Generation of acoustic phase-resolved partial discharge patterns by utilizing UHF signals

Ilkhechi, Hossein Dadashi; Samimi, Mohammad Hamed; Yousefvand, Reza

doi:10.1016/j.ijepes.2019.06.018

Cited by 37 publications

(8 citation statements)

References 30 publications

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“…Therefore, we focus on reducing noise individually in each detected signal by wavelet filtering and narrowing the noise bandwidth. Although in this work we have not used classification techniques to cluster noise and phantom signals, this post-processing can be applied, either as a phase-resolved partial discharge (PRPD) acoustic pattern [31,32] or with other approaches to signal and noise classification [33,34].…”

Section: Discussionmentioning

confidence: 99%

Multichannel Detection of Acoustic Emissions and Localization of the Source with External and Internal Sensors for Partial Discharge Monitoring of Power Transformers

2021

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The detection of acoustic emissions with multiple channels and different kinds of sensors (external ultrasound electronic sensors and internal optical fiber sensors) for monitoring power transformers is presented. The source localization based on the times of arrival was previously studied, comparing different strategies for solving the location equations and the most efficient strategy in terms of computational and complexity costs versus performance was selected for analyzing the error propagation. The errors of the acoustic emission source location (localization process) are evaluated from the errors of the times of arrival (detection process). A hybrid programming architecture is proposed to optimize both stages of detection and location. It is formed by a virtual instrumentation system for the acquisition, detection and noise reduction of multiple acoustic channels and an algorithms-oriented programming system for the implementation of the localization techniques (back-propagation and multiple-source separation algorithms could also be implemented in this system). The communication between both systems is performed by a packet transfer protocol that allows continuous operation (e.g., on-line monitoring) and remote operation (e.g., a local monitoring and a remote analysis and diagnosis). For the first time, delay errors are modeled and error propagation is applied with this error source and localization algorithms. The 1% mean delay error propagation gives an accuracy of 9.5 mm (dispersion) and a maximum offset of 4 mm (<1% in both cases) in the AE source localization process. This increases proportionally for more severe errors (up to 5% reported). In the case of a multi-channel internal fiber-optic detection system, the resulting location error with a delay error of 2% is negligible when selecting the most repeated calculated position. These aim at determining the PD area of activity with a precision of better than 1% (<10 mm in 110 cm).

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Section: Discussionmentioning

confidence: 99%

Multichannel Detection of Acoustic Emissions and Localization of the Source with External and Internal Sensors for Partial Discharge Monitoring of Power Transformers

2021

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“…Conventional PD detection methods utilize electronic measurements, including the electromagnetic coupling method [7,8], the capacitive coupling method [9,10], and the ultra-high frequency method [11,12]. Due to the high-voltage environment of power equipment, electromagnetic radiation and interference significantly impact these methods, resulting in poor measurement accuracy and a high probability of omission and misjudgment.…”

Section: Introductionmentioning

confidence: 99%

Research on partial discharge detection based on distributed optical fiber acoustic sensor

Sun,

Lv,

Xie

et al. 2024

Meas. Sci. Technol.

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Distributed acoustic sensors (DAS) have the advantage of long-distance and distributed monitoring of vibration signals. However, there are few studies on the application of DAS for partial discharge monitoring of power equipment. There is also a lack of related theoretical and methodological studies. In this paper, the DAS-measured phase signals are theoretically analyzed from the frequency and energy perspectives, and the method of partial discharge broadband signal coverage using spectrum and energy accumulation is proposed. Fiber optic rings are employed for the detection of partial discharge signals, and the precise localization of these signals is achieved by calculating the DAS energy spectrum. The fiber optic ring is wrapped around the cable joint to achieve the detection and locating of the partial discharge signal. The results indicate that the use of a fiber optic ring can realize the sensitive detection and locating of partial discharge. The signal strength is maximum when the length of the fiber ring is equal to the spatial resolution of DAS. The sensitivity of partial discharge detection in cable joints can reach 40 pC, and the simultaneous detection and localization of partial discharge at different locations can be realized. The research can provide support for theoretical and experimental for the monitoring of partial discharge in power equipment.

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“…The detection of the DP is possible by several methods, among which we can cite: electrical detection, ultra-high frequency detection, acoustic detection, chemical detection, and optical detection. Of these methods, the acoustic method has many advantages due to its immunity to electromagnetic signals, its better signal-to-noise ratio, and its ease of implementation, in addition to these, it makes it possible to simultaneously determine the magnitude, type, and location of PD source [ [18] , [19] , [20] , [21] ]. The acoustic detection is based on the measurement of the acoustic pressure at the level of the tank, thanks to the use of acoustic sensors placed on the tank.…”

Section: Introductionmentioning

confidence: 99%

Effect of sensor position on the measurement of acoustic wave produced by partial discharges

Fonkou Kongne,

Mengata Mengounou,

Nkouetcha

et al. 2024

Heliyon

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Generation of acoustic phase-resolved partial discharge patterns by utilizing UHF signals

Cited by 37 publications

References 30 publications

Multichannel Detection of Acoustic Emissions and Localization of the Source with External and Internal Sensors for Partial Discharge Monitoring of Power Transformers

Multichannel Detection of Acoustic Emissions and Localization of the Source with External and Internal Sensors for Partial Discharge Monitoring of Power Transformers

Research on partial discharge detection based on distributed optical fiber acoustic sensor

Effect of sensor position on the measurement of acoustic wave produced by partial discharges

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