Perancangan Sistem Pendeteksi Kerusakan Motor Induksi Berbasis IoT dengan Menggunakan Sensor Suhu, Arus dan Getaran
DOI:
https://doi.org/10.15575/telka.v11n1.64-75Kata Kunci:
IoT, Motor Induksi, Sistem monitoring, Akurasi, MikrokontrollerAbstrak
Motor induksi dikenal karena keunggulan dalam konstruksi sederhana, ketahanan terhadap beban, dan efisiensi yang tinggi, namun memiliki potensi kerusakan yang dapat mengurangi efisiensi operasional. Sebagai solusi, sistem monitoring kerusakan motor induksi berbasis IoT dikembangkan dengan menggunakan mikrokontroler Arduino yang terintegrasi dengan ESP 01. Pengujian meliputi pengukuran akurasi sensor dalam berbagai kondisi operasi untuk memastikan keandalan deteksi. Tiga sensor utama, yaitu sensor suhu DS18B20, sensor arus SCT-013, dan sensor getaran ADXL335 digunakan untuk mendeteksi suhu, arus, dan getaran. Hasil pengujian menunjukkan bahwa pengujian suhu motor memiliki akurasi hingga 97%, sementara pengujian arus mencapai 84,3%. Sistem pendeteksi kerusakan motor menunjukkan tingkat akurasi 100% dalam mendeteksi kerusakan pada motor. Selain itu, sistem ini dirancang untuk memberikan peringatan dini melalui platform IoT, sehingga pemeliharaan dapat dilakukan sebelum kerusakan signifikan terjadi. Secara keseluruhan, sistem ini menunjukkan efektivitas dalam mendeteksi potensi kerusakan pada motor induksi dengan fokus pada tiga parameter kunci: suhu, arus, dan getaran, yang meningkatkan keandalan dan efisiensi operasional motor induksi.
Induction motors are known for their advantages in simple construction, load resistance, and high efficiency. However, they have the potential for damage that can reduce operational efficiency. As a solution, an IoT-based induction motor fault monitoring system is developed using an Arduino microcontroller integrated with ESP 01. Testing includes measuring sensor accuracy in various operating conditions to ensure detection reliability. Three main sensors DS18B20, SCT-013, and ADXL335 are used to detect temperature, current, and vibration. Test results show that the motor temperature test has an accuracy of up to 97%, while the current test reaches 84.3%. The motor fault detection system demonstrates 100% accuracy in detecting motor faults. Additionally, the system is designed to provide early warnings through the IoT platform, enabling maintenance to be performed before significant damage occurs. Overall, this system demonstrates effectiveness in detecting potential faults in induction motors, focusing on three key parameters: temperature, current, and vibration, which enhances the reliability and operational efficiency of induction motors
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