Ezreen Farina Shair

Open switch faults analysis in voltage source inverter using spectrogram

The performance and effects is critical factor in industry, especially usage power inverter such as motor, switching and control circuit. Until now, the statistic of effects still increase in the application. In order to overcome this, the spectrogram technique is used to represent the signals in time frequency representation (TFR). This paper introduces time-frequency distribution (TFD) technique for detecting and identifying the open circuit fault in application of inverter. The condition monitoring is based on time-frequency distribution. Since Fast Fourier Transform (FFT) is one of the techniques to analyze the signal, but it has some limitations in non-stationary signal. From TFR the parameters such as root means square voltage (Vrms), total waveform distortion (TWD), total harmonic distortion (THD) and total non-harmonics (TnHD) for voltage source inverter (VSI) are used to identify the characteristic of the signals. The result shows that spectrogram technique capable to identify and evaluate the information of voltage source inverter (VSI). The proposed technique is verified as simulation results.

Cuckoo Search Approach for Cutting Stock Problem

Cutting Stock Problem has been used in many industries like paper, glass, wood and etc. Cutting Stock Problem has helped industries to reduce trim loss and at the same time meets the customer’s requirement. The purpose of this paper is to develop a new approach which is Cuckoo Search Algorithm in Cutting Stock Problem. Cutting Stock Problem with Linear Programming based method has been improved down the years to the point that it reaches limitation that it cannot achieve a reasonable time in searching for solution. Therefore, many researchers have to turn to metaheuristic algorithms as a solution to the problem which also makes these algorithms become famous. Cuckoo Search Algorithm is selected because it is a new algorithm and outperforms many algorithms. Hence, this paper intends to experiment the performance of Cuckoo Search in Cutting Stock Problem.

sEMG signals analysis using time-frequency distribution for symmetric and asymmetric lifting

Following the industrial revolution, a third of the worlds economic output is derived from manufacturing industries. In the manufacturing industry sectors, manual lifting is commonly practiced even though mechanized material handling equipment are provided. Due to this repetitive lifting behavior, it will contributes to muscle fatigue and low back pain that can lead to work efficiency and low productivity. This will cause great losses to the company and to the country. The purpose of this study is to investigate changes in the surface electromyography (sEMG) signals during repetitive manual lifting for different twist angle values. The EMG signals are taken from right Biceps Branchii of five healthy subjects (age range 21 - 25 years) while performing symmetric and asymmetric lifting of twist angle 0° and 90° at lifting height of 140 cm with load mass of 10 kg. The analysis is done by applying time-frequency distribution (TFD) which is spectrogram technique to represent the EMG signal in time-frequency representation (TFR) before displaying the instantaneous voltage, Vrms (t) value. This study found that symmetric lifting requires less force to lift the load and that asymmetric lifting has faster tendency to experienced fatigue. This study concludes that the twist angle has a significant influence to the muscle performance of right Biceps Branchii.