Design of Condition Based Monitoring on Traction Transformers Using the Fuzzy Mamdani Method Perancangan Condition Based Monitoring Pada Transformator Traksi Menggunakan Metode Fuzzy Mamdani
Main Article Content
Abstract
Condition Based Monitoring Real-Time, direct supervision of machine condition parameters to detect potential changes, focuses on nitrogen gas pressure and oil temperature of the traction transformer at ASEAN Station, using the Fuzzy Mamdani method. This method notifies the traction transformer's condition and activates fans, providing information to operators. Arduino Uno R3 functions as a receiver and processor of sensor values. These values are processed using Fuzzy Mamdani, sent to ESP8266, and displayed on localhost. Percentage errors for nitrogen gas pressure (3.7%) and temperature (1.55%) result in a total percentage of 5.25%. The Fuzzy Mamdani output is 771.53 with a percentage error of 0.0019%, compared to MATLAB 2023b testing results of 773. Real-time monitoring shows the traction transformer is in good condition, with additional control to maintain its condition and improve reliability.
Article Details
How to Cite
Reimondika, F., & Silaban, F. (2024). Design of Condition Based Monitoring on Traction Transformers Using the Fuzzy Mamdani Method. Journal Sensi: Strategic of Education in Information System, 10(2), 134-146. https://doi.org/https://doi.org/10.33050/sensi.v10i2.3472
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References
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[18] Aprililia Ningrum, Dewi (2020) Perancangan Sistem Exhasut Fan Otomatis Berbasis Sensor Suhu DHT22 Pada Panel Listrik Standing. S1 thesis, Universitas Mercu Buana.
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[3] Ardania, Lutfi (2020), “Perancangan Sistem Kontrol Suhu Pada Ruang Pengujian Ban menggunakan Logika Fuzzy Berbasis Arduino Uno”. S1 thesis, Universitas Mercu Buana.
[4] Febriyanti, Nurliana (2023) “Prototipe jaringan Ethernet Pada Data Logger suhu dan Kelembapan Menggunakan Protokol ModBus TCP/IP di PT. GMF AEROASIA”. S1 thesis, Universitas Mercu Buana
[5] Afriansyah, Nurizal (2022) “Rancang Bangun Monitoring Suhu Minyak Transformator IBT (Inter-Bus Trafo) Dengan Wireless Sensor Network”. S1 thesis, Universitas Mercu Buana.
[6] V. J. Hodge, S. O'Keefe, M. Weeks and A. Moulds, "Wireless Sensor Networks for Condition Monitoring in the Railway Industry: A Survey," in IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 3, pp. 1088-1106, June 2015, doi: 10.1109/TITS.2014.2366512.
[7] Sunardi, A. Yudhana and Furizal, "Tsukamoto Fuzzy Inference System on Internet of Things-Based for Room Temperature and Humidity Control," in IEEE Access, vol. 11, pp. 6209-6227, 2023, doi: 10.1109/ACCESS.2023.3236183.
[8] Altay, Ramazan & Santisteban, Agustín & Olmo, Cristian & Renedo, Carlos & Ortiz, Alfredo & Ortiz, Félix & Delgado, F.. (2020). Use of Alternative Fluids in Very High-Power Transformers: Experimental and Numerical Thermal Studies. IEEE Access. 8. 207054-207062. 10.1109/ACCESS.2020.3037672.
[9] K. Wei, W. Wang, Z. Hu and M. Du, "Condition Monitoring of IGBT Modules Based on Changes of Thermal Characteristics," in IEEE Access, vol. 7, pp. 47525-47534, 2019, doi: 10.1109/ACCESS.2019.2909928.
[10] Gil, E.S., Sivilla, J.E.M., González, A.S. et al. Fuzzy logic applied to the diagnosis of technical conditions of distribution transformers. J. Eng. Appl. Sci. 70, 129 (2023). https://doi.org/10.1186/s44147-023-00301-w
[11] Jiménez-Navarro, M.J., Martínez-Ballesteros, M., Martínez-Álvarez, F. et al. A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting. J Big Data 10, 80 (2023). https://doi.org/10.1186/s40537-023-00745-0
[12] Peter Brncal, Miroslav Gutten, Diagnostics of Insulating Condition of Traction Transformer by Frequency Method, Transportation Research Procedia, Volume 55, 2021, Pages 977-982, ISSN 2352-1465, https://doi.org/10.1016/j.trpro.2021.07.067.
[13] Ivan Ukhov, Andrey Sotskov, Viktor Anisimov, Fyodor Ryabtsev, Aleksandr Marusin, Alexey Marusin, Influence of performance criteria on the selection of electric traction equipment and a temperature control system for a battery-powered vehicle with an electric traction drive, Transportation Research Procedia, Volume 57, 2021, Pages 711-720, ISSN 2352-1465, https://doi.org/10.1016/j.trpro.2021.09.104.
[14] A. Medina-Santiago et al., "Adaptive Model IoT for Monitoring in Data Centers," in IEEE Access, vol. 8, pp. 5622-5634, 2020, doi: 10.1109/ACCESS.2019.2963061.
[15] Zhao, Z., Wu, J., Li, T. et al. Challenges and Opportunities of AI-Enabled Monitoring, Diagnosis & Prognosis: A Review. Chin. J. Mech. Eng. 34, 56 (2021). https://doi.org/10.1186/s10033-021-00570-7
[16] Durgesh, Beri & Reddy, Gurusundar & Reddy, M & Manoz, K & Reddy, Kumar & Ijmtst, Editor. (2022). Design and Implementation of Transformer Health Monitoring using IOT. International Journal for Modern Trends in Science and Technology. 8. 99-104. 10.46501/IJMTST0812016.
[17] Ukiwe, E.K., Adeshina, S.A. & Tsado, J. Techniques of infrared thermography for condition monitoring of electrical power equipment. Journal of Electrical Systems and Inf Technol 10, 49 (2023). https://doi.org/10.1186/s43067-023-00115-z
[18] Aprililia Ningrum, Dewi (2020) Perancangan Sistem Exhasut Fan Otomatis Berbasis Sensor Suhu DHT22 Pada Panel Listrik Standing. S1 thesis, Universitas Mercu Buana.