Deformation monitoring procedure and software system using robust method and similarity transformation for Iskandarnet

Abstract

Recently, repeated earthquake such as Sumatra earthquake (June 05 2012), Taitung earthquake (June 06 2012) and Honshu earthquake (June 08 2012) have brought the disastrous impacts on their nation and neighbourhood. Due to the geographical location of Malaysia proximity to Indonesia, only people in high rise buildings feel the tremors. However, with increased seismic activity in the region following a series of major earthquakes in recent years, deformation monitoring is desperately needed to monitor the physical facilities such as dams, bridges, Light Rail Transit (LRT), monorail networks and other major structures. A reliable deformation monitoring procedure and system has to be developed to ensure the displacements of structures are within the safety threshold. Among the available technologies, Global Positioning System (GPS) is increasingly being used for deformation monitoring. GPS sensors are able to provide fully-automated and continuous sub-centimetre displacement detection in real time. Therefore, a newly established GPS Continuous Operating Reference Station (CORS) network called ISKANDARnet was utilised to detect deformation displacement in Iskandar, Johor, Malaysia. In this study, three GPS CORS from ISKANDARnet had been utilised as the object monitoring stations along with four nearby International GNSS Services (IGS) stations (i.e.: NTUS (Singapore), XMIS (Christmas Island, Australia), COCO (Keeling Island, Australia) and PIMO (Quezon City, Philippines)) as the reference monitoring stations. GPS data was downloaded from File Transfer Protocol (FTP) server and processed by the high precision GPS processing software module, called Bernese Processing Engine (BPE). Subsequently, a continuous deformation analysis software system named ConDAS was developed using Matrix Laboratory (MATLAB) programming language to conduct a continuous two-epoch deformation analysis. By implementing the Iteratively Weighted Similarity Transformation (IWST) and final S-Transformation method, ConDAS is able to determine the measured displacement vector is statistically significant. The unstable object stations were identified and the displacement vectors were computed. The fluctuation of deformation displacement was visualised on-screen proportional to the associated time series results. The results obtained from deformation analysis of ISKANDARnet shows no significant displacement and all stations are stable within the threshold over these two years since 2010. Through the research, a robust deformation monitoring procedure and software system was attained which contributes to the current regional deformation studies in Malaysia.