Dry-type insulated transformers stand out for their higher applicability in substations, high-voltage instrumentation systems, and electrical installations. In this machine, the insulation system is constituted of dielectric materials such as epoxy resin and Nomex paper. Some critical issues in the operation of this equipment, such as overload, moisture, or heat, can induce a slow degradation of the physical-chemical properties of the dielectric materials, which can culminate in the total failure of the transformer. However, before the transformer's shutdown, it is common to detect discharge activity in the insulation system. Based on this issue, this work proposes an experimental and comparative analysis between acoustic emission and Hall-effect sensors, aiming at differentiating discharges in epoxy resin and Nomex paper, materials that constitute the insulation of the dry-type insulated transformers. Two signal processing techniques were studied: traditional frequency analysis and discrete wavelet transform. The objective is to develop signal processing techniques to differentiate each type of discharge since different discharges require different maintenance actions. The results obtained indicate that acoustic emission sensors and Hall sensors are promising in differentiating discharge in epoxy resin and Nomex paper. Furthermore, the pattern recognition tools presented by this work, which associated the wavelet levels energies and the energy of the full signals with the average band and the equivalent bandwidth, were effective to perform feature extraction of power transformer condition.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8915067PMC
http://dx.doi.org/10.3390/s22051716DOI Listing

Publication Analysis

Top Keywords

acoustic emission
12
epoxy resin
12
resin nomex
12
nomex paper
12
comparative analysis
8
emission sensors
8
dry-type insulated
8
insulated transformers
8
insulation system
8
dielectric materials
8

Similar Publications

In this paper, we introduce FUSION-ANN, a novel artificial neural network (ANN) designed for acoustic emission (AE) signal classification. FUSION-ANN comprises four distinct ANN branches, each housing an independent multilayer perceptron. We extract denoised features of speech recognition such as linear predictive coding, Mel-frequency cepstral coefficient, and gammatone cepstral coefficient to represent AE signals.

View Article and Find Full Text PDF

Review of advanced sensor system applications in grinding operations.

J Adv Res

January 2025

Department of Mechanics and Strength of Materials, Politehnica University Timisoara, 1 Mihai Viteazu Avenue, 300 222 Timisoara, Romania. Electronic address:

Background: Today, in a wide variety of industries, grinding operations are an extremely important finishing process for obtaining precise dimensions and meeting strict requirements for roughness and shape accuracy. However, the constant wear of abrasive tools during grinding negatively affects the dimensional and surface conditions of the workpiece. Therefore, effective monitoring of the wear process during grinding operations helps to predict tool life, plan maintenance and ensure consistent product quality.

View Article and Find Full Text PDF

There is very limited research in the literature investigating the way acoustic emission signals change when polymer materials are undergoing different fracture modes. This study investigates the capability of acoustic emission to recognize the fracture mode through acoustic emission parameter analysis, and can be considered the first-ever study which examines the impact of different loading conditions, i.e.

View Article and Find Full Text PDF

Excavation of underground engineering structures involving deeply buried water-rich soft rocks is generally carried out using the artificial freezing method. A series of undrained uniaxial and triaxial shear and creep tests were conducted on soft rocks under different confining pressures (0, 0.2, 0.

View Article and Find Full Text PDF

A primer on low-carbon design in architectural acoustics using a case study of residential floorsa).

JASA Express Lett

January 2025

Department of Architectural Engineering, The Pennsylvania State University, 104 Engineering Unit A, University Park, Pennsylvania 16802,

Designers are increasingly tasked to reduce the carbon footprint of buildings. While core disciplines (e.g.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!