# Development and Application of a Novel Tsunami Monitoring System Based on Submerged Mooring
## 3 Key Technologies
### Data Collection and Tsunami Wave Identification Methods  
The tsunami monitoring system completes pressure data collection, tsunami wave identification, and communication control through data acquisition units deployed underwater. After the system is deployed, it can be divided into deployment mode, standard mode, and tsunami alarm mode according to different data processing methods. The system is in deployment mode for 3 h after entering the water, at which point the pressure data have been stably obtained for a certain period of time; the standard mode mainly realizes the collection of pressure data and the determination of tsunami waves. The main implementation method is used to identify tsunami waves by inverting tidal level data based on historical pressure data and measured data and comparing them. The system status information is transmitted back every hour. The tsunami alarm mode detects tsunami waves and sends the original data back to the remote data center. The following is a detailed introduction to the method of determining tsunami waves and the data transmission scheme:  
(1) Use pressure sensors to obtain deep-sea seabed pressure data for a period of time (reaching data stability within 3 h after deployment), in order to obtain the corresponding tidal level values for the time period.  
(2) Perform real-time quality control processing of raw data on the data collector end. Firstly, coarse-grained removal of formatting errors and data exceeding the threshold in the original data is performed, and further detection is carried out using the three-sigma method within a 1 h data range. Discrete independent data are removed. Use interpolation polynomials to fit astronomical tidal waveforms, collect data at different times, use time as the interpolation point on the \(x\)-axis, and predict the tidal level value H' (t') for the next time t'.  
\[H^{\prime}(t^{\prime})=\sum_{i=0}^{3}w(i)\cdot H_{i}^{*}(t-p/2-i\Delta t)\]  
The tsunami processing algorithm is shown in Figure 2, where t is the current time, t' is the predicted time (data 5.25 min after the current time t), p is the duration of the arithmetic mean method (10 min), and \(\Delta\)t is the interval time (1 h) between two adjacent interpolation points. Set the end time of monitoring to the current time t = 0. Average the pressure data within the first p minutes before the current time t, \(\Delta\)t, 2\(\Delta\)t, and 3\(\Delta\)t to obtain four tidal levels: H\({}_{0}^{*}\), H\({}_{1}^{*}\), H\({}_{2}^{*}\), and H\({}_{3}^{*}\).  
(3) Measure the deep-sea seabed pressure data at time t' to obtain the measured tidal level value at time t'.  
(4) Calculate the difference between the measured tidal level value and the predicted tidal level value. Based on continuous multiple difference data, we determine whether there is tsunami wave propagation. If tsunami wave transmission is detected, activate the tsunami warning mode for feedback alarm. The system workflow is shown in Figure 3.  
Figure 3: Data collection and processing in the tsunami monitoring system.  
Figure 2: Schematic diagram of tsunami processing algorithm.