ELKHA
Not a member yet
182 research outputs found
Sort by
Rotor Speed Analysis of SMC-based IFOC for Low-Speed Induction Motor Control
Full text linkThe control of electric motors, particularly three-phase induction motors, has developed rapidly due to their application in industry. Indirect Field Oriented Control (IFOC) is one of the most widely used control systems due to its ease of application. IFOC controls a three-phase induction motor in the same way as a DC motor. However, IFOC requires a Sliding Mode Control (SMC) controller with Lyapunov stability theory to ensure robustness and stability. In exceptional conditions, such as low-speed settings, the SMC-based IFOC requires unique sets to operate with a steady-state error (Ess) at a speed response of less than 2%. Other parameters to be considered are rise time and electromagnetic torque response at low speeds. The addition of the boundary layer of the hyperbolic tangent function to a first-order SMC can increase induction motor (IM) control up to 175 rpm with a value of Ess = 1.96% compared to the saturation and signum functions, which are only capable of a reference speed of 300 rpm in no-load conditions with a value of Ess = 2% for the saturation function and 1.94% for the signum function. SMC with the hyperbolic tangent function boundary layer performs best under load conditions. The rising time value does not significantly differ under no-load or torque-load conditions between the SMC with the saturation, hyperbolic tangent function boundary layers and without the boundary layer. Adding a boundary layer with the hyperbolic tangent function can reduce ripple significantly compared to the saturation function under no-load or load conditions
Reliability Analysis of Biomass Power Plant Using Loss of Load Probability Index at PT. Tanjung Buyu Perkasa Plantation
Full text linkThe main function of a power generation system is to provide reliable electrical energy. This study aims to determine the reliability of Biomass Power Plants at PT. Tanjung Bayu Perkasa Plantation (PT. TBPP) in the years 2020, 2021, and 2022 using the Loss of Load Probability (LOLP) index calculation method. LOLP is a reliability index that indicates the possibility that the power plant cannot meet the demand. The LOLP of biomass power plants at PT. TBPP in 2020 amounted to 1.2769 days per year. However, the LOLP in 2020 does not comply with the standards set by the Republic of Indonesia Minister of Energy and Mineral Resources Decree in 2018. In contrast, in 2021, it was 0.53403 days per year, and in 2022, it was 0.41748 days per year, both of which meet the standards of the Republic of Indonesia Minister of Energy and Mineral Resources Decree in 2018. The LOLP is affected by the Forced Outage Rate (FOR) and demands exceeding the capacity. Based on the LOLP of biomass power plants at PT. TBPP in 2020, 2021, and 2022, it can be concluded that the reliability of biomass power plants at PT. TBPP is at a higher level of reliability compared to the micro-hydro power plant in Pantai Baru Pandasimo with a LOLP of 51.3627 days per year and the steam power plant at Pertamina EP Asset IV Field Sukowati with LOLP of 4.259535 days per year. The recommendation for future research is to explore ways better to optimize boiler operations in steam power plants at PT. TBPP
Wi-Fi Sensing for Indoor Localization via Channel State Information: A Survey
Full text linkWireless Fidelity (Wi-Fi) sensing utilization has been widespread, especially for human behavior/activity recognition. It provides high flexibility since it does not require the person/object to carry any device known as device-free. This "passive" concept is also helpful for another application of Wi-Fi sensing, i.e., indoor localization. The "sensing" is conducted using particular parameters extracted from communication links of Wi-Fi devices, i.e., channel state information (CSI). This paper explores the recent trends in CSI-based indoor localization with Wi-Fi technology as its core, including their advantages, challenges, and future directions. We found tremendous benefits can be gained by employing Wi-Fi sensing in localization supported by its performance and integrability for other intelligent systems for activity recognition
D-Tags Design by Combining Bluetooth Router, IoT, and Mobile Phone to Track Personal Items
Full text linkLosing personal items such as a wallet or room keys is disturbing. Problems arise when clues to find the item are lacking or even non-existent. Of one hundred-two people who filled out the questionnaire about how often losing their belongings, 76% had experienced it. Because of that, it must be hard to remember where the last they put the stuff. Therefore people need tools that can help them easily find their item with a transmitter and connect to a mobile phone. Previous research showed that the transmitter with a frequency system had a detection distance of only 5 meters. From this weakness, the authors propose the development of a tracking items device that combines an Internet of Things-based Bluetooth transmitter and receiver system approach called D-Tags by combining Bluetooth routers, IoT, and mobile phones. The system is designed for both indoor and outdoor areas. Bluetooth testing allows the device to detect items up to 7.43 meters without wall obstacles. The system provided location information such as Living Room or Bedroom and the coordinates when outside the room. Regarding time, a single detection item is faster in the range of 15.13 seconds to 15.60 seconds than searching for two things simultaneously. From the tracking radius of the outdoor area, the device can track items up to 31.8 meters from the last item's position. All information tracking history can be seen on the web application. The experiment results prove that D-Tags can be used to track items by indicating their location and with a relatively short search duration
Quality Improvement of 20 KV Voltage Profile Of PT. PLN (Persero) Ketapang According to SPLN No.72 Of 1987
Full text linkThis study aims to determine the magnitude of the increase in the voltage profile of the 20.kV distribution network system of PT. PLN (Persero) Ketapang with the installation of reactive power injection equipment. The research method used is the Newton Raphson power flow method with MATLAB simulation program. From the results of these calculations, Pawan 2 and Pawan 6 load buses each have a voltage drop above 5%, which is found on 42 buses. To overcome this, reactive power injection (Qc) was carried out: 150 KVAR on bus 26 of Pawan 2, and 900 KVAR on bus 40 and 46, and 600 KVAR on bus 51 of Pawan 6. This leads to the increase in voltage drop percentage on Pawan 2 and Pawan 6, thus, the profile meets SPLN No. 72 of 1987, which is below 5%
Deep Learning for Channel Estimation and Signal Detection in OFDM-Based Communication Systems
Full text linkThe goal of 6G communication networks requires higher transmission speeds, tremendous data processing, and low-latency communication. Orthogonal frequency-division multiplexing (OFDM), which is widely utilized in 5G communication systems, may be a viable alternative for 6G. It significantly reduces inter symbol interference (ISI) in the frequency-selective fading environment. Channel estimation is critical in OFDM to optimize system performance. Deep learning has been employed as an appealing alternative for channel estimation and signal detection in OFDM-based communication systems due to its better potential for feature learning and representation. In this study, we examine the deep neural network (DNN) layers created from long-short term memory (LSTM) for detecting the signals by learning the received signal as well as channel information. We investigate the performance of the system under various conditions. The simulation results show that the signal bit error (SER) is equivalent to and better than that of the minimum mean squared error (MMSE) and least square (LS) methods
Multi Sensor-Based Obstacle Avoidance Algorithm in Visual Engineering Environment
Full text linkObstacle avoidance is an essential problem for applications involving multiple wheeled mobile robots. This research proposes a simple obstacle avoidance rule utilizing only one type of sensor, i.e., infrared sensor. In this research, multiple infrared sensors are placed on a mobile robot, arranged 45° radially equidistance. By using a low-cost and easily available infrared sensor, the cost and time consumed to build and repair a wheeled mobile robot are considerably reduced. Avoiding rules, based on simple behavior, such as “turn”, “stop”, “follow”, and “ignore” are developed. By applying these rules, each robot can refer to the motion of other robot or stationary object to avoid collision. Simulation results show that the proposed algorithm performs well, at 66.7% chance of avoiding a moving object and at 93% chance of avoiding a stationary object
Implementation of Wireless Sensor Network (WSN) for Earthquake Detection
Full text linkThe current earthquake monitoring system uses a seismometer that can capture seismic vibrations very well but is expensive, heavy, and difficult to launch. Therefore, earthquake monitoring stations can only be launched in a few places in small numbers. This study aims to implement a Wireless Sensor Network (WSN) system for earthquake monitoring. The WSN system has advantages in cost, size, and ease of launch, so it is very appropriate to be used for this purpose. An earthquake detection sensor system has been designed in this study using a vibration sensor and a piezoelectric sensor. When an earthquake occurs, the resulting shock will trigger the vibration sensor and activate the sensor node. The shock data is then captured by the piezo sensor and processed by the microcontroller using Fast Fourier Transform (FFT) to determine the frequency value of the shock. The data is then sent to a gateway via a sensor network and uploaded to the Cayenne monitoring website. Operators can then view the data on the website. Three sensor nodes are implemented in this study. The test is done by placing those sensor nodes together in random positions. A shock is then given to the three sensor nodes, and the resulting data is then observed. The results show that the three sensors can detect, retrieve, process, and send shock data to the Cayenne monitoring website
Voice Command Recognition for Movement Control of a 4-DoF Robot Arm
Full text linkRobots are widely used in industry. Robots generally have a control system or intelligence embedded in the processor. The robots consist of mobile mode, manipulator, and their combination. Mobile robots usually use wheels, and manipulator robots have limited degrees of freedom. Both have their respective advantages. Mobile robots are widely applied to environments with flat floor surfaces. The manipulator robots are applied to a static environment to produce, print, and cut material. In this study, the robot arm 4 Degree of Freedom (DoF) is integrated with a computer. The computer controls the whole system, where the operator can control the Robot based on voice commands. The operator's voice is one person only with different intonations. Voice command recognition uses the Mel-Frequency Cepstral Coefficients (MFCC) and Artificial Neural Networks (ANN) methods. The MFCC and ANN programs are processed in the computer, and the program output is sent to the Robot via serial communication. There are nine types of voice commands with different MFCC patterns. ANN training data for each command is 10 data, so the total becomes 90. In this experiment, the Robot can move according to voice commands given by the operator. Tests for each voice command are ten experiments, so the total experiment is 90 times with a success rate of 94%. There is only one operator, and experiments have not yet been carried out with the voices of several operators. The error occurred because there were several similar patterns during system testing
Multi-Security System Based on RFID Fingerprint and Keypad to Access the Door
Full text linkIt is necessary to prepare for the increasing crime rate of household theft with a modern home security system that allows customers to monitor home security remotely. This can be accomplished by replacing the standard lock with a solenoid door lock, which is more difficult to duplicate and reduces the likelihood of theft when the house is unoccupied. The Authors developed a three-tiered home security system prototype that includes fingerprint, the RFID, and keypad biometric sensors. The device's finished prototype was tested ten times after it was designed. The Arduino Uno microcontroller, which also serves as the door-locking mechanism, turns on the door-lock solenoid. When authentication is successful, someone will be granted access to the door. The preliminary findings indicate that the fingerprint. The fingerprint sensor's ability to read fingerprints in 3.7 seconds on average demonstrates its effectiveness. Second, the RFID sensor detects the e-KTP, and the RFID scans the card in an average of 2.4 seconds. The third keypad contains the password for unlocking the door. After ten repetitions, the experiment input yields an average time of 3.66 seconds. Opening a door with a 3-level multi-sensor typically takes 9.8 seconds. In this study, the installation of each sensor is notified via a GSM SIM800L module, allowing customers to monitor security remotely