2017
DOI: 10.1049/iet-smt.2016.0362
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Identification of invalid time‐delay‐groups using discriminant and Jacobian‐determinant in acoustic emission PD source localisation

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Cited by 6 publications
(4 citation statements)
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“…CRP (6) was used to determine the TDOA (7) of UHF signals, the obtained TDOAs are correct up to the first decimal point (up to the resolution level) ( Table 9). The obtained TDOAs were validated and the source is localised by the non-iterative method [29,30]. A maximum deviation of 0.29 m was observed (Table 10) in localisation for the practical case, while in the simulation case, the maximum deviation was found to be 0.01 m. The cause for deviation in the practical case is because of limitation in the sampling rate of data acquired through an oscilloscope.…”
Section: Localisation Of Dischargesmentioning
confidence: 98%
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“…CRP (6) was used to determine the TDOA (7) of UHF signals, the obtained TDOAs are correct up to the first decimal point (up to the resolution level) ( Table 9). The obtained TDOAs were validated and the source is localised by the non-iterative method [29,30]. A maximum deviation of 0.29 m was observed (Table 10) in localisation for the practical case, while in the simulation case, the maximum deviation was found to be 0.01 m. The cause for deviation in the practical case is because of limitation in the sampling rate of data acquired through an oscilloscope.…”
Section: Localisation Of Dischargesmentioning
confidence: 98%
“…where v is the velocity of the electromagnetic signal, T is the time of propagation of the signal from the source to sensor 1. τ 12 , τ 13 , and τ 14 are propagation delays between sensor 1 and sensor 2, sensor 3 and sensor 4, respectively. This equation system ( 8)-( 11) can be solved non-iteratively to find source location [30]. In the present study, CRP is used to estimate propagation delay between sensors, further obtained TDOAs are validated [31] and water dropletinitiated discharges are localised.…”
Section: Source Localisationmentioning
confidence: 99%
“…A set of non-linear equations can be established by using the information about the TDOA, and the algorithms used to solve the non-linear equations can be classified into two categories: iterative algorithms and heuristic search algorithms. The iterative algorithms such as the Newton's method [11] are easy to implement, but require good initial value guesses for searching the PD sources. The heuristic search algorithms based on the metaheuristic techniques such as the genetic algorithms [7,12] and the particle swarm optimisation (PSO) algorithm [13][14][15] are used frequently for locating PD sources in recent years.…”
Section: Introductionmentioning
confidence: 99%
“…Most of the previous researchers have neglected the real transformer structure and produced PDs in oil tanks without cores and windings in laboratory tests [1,3,[7][8][9][10][11][12][13]; they assumed that the acoustic signals propagate from PD sources to sensors without obstacles. However, cores and windings can change arrival times when acoustic signals pass through them, which will affect the localisation accuracy.…”
Section: Introductionmentioning
confidence: 99%