3 research outputs found

    Simulation study on HST distribution for ONAN oil-filled transformer

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    Advanced monitoring system and preventive maintenance introduced on serviced transformer successfully reducing the equipment malfunction and breakdown rate. However, faults that occur and developed inside the transformer can be very unpredictable. One of the measures can be taken is to analyse the hottest spot temperature (HST) of the transformer, because high temperature will affect transformer insulation system performance and its life-span. HST distribution study on the transformer surface body can give better understanding on how HST will behave at inner and outer transformer surface tank, so that it can be correlated to the actual temperature inside the transformer. Therefore, this paper presents a simulation study on 100 KVA ONAN oil-filled type of distribution transformer with three types of HST intensity. Result shows that temperature distribution projectile is tending to go upwards in the insulation oil and inward into the winding. Moreover, location of HST can be identified by comparing the temperature distribution plot with and without HST

    Grading ring effect on surface charge distribution for polymer insulator

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    In the electrical power system, the insulator is used on the transmission line to separate the conductor from the transmission tower [1]. It is accepted that insulators under service are subjected to electrical stress due to environment. Uncertainty of environmental conditions can cause charge to be trapped on the insulator surface due to the existence of contamination. The excess charge distributed over the region of surface called surface charge distribution. The accumulation of surface charge on the insulator surface may alter the local electric field distribution and lead to degradation process [2]. Hence, it is important to observe the distribution of surface charge since it has a close relationship with the electrical performance of insulation materials [3

    Risk assessment of design components of building construction

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    Lack of designer's knowledge of construction safety risks and HSE personnel's knowledge of structural designs and means and methods of construction have been highlighted as significant barriers to the implementation of design for construction safety. These barriers often result in poor collaboration among designers and HSE personnel in addressing safety issues that lead to accidents and frequent work stoppages. This study explored the ability of HSE officers, engineers and superintendents to recognize and assess risk associated with constructing structural components of a building (foundation, columns, walls, beams and roofs). The objective was to determine how consensus is risk perceived among the three groups of field personnel. The paper used a quantitative methodology that evaluates safety risks related to performing construction activities to supports designers to carry out construction designs using a risk assessment-based approach. The methodology compares cumulative risks of five designs and ranks the severity level of each design. The methodology also compares risk perception among HSE personnel, engineers and superintendent. Using this method of risk assessment will identify significant risks during design stage and highlight them in advance. Thus, a range of risk elimination or mitigation measures will be implemented before and during construction. The study was done with a survey questionnaire, and 40 construction field personnel (12 HSE, 14 superintendents and 12 engineers) were asked to evaluate risk's level of severity and time of exposure for each activity. Data collected were analysed with SPSS Statistics using descriptive statistics, general linear models (Multivariate) and Bivariate correlations (Pearson and Spearman). The results of the analysis showed that roof construction was perceived to have the highest risk followed by beam, foundation, wall and column. The differences in risk perceptions among the respondents were found to be non-significant statistically
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