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De-noising of GPS structural monitoring observation error using wavelet analysis

机译:基于小波分析的GPS结构监测观测误差去噪

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In the process of the continuous monitoring of the structure's state properties such as static and dynamic responses using Global Positioning System (GPS), there are unavoidable errors in the observation data. These GPS errors and measurement noises have their disadvantages in the precise monitoring applications because these errors cover up the available signals that are needed. The current study aims to apply three methods, which are used widely to mitigate sensor observation errors. The three methods are based on wavelet analysis, namely principal component analysis method, wavelet compressed method, and the de-noised method. These methods are used to de-noise the GPS observation errors and to prove its performance using the GPS measurements which are collected from the short-time monitoring system designed for Mansoura Railway Bridge located in Egypt. The results have shown that GPS errors can effectively be removed, while the full-movement components of the structure can be extracted from the original signals using wavelet analysis.
机译:在使用全球定位系统(GPS)连续监视结构的状态属性(例如静态和动态响应)的过程中,观测数据中不可避免地会出现错误。这些GPS误差和测量噪声在精确监视应用中具有其缺点,因为这些误差掩盖了所需的可用信号。当前的研究旨在应用三种方法,这些方法被广泛用于减轻传感器观察误差。这三种方法基于小波分析,分别是主成分分析法,小波压缩法和去噪法。这些方法用于对GPS观测误差进行消噪,并使用GPS测量值来证明其性能,该GPS测量值是从为埃及曼苏拉铁路桥设计的短时监测系统收集的。结果表明,可以使用小波分析有效地消除GPS误差,同时可以从原始信号中提取结构的全部运动分量。

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