Research Output
A study on copper and galvanized grounding performance using palm oil fuel ash as new additive material
Prototyping a RF signal-based lightning warning device using with Internet of Things (IOT) integration
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Publication
This paper aimed to study the improvement of grounding performance by reducing the grounding electrode resistance using palm oil fuel ash as the backfill. This is achieved by mixing the soil with a specific portion of palm oil fuel ash and obtains the grounding electrode resistance value by using Three Pin Method. In order to obtain the grounding electrode resistance, the mixture of palm oil fuel ash and soil were compacted and installed with electrodes. Two types of electrodes were connected to measuring device which is Kyoritsu Digital Earth Tester Model 4105A and grounding electrode resistance values were displayed. The two types of electrodes used in this study were copper and galvanized steel electrodes. It was found that by adding palm oil fuel ash to the soil, the grounding performance can be improved to at least 90% and above for both copper and galvanized steel electrodes. The palm oil fuel ash is very effective in improving the grounding performance at low cost and environmentally friendly.
Publication
Lightning had caused at least 25, 000 deaths worldwide each year. The study aims to investigate the induced voltage generated by lightning strikes using a lightning detector. Proteus software was employed to simulate the main board of the lightning detector before fabrication. The lightning detector was designed as a radio frequencies receiver and it was tuned to the level (300 kHz to 500 kHz) which enabled it to receive signals from lightning strikes. A lightning simulator was designed using various resistance (100 Ω to 200 Ω) to test the functionality of a lightning detector in order to validate the accuracy of the proposed model. This lightning detector could be activated whenever a small induced voltage (0.2 V and above) were generated by lightning events occurred within 10 km from the detector. This detector captures both the induced voltage and the time difference detected lightning discharge and its sound for further analysis. The time to thunder method was employed to find the estimated lightning discharges distances in parallel to this system in order to validate the current lightning detector. The accuracy of the lightning detector was found to be 88.03%.The analysed data were delivered to the user's smartphone using cloud system.