2018
DOI: 10.3390/en11113054
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Symmetrical Loss of Excitation Fault Diagnosis in an Asynchronized High-Voltage Generator

Abstract: As a new type of generator, an asynchronized high-voltage generator has the characteristics of an asynchronous generator and high voltage generator. The effect of the loss of an excitation fault for an asynchronized high-voltage generator and its fault diagnosis technique are still in the research stage. Firstly, a finite element model of the asynchronized high-voltage generator considering the field-circuit-movement coupling is established. Secondly, the three phase short-circuit loss of excitation fault, thr… Show more

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Cited by 3 publications
(3 citation statements)
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“…The connection weights between the input signal and the hidden layer are w 1k , w 2k and w 3k . k is the number of neurons in the hidden layer, and according to the empirical formula [25],…”
Section: Time-varying Transient Parameter Identification Modelmentioning
confidence: 99%
“…The connection weights between the input signal and the hidden layer are w 1k , w 2k and w 3k . k is the number of neurons in the hidden layer, and according to the empirical formula [25],…”
Section: Time-varying Transient Parameter Identification Modelmentioning
confidence: 99%
“…The first and second zones are respectively regarded to detect the LOE incidents occurring in the generator's heavy and light loading operations. The common time delays for the first and second zones are respectively chosen as 0.1 and 0.5 s, while such delays are set to prevent the relay mal-operations facing power system events, such as SPS occurrence [3]. Although power swing studies are recommended to appropriately define the mentioned time delays, there is always a probability of mal-operation in the face of system transient events [2].…”
Section: Negative Offset Mho Relaymentioning
confidence: 99%
“…The WPT analysis has been explored extensively for signal feature extractions, such as EEG (electroencephalogram) signals [34] and AE signals [35]. Specifically, this technique is also widely used in condition monitoring and fault diagnosis in rotary mechanical systems such as generators [36], gears [37], bearings [38] and diesel engines [39,40]. Remarkably, Reference [41] developed a wavelet packet decomposition within the framework of multi-resolution analysis theory to investigate the failure of tribological systems using AE.…”
Section: Tribological Monitoring Features From Ae Signalsmentioning
confidence: 99%