Research on Wavelet Threshold Denoising Method for UWB Tunnel Personnel Motion Location

Abstract

In the process of tunnel construction, the problems of strong sealing, inconvenient communication, and harsh environment pose a serious threat to the personal safety of construction workers. erefore, personnel positioning technology has important application value in tunnel safety construction. A special environment for tunnel personnel positioning and the ultrawideband (UWB) positioning system are affected by personnel movement, which leads to the problem of lowering positioning accuracy. A wavelet threshold denoising method for motion positioning of people in tunnels is proposed. e positioning algorithm of the method adopts a three-sided positioning algorithm based on symmetric double-sided two-way ranging. e wavelet analysis is used to decompose the motion signal of the personnel in the tunnel, and the low frequency coefficient and high frequency coefficient of the signal are decomposed to determine the influence of the motion noise of the personnel on the UWB positioning. e soft threshold function and the hard threshold function are, respectively, selected to perform wavelet threshold denoising on the motion positioning result in the tunnel. According to the denoising effect, the db5 wavelet 5-layer decomposition, under the heuristic threshold estimation criterion, the soft threshold function denoising is the best denoising method. e verification by the positioning experiment shows that the method is suitable for tunnel personnel positioning. e wavelet threshold denoising method can weaken the influence of outliers in the motion positioning of UWB personnel and improve the positioning accuracy.

Safety enablers using emerging technologies in construction projects: empirical study in Malaysia

“…Current statistics indicate that the construction industry is considerably lagged behind other major industries in technology adoption and implementation (Bosch-sijtsema et al , 2021). Previous studies suggested that incorporating advanced technology into safety management practices could offer valuable opportunities for enhancing construction safety (Asadzadeh et al , 2020; Liu et al , 2020; Martinez et al , 2020; Nnaji et al , 2020). Unfortunately, despite a plethora of safety technology-related studies, implementation of safety technologies are still limited in construction(Nnaji et al , 2019), more so in the case of the developing world (Enshassi et al , 2016; Ghansah et al , 2021; Yusof et al , 2017).…”

Research on Indoor Positioning Algorithm Based on SAGA-BP Neural Network

“…Since GPS(Global Positioning System) signals cannot be received in an indoor environment, various indoor positioning technologies are required [1]. Common indoor wireless positioning technologies include: Wi-Fi positioning [2], Bluetooth technology [3], UWB [4], RFID, infrared positioning, RFID, ZigBee technology [5], ultrasonic and geomagnetic technology [6], etc. The current positioning algorithms mainly include nearest neighbor method [7], centroid positioning method [8], trilateral positioning method [9], triangulation method [10], fingerprint positioning method [11], dead reckoning algorithm [12], particle Group positioning algorithm [13] and neural network positioning algorithm [14], etc.…”