Jurnal Rekayasa Elektrika
Not a member yet
345 research outputs found
Sort by
Water Quality Level for Shrimp Pond at Probolinggo Area Based on Fuzzy Classification System
Full text linkSince several years ago, vaname shrimp (Litopenaeus vannamei) has been extensively cultivated in Indonesia because it has good business opportunities. In aquaculture activities, water quality is an important factor that dramatically impacts the survival and quality of shrimp in the pond. Therefore, information of water quality must be known by the farmer for obtaining a satisfactory harvest. This study aims to develop a water quality monitoring system based on information of temperature, pH, salinity, and dissolved oxygen. The data from sensors are sent to the cloud utilizing Internet of Things (IoT) technology and then classified by a fuzzy logic system. In order to help farmers easily know the water quality of their shrimp pond, four sensor data including the result of classification from fuzzy logic are sent to the phone. After a trial of the system, 100% of the data are successfully sent to the cloud (google spreadsheet). The system also successfully classified the level of water quality as the expectation of the farmer. With this system, it is hoped that it can assist farmers in monitoring the water quality of shrimp pond to improve the quality and quantity of shrimp
Sistem Kontrol pada Automated Guided Vehicle Beroda Mekanum menggunakan Sliding Mode Controller
No full textThe production in industry, are involving distribution to transport the goods. Recently, distribution activities are using unmanned vehicle, that is Automated Guided Vehicle (AGV). In real condition, AGV are facing environment with complexity of high uncertainity and unlinearity. Because of this, robust control method could be considered to be used to improve the control performance. For instance, Sliding Mode Control has good robustness to the uncertainity of the system and disturbances. However, the chattering phenomenon is one of the major issues of the sliding mode control. This phenomenon could damage the motor. This research aim to reduce chattering and improve the control performance, with modifying signum function to saturation function. This research are using ROS, V-Rep and microcontroller. Microcontroller for processing algorithm and another function. Moreover, saturation function had succcessfully reducing rise time about 30%, overshoot 16% and RMSE 0.21%
Plant Monitoring Using a Web-View-Based Android Application as a Realization of the Implementation of the Smart Agriculture Concept
Full text linkThe concept of Smart Farming has been adopted by utilizing microcontrollers, sensor devices, and actuators to regulate plant conditions. However, the communication methods with farmers, such as text messaging applications, are considered ineffective due to their limited features, and farmers cannot control monitoring devices. To address this issue, we developed a web-view-based application named Prospherine Smart Farming using PHP, Java, and MongoDB. The Software Development Life Cycle (SDLC) methodology was employed to ensure the proper functioning of the application. This application has comprehensive features that enable farmers to control monitoring devices, even remotely, and provide continuous information about farming conditions. Testing was conducted to ensure that all features functioned properly, and feedback was obtained from farmers. The research results indicate that using the Prospherine Smart Farming Application positively impacts farming activities. With this application, farmers can monitor their farming conditions in real-time and take necessary actions to enhance crop yields. The Prospherine Smart Farming Application can potentially improve agricultural efficiency and assist farmers in tackling challenges in the digital era
Identification of Power Quality Disturbances Based on Fast Fourier Transform and Artificial Neural Network
Full text linkThis paper presents the proposed algorithms for the identification of Short Duration RMS Variations and Long Duration RMS Variations combined with harmonic. The proposed algorithms are Fast Fourier Transform (FFT) and Artificial Neural Network (ANN). The Algorithms identify nine types of Power Quality (PQ) disturbances such as normal signal, voltage sag, voltage swell, under voltage, over voltage, voltage sag combined harmonic, voltage swell combined harmonic, undervoltage combined harmonic, and over voltage combined harmonic. FFT is used to obtain the frequency spectrum of each PQ disturbance with frequency sampling of 1000 Hz, data length of 200. Output FFT is used to input data for ANN. Output ANN is a type of nine PQ disturbances. The result shows that proposed algorithms (FFT combined ANN) are effective for identification, which ANN with 20 neurons in the hidden layer has an accuracy of approximately 99.95
Declining Cogging Torque Technique of an Integral Slot Number for Permanent Magnet Machines
Full text linkThe existence of cogging torque in electric equipment has been considered undesirable. This kind of friction in the air-gap impacts the alignment of flux and the stator slots, resulting in the observed outcome. Consequently, the imposition of restrictions on the rotation of the rotor is employed to generate electrical energy. This research endeavor primarily aims to mitigate the cogging torque of electrical machinery. The current utilization involves employing a total of 3 permanent magnet synchronous machines, often known as inset PMMs, which possess a slot count of 24 and a pole count of 8. The employed technique involves the integration of an optimal pole arc method in conjunction with the implementation of slots cut into the magnet's edge. The machine model under investigation has two fundamental variants, namely Models 1 and 2. These models are equipped with 1one-step slotted (OSS) and 2two-step slotted (TSS) edges on each magnet, in addition to pole arc optimization. The simulation was conducted using the Finite Element Method Magnetics (FEMM) 4.2 software together with LUA scripts, with a focus on rotor rotation ranges of 1 degree. Model 2 exhibited a decrease in cogging torque of 0.01 Nm, whereas Model 1 demonstrated a reduction of 0.015 Nm, and the basic model had a decrease of 0.02 Nm. When implementing a dual-layered cutting edge on a magnet and attempting to optimize its pole arc, it is imperative to consider that the cogging torque's peak magnitude becomes substantially diminished or entirely eliminated
Secrecy Capacity of Cooperative D2D Multi-relay Communication System with Multiple Protocols Based on Max-Min Relay Selection
Full text linkThe utilization of other devices as relays in cooperative device-to-device (D2D) communication systems does not fully guarantee the security of confidential information from being intentionally or unintentionally accessed by eavesdroppers. Therefore, the implementation of a method to enhance the security performance of information is highly necessary. This paper proposes the application of relay selection mechanisms in a communication system with three relay protocols: Amplify-and-Forward (AF), Decode-and-Forward (DF), and Quantize-and-Forward (QF). The research method employs a mathematical modeling approach and simulations. The simulation results demonstrate an improvement in the level of information security in cooperative D2D communication systems using the proposed method in multiple relay protocols. The relay selection method has been evaluated and compared based on the Secrecy Outage Probability (SOP), which is one of the parameters for information security in the communication system. The SOP achieved is smaller with the implementation of the Max-Min relay selection technique in multi-relay cooperative communication networks. Considering the presence or absence of eavesdroppers, the SOP of the DF relay is smaller compared to other protocols. The impact of distance on secrecy capacity also indicates that the DF protocol utilizing multiple relays achieves higher results compared to other protocols, and the increased usage of relays also affects the simulation outcomes
IoT based System for Air Pollution Monitoring in Banda Aceh
Full text linkAir pollution is a factor that affects the clear skies and breathable air of the city. Humans cannot directly quantify the changes in air quality; hence we need a technological tool to detect the changes in air quality around them. This study proposed a prototype to monitor air quality using embedded system hardware of Arduino Uno-R4 and ESP8266. A Thingspeak database is used as a platform for data communication between smartphones and sensors in real time. The data is retrieved once every 15 seconds. In this prototype, the Arduino Uno-R3 is used as the main brain of the system to connect to WiFi communication via ESP8266 and to four (4) sensors, namely CO (MQ-7), CO2 (MQ-9), dust (PM10), and DHT22 (temperature and humidity). The developed prototype is portable and has low power consumption. Several testing locations have been identified to monitor the air pollution; (1) Simpang Lima Intersection and (2) Jeulingke Bus Stop in Banda Aceh. The system performance shows the connectivity between devices has only a delay of 1.1 seconds; therefore, the system is suitable for real-time usage
Gas Detection and Classification Using Neural Network Based Gas Sensors
No full textAlcoholic beverages, apart from being haram, also cause loss of consciousness. The influence of alcohol while driving is very dangerous and can result in an accident. For this reason, it is necessary to detect the alcohol content in beverages so that their halal status is known and to avoid the dangers of consuming alcohol. This research is to detect the aroma of alcohol using the MQ-3 gas sensor, which consists of an aroma sensor in general with an Artificial Neuron Network (ANN), such as the number of neurons, layers, and epoch. Most of the learning schemes require testing to optimize the model structure. For this experiment, ANN is used as a liquid classification in grouping alcoholic and non-alcoholic liquids. The MQ-3 gas sensor successfully reads liquid vapor in alcohol with levels of 30%, 50%, 70%, and other water-based liquids. An artificial neural network with 2 hidden layers, 10 neurons, and 1000 iterations with the sigmoid activation function can approach a regression score of 1.1545 and sq error score of 0.5781
Analisis Kinerja Penggabungan Logika Fuzzy dan PID pada Penjejak Matahari Dua Sumbu
Full text linkUtilization of renewable energy from solar panel systems is increasingly being applied, but until now its utilization has not been maximized. The movement of the sun caused by rotation of the earth and cloudy condition should be taken into account to maximize the electrical energy in solar panels. In this study, a concept to calculate the movement of a two-axis sun tracker is proposed by using a combination of two controller methods, i.e. Proportional Integral Derivative (PID) and Fuzzy logic known as Fuzzy-PID (F-PID). To follow the movement of the sun, the LDR sensor is used as an input to light as well as output used to drive 2 units servo for x-axis and y-axis. Sun tracker that is used is based on tetrahedron geometry and uses three Light Dependent Resistor (LDR) sensors as input. Input and output components are connected to the Atmega 328P by using a combination of Fuzzy logic and PID programs (F-PID). Fuzzy logic programming is first performed on the Matlab application using Fuzzy Inference System (FIS), then converted into an Arduino-based programming language. The sun tracker movement and the voltage received by the solar panel will be stored into the SD card using a data logging module. Adjusting the sun tracker movement using the combined Fuzzy logic and PID method intends to maximize the electrical energy received by the solar panel. The results showed that the F-PID method obtained the maximum voltage of 5.3 V, a maximum current of 0.11 A, and a maximum power of 0.61 W
Defect Detection System on Stamping Machine Using the Image Processing Method
Full text linkQuality products are very influential in creating profits for the company and are also closely related to the level of customer satisfaction. The higher the quality of the products produced by a company, the higher the satisfaction felt by consumers. The biggest challenge in the production process is achieving good quality with a product defect rate close to zero defect. Defects in the product are usually small. This is of course very difficult for workers to inspect each product for a long time. Thus, manual inspection is certainly ineffective and inefficient because humans have a saturation point and get tired if they work for a long time. Previous research on detecting defective objects using image processing has been carried out but has not been able to detect up to the shape and size, while in this study it can detect up to the shape and size. Therefore, to implement an automatic product defect detection system we will use image processing and RFID technology. Image processing is processing on the image using a computer so that the image quality becomes better and produces value information for each color. Image processing techniques consist of image conversion from RGB to grayscale, thresholding (binarization), and morphological operations (segmentation). While RFID is an identification method by using a means called an RFID label or transponder to store and retrieve data remotely This study aims to implement a control system on HMI and also a detection system on defect products using a visual inspection system with the aim of getting the machine effectiveness value. One method to get this value is the Overall Equipment Effectiveness (OEE) method. It is proven by implementing a visual inspection system that gets an accuracy rate of 95.97% to detect rejected products and optimize the OEE presentation value obtained. In this study, the implementation of the production monitoring system was successfully implemented with an average OEE value of 52.49%