Rancang Bangun Monitoring Motor Induksi Tiga Fasa  Berbasis IoT (Internet Of Things)

Farah Salsabila Habib; Fakhruddin Mangkusasmito

doi:10.14710/gt.v23i2.90345

DOI: https://doi.org/10.14710/gt.v23i2.90345

Rancang Bangun Monitoring Motor Induksi Tiga Fasa Berbasis IoT (Internet Of Things)

*Farah Salsabila Habib - Universitas Diponegoro, Indonesia

Fakhruddin Mangkusasmito - Universitas Diponegoro, Indonesia

BibTex Citation Data :

@article{GT90345,
    author = {Farah Salsabila Habib and Fakhruddin Mangkusasmito},
    title = {Rancang Bangun Monitoring Motor Induksi Tiga Fasa  Berbasis IoT (Internet Of Things)},
    journal = {Gema Teknologi},
  volume = {23},
    number = {2},
    year = {2025},
    keywords = {Three-phase induction motor, Internet of Things, PZEM-004T, DS18B20, real-time monitoring, unbalanced voltage, unbalanced current, motor load.},
    abstract = {  Three-phase induction motors are widely used as the primary drive in the industrial sector because of their high reliability in supporting production processes. This final-year research project developed an IoT-based monitoring system for three-phase induction motors to monitor voltage, current, power, and temperature in real time via a website, using PZEM-004T (voltage, current, power) and DS18B20 (temperature) sensors. Motor condition analysis was performed using a diagnostic approach based on the National Electrical Manufacturers Association (NEMA) MG-1 14.36 standard, by calculating the percentage of unbalanced voltage, unbalanced current, and motor load percentage. Testing was conducted on two motor conditions: a loaded Direct-on-Line (DOL) motor with specifications of 2,200 watts (3 HP) and an unloaded star-connected motor with specifications of 0.5 HP. Test results for the DOL motor showed a current sensor accuracy of 98.79% (error 1.21%), a voltage sensor accuracy of 99.38% (error 0.63%), and a power sensor accuracy of 98.87% (error 1.13%), with unbalanced voltage at 1.23% and unbalanced current at 2.99%, both of which indicate that the motor is in good condition. For the star-connected motor under no-load conditions, the IoT system recorded an unbalanced voltage of 2.37% (risky condition) and an unbalanced current of 8.79% (good condition), which are consistent with manual measurements taken using a digital multimeter and a digital clamp meter (unbalanced voltage of 2.04% and unbalanced current of 9.09%).  },
   issn = {2656-582X},   pages = {78--87}  doi = {10.14710/gt.v23i2.90345},
    url = {https://ejournal.undip.ac.id/index.php/gema_teknologi/article/view/90345}
}

Citation Format:

Abstract

Three-phase induction motors are widely used as the primary drive in the industrial sector because of their high reliability in supporting production processes. This final-year research project developed an IoT-based monitoring system for three-phase induction motors to monitor voltage, current, power, and temperature in real time via a website, using PZEM-004T (voltage, current, power) and DS18B20 (temperature) sensors. Motor condition analysis was performed using a diagnostic approach based on the National Electrical Manufacturers Association (NEMA) MG-1 14.36 standard, by calculating the percentage of unbalanced voltage, unbalanced current, and motor load percentage. Testing was conducted on two motor conditions: a loaded Direct-on-Line (DOL) motor with specifications of 2,200 watts (3 HP) and an unloaded star-connected motor with specifications of 0.5 HP. Test results for the DOL motor showed a current sensor accuracy of 98.79% (error 1.21%), a voltage sensor accuracy of 99.38% (error 0.63%), and a power sensor accuracy of 98.87% (error 1.13%), with unbalanced voltage at 1.23% and unbalanced current at 2.99%, both of which indicate that the motor is in good condition. For the star-connected motor under no-load conditions, the IoT system recorded an unbalanced voltage of 2.37% (risky condition) and an unbalanced current of 8.79% (good condition), which are consistent with manual measurements taken using a digital multimeter and a digital clamp meter (unbalanced voltage of 2.04% and unbalanced current of 9.09%).

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Keywords: Three-phase induction motor, Internet of Things, PZEM-004T, DS18B20, real-time monitoring, unbalanced voltage, unbalanced current, motor load.

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Section: Articles

Language : ID

In Vol 23, No 2 (2025): October 2024 - April 2025

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