New Partial Discharge location method in power transformer based on acoustic wave propagation characteristics using numerical simulation

2012 ◽  
Author(s):  
Masahiro Kozako ◽  
Hiroki Murayama ◽  
Masayuki Hikita ◽  
Kenji Kashine ◽  
Itaru Nakamura ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Wave Propagation ◽  
Acoustic Wave ◽  
Power Transformer ◽  
Partial Discharge ◽  
Propagation Characteristics ◽  
Acoustic Wave Propagation ◽  
Location Method ◽  
Discharge Location

Modelling of Acoustic Wave Propagation Due to Partial Discharge and Its Detection and Localization in an Oil-Filled Distribution Transformer

Frequenz ◽  
2020 ◽  
Vol 74 (1-2) ◽  
pp. 73-81 ◽  
Author(s):  
Sorokhaibam Nilakanta Meitei ◽  
Kunal Borah ◽  
Saibal Chatterjee
Keyword(s):  
Wave Propagation ◽  
Acoustic Wave ◽  
Partial Discharge ◽  
Piezoelectric Sensor ◽  
Comsol Multiphysics ◽  
Distribution Transformer ◽  
Acoustic Wave Propagation ◽  
Wave Signal ◽  
Artificial Neural Network Ann ◽  
Detection And Localization

AbstractPartial discharge (PD) is the main cause of the insulation decay and hence periodical testing of the insulation condition of a distribution transformer is necessary. This paper presents a model of PD acoustic wave propagation, detection, and localization in an oil-filled distribution transformer using finite element method supported by COMSOL Multiphysics software. Using an acoustic module and AC/DC module of COMSOL Multiphysics software, oil filled distribution transformer, and the acoustic piezoelectric sensor are simulated to analyze and detect the PD inside the transformer. PD is numerically simulated in the transformer windings, core, and oil ducts that produce acoustic wave signal. The distribution of the acoustic pressure wave inside the model transformer is analyzed first. Next, the acoustic piezoelectric sensors are modelled at four different locations of the model transformer to detect the pressure acoustic wave signal induced due to PD in the transformer. Finally, using an artificial neural network (ANN), the localization, and identification of PD in various parts of the transformer have been analyzed. The results obtained for location and detection are quite encouraging.

Influence of Moisture of Wheat on Acoustic Wave Propagation Characteristics

2020 ◽  
Vol 63 (5) ◽  
pp. 1315-1326
Author(s):  
Chi Zhang ◽  
Aini Dai ◽  
Haiying Yang ◽  
Zidan Wu ◽  
Xiaoguang Zhou ◽  
...  
Keyword(s):  
Wave Propagation ◽  
Moisture Content ◽  
Acoustic Wave ◽  
Attenuation Coefficient ◽  
Wave Velocity ◽  
Propagation Constant ◽  
Pso Algorithm ◽  
Average Radius ◽  
Propagation Characteristics ◽  
Acoustic Wave Propagation

HighlightsA novel measuring device was developed for the propagation constant of acoustic waves in grain.Increase in moisture of wheat from 1.1% to 7.8% (wet basis) decreased the wave velocity and increased the attenuation coefficient.Increase in moisture of wheat from 7.8% to 21.2% increased the wave velocity and decreased the attenuation coefficient.Using the Johnson-Champoux-Allard (JCA) model and particle swarm optimization (PSO) algorithm, the influence of moisture on the pore structure in wheat was characterized.Abstract. Acoustic methods have been widely used for the measurement of grain moisture content and temperature as well as for detecting the presence of insects in grain. Therefore, this study was conducted to understand the influence of wheat moisture content on acoustic wave propagation characteristics. A novel device was developed for measuring the acoustic wave propagation constant. The propagation constants of 12 samples of wheat were measured, with each sample having a different moisture content in the range from 1.1% to 21.2% (wet basis). The results showed that the acoustic wave velocity decreased slightly with an increase in moisture from 1.1% to 7.8%, while the attenuation coefficient increased slightly. When the moisture increased from 7.8% to 21.2%, the velocity increased gradually, while the attenuation coefficient decreased. A quadratic equation described the results well. In addition, a Johnson-Champoux-Allard (JCA) model was adopted to study the influence of moisture on the pore structure of wheat samples. With the increase in moisture from 1.1% to 21.2%, the average radius of interconnection between two adjacent pores decreased from 0.275 to 0.262 mm at moisture below 7.8% and then increased to 0.304 mm, and the average radius of the pores decreased from 0.773 to 0.481 mm at moisture below 7.8% and then increased to 1.2 mm. Keywords: Acoustic standing wave tube, JCA model, Moisture content, Propagation constant, PSO algorithm, Wheat.

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