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

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Acoustic Monitoring Instrumentation System

#### 2.2. Fiber-Optic Sensing Probe and Multichannel Fiber-Optic System

## 3. Location Based on Acoustic Emission

#### 3.1. Location by Time Diference of Arrival with OF and PZT Sensors

_{k}from the AES to the PZT

_{k}sensor. In this case, the reference is the OF sensor (Figure 1).

_{0i}) are obtained from five sensors and the reference is from the sensor closest to the AES (T). Figure 6 illustrates these time differences of the acoustic signals with an unknown timing reference.

_{s}is the speed of sound in the medium, x

_{OF}, y

_{OF}, z

_{OF}are the coordinates of the reference sensor and x

_{PZTk}, y

_{PZTk}, z

_{PZTk}are the coordinates of the kth PZT sensor. The minimum number of sensors is 5 (N ≥ 5). The position is determined by obtaining x, y, z, T.

#### 3.2. Location by Time of Arrival with OF Internal Sensors

## 4. Results

#### 4.1. Hybrid Processing System

#### 4.2. Analysis of the Error Propagation to the Location of the AES

_{R}, y

_{R}, z

_{R}) are the coordinates of the real position of the AES and (x

_{M}, y

_{M}, z

_{M}) are the mean value of the solutions.

_{x}, σ

_{y}and σ

_{z}are the STD of each axis.

_{Tank}is the diagonal:

#### 4.3. Evaluation of the Location Error with OF Internal Sensors

## 5. Discussion

## 6. Conclusions

## Author Contributions

## Funding

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

- IEEE. IEEE Guide for the Detection and Location of Acoustic Emissions from Partial Discharges in Oil-immersed Power transformers and Reactors. IEEE Stand.
**2007**, 127, C57. [Google Scholar] - Wang, M.; Vandermaar, A.J.; Srivastava, K.D. Review of condition assessment of power transformers in service. IEEE Electr. Insul. Mag.
**2002**, 18, 12–25. [Google Scholar] [CrossRef] - ASTM. Standard Guide for Application of Acoustic Emission for Structural Health Monitoring. In Active Standard ASTM E2983–14; American Society for Testing and Materials (ASTM): West Conshohocken, PA, USA, 2019. [Google Scholar]
- Wang, Q.; Hong, M.; Su, Z. An In-Situ Structural Health Diagnosis Technique and Its Realization via a Modularized System. IEEE Trans. Instrum. Meas.
**2015**, 64, 873–887. [Google Scholar] [CrossRef] - AMSY-6 of Vallen Systeme. Available online: http://www.vallen.de/products/multi-channel-systems (accessed on 20 August 2021).
- LAN-XI of Brüel & Kjær. Available online: http://www.bksv.com/Products/frontends/lanxi (accessed on 20 August 2021).
- PXI of National Instruments. Available online: http://www.ni.com/pxi/esa/ (accessed on 20 August 2021).
- Yongfen, L.; Xiaohu, X.; Fei, D.; Xiao, T.; Yanming, L. Comparison of DOA Algorithms Applied to Ultrasonic Arrays for PD Location in Oil. IEEE Sens. J.
**2015**, 15, 2316–2323. [Google Scholar] [CrossRef] - Song, L.; Cooper, K.L.; Wang, Z.; Wang, A.; Liu, Y. Position location of partial discharges in power transformers using fiber acoustic sensor arrays. Opt. Eng.
**2006**, 45, 114401. [Google Scholar] [CrossRef] - Posada-Roman, J.E.; Garcia-Souto, J.A.; Rubio-Serrano, J. Multichannel optical-fibre heterodyne interferometer for ultrasound detection of partial discharges in power transformers. Meas. Sci. Technol.
**2013**, 24, 094015. [Google Scholar] [CrossRef] - Kundu, P.; Kishore, N.K.; Sinha, A.K. Identification of two simultaneous partial discharge sources in an oil-pressboard insulation system using acoustic emission techniques. Appl. Acoust.
**2012**, 73, 395–401. [Google Scholar] [CrossRef] - Boya, C.; Ruiz-Llata, M.; Posada-Roman, J.E.; Garcia-Souto, J.A. Identification of multiple partial discharge sources using acoustic emission technique and blind source separation. IEEE Trans. Dielectr. Electr. Insul.
**2015**, 22, 1663–1673. [Google Scholar] [CrossRef] - Bua-Nuñez, I.; Posada-Roman, J.E.; Rubio-Serrano, J.; Garcia-Souto, J.A. Instrumentation System for the Location of Partial Discharges using Acoustic Detection with Piezoelectric Transducers and Optical Fiber Sensors. IEEE Trans. Instrum. Meas.
**2014**, 63, 1002–1013. [Google Scholar] [CrossRef][Green Version] - Prasanta Kundu, N.; Kishore, K.; Sinha, A.K. A non-iterative partial discharge source location method for transformers employing acoustic emission techniques. Appl. Acoust.
**2009**, 70, 1378–1383. [Google Scholar] [CrossRef] - Lima, S.E.U.; Frazao, O.; Farias, R.G.; Araujo, F.M.; Ferreira, L.A.; Miranda, V.; Santos, J.L. Acoustic Source Location of Partial Discharges in Transformers. In Proceedings of the Fourth European Workshop on Optical Fibre Sensors. International Society for Optics and Photonics, Porto, Portugal, 8–10 September 2010; p. 76532N. [Google Scholar]
- Tang, L.; Luo, R.; Deng, M.; Su, J. Study of Partial Discharge Localization using Ultrasonics in Power Transformer based on Particle Swarm Optimization. IEEE Trans. Dielectr. Electr. Insul.
**2008**, 15, 492–495. [Google Scholar] - Mirzaei, H.R.; Akbari, A.; Gockenbach, E.; Zanjani, M.; Miralikhani, K. A novel method for ultra-high-frequency partial discharge localization in power transformers using the particle swarm optimization algorithm. IEEE Electr. Insul. Mag.
**2013**, 29, 26–39. [Google Scholar] [CrossRef] - Posada-Roman, J.E.; Garcia-Souto, J.A.; Serrano, J.R.; Nunez, I.B. Multichannel ultrasound instrumentation for on-line monitoring of power transformers with internal fiber optic sensors. In Proceedings of the 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Minneapolis, MN, USA, 6–9 May 2013; pp. 200–205. [Google Scholar]
- Peiqing, M.; Xiuwei, L.; Yue, H.; Gehao, S.; Haifeng, Y.; Xiuchen, J. Acoustic-electrical based detection system for partial discharge localization of GIS. In Proceedings of the 2012 Power Engineering and Automation Conference, Wuhan, China, 18–20 September 2012. [Google Scholar]
- Rubio-Serrano, J.; Garcia-Souto, J.A.; Posada-Roman, J.E. Instrumentation system and digital signal processing for studying the characteristics of the acoustic and electrical signals generated by partial discharges. In Proceedings of the 2012 IEEE International Conference on Industrial Technology, Athens, Greece, 19–21 March 2012; pp. 573–578. [Google Scholar]
- Markalous, S.M.; Tenbohlen, S.; Feser, K. Detection and location of partial discharges in power transformers using acoustic and electromagnetic signals. IEEE Trans. Dielectr. Electr. Insul.
**2008**, 15, 1576–1583. [Google Scholar] [CrossRef] - Vakulya, G.; Simon, G. Fast Adaptive Acoustic Localization for Sensor Networks. IEEE Trans. Instrum. Meas.
**2011**, 60, 1820–1829. [Google Scholar] [CrossRef] - Ramírez-Niño, J.; Pascacio, A. Acoustic measuring of partial discharge in power transformers. Meas. Sci. Technol.
**2009**, 20, 115108. [Google Scholar] [CrossRef] - Bua-Nuñez, I.; Posada-Roman, J.E.; Garcia-Souto, J.A. Two-Stage Processing System for the Detection and On-Site Localization of Acoustic Emissions. In Proceedings of the 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, Pisa, Italy, 11–14 May 2015; pp. 1921–1926. [Google Scholar]
- Posada-Roman, J.; Garcia-Souto, J.A.; Rubio-Serrano, J. Fiber Optic Sensor for Acoustic Detection of Partial Discharges in Oil-Paper Insulated Electrical Systems. Sensors
**2012**, 12, 4793–4802. [Google Scholar] [CrossRef][Green Version] - Wang, Y.B.; Chang, D.G.; Fan, Y.H.; Zhang, G.J.; Zhan, J.Y.; Shao, X.J.; He, W.L. Acoustic localization of partial discharge sources in power transformers using a particle-swarm-optimization-route-searching algorithm. IEEE Trans. Dielectr. Electr. Insul.
**2017**, 24, 3647–3656. [Google Scholar] [CrossRef] - Wu, M.; Cao, H.; Cao, J.; Nguyen, H.-L.; Gomes, J.B.; Krishnaswamy, S.P. An overview of state-of-the-art partial discharge analysis techniques for condition monitoring. IEEE Electr. Insul. Mag.
**2015**, 31, 22–35. [Google Scholar] [CrossRef] - IEEE. Draft Guide for the Detection and Location of Acoustic Emissions from Partial Discharges in Oil Immersed Power Transformers and reactors. In IEEE PC57.127 Standards Draft; IEEE: Piscatway, NJ, USA, 2003. [Google Scholar]
- Roslan, M.H.; Azis, N.; Kadir, M.Z.A.A.; Jasni, J.; Ibrahim, Z.; Ahmad, A. A Simplified Top-Oil Temperature Model for Transformers Based on the Pathway of Energy Transfer Concept and the Thermal-Electrical Analogy. Energies
**2017**, 10, 1843. [Google Scholar] [CrossRef][Green Version] - N’Cho, J.S.; Fofana, I. Review of Fiber Optic Diagnostic Techniques for Power Transformers. Energies
**2020**, 13, 1789. [Google Scholar] [CrossRef][Green Version] - Kunicki, M.; Cichon, A. Application of a Phase Resolved Partial Discharge Pattern Analysis for Acoustic Emission Method in High Voltage Insulation Systems Diagnostics. Arch. Acoust.
**2018**, 43, 235–243. [Google Scholar] - Ilkhechi, H.D.; Samimi, M.H.; Yousefvand, R. Generation of acoustic phase-resolved partial discharge patterns by utilizing UHF signals. Int. J. Electr. Power Energy Syst.
**2019**, 113, 906–915. [Google Scholar] [CrossRef] - Rubio-Serrano, J.; Rojas-Moreno, M.V.; Posada, J.; Martínez-Tarifa, J.M.; Robles, G.; Garcia-Souto, J.A. Electro-acoustic detection, identification and location of partial discharge sources in oil-paper insulation systems. IEEE Trans. Dielectr. Electr. Insul.
**2012**, 19, 1569–1578. [Google Scholar] [CrossRef] - Ardila-Rey, J.A.; Montaña, J.; De Castro, B.A.; Schürch, R.; Ulson, J.A.C.; Muhammad-Sukki, F.; Bani, N.A. A Comparison of Inductive Sensors in the Characterization of Partial Discharges and Electrical Noise Using the Chromatic Technique. Sensors
**2018**, 18, 1021. [Google Scholar] [CrossRef][Green Version]

**Figure 8.**Typical AE signal detected by the system using three sensors and the TOA related each of them.

**Figure 12.**Sweep of the AES position within the tank, scanning XY (top view) in (

**a**) and scanning XZ (front view) in (

**b**).

**Figure 16.**Analysis of errors in the calculated standard deviations of the location for each axis: actual position, detected position (mean) and errors (std. deviation), as well as detected position reducing the dispersion error (mode); (

**a**) in the Y axis, and (

**b**) in the Z axis.

Type of Method | Method | Equations | N° of Sensors Used | References |
---|---|---|---|---|

Direct | “Solve” (Matlab) | - | 5 | - |

Least Squares (LS) | $X={\left({A}^{T}A\right)}^{-1}{A}^{T}B$ | 5 | - | |

Least Norm (LN) | $X={A}^{T}{\left(A{A}^{T}\right)}^{-1}B$ | 5 | - | |

Cramer | $A=\left[{A}_{x}{A}_{y}{A}_{z}{A}_{T}\right],\left|A\right|\ne 0$ $x=\frac{\left|B{A}_{y}{A}_{z}{A}_{T}\right|}{\left|A\right|},y=\frac{\left|{A}_{x}B{A}_{z}{A}_{T}\right|}{\left|A\right|},$ $z=\frac{\left|{A}_{x}{A}_{y}B{A}_{T}\right|}{\left|A\right|},T=\frac{\left|{A}_{x}{A}_{y}{A}_{z}B\right|}{\left|A\right|}$ | 5 | - | |

Indirect | Non-Iterative (INI) | - | 4 | [14] |

Particle Swarm Optimization (PSO) | Fitness function: $f\left(p\right)={\displaystyle \sum _{j=1}^{n}}{\displaystyle \sum _{i=1}^{m}}\left|\left[{\left(p{x}_{j}-{x}_{i}\right)}^{2}+{\left(p{y}_{j}-{y}_{i}\right)}^{2}+{\left(p{z}_{j}-{z}_{i}\right)}^{2}-{v}_{s}^{2}{\left(p{T}_{j}-{\tau}_{i}\right)}^{2}\right]\right|$ Refinement equations: ${v}_{j}\left(t+1\right)={w}_{k}\xb7{v}_{j}\left(t\right)+{c}_{1}{R}_{1}\left[{p}_{j}^{best}\left(t\right)-{p}_{j}\left(t\right)\right]+{c}_{2}{R}_{2}\left[{g}^{best}\left(t\right)-{p}_{j}\left(t\right)\right]$ ${p}_{j}\left(t+1\right)={p}_{j}\left(t\right)+\mathsf{{\rm Y}}\xb7{v}_{j}\left(t+1\right)$ Inertia weight: ${w}_{k}={w}_{max}-\frac{{w}_{max}-{w}_{min}}{N}k$ Constriction coefficient: $\mathsf{{\rm Y}}=\frac{2}{\left|2-\gamma -\sqrt{{\gamma}^{2}-4\gamma}\right|},\gamma ={c}_{1}+{c}_{2}and\gamma 4$ | 5 | [15,16,17] |

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Búa-Núñez, I.; Posada-Román, J.E.; García-Souto, J.A.
Multichannel Detection of Acoustic Emissions and Localization of the Source with External and Internal Sensors for Partial Discharge Monitoring of Power Transformers. *Energies* **2021**, *14*, 7873.
https://doi.org/10.3390/en14237873

**AMA Style**

Búa-Núñez I, Posada-Román JE, García-Souto JA.
Multichannel Detection of Acoustic Emissions and Localization of the Source with External and Internal Sensors for Partial Discharge Monitoring of Power Transformers. *Energies*. 2021; 14(23):7873.
https://doi.org/10.3390/en14237873

**Chicago/Turabian Style**

Búa-Núñez, Iago, Julio E. Posada-Román, and José A. García-Souto.
2021. "Multichannel Detection of Acoustic Emissions and Localization of the Source with External and Internal Sensors for Partial Discharge Monitoring of Power Transformers" *Energies* 14, no. 23: 7873.
https://doi.org/10.3390/en14237873