acoustic emission signal analysis of on-load tap changer

2013 IEEE 1st International Conference on Condition Assessment Techniques in Electrical Systems

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Acoustic emission signal analysis of On-Load Tap Changer (OLTC)

T. Bhavani Shanker, H. N. Nagamani Central Power Research Institute

Bangalore- 560 012, India e-mail: [email protected], [email protected]

Gururaj S Punekar

Dept. of EEE, NITK, Surathkal Mangalore-575 025, India

e-mail:[email protected]

Abstract—On-Load Tap Changer (OLTC) forms a vital part of a transformer. Acoustic emission signals have been acquired from OLTC of 230 kV 3 phase power transformers for signature analysis. The acoustic emission signals have been analyzed to characterize the signals with reference to energy and frequency using Discrete Wavelet Transform. Case studies of AE signals obtained from healthy OLTCs have been presented in the paper for probable consideration as reference signals for healthy and normally operating OLTCs.

Keywords—Acoustic Emission (AE), Electrical discharges, Discrete Wavelet Transform (DWT), On-Load Tap Changer (OLTC)

I. INTRODUCTION On-load tap changers (OLTC) are the most essential and

expensive components of power transformers. Continuous switching operations of OLTC may lead to their degradation mainly due to erosion of contacts and driving mechanism [1,2]. This degradation of the contacts may lead to failure of OLTC components and consequent failure of power transformers. On-line diagnosis of OLTC with the help of Acoustic emission (AE) method during OLTC operation may help in avoiding premature failures

During tap changing, electric discharges lead to burning of the oil causing carbon build up. Additionally, wear out of electrical contacts leads to release of metal particles due to mechanical friction. These two phenomenon may lead to degradation of insulating oil and thus result in excessive electrical discharges. The process leading to power transformer failure due to OLTC is depicted in Fig.1. AE signals are generated during tap changing operation which propagates through the constituent components/media, before reaching OLTC tank surface. Capturing these AE signals by suitable AE sensors may help in assessing the condition of OLTC.

In the present study AE signals from two different 230 kV class power transformers have been captured during OLTC operation employing AE sensors and AE work station [4]. Analysis of AE signals generated during OLTC operations are presented with the help of data captured in the field. Two such case studies are discussed.

Fig. 1. Process showing the degradation of Dielectric strength of insulating oil in a tap changer

II. MEASUREMENT SETUP Acoustic emission work station along with DT 15I sensor

[4] is employed for capturing the AE signals. An AE sensor mounted on the outer surface of the OLTC tank with a magnetic hold is used for measurement.

III. ACOUSTIC EMISSION SIGNAL FROM OLTC OPERATION

AE signals from OLTC are recorded for a time period of about 120 seconds to cover the complete event of tap changing. AE data recorded before, during and after an OLTC operation is shown in Fig.2. OLTC was operated intentionally for acquiring data. Threshold for AE signal in the data acquisition and measuring system was set at 30dB. The reference time will be 0 s for start of data acquisition by the AE system.

Fig. 2. Amplitude of AE signals (dB) versus Time (s) before, during and after tap changing operation.


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IV. SIGNAL ANALYSIS AE signal samples captured have been analyzed using

Discrete Wavelet Transform (DWT) to find out the energy distribution of the signal over different frequency ranges.

A. Discrete Wavelet Transform Multi-resolution decomposition methods have been

extensively used in many of the signal processing applications [5].

Wavelet transform is a linear decomposition method use a set of signals derived from mother wavelet. Wavelets constitute a family of functions, derived from one single function, and indexed by two labels, one for position and one for frequency [6]. More explicitly

Ψ (a, b) (k) = |a|-1/2 Ψ [(k-b)/a] (1)

where a is dilation parameter which governs the frequency, b gives the position of wavelet and Ψ is the wavelet function.

Discrete wavelet transform (DWT) is continuous dilation and translation replaced by discrete parameters a=ao

m and b=n bo ao

m . Where ao> 1 and bo>1 are fixed constants, m and n Є Z .The DWT can be expressed as

DWT [m, n] = [| aom |-1/2] ∑ X[k] Ψ [(k- n bo ao

m)/ aom] (2)

where X[k] is the discrete signal.

The DWT algorithm decomposes the signal X[k] into detail d[k] (high frequency) and approximation h[k] (low frequency) coefficients:

h[k] = ∑ x[k]G[2n-k] (3)

d[k] = ∑ x[k]Z[2n-k] (4)

where G and Z are respectively low-pass and high-pass filters. At each level of wavelet decomposition the signal is down sampled by a factor of two.

Fig. 3. Wavelet Decomposition of signal X[k] into approximation (hm[k]) and detail (dm[k]) coefficients.

TABLE I. FREQUENCY RANGES FOR DIFFERENT DECOMPOSITION LEVELS

Decomposition Level

Frequency Range(kHz)

D1 250-500 D2 125-250 D3 62.5-125 D4 31.25-62.5 D5 15.62-31.25 D6 7.81-15.62 D7 3.90-7.81 A7 0-3.90

The signals are decomposed to seventh level using ‘symlet8’ as the mother wavelet [7]. The signals within the frequency range of 0 – 500 kHz are considered for the analysis. The range of frequencies over different decomposition levels are shown in Table I. The distribution of energy over different frequency ranges has been calculated.

V. CASE STUDIES The data presented in the paper are from the OLTCs of 230

kV power transformers in operation at two different substations. Rating of the power transformers considered for the study are (a) 230 kV/6.6 kV, 22.5 MVA 3 phase power transformer and (b) 230 kV/3.3 kV, 20 MVA 3 phase power transformer. For capturing AE signals, the AE sensor was mounted on the OLTC compartment and AE signals were captured during the tap changing operations. AE signals were analyzed using DWT as explained in section IV. Details of analysis for the two case studies are outlined below.

Case study-1: 230 kV/6.6 kV, 22.5 MVA 3 phase power transformer with integrated OLTC.

OLTC was with 5 tap positions and was integrated inside the transformer. Amplitude of AE signals captured as a function of time during tap changing operation from Tap 1 to Tap 2 with load of about 25 A and power factor of 0.95 on HV side (230kV) of the transformer is shown in Fig. 2. Time zoomed figure of Fig. 2 depicting the details of AE signals from start to completion of tap changing operation is shown in Fig. 4.

Fig. 4. Amplitude of AE signals (dB) versus Time (s) during tap changing operation.

No AE signals were recorded before and after the tap changing operation. As can be seen from Fig. 4, based on the magnitude of signals, tap changing event has happened between 17.5 s to 23.5 s (with 0 s as reference for the start of data acquiisition). AE signals received during tap changing operation can be classified as (a) AE signals of lower amplitude and (b) AE burst activity with very high amplitude.

Detailed analysis by DWT has been performed separately on low amplitude and high amplitude AE signals captured during tap changing operation. The approximate and detail coefficient of these AE signals are shown in Fig. 5a and Fig. 5b.

The energy distribution of the captured AE signals over different frequency ranges has been obtained using DWT as


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depicted in Fig. 6a and Fig. 6b. Energy (V2/kHz) of decomposition levels are shown in Table II and Table III for low amplitude and high amplitude signals, respectively. Out of eight decomposition levels, energy distribution has been observed at 4 levels, namely, A7, D4, D3 and D2. Decomposition level D3 consists of the highest energy of about 0.01 V2/kHz (Table II) for low amplitude signals and about 0.98 V2/kHz (Table III) for high amplitude signals in the frequency range of 62.5 kHz to 125 kHz A few higher frequency signals were found in the frequency range of 125 kHz to 250 kHz which fall in D2 range, but with lower energy as compared to D3 range. Next lower energy was found in D4. Decomposition level A7 consists of very low frequency signals in the range of 0-3.90 kHz having energy ≈ 0.0002 V2/kHz (Table II) for low amplitude signals and ≈ 0.002 V2/kHz (Table III) for high amplitude signals.

(a)

(b)

Fig. 5. Approximate and Detail coefficient decomposition(A7, D1 to D7) of AE signal voltage(V) versus time(µs) during on-load tap changing operation of 230 kV/6.6 kV, 3 Phase power transformer: a) Low amplitude signals and b) High amplitude signals

(a)

(b)

Fig. 6. Energy distribution of AE signal over different frequency ranges during on-load tap changing operation of 230 kV/6.6 kV, 3 Phase power transformer: a) Low amplitude signals and b) High amplitude signals

TABLE II. ENERGY IN DIFFERENT DECOMPOSITION LEVELS SHOWN IN FIG.6A

Decomposition Level Energy(V2/kHz)

D1 0.000051 D2 0.002809 D3 0.010028 D4 0.000321 D5 0.000020 D6 0.000007 D7 0.000002 A7 0.000224

The above DWT analysis for energy versus frequency has indicated that AE signals of high amplitude have nearly 2 orders more energy than that from low amplitude AE signals. Decomposition of signals by DWT has identified the frequency range of AE signals with reference to energy. Signals of low and high amplitude were found to have maximum energy in the D3 level having frequency range as 62.5 kHz to 125 kHz.

As can be seen from Fig. 4, time taken by the OLTC to change the tap position from Tap 1 to Tap 2 is about 6 s and


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the high amplitude signals were observed for less than 0.01 s. During 24th s, (with 0 s as reference for the start of data acquisition). the tap changing operation has got completed and no further AE signals were recorded indicating establishment of firm contact after tap changing operation .

TABLE III. ENERGY IN DIFFERENT DECOMPOSITION LEVELS SHOWN IN FIG.6B


D1 0.000956

D2 0.271100

D3 0.979000

D4 0.006834

D5 0.000513

D6 0.000258

D7 0.000072

A7 0.002458

Case study-2: 230 kV/3.3 kV, 20 MVA 3 phase power transformer with externally fitted OLTC.

OLTC was with 25 tap positions and was fixed externally to the transformer. Amplitude of AE signals captured as a function of time during tap changing operation from Tap 22 to Tap 23 and back to 22 with load of about 20 A and power factor of 0.95 on HV side (230kV) of the transformer load is shown in Fig. 7. There were no AE signals (threshold of 30 dB is chosen) before and after tap changing operation.

Fig. 7. Amplitude of AE signals (dB) versus Time (s) before, during and after tap changing operation.

Tap change from Position 22 to 23 Time zoomed figure of Fig. 7 depicting the details of AE

signals from start to completion of tap changing operation is shown in Fig. 8.

Fig. 8. Amplitude(dB) versus Time(s) during tap changing operation from Tap 22 to Tap 23.

As can be seen from Fig. 8, the tap changing event has been recorded between 51.5 s to 57.5 s. (with 0 s as reference for the start of data acquiisition). Low amplitude signals in the range of 30 dB to 35 dB were recorded. At 57ths a sudden burst of AE signals of very high amplitude above 90dB were obsereved.

The approximate and detail coefficient of the AE signals for these two types of AE signals are shown in Fig. 9a and Fig. 9b. Energy distribution over different frequency ranges for low amplitude and high amplitude AE signals are depicted in Fig. 10a & Fig. 10b.

Energy (V2/kHz) of AE signals over different frequency ranges for low amplitude and high amplitude signals are shown in Table IV & Table V respectively. Out of eight decomposition levels, energy distribution has been observed at A7, D3, D4 and D2

(a)


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(b) Fig. 9. Approximate and Detail coefficient decomposition(A7, D1 to D7) of AE signal voltage(V) versus time(µs) during on-load tap changing operation of 230 kV/3.3 kV, 3 Phase power transformer: a) Low amplitude signals and b) High amplitude signals

(a)

(b)

Fig. 10. Energy distribution of AE signal over different frequency ranges during on-load tap changing operation of 230 kV/3.3 kV, 3 Phase power transformer: a) Low amplitude signals and b) High amplitude signals

TABLE IV. ENERGY IN DIFFERENT DECOMPOSITION LEVELS SHOWN IN FIG.10A


D1 0.000012 D2 0.000568 D3 0.002346 D4 0.000016 D5 0.000003 D6 0.000006 D7 0.000001 A7 0.000049

TABLE V. ENERGY IN DIFFERENT DECOMPOSITION LEVELS SHOWN IN FIG.10B


D1 0.001164 D2 0.057264 D3 0.199610 D4 0.002887 D5 0.000378 D6 0.000214 D7 0.000226 A7 0.019398

Analysis of energy indicate high amplitude AE signals

have nearly 2 orders more energy than that of low amplitude during tap changing operation which is same as in case study-1. Also, decomposition level D3 consists of the highest energy in the frequency range of 62.5 kHz to 125 kHz. A few higher amplitude signals in the frequency range of 125 kHz to 250 kHz which fall in D2 range, but for low energy compared to D3 range were found to co-exist.

The above DWT analysis for energy versus frequency indicates the occurrence of high amplitude and low amplitude signals which were found to be identical in both the case studies. In order to observe the condition of tap changing operation of OLTC and to restore the tap changer position back to tap number 22, another intentional tap changing operation was performed from tap position 23 to tap position 22 (Fig. 7) with same voltage, current and power factor as during tap changing operation from Tap 22 to 23. Similar observation as explained in case study-2 has been observed during this tap changing operation.

The total time taken for tap changing in both the case studies has been observed to be around 6s. At the time of closing of contacts a sudden burst high amplitude AE signals (above 90dB) has been observed for 0.01 s, in both the cases.

The OLTCs considered under case study-1 and case study-2 have shown similar behavior in terms of acoustic signals with reference to amplitude, energy and frequency. AE signal data acquired from two OLTCs of 230 kV power transformers and frequency-energy analysis based on DWT can be used as reference for healthy OLTCs operating at similar voltage, current and power factor.


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SUMMARY

Acoustic emission signals acquired during operation of OLTCs from two different transformers of rating 230 kV/6.6 kV, 22.5 MVA 3 phase and 230 kV/3.3 kV, 20 MVA 3 phase at site have been studied. The duration for OLTC operation, amplitude, energy and frequency of AE signals acquired during the tap changing operation have been analyzed. The analysis carried using DWT indicated that the energy of AE signals was maximum in frequency range of 62.5 kHz to 125 kHz corresponding to decomposition level D3. The tap changing operation has observed to be completed within 6 s in both the cases considered for the study. Data presented in the paper could be considered as reference for healthy and normal operating OLTC used in 230 kV power transformers.

ACKNOWLEDGMENT

The authors acknowledge CPRI Bangalore India and NITK Surathkal India for support and cooperation in carrying out this research work. Authors acknowledge the research assistance by D. Vikram, SRF and Viji Venugopal, SRF.

REFERENCES [1] P.Kang and D.Birthwhistle ,”Condition monitoring of power transformer

on-load-tap-changers.part 1:Automatic condition diagnostics,”Generation,Transmission and Distribution,IEE proceedings,vol.148,no.4,pp.301-306,2001.

[2] P.Kang and D.Birthwhistle ,”Condition monitoring of power transformer on-load-tap-changers.part 2: Detection and ageing from vibration signatures,”Generation,Transmission and Distribution,IEE proceedings,vol.148,no.4,pp.307-311,2001.

[3] Edurado F.Simas Filho and Luiz A.L.de Almeida,”Self –Organized Classification of On-load Tap Changers Acoustic Signatures”IEEE International Instrumentation and Measurement Technology Conference Victoria,Canada,May 12-15,2008.

[4] Manual of 16 channel acoustic emission workstation,M/s Physical Acoustic Corporation(PAC),NJ,USA.

[5] S.G.Mallat,”A theory for multiresolution signal decomposition:The wavelet representation,”IEEE Transactions on Pattern Analysis and Machine Intelligence,vol .2,pp.674-693,July 1989.

[6] I.Daubechies, “The wavelet transform,time frequency localization and signal analysis”, IEEE Transactions on Information Theory., vol.36,pp.961-1005,September 1990.

[7] T.Boczar, D.Zmarzly, “ Application of wavelet analysis to acoustic emission pulses generated by partial discharges”, IEEE Trans. On DEI, vol.11,no.3,pp433-449,June 2004.

acoustic emission signal analysis of on-load tap changer

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