Assessment of Macro Fiber Composite Sensors for Measurement of Acoustic Partial Discharge Signals in Power Transformers

Abstract

This paper presents a performance assessment of macro fiber composite (MFC) sensors for measuring acoustic emission (AE) signals from partial discharges (PD) in power transformers filled with mineral oil. MFC sensors are low-profile and flexible, allowing them to be attached to uneven surfaces, such as a transformer wall. Two types of MFC sensors were assessed: P1 (d33 effect) and P2 (d31 effect), which are optimized for different deformations in the structure, such as elongation and contraction, respectively. In addition, a conventional AE sensor, R15I-AST model from Physical Acoustics South America, was also used as a reference for comparative analysis. Four metrics were applied to the signals: root mean square, energy criterion, Akaike criterion, power spectral density, and correlation. The experimental results indicate a high similarity between the MFC sensors and the conventional AE sensor, which expands the research field in acoustic PD measurement in power transformers by using low-cost and flexible sensors.

Evaluation of Low Cost Piezoelectric Sensors for the Identification of Partial Discharges Evolution

“…The power spectral density criterion (PSD) is a standard method to extract the characteristics of stochastic signals and describe the energy distribution of a signal in the frequency domain [2]. In this method, a signal ( ) x n is divided into L equal segments of length M. The PSD of a segment, i is given by Equation (2) [3]:…”

“…For this purpose, the piezoelectric sensors have become an economic alternative and presented similar results with regard to the transducers commonly used [3,4]. Thus, the use of these sensors has been growing significantly in this field, aiming to monitor the PD evolution.…”

“…Power transformers are essential equipment in electrical energy systems and their failure can affect the quality of electric power supply or may lead to lack of it, resulting in losses to consumers and electric companies [1][2][3][4]. Therefore, nowadays, both industry and science have sought to develop sensors and low-cost solutions for the correct diagnosis of their operational condition.…”

“…It is characterized by the emission of light, heat, electromagnetic, and acoustic waves. There are a variety of PD detection methods in the specialized literature and they are classified as electrical, optical, chemical, and acoustical detection [1][2][3][4]. A well-known method is the acoustic emission, which employs sensors to capture the acoustic signals generated by PD [5,6].…”

“…In this way, many failures in transformers can be avoided with implementation of monitoring systems, that enable the failure evolution and then plan futures actions, such as preventive maintenance or replacement of existing equipment. Nevertheless, the sensors typically used for this purpose still have high financial costs, which makes them unfeasible for constant monitoring during the life time of a transformer [2][3][4]. Therefore, engineering have shown interest in developing low cost solutions, in order to make the monitoring systems more accessible, and to provide correct and precise diagnoses for failure in this type of equipment.…”