Design of Condition Based Monitoring on Traction Transformers Using the Fuzzy Mamdani Method

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.

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Publication Details

Journal
Journal Sensi
Published
2024-08-31
DOI
https://doi.org/10.33050/sensi.v10i2.3472
Primary Topic
IoT-based Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Design of Condition Based Monitoring on Traction Transformers Using the Fuzzy Mamdani Method

Freddy Artadima Silaban, Fegi Arga Reimondika
Journal Sensi
IoT-based Control Systems
article

Design of Condition Based Monitoring on Traction Transformers Using the Fuzzy Mamdani Method

Freddy Artadima Silaban, Fegi Arga Reimondika
article en

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.

Journal SensiVol. 10(2)
Mercu Buana University (ID)
Openalex Percentile: Top 71%
IoT-based Control Systems
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Design of Condition Based Monitoring on Traction Transformers Using the Fuzzy Mamdani Method — Freddy Artadima Silaban, Fegi Arga Reimondika · Journal Sensi (2024) | TGRS Research Map | TGRS