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    A Study of Improved Indoor Localization Accuracy using Looping Min-Max Technique
    (2024-01-01)
    Tiengthong, Thanadol
    ;
    Mankong, Thanadon
    ;
    Suwansukho, Nattapan
    ;
    Southisombath, Phouthong
    ;
    Chaisang, Aditep
    This paper investigates the efficacy of WLAN technology at 5.8 GHz for indoor localization, a widely adopted and versatile approach due to its adaptability and ease of implementation. The choice of 5.8 GHz frequency offers several advantages, including reduced interference and higher data transmission rates, enhancing the precision and reliability of localization systems. Utilizing Received Signal Strength (RSS) for distance calculation is employed due to its computational simplicity and efficiency. The proposed methodology employs a modified Min-Max technique for estimating positions, iterating the Min-Max process until the distance error aligns with a predefined threshold. Comparative evaluation using Cumulative Distribution Function (CDF) demonstrates improved accuracy compared to conventional Min-Max methods. The research findings indicate promising enhancements in accuracy and efficacy for indoor localization using WLAN technology at 5.8 GHz. These advancements hold significant potential for real-time indoor localization applications, paving the way for improved indoor navigation and tracking systems in the future.
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    Dielectric Response Analysis Characteristic of Service-Aged XLPE Cables
    (2024-01-01)
    Thongkong, Patchara
    ;
    Promphanich, Wiboon
    ;
    Udomluksananon, Patt
    ;
    Jeenmuang, Siwakorn
    ;
    Wiangtong, Theerayod
    The main insulation used in plastic underground cables is cross-linked polyethylene (XLPE). The XLPE underground cable which has been utilized in service for a long time, has experienced various stresses, or so-called TEAM stresses. Consequently, the XLPE insulation will be degraded over time and lead to insulation properties degradation. This paper represents the dielectric response analysis technique for characterizing the insulation condition of the service-aged XLPE medium voltage underground cable. The dielectric response analysis was performed on the 22 kV XLPE underground cables that have been in service for more than 10 years and were directly buried. The dielectric response analysis measurement consists of a combination of polarization and depolarization current (PDC) measurement in the time-domain and frequency-domain spectroscopy (FDS) measurement. After that, test results were analyzed to evaluate the insulation condition and compare it to the new 22 kV underground cable. The analyzed dielectric response analysis test results will be reported in this paper.
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    Partial Discharge Classification with Transformer Neural Networks
    (2024-01-01)
    Cheypoca, Thepjit
    ;
    Promphanich, Wiboon
    ;
    Thway, Aung Ye
    ;
    Hankae, Angelina Phimpissada
    ;
    Jeenmuang, Siwakorn
    This paper introduces an approach with the Transformer Neural Networks model for partial discharge patterns classification, that consists of corona discharge, internal discharge and surface discharge. The PD measuring circuit suggested in IEC 60270:2000 is used to record Partial discharge signals. Independent parameters such as phase and charge of PD patterns were recorded. The phase value will be encoded into the charge array and Transformer Neural Network is constructed using Positional Embedding and Transformer Encoder Layer. 80% of the recorded data will be used as a training data and 20% recorded data was used for testing of the classification models. Impacts of neuron numbers and network architecture on the PD classification performance will be observed
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    Comparison of Dissolved Gas Analysis (DGA) Between Mineral Oil, Neutural Ester, and Palm Oil With Nano-Particle BaTiO3
    (2024-01-01)
    Laohapongpan, Triani
    ;
    Promphanich, Wiboon
    ;
    Boonlaksananusorn, Chanin
    ;
    Jeenmuang, Siwakorn
    ;
    Pattanadech, Norasage
    The dielectric liquid properties can be improved by adding suitable nano-particles to increase the dielectric and other properties. The BaTiO<inf>3</inf> has been interesting for a decade for use to improve the liquid insulation characteristics. Such nanoparticles were used to mixed with mineral oil, natural ester, and palm oil. This paper focuses on a comparison of mineral oil, natural ester, and palm oil with BaTiO<inf>3</inf> by the Dissolved Gas Analysis (DGA) technique. Hydrogen (H2), Methane (CH4), Acetylene (C2H2), Ethylene (C2H4), Ethane (C2H6), Carbon Monoxide (CO), Carbon dioxide (CO<inf>2</inf>) were mainly considered gases to compare because they are in the gas limitation used to diagnose a transformer problem. This researcher found that palm oil produces the most gas after undergoing thermal stress but its generating trend was better than others because the gas-producing rate decreases at higher temperatures.
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    Partial Discharge Classification With 1D Convolutional Neural Network
    (2024-01-01)
    Cheypoca, Thepjit
    ;
    Promphanich, Wiboon
    ;
    Thway, Aung Ye
    ;
    Hankae, Angelina Phimpissada
    ;
    Jeenmuang, Siwakorn
    This paper introduces a novel approach for classifying with the 1D Convolutional Neural Network model for partial discharge patterns, that consists of corona discharge, surface discharge and internal discharge. The PD measuring circuit suggested in IEC 60270:2000 is used to record Partial discharge signals. Independent parameters such as phase and charge of PD patterns were recorded. The Artificial Neural Network for the classification model was constructed. Moreover, 2×1D CNN feature extraction was utilized to reduce the curse of dimensionality in the dense layer of the proposed PD classification model. 80% of the recorded data will be used as a training data and 20% recorded data was used for testing of the classification models. Impacts of neuron numbers and network architecture on the PD classification performance will be observed.