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|Acoustic Emission Signal Based Investigations Involving Laboratory and Field Studies Related To Partial Discharges & Hot-Spots in Power Transformers
|Shanker, Tangella Bhavani
|Punekar, G. S.
Nagamani, H. N.
|Department of Electrical and Electronics Engineering;Acoustic emission (AE);Acoustic emission partial discharge (AEPD);Discharge magnitude;Discrete wavelet transform (DWT);Dissolve gas analysis (DGA);Fast Fourier transform(FFT);Generator transformer(GT);Hot-spots (heat-waves);On-load tap changer (OLTC);Partial discharge (PD)
|National Institute of Technology Karnataka, Surathkal
|Power transformers are important and vital components of ac power systems. It is essential to monitor the condition of these transformers periodically in order to ascertain the performance for continuous operation for its expected average life of 25-30 years. The defects in power transformers lead to the deterioration of insulation and eventual premature failure. The deterioration of insulation of power transformers can be assessed by carrying out the condition monitoring tests periodically. The condition monitoring test techniques can be off-line or on-line. The off-line test techniques are being followed as given in IEEE Std. 62(1995). These tests require outage of the transformer, thereby causing interruption of power supply. Whereas, on-line test techniques do not require any outage. Hence, on-line diagnostic techniques have gained importance. Literature review shows application of Acoustic Emission (AE) detection technique as a promising on-line tool for condition monitoring/diagnosis of the power transformers. The general guidelines for the application of AE technique for this purpose are outlined in IEEE Std. C57.127 (2007). Few typical case studies of AE signal measurements are discussed involving (i) two identical transformers, (ii) same transformer on different occasions (years) in power stations in India are reported. Some case studies with AE signals, involving On-Load Tap Changer (OLTC) and cooling system pump are also reported. These case studies also help in comprehending the efficacy of integrating the Dissolved Gas Analysis (DGA) data with the AE test results. Laboratory experimental work is carried out by simulating the most probable defects like Partial Discharge (PD) and hot-spots (leading to heat-waves) in order to capture AE signals in the range of 0-500 kHz. The classification and characterization of the defects based on the energy distribution of AE signals over the different frequency ranges is carried out using Discrete Wavelet Transform (DWT) utilizing the MATLAB toolbox. The eight-level decomposition revealed that the dominant frequency ranges for the energy distribution of the AE signals due to PD and heat-wave are 125 kHz-250 kHz and 62.5 kHz–125 kHz, respectively. The AE signal data from the transformers (field test) involving PD and hotspots are also analyzed using DWT. The laboratory based characterization of PD and heatwave got validated through the analysis of field data. The proposed method of identifying defects by AE signal analysis using DWT would complement the DGA of the transformeroil. Thus this would be a better substitute for DGA based analysis as AE based technique can be adopted in real time. The Acoustic Emission Partial Discharge (AEPD) signal parameters such as discharge magnitude and peak frequencies are studied using Fast Fourier Transform (FFT) to understand the behavior of AE signals at temperatures ranging from 30°C to 75°C. The results reported are intended to give an understanding of behavior of AEPD signals over the entire working temperature range of a transformer. At temperatures above 65°C a reduction in AEPD magnitude and peak frequencies are observed. Such behavior is noticed and probably being reported for the first time. An attempt is also made to explain the same.
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|1. Ph.D Theses
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