Jurnal Rekayasa Elektrika最新文献_第3页

Optimization of Fuzzy Social Force Model Adaptive Parameter using Genetic Algorithm for Mobile Robot Navigation Control 基于遗传算法的模糊社会力模型自适应参数优化在移动机器人导航控制中的应用

Jurnal Rekayasa Elektrika Pub Date : 2023-03-27 DOI: 10.17529/jre.v19i1.28330

Alif Wicaksana Ramadhan, Bima Sena Bayu Dewantara, Setiawardhana Setiawardhana

{"title":"Optimization of Fuzzy Social Force Model Adaptive Parameter using Genetic Algorithm for Mobile Robot Navigation Control","authors":"Alif Wicaksana Ramadhan, Bima Sena Bayu Dewantara, Setiawardhana Setiawardhana","doi":"10.17529/jre.v19i1.28330","DOIUrl":"https://doi.org/10.17529/jre.v19i1.28330","url":null,"abstract":"The Social Force Model (SFM) is a popular navigation technique for mobile robots that is primarily used to simulate pedestrian movement. The SFM method's drawback is that several parameter values, such as gain, k, and impact range, σ, must be determined manually. The reaction of the SFM is frequently inappropriate for certain environmental circumstances as a result of this manual determination. In this paper, we propose employing the Fuzzy Inference System (FIS), whose rules are optimized using a Genetic Algorithm (GA) to manage the value of the gain, k, parameter adaptive. The relative distance, d, and relative angle, α, concerning the robot's obstacle are the inputs for the FIS. The test results using a 3-D realistic CoppeliaSim demonstrated that the learning outcomes of FIS rules could provide adaptive parameter values suitable for each environmental circumstance, allowing the robot to travel smoothly is represented using the robot’s heading deviation which decreasing by and reaching the goal 1.6 sec faster from the starting point to the goal, compared to the SFM with the fixed parameter value. So that the proposed method is more effective and promising when deploying on the real robot implementation.","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46000191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Defect Detection System on Stamping Machine Using the Image Processing Method 基于图像处理方法的冲压机缺陷检测系统

Jurnal Rekayasa Elektrika Pub Date : 2023-03-27 DOI: 10.17529/jre.v19i1.29111

Nur Wisma Nugraha, Suharayadi Pancono, G. Maulana

{"title":"Defect Detection System on Stamping Machine Using the Image Processing Method","authors":"Nur Wisma Nugraha, Suharayadi Pancono, G. Maulana","doi":"10.17529/jre.v19i1.29111","DOIUrl":"https://doi.org/10.17529/jre.v19i1.29111","url":null,"abstract":"Quality 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%. ","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46363509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of Power Quality Disturbances Based on Fast Fourier Transform and Artificial Neural Network 基于快速傅里叶变换和人工神经网络的电能质量扰动辨识

Jurnal Rekayasa Elektrika Pub Date : 2023-03-27 DOI: 10.17529/jre.v19i1.27120

D. O. Anggriawan, E. Wahjono, I. Sudiharto, Anang Budikarso

引用次数: 0

An Implementation of Measurement System Analysis for IoT-Based Waste Management Development 基于物联网的废物管理发展测量系统分析的实现

Jurnal Rekayasa Elektrika Pub Date : 2022-12-01 DOI: 10.17529/jre.v18i4.26910

Heru Wijanarko, Arianysah Saputra, Ika Karlina Laila Nur Suciningtyas, Rifqi Amalya Fatekha

{"title":"An Implementation of Measurement System Analysis for IoT-Based Waste Management Development","authors":"Heru Wijanarko, Arianysah Saputra, Ika Karlina Laila Nur Suciningtyas, Rifqi Amalya Fatekha","doi":"10.17529/jre.v18i4.26910","DOIUrl":"https://doi.org/10.17529/jre.v18i4.26910","url":null,"abstract":"A measurement system is a process that consists of standards, employees, and methods for measuring particular quality characteristics. Measurement System Analysis (MSA) attempts to evaluate a measuring system's precision, accuracy, and consistency so that clients receive high-quality goods. The previous study implements the MSA for machinery and industrial lines, electronics manufacturing, agricultural and poultry, aviation, and even employee monitoring and inspection. Elsewhere, waste management has problems, especially with capacity measurement instruments and weight sensors. This study aims to: (i) build an IoT-based waste management system; and (ii) evaluate the developed system by implementing the MSA technique, focusing on measurement equipment. The Gauge Repeatability and Reproducibility (GRR) Study Type 1, the (GRR) Study, and the Analysis of Variance (ANOVA) are conducted to evaluate the measurement instrument of the waste management system. The study findings that the total variance of the GRR is 20.95 %, and the distinct categories are 6. Thus, as the Automotive Industry Action Group (AIAG) GRR recommendation, the measuring system is marginal (acceptable in certain conditions). Moreover, the ANOVA result indicates that interaction and operators did not affect measurement outcomes because the blue dots remain inside the acceptable range.","PeriodicalId":30766,"journal":{"name":"Jurnal Rekayasa Elektrika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47528935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Perancangan dan Implementasi Alat Pendeteksi Dini Penyakit Jantung Koroner 设计和执行早期发现冠状动脉心脏病的设备

Jurnal Rekayasa Elektrika Pub Date : 2022-12-01 DOI: 10.17529/jre.v18i4.27240

B. Iman, Raay Rafikasitha, Kemalasari Kemalasari

引用次数: 0

Perbandingan Kinerja Algoritma Optimasi pada Metode Random Forest untuk Deteksi Kegagalan Jantung 心力衰竭检测中随机森林法执行器优化算法的比较

Jurnal Rekayasa Elektrika Pub Date : 2022-12-01 DOI: 10.17529/jre.v18i4.26981

Unang Sunarya, Tita Haryanti

引用次数: 1

Penerapan Algoritma HSV pada Autonomous Car untuk Sistem Self-Driving Berbasis Raspberry Pi 4 基于树莓派的自动驾驶汽车系统

Jurnal Rekayasa Elektrika Pub Date : 2022-12-01 DOI: 10.17529/jre.v18i4.27495

F. Setiawan, Padang Ufqi Sutrisno, L. H. Pratomo, Slamet Riyadi