Clarke 변환을 응용한 3상 유도전동기의 Inter Turn Short Circuit 진단

고영진,김경민 한국전기전자학회 2023 전기전자학회논문지 Vol.27 No.4

고정자 권선단락은 미세한 턴이 단락되어 급격히 고장이 심각해짐에 따라 ITSC의 진단이 중요시되고 있다. 그러나, 3상 유도전동기의 노이즈 및 손실등과 유사한 특징을 가짐에 따라 ITSC진단에 많은 어려움이 있다. 이를 효율적으로 진단하기 위해서 인공지능기법으로 연구되고 있으나, 현장에서는 모델기반 기법이 두루 활용되고 있음에 따라 모델기반 기법에 대한 진단 성능개선 연구가필요한 실정이다. 이에 본 논문에서는 회전하고 있는 자속에 변화를 무시하며, 전류 성분만을 이용할 수 있도록 Clarke변환 방법을응용하여 진단방법을 제안하였다. 이에 30분간의 정상 및 ITSC 상태의 측정 결과, 정상상태를 ITSC 상태로 오인식하는 경우0.2[%], ITSC상태를 정상상태로 오거부하는 경우 0.26[%]로 효율적인 진단 방법임을 실험을 통해 알 수 있었다. solid foundation for efficient learning and accurate voltage estimation. The observer iteratively updates its weights

하이브리드 능동전력필터의 전력품질 개선을 위한 Coordinate Transformation 기법에 대한 성능 비교

손진근,박현수,이현재,박훈양 대한전기학회 2022 전기학회논문지 P Vol.71 No.1

In this paper, the performances of Coordinate transformation method for harmonic and reactive power compensation of hybrid active power filters were compared and analyzed. Recently, as the spread of power electronic devices is expanding, the occurrence of harmonics in the system is increasing, and the harmonics have a bad effect on the system and electrical equipment. As a measure against such harmonics, the parallel resonance problem of passive power filters among filters can be solved, and a hybrid active power filter with a small compensation capacity of the active power filter can be considered. However, In order to control the hybrid active power filter to the required power factor, it is necessary to control it through fast tracking even when the load changes. Therefore, in this paper, the performance was analyzed by applying the p-q theory method and the compensation current control method using d-q respectively to the hybrid active power filter. As a result of comparing and analyzing the effects through simulation, it was confirmed that using the p-q theory method quickly followed the target value with a relatively small error even with a variable load than using the d-q method.

Fault Detection and Diagnosis System for a Three-Phase Inverter Using a DWT-Based Artificial Neural Network

Ali Rohan,Sung Ho Kim 한국지능시스템학회 2016 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.16 No.4

Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

Fault Detection and Diagnosis System for a Three-Phase Inverter Using a DWT-Based Artificial Neural Network

Rohan, Ali,Kim, Sung Ho Korean Institute of Intelligent Systems 2016 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.16 No.4

Inverters are considered the basic building blocks of industrial electrical drive systems that are widely used for various applications; however, the failure of electronic switches mainly affects the constancy of these inverters. For safe and reliable operation of an electrical drive system, faults in power electronic switches must be detected by an efficient system that is capable of identifying the type of faults. In this paper, an open switch fault identification technique for a three-phase inverter is presented. Single, double, and triple switching faults can be diagnosed using this method. The detection mechanism is based on stator current analysis. Discrete wavelet transform (DWT) using Daubechies is performed on the Clarke transformed (-) stator current and features are extracted from the wavelets. An artificial neural network is then used for the detection and identification of faults. To prove the feasibility of this method, a Simulink model of the DWT-based feature extraction scheme using a neural network for the proposed fault detection system in a three-phase inverter with an induction motor is briefly discussed with simulation results. The simulation results show that the designed system can detect faults quite efficiently, with the ability to differentiate between single and multiple switching faults.

Comparative Study of Three Fault Diagnostic Methods for Three Phase Inverter with Induction Motor

Furqan Asghar,Muhammad Talha,Sung Ho Kim 한국지능시스템학회 2017 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.17 No.4

In recent times, inverters are considered as the basic building block in an electrical drive system used widely in many industrial drive applications. However, the reliability of these inverters is mainly affected by the failure of power electronic switches. Various faults in inverter may influence the system operation by unexpected maintenance, which increases the cost factor and reduce overall efficiency. In this paper, comparative study of three different fault detection and diagnosis systems for three phase inverter is presented. The basic purpose of these fault detection and diagnosis systems is to detect single or multiple faults efficiently. These techniques rely on the neural network for fault detection and diagnosis by using Clarke transformed two-dimensional features extraction, three-dimensional features extraction and features extraction using discrete wavelet transform (DWT) with a different number of features in each technique. Several features are extracted using different mechanisms and used in the neural network as input for fault detection and diagnosis. Furthermore, a simulation study is carried out to analyze the fault detection and diagnosis response of these techniques. Also, a comparative study has been performed by considering fault detection time and accuracy. Comparison results prove the supremacy of three-dimensional feature extraction technique over other two techniques as it can detect and diagnose single, double and triple faults in a single cycle with high accuracy as compared to other two techniques multi-cycles detection.

A Novel Reference Current Extraction Technique with Multi‑Functional Capability for Shunt Active Filter

Kumar Reddy Cheepati,Nageswara Rao Maddala,Surya Kalavathi Munagala 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.2

The exponential growth of non-linear loads results the generation of harmonics in electrical distribution system. Major Harmonic generation efects due to non-linear loads are energy loss, nuisance tripping, equipment failure/mal-operation, and transformer saturation, overheating of neutral conductors and/or capacitors, interference with communication circuits, excess reactive power burden and lowering the true power factor. Improving the current quality is the prime responsibility of the consumers whereas utility is accountable for minimizing the supply voltage distortions. Shunt active flters (SAFs) were being used for many years to mitigate the current harmonics typically up to 25th order. Mainly, time and frequency domain reference current extraction control techniques were being used for SAF. Time-domain reference current extraction techniques were proved efcient than frequency-domain techniques due to their faster response. Time-domain reference current extraction techniques such as real and reactive (p-q) and synchronous reference frame (SRF) are having their own merits and demerits. The p-q control does not perform well under distorted and unbalanced supply voltage conditions whereas SRF control is limited to balanced loads. In this paper a novel reference current extraction control strategy is proposed i.e. inverse matrix averaging pq-SRF (IMApq-SRF) control. IMApq-SRF control extract the features of both conventional p-q and SRF control, based on inverse matrix average. The mathematical modeling of the proposed IMApq-SRF control is tested with MATLAB Simulink environment and it validates that the proposed IMApq-SRF control gives the superior performance as compared with conventional p-q and SRF techniques under balanced, unbalanced and distorted supply voltage and dynamic loading conditions.