Identification and forewarning of GNSS deformation information based on a modified EWMA control chart

Abstract

Abstract Safety of people's lives and property is an unquestionably priority of any plan for disaster mitigation and its societal impact. This study reports on a new mathematical method to process and analysis the global navigation satellite system (GNSS) data to effectively monitoring deformation of buildings. A new method combining the ensemble-integrated empirical mode decomposition (EEMD) algorithm and the EWMA control chart is proposed to identify and alert GNSS deformation information. This new approach tries to overcome the limitations affecting some classical methods like cumulative sum (CUSUM) control chart, which has a poor detection effect on continuous small offset deformation data in GNSS time series, and considering that the noise will be a certain degree inhibit the deformation information, thus affect its recognition results. The experimental results show that the recognition accuracy of the EWMA control chart method and the modified EWMA method is higher than that of the CUSUM control chart method. The modified EWMA method has the best inspection capability. The use of a modified EWMA control chart improves the accuracy of deformation information identification and early warning, which reduces the false alarm rate and missing alarm rate of disaster early warning.