SYAHPUTRO, ENGGAR TYASTO RONI (2025) RANCANG BANGUN SISTEM MONITORING VIBRASI PORTABEL MOTOR INDUKSI BERBASIS IOT. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
Electric motors are vital components in industrial applications, used to drive various equipment such as conveyors, pumps, blowers, and heavy machinery. One common issue that often arises is excessive vibration caused by mechanical failures such as rotor imbalance, shaft misalignment, or bearing wear. Manual vibration detection using portable devices like vibration meters is periodic and highly dependent on inspection schedules. As a result, potential failures that occur outside these schedules often go undetected, leading to unexpected downtime and increased operational costs. To address this issue, a vibration monitoring system based on the Internet of Things (IoT) was developed using the MPU6050 sensor and WeMos D1 microcontroller. This system is capable of measuring three-axis vibrations, transmitting real-time data via WiFi to the ThingSpeak platform, and providing automatic alerts through a buzzer and OLED display. This approach enables continuous monitoring of motor conditions without relying on manual inspections and supports the implementation of more efficient predictive maintenance. Testing results show that after calibration using a multiplication factor of 1.492, the system achieved high accuracy with a Mean Absolute Error (MAE) of 0.115 mm/s and an Average Relative Error (ARE) of 4.03%. The alarm feature effectively classified vibration conditions and activated warnings according to the programmed danger levels. The average data transfer response time via WiFi was recorded at 124.13 ms, and the system was able to operate continuously for approximately 21 hours per full battery charge. Data synchronization with ThingSpeak ran optimally without data loss. Keywords: Vibration, Electric Motor, IoT, MPU6050, WeMos D1, ThingSpeak, Real-Time Monitoring. Motor listrik merupakan komponen vital dalam industri yang digunakan untuk menggerakkan berbagai peralatan. Namun, salah satu masalah umum yang sering terjadi adalah getaran berlebih akibat kerusakan mekanis seperti ketidakseimbangan rotor atau keausan bearing. Deteksi getaran secara manual menggunakan alat portabel seperti vibration meter bersifat periodik dan sangat bergantung pada jadwal inspeksi teknisi, sehingga potensi kerusakan yang terjadi di luar jadwal sering tidak terdeteksi. Hal ini dapat menyebabkan downtime tak terduga serta biaya operasional yang tinggi. Untuk mengatasi permasalahan tersebut, dikembangkanlah sistem monitoring getaran berbasis Internet of Things (IoT) yang menggunakan sensor MPU6050 dan mikrokontroler WeMos D1. Sistem ini mampu mengukur getaran tiga sumbu, mengirimkan data secara real-time melalui koneksi WiFi ke platform ThingSpeak, serta memberikan peringatan otomatis melalui alarm buzzer dan tampilan OLED. Dengan pendekatan ini, pemantauan kondisi motor listrik dapat dilakukan secara kontinu, tanpa perlu ketergantungan terhadap inspeksi manual, serta mendukung implementasi perawatan prediktif yang lebih efisien. Hasil pengujian menunjukkan bahwa setelah proses kalibrasi dengan faktor pengali 1,492, sistem mampu mencapai tingkat akurasi tinggi dengan nilai MAE sebesar 0,115 mm/s dan ARE sebesar 4,03%. Fitur alarm bekerja dengan baik untuk mengklasifikasikan kondisi getaran dan mengaktifkan peringatan sesuai level bahaya. Waktu respon transfer data tercatat rata-rata 124,13 ms melalui jaringan WiFi, dan sistem mampu bekerja terus-menerus selama ±21 jam dalam satu siklus pengisian baterai. Sinkronisasi data ke ThingSpeak berjalan optimal tanpa kehilangan data. Kata Kunci: Getaran, Motor Listrik, IoT, MPU6050, WeMos D1, ThingSpeak, Monitoring Real-Time.
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