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All Journal Mechatronics, Electrical Power, and Vehicular Technology Jurnal INKOM Jurnal Elektronika dan Telekomunikasi Teknologi Indonesia
Edwar Yazid
Research Centre for Electrical Power and Mechatronics – Indonesian Institutes of Sciences, Komp. LIPI Bandung, Jl Sangkuriang, Gd 20, Lt 2, Bandung West Java 40135, Indonesia
Computer Science & IT Electrical & Electronics Engineering Engineering

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Journal : Mechatronics, Electrical Power, and Vehicular Technology

 1 
Mathematical Modeling of a Moving Planar Payload Pendulum on Flexible Portal Framework Yazid, Edwar
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 2, No 2 (2011)
Publisher : Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (297.515 KB) | DOI: 10.14203/j.mev.2011.v2.95-104

Abstract

Mathematical modeling of a moving planar payload pendulum on elastic portal framework is presented in this paper. The equations of motion of such a system are obtained by modeling the portal frame using finite element in conjunction with moving finite element method and moving planar payload pendulum by using Lagrange’s equations. The generated equations indicate the presence of nonlinear coupling between dynamics of portal framework and the payload pendulum. The combinational direct numerical integration technique, namely Newmarkand fourth-order Runge-Kutta method, is then proposed to solve the coupled equations of motion. Several numerical simulations are performed and the results are verified with several benchmarks. The results indicate that the amplitude and frequency of the payload pendulum swing angle are greatly affected by flexibility of structure and the cable in term of carriage speed. 
Application of empirical mode decomposition method for characterization of random vibration signals Parman, Setyamartana; Yazid, Edwar
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 7, No 1 (2016)
Publisher : Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (574.549 KB) | DOI: 10.14203/j.mev.2016.v7.21-26

Abstract

Characterization of finite measured signals is a great of importance in dynamical modeling and system identification. This paper addresses an approach for characterization of measured random vibration signals where the approach rests on a method called empirical mode decomposition (EMD). The applicability of proposed approach is tested in one numerical and experimental data from a structural system, namely spar platform. The results are three main signal components, comprising: noise embedded in the measured signal as the first component, first intrinsic mode function (IMF) called as the wave frequency response (WFR) as the second component and second IMF called as the low frequency response (LFR) as the third component while the residue is the trend. Band-pass filter (BPF) method is taken as benchmark for the results obtained from EMD method.
Design of switched reluctance motor as actuator in an end-effector-based wrist rehabilitation robot Azhari, Budi; Hikmawan, Muhammad Fathul; Nugraha, Aditya Sukma; Yazid, Edwar; Pakha, Aji Nasirohman; Baskoro, Catur Hilman Adritya Haryo Bhakti; Rahmat, Rahmat; Ramadiansyah, Mohamad Luthfi
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 2 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.1109

Abstract

The non-communicable diseases have become the top cause of global mortality. One of them is stroke, which also become the first cause of disability worldwide. To help rehabilitate the upper extremities function of stroke survivors, a rehabilitation aid robot is developed, also to bridge the gap between patient and medical staff numbers. An end-effector-based rehabilitation robot is one proposed device. In this case, a switched reluctance motor (SRM) can be utilized as the actuator for its simplicity, robustness, high low-speed torque, and low cost. Thus, this paper proposes a design of SRM to be used as the actuator of an end-effector-based wrist rehabilitation robot. The proposed design is made based on the required torque. To extract the outputs, calculation and simulation using finite element magnetic FEMM 4.2 are conducted. The results show that the SRM produces enough torque, according to references. Moreover, rotor tooth width reduction is not preferred, as it increases the negative torque even though it raises the saliency ratio and cuts the mass of the motor.
Three-axis flexible tube sensor with LSTM-based force prediction for alignment of electric vehicle charging ports Saputra, Hendri Maja; Pahrurrozi, Ahmad; Baskoro, Catur Hilman Adritya Haryo Bhakti; Nor, Nur Safwati Mohd; Ismail, Nanang; Rijanto, Estiko; Yazid, Edwar; Zain, Mohd Zarhamdy Md; Darus, Intan Zaurah Mat
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 15, No 2 (2024)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2024.1104

Abstract

This paper introduces a novel three-axis flexible tube sensor designed for force measurement in electric vehicle (EV) charging port alignment, utilizing long short-term memory (LSTM) networks. The research aims to develop and validate a flexible and accurate sensor system capable of predicting multi-axis forces during alignment. The sensor integrates a magnetic sensor at the center of a flexible tube to capture three-dimensional (3-D) magnetic field variations corresponding to force changes. Fabricated using thermoplastic polyurethane (TPU) via 3-D printing technology, the sensor leverages machine learning to predict force values along the , , and  axes ( , , ). Finite element method (FEM) analysis was conducted to assess the deflection characteristics of the flexible tube under various force conditions. Experimental results demonstrate that integrating LSTM significantly enhances the accuracy of force prediction, achieving an R² score exceeding 97 % for all axes, with mean squared error (MSE) values of 0.2819 for the -axis, 0.3567 for the -axis, and 2.8086 for the -axis. The sensor is capable of measuring forces up to 30 N without exceeding its elastic limits. These findings highlight the sensor’s potential for improving alignment accuracy and reliability in automated EV charging systems.
Co-Authors Baskoro, Catur Hilman Adritya Haryo Bhakti Budi Azhari Darus, Intan Zaurah Mat Estiko Rijanto Hendri Maja Saputra Hikmawan, Muhammad Fathul Nanang Ismail Nor, Nur Safwati Mohd Pahrurrozi, Ahmad Pakha, Aji Nasirohman Parman, Setyamartana Rahmat Rahmat Rahmayanti, Rifa Ramadiansyah, Mohamad Luthfi Rizqi Andry Ardiansyah Sukma Aditya Zain, Mohd Zarhamdy Md