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Rahmat Hidayat
Department of Electrical Engineering, Faculty of Engineering, Universitas Negeri Padang, Indonesia
Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Real-time Identification of Electric Motor Faults Using Arduino Ilham Sabri Alamsyah; Dwiprima Elvanny Myori; Ichwan Yelfianhar; Rahmat Hidayat
Journal of Industrial Automation and Electrical Engineering Vol. 1 No. 1 (2024): Vol 1 No 1 (2024): June 2024
Publisher : Department of Electrical Engineering Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/

Abstract

The reliability of electric motors is very important in various industries. Damage to electric motors caused by disturbances that are not detected early results in large losses, both in terms of time and cost. This research aims to design and build an Arduino-based electric motor fault detection device equipped with a PZEM-004t sensor, buzzer as an alarm, relay to turn off the motor when there is a disturbance and LCD I2C 16x2 to display the measured value. This tool is designed to provide protection to the motor from overvoltage, undervoltage and overcurrent disturbances. Based on the results of testing and analysis, the designed tool can detect and protect the motor from interference. The buzzer functions effectively as an alarm when the voltage and current values are close to the fault occurrence value. The relay can respond well in breaking the current in the motor when a disturbance occurs. Thus, this tool has the potential to be applied as a practical solution in preventing damage to electric motors in industrial environments
Monitoring and Controlling Electric Energy Usage Based on the Internet of Things Luthfi Abdul Latif; Hambali; Ricky Maulana; Rahmat Hidayat
Journal of Industrial Automation and Electrical Engineering Vol. 1 No. 1 (2024): Vol 1 No 1 (2024): June 2024
Publisher : Department of Electrical Engineering Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mr63n324

Abstract

Electrical energy is one of the basic human needs whose use continues to increase along with the increase in daily activities. Uncontrolled electricity consumption can lead to energy waste and increased costs. Therefore, a system is needed that can monitor and control the use of electrical energy effectively. In this final project, we develop an Internet of Things (IoT)-based tool that is able to monitor and control the use of household electrical energy in real-time. This system uses ESP32 microcontroller, PZEM-004T current sensor, LCD to display the sensor output, and Relay as an automatic switch to regulate the on or off of electronic devices. Blynk platform is used as an intermediary between microcontroller and smartphone or PC to facilitate remote control. With this system, users can monitor daily energy consumption and control electricity usage efficiently, thus saving energy and costs. This research is expected to contribute to a smarter and more efficient management of household electrical energy
Implementation of Maximum power control of Solar Panels using Modified Perturb and Observe Algorithm based on Adaptive Neuro Fuzzy Inference System Ilham Kurniawan; Muldi Yuhendri; Ayu Hendra; Rahmat Hidayat
Journal of Industrial Automation and Electrical Engineering Vol. 1 No. 1 (2024): Vol 1 No 1 (2024): June 2024
Publisher : Department of Electrical Engineering Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/87da0h21

Abstract

In this modern era, the need for renewable energy is increasing, and solar panels are one of the main solutions. To maximize the efficiency of energy extraction from solar panels, a method is needed. Based on the characteristics of voltage and current, the output power of these solar panels changes following changes in irradiation and temperature. Changes in the output power value have a maximum point, where each voltage and current value has a different maximum power point at each change in temperature. For this reason, the Maximum Power Point Tracker (MPPT) method is used to solve this problem by adjusting the solar panel voltage at the maximum point using a power converter. In this study, the MPPT control system will be implemented using a boost converter. This study develops a Maximum Power Point Tracking (MPPT) control system based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), which is developed from conventional perturbation and observation algorithms. The ANFIS-based MPPT control system is implemented using an Arduino microcontroller. The experimental results verify that the proposed ANFIS-based MPPT system has successfully controlled the output power of solar panels at the maximum point
Co-Authors Ayu Hendra Dwiprima Elvanny Myori Hambali Ichwan Yelfianhar Ilham Kurniawan Ilham Sabri Alamsyah Luthfi Abdul Latif Muldi Yuhendri Ricky Maulana