Micro-peat as a potential low-cost adsorbent material for COD and NH3-N removal

Micro-peat (M-P) was demonstrated in the present study as a potential low cost natural adsorbent for the removal of COD and ammoniacal nitrogen (NH3-N) from landfill leachate. A series of batch experiments were carried out under fixed conditions and the influence of mixture ratio was investigated. The characteristics of leachate were then determined. Results indicated that leachate is non-biodegradable with high concentration of COD (2739.06 mg/L), NH3-N (1765.34 mg/L) and BOD5/COD ratio (0.09). The optimum ratio for activated carbon (AC) and M-P in the removal of COD and NH3-N obtained were at 2.5:1.5 (87%) and 1.0:3.0 (65%) respectively. The low-cost natural adsorbent used in the present investigation is an attractive alternative to the conventional adsorbent (AC). Thus, M-P can be appropriated for use in leachate treatment that could be cost-effective due its local availability and adsorption property

To develop an efficient variable speed compressor motor system

This research presents a proposed new method of improving the energy efficiency of a Variable Speed Drive (VSD) for induction motors. The principles of VSD are reviewed with emphasis on the efficiency and power losses associated with the operation of the variable speed compressor motor drive, particularly at low speed operation.The efficiency of induction motor when operated at rated speed and load torque is high. However at low load operation, application of the induction motor at rated flux will cause the iron losses to increase excessively, hence its efficiency will reduce dramatically. To improve this efficiency, it is essential to obtain the flux level that minimizes the total motor losses. This technique is known as an efficiency or energy optimization control method. In practice, typical of the compressor load does not require high dynamic response, therefore improvement of the efficiency optimization control that is proposed in this research is based on scalar control model.In this research, development of a new neural network controller for efficiency optimization control is proposed. The controller is designed to generate both voltage and frequency reference signals imultaneously. To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. The simulation of the proposed controller for variable speed compressor is presented. The results obtained clearly show that the efficiency at low speed is significant increased. Besides that the speed of the motor can be maintained. Furthermore, the controller is also robust to the motor parameters variation. The simulation results are also verified by experiment

Data-driven online temperature compensation for robust field-oriented torque-controlled induction machines

Squirrel-cage induction machines (IMs) with indirect field-oriented control are widely used in industry and are frequently chosen for their accurate and dynamic torque control. During operation, however, temperature rises leading to changes in machine parameters. The rotor resistance, in particular, alters, affecting the accuracy of the torque control. The authors investigated the effect of a rotor resistance parameter mismatch in the control algorithm on the angular rotor flux misalignment and the subsequent deviation of stator currents and motor torque from their setpoints. Hence, an online, data-driven torque compensation to eliminate the temperature effect is proposed to enable robust torque-controlled IMs. A model-based analysis and experimental mapping of the temperature effect on motor torque is presented. A temperature-torque lookup-table is subsequently implemented within the control algorithm demonstrating the ability to reduce the detrimental effect of temperature on torque control. Experimental results on a 5.5 kW squirrel-cage induction motor show that the proposed data-driven online temperature compensation method is able to reduce torque mismatch when compared to having no temperature compensation. Up to 17% torque mismatch is reduced at nominal torque and even up to 23% at torque setpoints that are lower than 20% of the nominal torque. A limited torque error of <1% remains in a broad operating range

Detection and Diagnosis of Motor Stator Faults using Electric Signals from Variable Speed Drives

Motor current signature analysis has been investigated widely for diagnosing faults of induction motors. However, most of these studies are based on open loop drives. This paper examines the performance of diagnosing motor stator faults under both open and closed loop operation modes. It examines the effectiveness of conventional diagnosis features in both motor current and voltage signals using spectrum analysis. Evaluation results show that the stator fault causes an increase in the sideband amplitude of motor current signature only when the motor is under the open loop control. However, the increase in sidebands can be observed in both the current and voltage signals under the sensorless control mode, showing that it is more promising in diagnosing the stator faults under the sensorless control operation

Enhancing cosmetology students’ communication skills in Malaysian upper secondary vocational education program

The quality of beauty treatment services will be evaluated by the clients subjectively whether they are satisfied or otherwise with the services provided. However, the reports and complaints related to customer dissatisfaction when receiving beauty treatment services at beauty centers are increasing. Unfortunately, the suggestions for improvement from the previous studies are still insufficient. Therefore, this study was conducted to examine the importance of proficiency in communication skills and the need for training modules in the teaching and learning process (T&L). It is required to improve communication skills among cosmetology students for Upper Secondary Vocational Education Program (USVEP) in beauty arts course. The data were collected through the interview method on six USVEP teachers and a beauty salon entrepreneur. The findings of the study found that the proficiency in communication skills among the cosmetology students is an important requirement for employers in selecting their employees, increasing customer loyalty and the customer’s frequency to visit beauty salons, and maintaining the excellent performance of cosmetology students in the workplace. In addition, there is also a high demand for the development of communication skills training modules in helping cosmetology students to constantly updated with new knowledge and skills needed from time to time. Therefore, adequate training is required to improve the competency in communication skills among the cosmetology students

Three-Phase Induction Motor Speed Estimation Using Recurrent Neural Network

In induction motor speed control method, the development of the field-oriented control (FOC) algorithm which can control torque and flux separately enables the motor to replace many roles of DC motors. Induction motor speed control can be done by using a close loop system which requires a speed sensor. Referring to the speed sensor weaknesses such as less accurate of the measurement, this is due to the placement of the sensor system that is too far from the control system. Therefore, a speed sensorless method was developed which has various advantages. In this study, the speed sensorless method using an artificial neural network with recurrent neural network (RNN) as speed observer on three-phase induction motor has been discussed. The RNN can maintain steady-state conditions against a well-defined set point speed, so that the observer is able and will be suitable if applied as input control for the motor drives. In this work, the RNN has successfully estimated the rotor flux of the induction motor in MATLAB R2019a simulation as about 0.0004Wb. As based on speed estimation error, the estimator used has produced at about 26.77%, 8.7% and 6.1% for 150rad/s, 200rad/s and 250rad/s respectively. The future work can be developed and improved by creating a prototype system of the induction motor to get more accurate results in real-time of the proposed RNN observer

FUZZY OPTIMIZATION FOR SPEED CONTROLLER OF AN INDIRECT VECTOR CONTROLLED INDUCTION MOTOR DRIVE USING MATLAB SIMULINK

The aim of this paper is to investigate the performance of a Fuzzy-Logic-Controller (FLC) which is applied on three-phase induction motor drive system for high-performance industrial applications. In this paper, the FLC is used as a speed controller to replace the conventional PI speed controller. The FLC will determine the time of switching on the Space Vector Pulse Width Modulation (SVPWM) inverter that supplies power to drive the induction motor considering variable direct and quadrature axis inductances. The performance of the suggested technique has been simulated and developed using MATLAB/ SIMULINK for dynamic operating condition, such as certain change in command speed, and step change in load. The simulation result shows the feasibility of the proposed technique in order to improve the speed response and low torque ripple on three phase induction motor drive