Muhajir Ab. Rahim
Thumbnail Image
Preferred name
Muhajir Ab. Rahim
Official Name
Muhajir, Ab. Rahim
Alternative Name
Rahim, Muhajir
Rahim, M. A.
Main Affiliation
Scopus Author ID
56739343200
Researcher ID
FXA-2537-2022

Research Output

Filters

12 1
6 1
12
Reset filters

Settings
Now showing 1 - 10 of 12
  • Publication
    Classification of Human Emotions Using EEG Signals in a Simulated Environment
    ( 2022-01-01)
    Hafiz Halin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Muhajir Ab. Rahim
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    The Brain-Computer Interface (BCI) is a computer-based system that acquires and analyses brain signals. The analysis of brain signals shows the physiological change that happens to the drivers. The physiological changes detected by the BCI system may not be visible to the naked eye. By using the BCI, it increases the diagnostic capability to detect the drivers' emotions. The negative drivers' emotions may cause bad decision making during driving the vehicle. The proposed method was developed to study the related emotions that occur during driving in the simulation environment. The experiments were designed in two situations, which are manual and autonomous drive. In the manual mode, the subjects will control the steering wheel and acceleration of the simulated vehicle. While in autonomous mode, all controls are disable and the subjects will experience the automatic simulation drive. The EEG data was recorded during the simulated drive (manual and autonomous). The EEG data from the subjects were then categorised into five emotions classifications.
  • Publication
    Wireless mass air flow device for thermal comfort data acquisition
    ( 2024)
    Ismail I. Ibrahim
    ;
    M. N. I. Mohamad Zubir
    ;
    Shazmin Aniza Abdul Shukor
    ;
    Muhajir Ab. Rahim
    ;
    K. Kohlhof
    This paper aims to build and implement an IoT-based mass air flow sensor device using the FS7 sensor from IST Innovative Sensor Technology and the ESP32. The scope of the project includes design and implementation of the device, the evaluation of its performance, and the presentation of the results. To achieve its objective, the project will employ literature evaluation, hardware design, programming, testing, and data analysis methodologies. The IoT-based mass air flow sensing device has the potential to improve the performance of air flow-dependent systems by providing real-time data, remote monitoring and control, and enhanced precision and dependability. In addition, it will be calibrated, maintained, and upgraded remotely, decreasing the need for on-site maintenance and extending the device's lifespan.
  • Publication
    Suppresion of sommerfeld effect in power transmission system employing cardan shaft through phase angle arragement
    ( 2024-07-01)
    Omar M.H.
    ;
    Muhajir Ab. Rahim
    ;
    Mohd Noor Arib Md Rejab
    ;
    Rani M.N.A.
    In a power transmission system with a cardan shaft, the Sommerfeld effect occurs, which is characterized by speed capture and release at the resonance range. Suppression of the Sommerfeld effect is critical for smooth and reliable operation. This study aims to suppress the Sommerfeld effect in a transmission system by compensating the phase angle between the two universal joints installed in the cardan shaft. The differential equations of motion representing the dynamics of the system are derived using the Lagrange equation. The responses are simulated numerically using the Runge–Kutta algorithm for scenarios with constant and gradually varying input torque. To suppress the Sommerfeld effect, the phase angle is set to 25%, 50%, 75% and 100% of the maximum twist angle observed in the subcritical speed range of the in-phase configuration. With the phase angle of 25%, the Sommerfeld effect is damped, where the output speed only deviates by 5% from the estimated value for both input torque scenarios. It is shown how the change of the phase angle attenuates the Sommerfeld effect and the system vibrations, which should be considered in the development and practical implementation.
  • Publication
    Connected car: Engines diagnostic via Internet of Things (IoT)
    ( 2017-10-29)
    Azrul Fahmi A.Hamid
    ;
    Md. Tasyrif bin Abdul Rahman
    ;
    Shah Fenner Khan Mohamad Khan
    ;
    Abdul Hamid Adom
    ;
    Muhajir Ab. Rahim
    ;
    Norasmadi Abdul Rahim
    ;
    Ismail M.H.N.
    ;
    Norizan A.
    This paper is about an experiment for performing engines diagnostic using wireless sensing Internet of Thing (IoT). The study is to overcome problem of current standard On Board Diagnosis (OBD-II) data acquisition method that only can be perform in offline or wired method. From this paper it show a method to determined how the data from engines can be collected, make the data can be easily understand by human and sending data over the wireless internet connection via platform of IOT. This study is separate into three stages that is CAN-bus data collection, CAN data conversion and send data to cloud storage. Every stage is experimented with a two different method and consist five data parameter that is Revolution per Minute (RPM), Manifold Air Pressure (MAP), load-fuel, barometric pressure and engine temperature. The experiment use Arduino Uno as microcontroller, CAN-bus converter and ESP8266 wifi board as transfer medium for data to internet.
  • Publication
    Development of Driving Simulation Experiment Protocol for the Study of Drivers’ Emotions by using EEG Signal
    ( 2024-06-01)
    Abdul Hafiz Abd Halin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Muhajir Ab. Rahim
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    ;
    Saidatul Ardeenawatie Awang
    The Brain-Computer Interface (BCI) is a field of research that studies the EEG signal in order to elevate our understanding of the human brain. The applications of BCI are not limited to the study of the brain wave but also include its applications. The studies of human emotions specific to the vehicle driver are limited and not vastly explored. The EEG signal is used in this study to classify the emotions of drivers. This research aims to study the emotion classifications (surprise, relax/neutral, focus, fear, and nervousness) while driving the simulated vehicle by analyse the EEG signals. The experiments were conducted in 2 conditions, autonomous and manual drive in the simulated environment. In autonomous driving, vehicle control is disabled. While in manual drive, the subjects are able to control the steering angle, acceleration, and brake pedal. During the experiments, the EEG data of the subjects is recorded and then analyzed.
  • Publication
    Design of Experiment (DOE) for the Investigation of Human Emotions while Driving in a Virtual Environment through Brain Signal (EEG)
    ( 2021-01-01)
    Hafiz Halin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Muhajir Ab. Rahim
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    The transition from the conventional vehicle to the autonomous vehicle is going to take place but, the acceptance of users to the autonomous vehicle still lacking. The past research more focusses on the driver attention, drowsiness, fatigue or the alertness of the driver. This research aims to study the drivers' emotions/reactions during the autonomous and manual drive in the simulated environment. The environment for the manual and autonomous drive is developed by using simulator software, Unity. This paper focus only on the experimental setup for the human emotions' detection using EEG signal during the manual and autonomous drive. The Emotiv Epoc+ use for the EEG signal acquisition. The simulated environments are displayed through a Head Mount Display (HMD). The analysis of the EEG signal which includes the pre-processing, feature extraction, and classification will be discussed in future works.
      1
  • Publication
    NUMERICAL STUDY ON EFFECT OF PHASE ANGLE ON TORSIONAL AND LATERAL VIBRATIONS IN POWER TRANSMISSION SYSTEM EMPLOYING CARDAN SHAFT
    ( 2023-07-01)
    Omar M.H.
    ;
    Muhajir Ab. Rahim
    ;
    Mohd Noor Arib Md Rejab
    A power transmission system driven by a Cardan shaft may experience severe vibration due to fluctuating rotational speed and moments transferred to the final drives, determined by the level of angular misalignment and phasing of the joint yokes. This study investigates the potential of an out-of-phase position displaced by a phase angle in attenuating vibrations. The governing equations representing the dynamics of the system are derived. The torsional and lateral vibration responses are numerically calculated over a range of input rotational speeds. When attenuating the vibration, the phase angle is set equal to the maximum twist that occurs during the in-phase position. Relative attenuation is used to investigate the phase angle effects. The effectiveness is studied for different levels of static angular misalignment. For the considered system, the results showed that for static angular misalignment greater than 20 degrees, the proposed phase angle arrangement could attenuate torsional vibration by more than 10 percent and significantly attenuate the lateral vibration.
      1
  • Publication
    Classification of human emotions using EEG Signals in a simulated environment
    ( 2022-01-01)
    Hafiz Halin
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Wan Azani Wan Mustafa
    ;
    Muhajir Ab. Rahim
    ;
    Zuradzman Mohamad Razlan
    ;
    Shahriman Abu Bakar
    The Brain-Computer Interface (BCI) is a computer-based system that acquires and analyses brain signals. The analysis of brain signals shows the physiological change that happens to the drivers. The physiological changes detected by the BCI system may not be visible to the naked eye. By using the BCI, it increases the diagnostic capability to detect the drivers' emotions. The negative drivers' emotions may cause bad decision making during driving the vehicle. The proposed method was developed to study the related emotions that occur during driving in the simulation environment. The experiments were designed in two situations, which are manual and autonomous drive. In the manual mode, the subjects will control the steering wheel and acceleration of the simulated vehicle. While in autonomous mode, all controls are disable and the subjects will experience the automatic simulation drive. The EEG data was recorded during the simulated drive (manual and autonomous). The EEG data from the subjects were then categorised into five emotions classifications.
      4  3
  • Publication
    Numerical Study on the Torsional and Lateral Vibrations of Double Universal Joint Driveline System
    ( 2023-01-01)
    Omar M.H.
    ;
    Muhajir Ab. Rahim
    ;
    Mohd Noor Arib Md Rejab
    Utilizing a universal joint can lead to significant vibration within a driveline system. This study presents a model for analyzing the torsional and lateral vibrations of a driveline connected by a double universal joint. The governing equations of motion are derived, and the Runge-Kutta method computes steady-state responses across a spectrum of input rotational speeds. The focus is to examine the effect of system parameters, including static angular misalignment, load torque, and lateral stiffness. Relative amplification is used to analyze the effects of parameters on system vibration. Results indicated that the second-order component of input rotational speed induced by the universal joint was the factor that caused the vibrations. For the considered system, static angular misalignment significantly impacts both the torsional and lateral vibrations. Increasing the angular misalignment from 15° to 30° results in a threefold increase in lateral vibration amplification, while torsional vibration amplification is increased by nearly two times. The effect of load torque is almost linearly proportional to torsional vibration but is nonlinear to lateral vibration. Thus, lateral vibration is significantly impacted compared to torsional vibration for higher load torque. Changing the stiffness leads to a modification of the natural frequency. Increasing the lateral stiffness shifts the critical speed to a higher speed range, resulting in reduced lateral vibration amplitude. It is demonstrated that a slight fluctuation in angular misalignment due to lateral vibration will not affect the torsional vibration even if both vibrations are coupled. The findings may enhance understanding of how changing system parameters affects vibration.
      2
  • Publication
    Reliability of Response-Controlled Stepped Sine Testing for Experimental Detection of Nonlinear Structure
    ( 2023-01-01)
    Bahari A.R.
    ;
    Yunus M.A.
    ;
    Rani M.N.A.
    ;
    Yahya Z.
    ;
    Muhajir Ab. Rahim
    Nonlinear structural dynamic analysis is required for mechanical structures experiencing nonlinearity through large force-vibration response ranges. Nonlinearities can be caused by large vibration displacements, material properties, or joints. Experimental modal analysis for nonlinear detection is achieved using conventional force-controlled stepped sine testing. However, this approach often encounters premature jumps in frequency response curves before reaching actual resonance peaks. In recent years, response-controlled stepped sine testing (RCT) has been introduced to quantify resonant peaks precisely. This approach, however, has only been limitedly utilised to detect and analyse nonlinearity in jointed structures and structures experiencing large displacement. In this paper, the reliability of the RCT approach is assessed for detecting nonlinearity from different sources. The experimental setup involves placing two magnets on opposite sides of a plate’s free end to induce localised nonlinearity through magnet attraction. A low force magnitude of random excitation is employed to identify the frequency range of the first vibration mode using an electromagnetic shaker. Subsequently, RCT is performed within this range to measure the nonlinear forced response. Frequency response functions are measured at ten different controlled displacement amplitudes at the driving point. The analysis observed a symmetry curve of response in the measured FRFs. The results indicate that nonlinear hardening is detected at structures with localised magnet attraction. In conclusion, the reliability of applying the RCT approach for detecting nonlinearity from magnet attraction is achieved due to the absence of a jump issue in FRFs.
      1