Two-stage processing system for the detection and on-site localization of acoustic emissions

In this paper a system of two-stage processing for the detection of acoustic emissions and the localization of the sources is presented. The first stage is programmed in LabVIEW and is dedicated to the detection. A second stage is programmed in Matlab and is devoted to the localization. They are connected by a packet-transfer protocol, which also provides of communication for a remote operation. This system combines the advantages of LabVIEW for the multichannel acquisition and denoising of signals and the advantages of Matlab for the data processing. Additionally, several methods of solving the localization equations system have been described and tested. Different solution strategies are compared. The figure of merit is the precision over the runtime. The indirect non-interactive method and the particle-swarm-optimization method provide the best results under conditions of noisy detection.

[1]  Orlando Frazão,et al.  Acoustic source location of partial discharges in transformers , 2010, European Workshop on Optical Fibre Sensors.

[2]  Julio E. Posada-Roman,et al.  Instrumentation System for Location of Partial Discharges Using Acoustic Detection With Piezoelectric Transducers and Optical Fiber Sensors , 2014, IEEE Transactions on Instrumentation and Measurement.

[3]  Julio E. Posada-Roman,et al.  Fiber Optic Sensor for Acoustic Detection of Partial Discharges in Oil-Paper Insulated Electrical Systems , 2012, Sensors.

[4]  Min Deng,et al.  Study of Partial Discharge Localization Using Ultrasonics in Power Transformer Based on Particle Swarm Optimization , 2008, IEEE Transactions on Dielectrics and Electrical Insulation.

[5]  Julio E. Posada-Roman,et al.  Multichannel acquisition system and denoising for the detection and location of partial discharges using acoustic emissions , 2013, 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[6]  Yilu Liu,et al.  Position location of partial discharges in power transformers using fiber acoustic sensor arrays , 2006 .

[7]  J. Ramírez-Niño,et al.  Acoustic measuring of partial discharge in power transformers , 2009 .

[8]  Ye Haifeng,et al.  Acoustic-electrical based detection system for partial discharge localization of GIS , 2012, 2012 Power Engineering and Automation Conference.

[9]  Gyula Simon,et al.  Fast Adaptive Acoustic Localization for Sensor Networks , 2011, IEEE Transactions on Instrumentation and Measurement.

[10]  Prasanta Kundu,et al.  A non-iterative partial discharge source location method for transformers employing acoustic emission techniques , 2009 .

[11]  Julio E. Posada-Roman,et al.  Multichannel ultrasound instrumentation for on-line monitoring of power transformers with internal fiber optic sensors , 2013, 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[12]  Y. Lu,et al.  PD detection and localisation by acoustic measurements in an oil-filled transformer , 2000 .

[13]  J. Rubio-Serrano,et al.  Instrumentation system and digital signal processing for studying the characteristics of the acoustic and electrical signals generated by partial discharges , 2012, 2012 IEEE International Conference on Industrial Technology.

[14]  E. Gockenbach,et al.  A novel method for ultra-high-frequency partial discharge localization in power transformers using the particle swarm optimization algorithm , 2013, IEEE Electrical Insulation Magazine.

[15]  S. Tenbohlen,et al.  Detection and location of partial discharges in power transformers using acoustic and electromagnetic signals , 2008, IEEE Transactions on Dielectrics and Electrical Insulation.

[16]  L.E. Lundgaard,et al.  Partial discharge. XIV. Acoustic partial discharge detection-practical application , 1992, IEEE Electrical Insulation Magazine.