Pengesanan pegerakan struktur menggunakan model autoregresi purata bergerak bersepadu

Abstract

Global Positioning System (GPS) has been widely used to monitor large engineering structures such as dams, bridges, towers and high rise buildings. There are several GPS methods that can be used for coordinate determination including Real Time Kinematic (RTK-GPS). This method uses carrier phase observation in real time to determine position coordinates. The coordinates produced by this method can indicate the displacement due to vibration caused by several factors such as temperature change, wind loading, earthquakes, landslides and other environmental factors. In this study, a technique based on time domain has been developed to analyze the response of a structure or an object. This technique uses time series algorithm to detect movements that occur and produces forecasting of movements of the object. The vibration signal obtained by the GPS sensor is used to model Autoregressive Integrated Moving Average (ARIMA) time series based on Box-Jenkins methodology. This method is used for making forecasting and it uses iterative approach to identify appropriate model. ARIMA model can be accepted after passing through four main steps that is identification of model, estimation of model parameter, model checking and forecasting of model. In this study, the Minitab software was used to develop the ARIMA model which can be used for forecasting of observed GPS data. The results of this study were obtained using the ARIMA model for the X, Y and Z axes. Also the results of this study proved that ARIMA model is capable of detecting movement of structures based on analyses that have been carried out.