abstract: Early diagnosis of interturn short circuit (ITSC) fault is essential to prevent catastrophic electrical machine failures. Along with the detection, locating the faulty winding at its incipient stage is also critical to reduce the outage duration and operation losses. This article proposes a practical method to detect the ITSC fault and locate the faulty winding in permanent magnet synchronous motors (PMSMs) through stray magnetic flux monitoring. It is shown that relying on the fundamental stray flux component can potentially underperform at certain operating conditions leading to fault negative error. To compensate this shortcoming, the third harmonic component of stray flux is comprehensively analyzed and proposed as a complementary ITSC fault indicator. Furthermore, its reliability over the wide range of motor operation is verified to eliminate potential fault negative errors. It is also shown that the proposed method is independent of the fault severity which is a major advantage for practical applications. The findings are supported through 2-D-FEA PMSM drive system simulations and experiments under two different fault severity cases.

Combination of Model-based Observer and Support Vector Machines for Fault Detection of Wind Turbines

Abstract: Support vector machines and a Kalman-like observer are used for fault detection and isolation in a variable speed horizontal-axis wind turbine composed of three blades and a full converter. The support vector approach is data-based and is therefore robust to process knowledge. It is based on structural risk minimization which enhances generalization even with small training data set and it allows for process nonlinearity by using flexible kernels. In this work, a radial basis function is used as the kernel. Different parts of the process are investigated including actuators and sensors faults. With duplicated sensors, sensor faults in blade pitch positions, generator and rotor speeds can be detected. Faults of type stuck measurements can be detected in 2 sampling periods. The detection time of offset/scaled measurements depends on the severity of the fault and on the process dynamics when the fault occurs. The converter torque actuator fault can be detected within 2 sampling periods. Faults in the actuators of the pitch systems represents a higher difficulty for fault detection which is due to the fact that such faults only affect the transitory state (which is very fast) but not the final stationary state. Therefore, two methods are considered and compared for fault detection and isolation of this fault: support vector machines and a Kalman-like observer. Advantages and disadvantages of each method are discussed. On one hand, support vector machines training of transitory states would require a big amount of data in different situations, but the fault detection and isolation results are robust to variations in the input/operating point. On the other hand, the observer is model-based, and therefore does not require training, and it allows identification of the fault level, which is interesting for fault reconfiguration. But the observability of the system is ensured under specific conditions, related to the dynamics of the inputs and outputs. The whole fault detection and isolation scheme is evaluated using a wind turbine benchmark with a real sequence of wind speed.