Robust measurement, monitoring and analysis of partial discharges in transformers and other HV apparatus

Kraetge, A.; Hoek, S.M.; Koch, M.; Kołtunowicz, W.

doi:10.1109/tdei.2013.6678852

Cited by 26 publications

(14 citation statements)

References 13 publications

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“…(c + m sin(2 f m t)) sin(2 f i t) (17) with c = 1, m = 0.4, f m = 1 kHz and f i varying from 600 kHz to 1400 kHz in steps of 200 kHz. We added to the reference signals the AM noise defined by (17) with SNR = 1 and a stochastic Gaussian white noise with SNR = 1, and performed for each signal 50 filtering simulations.…”

Section: Discrete Spectral Interferencementioning

confidence: 99%

“…In [16], spectral power analyses of PD pulses was employed to classify PD sources and noise by means of a graphical representation. In [17], modern methods for robust measurement and monitoring of highvoltage apparatus are described, while in [18] and [19] the designs of Hilbert fractal antenna and stacked Hilbert antenna array to increase the frequency bandwidth and sensitivity of the PD measurement system are discussed.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A new wavelet selection method for partial discharge denoising

Cunha

Carvalho

Petraglia

et al. 2015

Electric Power Systems Research

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Section: Discrete Spectral Interferencementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A new wavelet selection method for partial discharge denoising

Cunha

Carvalho

Petraglia

et al. 2015

Electric Power Systems Research

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“…In contrast, the main advantage of the AE method is the ability to determine the localization of the PD source [3], [13]. Typically, this principle uses several AE sensors installed on the transformer wall to detect ultrasound waves generated by the PD and the localization of the PD-source is determined based on the time of flight differences between the acoustic PD signals [10]- [14]. The use of two combined measurement methods is required because the signals from the AE sensors have low signal-tonoise ratio (SNR) due to the damping that the acoustic waves undergo in the propagation paths between the PD-source and the sensors [14], [15].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Macro Fiber Composite Sensors for Measurement of Acoustic Partial Discharge Signals in Power Transformers

et al. 2017

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This paper presents a performance assessment of macro fiber composite (MFC) sensors for measuring acoustic emission (AE) signals from partial discharges (PD) in power transformers filled with mineral oil. MFC sensors are low-profile and flexible, allowing them to be attached to uneven surfaces, such as a transformer wall. Two types of MFC sensors were assessed: P1 (d33 effect) and P2 (d31 effect), which are optimized for different deformations in the structure, such as elongation and contraction, respectively. In addition, a conventional AE sensor, R15I-AST model from Physical Acoustics South America, was also used as a reference for comparative analysis. Four metrics were applied to the signals: root mean square, energy criterion, Akaike criterion, power spectral density, and correlation. The experimental results indicate a high similarity between the MFC sensors and the conventional AE sensor, which expands the research field in acoustic PD measurement in power transformers by using low-cost and flexible sensors.

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“…Measured apparent charge values and phase angle of the power voltage cycle correlation have been supported by the PRPD. Not only the highest effectiveness but also analysis capabilities of the measured phenomena have been delivered by a PRPD pattern tool [10][11][12][13][14]. A stochastic nature of a PD phenomena has been the highest challenge for all of PD measurement methods so far.…”

Section: Introductionmentioning

confidence: 99%

Comparison of capacitive and inductive sensors designed for partial discharges measurements in electrical power apparatus

Kunicki

2017

E3S Web Conf.

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Abstract. In the paper results of simultaneously conducted measurements achieved using capacitive and inductive sensors are presented according to different PD model sources immersed in a mineral transformer insulation oil. All measurements are preceded under laboratory conditions using typical measurement set up commonly applied for on-site PD detection: measuring impedance and capacitor and high frequency current transformer (HFCT) are used respectively. Measuring frequency and voltage level influence as well as phase resolved PD patterns analysis are investigated in the research. Various fundamental PD signal descriptors assigned for selected frequencies are also proposed and compared for chosen sensors. The main purpose of the presented research is to compare PD measurement results achieved using selected type of sensors during laboratory measurements and to point the best application areas in fields of PD detection in high voltage apparatus under normal operating conditions. Furthermore a proper measurement results interpretation coming from different sensors as well as measurement conducting problems and achieved patterns disparities are also discussed in the paper.

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Robust measurement, monitoring and analysis of partial discharges in transformers and other HV apparatus

Cited by 26 publications

References 13 publications

A new wavelet selection method for partial discharge denoising

A new wavelet selection method for partial discharge denoising

Assessment of Macro Fiber Composite Sensors for Measurement of Acoustic Partial Discharge Signals in Power Transformers

Comparison of capacitive and inductive sensors designed for partial discharges measurements in electrical power apparatus

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