# Spatiotemporal Monitoring and Evaluation Method for Sand-Filling of Immersed Tube Tunnel Foundation
###### Abstract  
The sand-filling method has been widely used in immersed tube tunnel engineering. However, for the problem of monitoring during the sand-filling process, the traditional methods can be inadequate for evaluating the state of sand deposits in real-time. Based on the high efficiency of elastic wave monitoring, and the superiority of the backpropagation (BP) neural network on solving nonlinear problems, a spatiotemporal monitoring and evaluation method is proposed for the filling performance of foundation cushion. Elastic wave data were collected during the sand-filling process, and the waveform, frequency spectrum, and time-frequency features were analysed. The feature parameters of the elastic wave were characterized by the time domain, frequency domain, and time-frequency domain. By analysing the changes of feature parameters with the sand-filling process, the feature parameters exhibited dynamic and strong nonlinearity. The data of elastic wave feature parameters and the corresponding sand-filling state were trained to establish the evaluation model using the BP neural network. The accuracy of the trained network model reached 93%. The side holes and middle holes were classified and analysed, revealing the characteristics of the dynamic expansion of the sand deposit along the diffusion radius. The evaluation results are consistent with the pressure gauge monitoring data, indicating the effectiveness of the evaluation and monitoring model for the spatiotemporal performance of sand deposits. For the sand-filling and grouting engineering, the machine-learning method could offer a better solution for spatiotemporal monitoring and evaluation in a complex environment. insufficient filling of the foundation [9]. Such problems as the gap between the tunnel floor and foundation growth could occur, causing uneven settlement deformation of the immersed tube tunnel [10; 11]. At present, the methods for evaluating the sand deposit state during construction are mainly indirect ones, including the sand quantity control, pressure gauge monitoring, and pipe levelness measurement. The traditional indirect monitoring methods are realized by controlling the monitoring indicators, including sand quantity, sand-filling pressure, pipe displacement, etc. Sand quantity control method evaluates the sand-filling state by comparing the sand-filling quantity with its design value. By setting a pressure gauge at the position of the sand-filling hole, the pressure gauge monitoring method evaluates the sand-filling state based on the pressure change. Pipe levelness measurement method measures the settlement and uplift state of the pipe section through a level gauge. The traditional methods have single monitoring indicators and cannot realize spatiotemporal monitoring. Especially, the diffusion radius of sand deposits cannot be evaluated effectively, leading to probable problems such as hole blocking or insufficient filling. In addition, non-destructive monitoring technology is increasingly being used in tunnels. In recent years, monitoring research on the tunnel under complex environmental conditions developed rapidly. [PERSON] et al. [12] used a fibreglass reinforced plastic bolt as a probe in tandem with an anchor-head dynamometer to monitor the internal force of the rocks surrounding a mine-shield tunnel for initial support. [PERSON] et al. [13] used the P wave to monitor the construction process of sand-filling for the first time on the basis of a physical immersed tube tunnel model test. [PERSON] [14] adopted the impact-echo method to detect the voids behind the lining in tunnels and established that a tunnel void can be evaluated through the vibration energy (amplitude and duration) in the time domain, the resonance frequency and dynamic stiffness in the frequency domain, and the energy distribution in the time-frequency domain. Among the above methods, elastic wave tests with strong penetrability are widely used in the field of civil engineering monitoring and detection as nondestructive testing technology [15; 16].