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Heading control for quadruped stair climbing based on PD controller for the KRSRI competition
Full text linkQuadruped, a robot that resembles four-legged animals, is developed for many purposes, such as surveillance and rescue. Such a caveat requires the robot to have the capability to overcome various terrain and obstacles. When moving across such a landscape, it is essential to maintain the robot's orientation steadily. Inclined terrains such as stairs have posed another challenge to the control strategy as the robot is unstable while climbing. Therefore, the contribution of this work is to address the need for heading control because of the relatively longer stairs used for the current competition compared to the past. The proposed control system simultaneously maintains the heading while keeping the body stable. The inertial measurement unit sensor carried by the robot would provide the pose needed for heading control calculations. The robot's heading becomes the base for the PD controller calculation. The final pose that stabilizes the robot while tackling heading error is a combination of correction from the PD controller and the stabilization part of the control strategy. Then, the leg servo angle determination deployed the inverse kinematics calculation from the suitable robot pose. The proposed method enabled the designed robot to maintain its heading with a 4.4-degree margin of error and stabilize the body. The quadruped also completes the stair climbing at the shortest time of 20 seconds with a speed of up to 5.5 centimeters per second
Computer Aided Classification of X-ray Images from Pediatric Pneumonia Subjects Collected in Developing Countries
Full text linkPneumonia is a lower tract respiratory infection due to bacteria or viruses. It is a severe disease in the pediatric population. Pneumonia is the leading cause of mortality in children under five years worldwide. One of the problems with pneumonia is the diagnosis, as the symptoms of pneumonia may overlap with other diseases, such as asthma and bronchiolitis. In this work, we propose to develop a method for classifying pneumonia and non-pneumonia using X-ray images. We collected 60 X-ray images from Dr. Sardjito Hospital, Yogyakarta, Indonesia, and the dataset from Kaggle. We processed these images through pre-processing algorithms to enhance the image quality, segmentation, white pixel computation, and classification. The novelty of our method is using the ratio of the white pixels from edge detection using the Canny algorithm with the white pixels from segmentation for classifying pneumonia/non-pneumonia. In the Kaggle dataset, our proposed method achieved an accuracy of 86.7%, a sensitivity of 100%, and a specificity of 85%. The classification using the dataset from Dr. Sardjito Hospital yields sensitivity, specificity, and accuracy of 80%, 60%, and 66.7%, respectively. Despite the low performance in the results, we proved our novel feature, ratio of white pixels, can be used to classify pneumonia/non-pneumonia. We also identified that the local dataset is essential in the algorithm development as it has a different quality from the dataset from modern countries. Further, our simple method can be developed further to support pneumonia diagnosis in resource-limited settings where the advanced computing devices or cloud connection are not available
Interference Analysis Between 5G System and Fixed Satellite Service in the 28 GHz Band
Full text linkOne of the most favorable frequency bands for 5G technology is the 27.5 - 28.5 GHz band which has been used by Fixed Satellite System (FSS) service in the uplink direction. This potentially causes interference between the two systems. This study aims to analyze the interference that occurs between satellite earth stations and 5G access points (AP), and between 5G AP and satellite sky stations. The analysis is carried out based on simulations using the Spectrum Engineering Advanced Monte Carlo Analysis Tool (SEAMCAT) software, with two scenarios. The first scenario is to analyze interference between the 5G AP and the FSS sky station. With the C/I interference criterion of 40.2 dB, the simulation results show that the 5G AP will not interfere with the FSS sky station. The second scenario is the interference simulation between FSS earth station and 5G AP. The simulation is carried out by varying the distance between the earth station and the 5G AP, the height of the earth station, and the height of the 5G AP. Based on the simulations, it is shown that the FSS earth station can interfere with 5G AP with a probability of up to 60%, so it is necessary to adjust the distance between systems and the height of the antenna to minimize the interference. The shortest distance needed to minimize interference is 36 km with an earth station height of 5 meters
Temperature and Humidity Control System for Pole-Mounted Metering Circuit Breaker with Artificial Neural Network Methods
Full text linkPole-mounted Metering Circuit Breaker (PMCB) is a medium voltage protection device. Problems in the PMCB because operating at medium voltage causes insulation problems. The isolation problem that arises is due to partial discharge. Partial discharge can trigger the risk of flashover. In addition, corona discharge causes corrosion of the conductor, the effect is a failure and disconnection of electricity. This control system aims to maintain the temperature and humidity of the PMCB at the nominal values according to the standard. Based on SPLN D3.021-1:2020, it is known that under normal service conditions, the ambient air temperature does not exceed 40°C and the average temperature for 24 hours does not exceed 35°C and the highest relative humidity is 100% RH. The control system uses an AC voltage controller which is used to control the input voltage of the heater and exhaust fan so that the temperature and humidity can reach nominal operating conditions. The control method used is an artificial neural network (ANN) to find the ignition angle of the AC voltage controller as a TRIAC control. The test results using the ANN control method, system simulation produces a temperature error of 1.029% and humidity error of 2.48% and the hardware system produces a temperature error of 2.364% and humidity error of 8.673% compared to the set point temperature of 35°C and humidity of 50% RH. It can be concluded that the ANN control method can maintain the PMCB temperature and humidity according to standard
Comparison Between Trot and Wave Gait Applied in Quadruped Robot
Full text linkA Quadruped robot is a type of robot that moves on four legs and has a structure like a four-legged animal. The quality of movement based on mechanics and movement patterns on quadruped robots tends to have poor movement patterns. This study investigates the best movement between trot and wave gait by comparing the speed performance, stopping distance accuracy, and the tilt of the robot body angle. To minimize the influence of the mechanical quality of the robot, this study used two robots based on the type of servo used (based on the SG90 and MG995 servos). In this study, the motion pattern based on Trot and Wave gait is realized using Inverse Kinematics and Polynomial trajectory on each leg. The verification experiment showed that the Wave gait has better in both the robot body angle and distance error. In contrast the Trot gait has better in speed
Analysis of ITO/a-Si:H(p)/a-Si:H(i)/c-Si(n)/Al HIT (Heterostructure with Intrinsic Thin Layer) solar cell performances.
Full text linkNumerical simulation on HIT (Heterostructure with Intrinsic Thin Layer) solar cell using hetero-structure ITO/(p+)a-Si:H/(i)a-Si:H/(n)c-Si/Al solar cell has been done using AFORS-HET (Automate For Simulation of Heterostructure) software. The purpose of this study is to provide validation as well optimization model of solar cell enhanced performances. Data analysis shows a significant increase on solar power generation. An intrinsic thin layer given between the hetero-interface to reduce defect properties on solar cell structure. The optimization using an optimal value of acceptor-donor doping, dangling-bond defects ( ), thin conductive oxide work function ( ), and other input shows a reducing recombination-rates, as a validation Figure of Merits (FOMs) data reach a maximum efficiency value at 23,67% ( = 634,2 mV; = 51,2 mA/cm2; = 72,91%, this result achieved on peak data such = 5,2 eV, Na (doping) = 5.0 x 1019 cm-3, = 1.0 x 1018 cm-3, (interface defect) = 1.0 x 1010 cm-3. The results obtained from this simulation produce a number of optimum parameters that can be followed up experimentally to obtain better solar cell performances
Optimization Objective Function Corona Discharge Acoustic Using Fuzzy c-Means (FcM )
Full text linkIn many electrical networks in Indonesia, insulation failure due to high voltage phenomena like Corona Discharge (CD) still happens. This is a result of our inability to perform early Corona Discharge (CD) identification. This study’s objective is to optimalize the sound properties of Corona Discharge (CD) as a first step throught the early identification of insulation failure in the form of clustering 20 kV cubicle. Based on observations on the needle-rod electrode 3 cm apart, the smallest breakdown was obtained at 34.3 kV. So that the classification of CD sound by 3 clusters starting 20 kV cubicle voltage until before the failure occurs on 33 kV. The temperature in the cubical is between 27.5℃ - 35.3℃ and humidity ranges from 70% - 95%. It was stated in the study that the FcM method was the most widely used and successful method. In this case, FcM can obtain more flexible results that classify data into clusters easily. This research will be carried out using the Fuzzy c-Means (FcM) method. Feature extraction with linear predictive coding (LPC) method, then optimization by using the Fuzzy c-Means (FcM) method which is expected to be used as an initial step for early detection of insulation failure
Assessment of Solar Energy Resource for PV Plant Development Using a Low-cost PV Monitoring System
Full text linkIn this work, we propose the use of a low-cost PV monitoring system for providing accurate and comprehensive data required in the development of efficient and reliable solar PV plants. The system is developed based on an open-source Arduino platform with the capability to monitor solar irradiance, and electric outputs and temperature of multiple solar panels, which should enable the accurate assessment of solar energy resource, as well as electrical energy produced by PV plant under real operating conditions. To demonstrate its applicability, the system has been installed at the campus of Politeknik Negeri Pontianak in Pontianak City, and the data collected by the system is used to assess solar energy resource at the location. Data collected by the system from August 2020 to September 2021 shows that the values of solar irradiation are in the range of 2.9–4.1 kWh/m2 per day, and electric energy produced by commercial solar panels are in the range of 0.30–0.46 kWh/m2 per day, correspond to the monthly averaged efficiencies of 8–13%. The values of solar irradiation are 15–40 % lower than those obtained from the space-averaged satellite data which are in the range of 4.1–5.8 kWh/m2 per day. This shows the significant effects of local conditions, and confirms the advantage of assessment using the low-cost monitoring system that directly accounts for the effects of local conditions without the need of simulation using complex model and sophisticated software that required in the assessment using satellite-derived data
Designing a Monitoring and Controlling System on IOT-Based Sockets
Full text linkThe government's program to promote energy conservation efforts by reducing the occurrence of vampire power in the surrounding environment, particularly in the household sector. For this reason, modifications are made to the socket so that it can be controlled and monitored remotely through an application on a smartphone. The hardware design uses the NodeMCU ESP8266 V3 as a microcontroller. Combined with the PZEM-004T sensor module to read current, voltage, and power values. Relay module to secure the circuit in case of higher loads. So that in the system, the socket can be monitored 3 sockets simultaneously. While the software design uses the MIT app inventor as the user interface, and the Thingspeak platform as a server. The data is saved in.csv format, which can be opened in Microsoft Excel. The data stored is in the form of the name of the electronic equipment, the time of use, as well as the voltage, current, and power of the device. So that users can manage the use of electrical appliances at home and reduce the occurrence of electric vampires. The test results showed an average voltage error rate of 0.24% with a voltage range of 226 V–230 V, an average current error rate of 22.18%, and an error rate on power of 15.39%. This is caused by the measured load being too small, resulting in higher errors in current and power.
Differential Drive Mobile Robot Motion Accuracy Improvement with Odometry-Compass Sensor Fusion Implementation
Full text linkThe Implementation of wheeled robot technology in the development of transportation vehicles makes them capable for operating automatically. In order to operate automatically, a vehicle requires stable control system which including motion kinematic algorithm where is developed in a robotic system. With the aim of being able to build an Unmanned Grounded Vehicle (UGV), in this study an UGV prototype was made in the form of a wheeled robot with Differential Drive Mobile Robot (DDMR) system. The robot is controlled by motion kinematic control algorithm and a trajectory tracking system that is used to get an estimate of the position caused by the robot’s movement, beside it made the robot can operate automatically. To support the performance of the control system, the robot prototype is added with a compass sensor which used as the wheel odometry sensor’s support. The process of combining wheel odometry and compass sensor data is carried out by using the sensor fusion algorithm, where the limit value for the RMS error for the position accuracy is not more than 0.15 meters. As the result of the trials, by adding a compass sensor and implementing sensor fusion algorithm is able to reduce the average RMS (Root Mean Square) error value of the motion accuracy into below 0.15 meters which previously worth 0.392 meters decreased into 0.075 meters