Sand site liquefaction monitoring and early warning system

Abstract

This invention provides a monitoring and early warning system for liquefaction of sandy soil sites, comprising distributed wireless sensing nodes, a regional signal relay receiver, a data processing center, and an early warning terminal. The distributed wireless sensing nodes include an underground shell, a horizontal plate, a wireless signal transmitter, a power supply device, a vibration acceleration sensor, a pore water pressure sensor, and a filter plate. The system primarily uses the pore water pressure sensor, supplemented by the vibration acceleration sensor. Combined with the regional signal relay receiver and the data processing center, it enables real-time acquisition, transmission, and analysis of pore pressure and vibration signals within the region. Furthermore, it utilizes a wavelet packet energy analysis algorithm to extract the energy characteristics of the vibration signals. By setting energy change thresholds, it achieves the identification and graded early warning of earthquake precursor signals, significantly improving the accuracy and timeliness of earthquake monitoring and early warning. This system is suitable for earthquake monitoring and early warning scenarios in areas prone to sandy soil liquefaction, major engineering sites, and densely populated areas.

Description

Technical Field

[0001] This invention relates to the field of earthquake monitoring technology, and in particular to a monitoring and early warning system for liquefaction of sandy soil sites. Background Technology

[0002] Earthquake disasters are characterized by their suddenness and destructiveness. Especially in key seismic fortification areas such as sandy soil liquefaction zones and major engineering sites, rapid and accurate earthquake monitoring and early warning are crucial to reducing disaster losses. Traditional earthquake monitoring relies on fixed seismic networks, which suffer from problems such as insufficient monitoring point density and signal coverage blind spots in some areas. At the same time, traditional monitoring methods are mostly based on vibration amplitude judgment, which has low accuracy in identifying non-stationary signals in the precursory stage of earthquakes and is susceptible to external noise interference, leading to false alarms or missed alarms, making it difficult to meet the needs of refined monitoring and early warning. Summary of the Invention

[0003] In view of this, the present invention proposes a sandy soil liquefaction monitoring and early warning system, which can monitor pore water pressure based on the precursor stage of earthquakes, thereby improving the reliability and accuracy of earthquake early warning.

[0004] The technical solution of this invention is implemented as follows: A sandy soil liquefaction monitoring and early warning system includes distributed wireless sensor nodes, a regional signal relay receiver, a data processing center, and an early warning terminal. Each distributed wireless sensor node includes a buried shell, a horizontal plate, a wireless signal transmitter, a power supply device, a vibration acceleration sensor, and a pore water pressure sensor. The buried shell is installed underground in the monitoring area. The horizontal plate divides the interior of the buried shell into an electrical cavity, a first detection cavity, and a second detection cavity. The wireless signal transmitter and power supply device are located in the electrical cavity. The vibration acceleration sensor is located in the first detection cavity, and the pore water pressure sensor is located in the second detection cavity. The second detection cavity has an opening on its sidewall. The power supply device powers the wireless signal transmitter, the vibration acceleration sensor, and the pore water pressure sensor. The wireless signal transmitter is connected to the regional signal relay receiver, the vibration acceleration sensor, and the pore water pressure sensor for data transmission. The data processing center is connected to the regional signal relay receiver and the early warning terminal for data transmission.

[0005] Preferably, the early warning terminal includes an audible and visual alarm, an emergency broadcast system, and a mobile terminal.

[0006] Preferably, the data processing center includes: The wavelet packet energy analysis module is used to select a suitable wavelet basis function, decompose the signals collected by the vibration acceleration sensor and the pore water pressure sensor into multiple frequency subspaces, calculate the energy value of each subspace, construct an energy feature vector, and then calculate the change amplitude of the energy feature vector per unit time to obtain the real-time energy change. The threshold warning judgment module is used to set graded thresholds based on the background vibration data and historical earthquake precursor data of the monitoring area. When the real-time energy change reaches different graded thresholds, it outputs multi-level warning instructions. The wavelet packet energy analysis module is connected to the regional signal relay collector and the threshold early warning judgment module, respectively. The threshold early warning judgment module is connected to the early warning terminal.

[0007] Preferably, the execution steps of the threshold warning judgment module include: Background vibration data and historical earthquake precursor data under the same geological conditions of the monitoring area were acquired and preprocessed. Then, the 95% confidence interval method was used to set the first-level attention threshold, the second-level early warning threshold, and the first- and third-level alarm thresholds. When the real-time energy change of the pore water pressure sensor reaches the first-level concern threshold, a first-level concern command is generated, and the sampling and analysis frequency of the vibration acceleration sensor signal is increased. When the real-time energy change of the vibration acceleration sensor reaches the secondary warning threshold, a secondary warning command is generated. When the real-time energy change of the pore water pressure sensor and the real-time energy change of the vibration acceleration sensor both reach the level 3 alarm threshold, a level 3 alarm command is generated and sent to the early warning terminal.

[0008] Preferably, the data processing center further includes: The multi-parameter collaborative analysis module is used to distinguish between effective signals and interference signals based on the data collected by the vibration acceleration sensor and the pore water pressure sensor, and to dynamically adjust the grading threshold. The multi-parameter collaborative analysis module is connected to the regional signal relay receiver and the threshold early warning judgment module respectively.

[0009] Preferably, the execution steps of the multi-parameter collaborative analysis module include: Extract the temporal characteristics of energy change in pore water pressure data and vibration acceleration data collected by vibration acceleration sensor and pore water pressure sensor within the same time window and frequency subspace; Based on the temporal characteristics of energy change, the wavelet packet cross-spectral coherence coefficient and phase difference are calculated. When the coherence coefficient is lower than the preset threshold and the phase difference does not conform to the propagation law of seismic waves in the soil, it is determined to be noise interference, and a graded threshold adjustment instruction is sent to the threshold early warning judgment module.

[0010] Preferably, the regional signal relay receiver includes a filtering unit and a multi-hop networking unit. The filtering unit is connected to the vibration acceleration sensor, the pore water pressure sensor and the multi-hop networking unit respectively. The multi-hop networking unit is connected to the data processing center.

[0011] Preferably, the distributed wireless sensing node further includes a vertical plate, a calibration pressure core, a miniature piezoelectric actuator, an elastic diaphragm, and a conductive medium. The vertical plate is disposed in the second detection cavity, dividing the second detection cavity into a measurement cavity and a calibration cavity. The opening is disposed on one side of the measurement cavity. The pore water pressure sensor is disposed in the measurement cavity with its measuring end facing the opening. The reference end of the pore water pressure sensor extends into the calibration cavity. The calibration pressure core, the miniature piezoelectric actuator, and the elastic diaphragm are all disposed in the calibration cavity. The reference end of the calibration pressure core is vacuum sealed. The elastic diaphragm is located on one side of the miniature piezoelectric actuator. The conductive medium fills the calibration cavity. The wireless signal transmitter is connected to the calibration pressure core and the miniature piezoelectric actuator for data transmission.

[0012] Preferably, the distributed wireless sensing node further includes a filter plate, a trough, an electrically controlled door, an air reservoir, and spikes. The filter plate is disposed inside the opening, the trough is disposed on the top surface of the measuring chamber with an open bottom, the electrically controlled door is rotatably disposed on the bottom surface of the trough, the air reservoir is disposed inside the trough, and the spikes are disposed on the bottom surface of the measuring chamber and located below the air reservoir. The air reservoir stores high-pressure inert gas, and the wireless signal transmitter is connected to the electrically controlled door via data transmission.

[0013] Compared with the prior art, the beneficial effects of the present invention are: Distributed wireless sensor nodes are buried underground in the monitoring area to collect vibration acceleration data and pore water pressure data. The collected data can be transmitted to a regional signal relay receiver via a wireless signal transmitter. The regional signal relay receiver can then send the data to a data processing center for monitoring and early warning. In the early stages of an earthquake, the pore water pressure data collected by the pore water pressure sensor will show anomalies. Based on this, a first-level attention command can be generated, and the system enters a real-time monitoring state. At the same time, the sampling frequency of the vibration acceleration sensor increases. If the data collected by the vibration acceleration sensor also shows anomalies, it indicates that the probability of an earthquake is high, and an early warning terminal will be issued to buy time for emergency evacuation in the monitored area. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only preferred embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of a sandy soil liquefaction monitoring and early warning system according to the present invention; Figure 2This is a schematic diagram of the regional signal relay receiver of a sandy soil site liquefaction monitoring and early warning system according to the present invention; Figure 3 This is a schematic diagram of the data processing center of a sandy soil site liquefaction monitoring and early warning system according to the present invention; Figure 4 This is a schematic diagram of the structure of a distributed wireless sensor node according to a first embodiment of a sandy soil liquefaction monitoring and early warning system of the present invention. Figure 5 This is a schematic diagram of the structure of a distributed wireless sensor node according to a second embodiment of a sandy soil liquefaction monitoring and early warning system of the present invention. Figure 6 This is a schematic diagram of the structure of a distributed wireless sensor node in a third embodiment of a sandy soil liquefaction monitoring and early warning system of the present invention. In the diagram, 1. Distributed wireless sensor node; 2. Regional signal relay receiver; 3. Data processing center; 4. Early warning terminal; 5. Buried shell; 6. Horizontal plate; 7. Wireless signal transmitter; 8. Power supply device; 9. Vibration acceleration sensor; 10. Pore water pressure sensor; 11. Filter plate; 12. Electrical cavity; 13. First detection cavity; 14. Second detection cavity; 15. Opening; 16. Wavelet packet energy analysis module; 17. Threshold early warning judgment module; 18. Multi-parameter collaborative analysis module; 19. Filtering unit; 20. Multi-hop networking unit; 21. Vertical plate; 22. Calibration pressure core; 23. Miniature piezoelectric actuator; 24. Elastic diaphragm; 25. Conducting medium; 26. Measurement cavity; 27. Calibration cavity; 28. Slot box; 29. ​​Electrically controlled door; 30. Air storage bag; 31. Spike. Detailed Implementation

[0016] To better understand the technical content of this invention, a specific embodiment is provided below, and the invention will be further described in conjunction with the accompanying drawings.

[0017] See Figures 1 to 4The first embodiment provides a sandy soil liquefaction monitoring and early warning system, including a distributed wireless sensor node 1, a regional signal relay receiver 2, a data processing center 3, and an early warning terminal 4. The distributed wireless sensor node 1 includes a buried housing 5, a horizontal plate 6, a wireless signal transmitter 7, a power supply device 8, a vibration acceleration sensor 9, and a pore water pressure sensor 10. The buried housing 5 is buried underground in the monitoring area. The horizontal plate 6 divides the interior of the buried housing 5 into an electrical cavity 12, a first detection cavity 13, and a second detection cavity 14. The wireless signal transmitter 7 and the power supply device 8 are equipped with… The vibration acceleration sensor 9 is located in the first detection chamber 13, and the pore water pressure sensor 10 is located in the second detection chamber 14. The second detection chamber 14 has an opening 15 on its side wall. The power supply device 8 supplies power to the wireless signal transmitter 7, the vibration acceleration sensor 9, and the pore water pressure sensor 10. The wireless signal transmitter 7 is connected to the regional signal relay receiver 2, the vibration acceleration sensor 9, and the pore water pressure sensor 10, respectively. The data processing center 3 is connected to the regional signal relay receiver 2 and the early warning terminal 4, respectively.

[0018] This invention discloses a sandy soil liquefaction monitoring and early warning system for earthquake monitoring and early warning. Multiple distributed wireless sensor nodes 1 are buried underground in the monitoring area, and a regional signal relay receiver 2 is set at the center of each monitoring area. A data processing center 3 is set up in the city center. The distributed wireless sensor nodes 1 are pre-buried in the soil at different depths in the seismic fortification area, enabling them to capture vibration responses and pore water data at different depths. The collected data is then transmitted to the regional signal relay receiver 2 for preliminary filtering and noise reduction to overcome signal distortion and interference caused by long-distance transmission. The processed data is then sent to the data processing center 3, which is responsible for receiving and analyzing global information and issuing early warning commands. When an earthquake is deemed highly probable, an early warning command is sent to the early warning terminal 4, which can then trigger an alarm, providing the monitoring area with time for emergency evacuation.

[0019] The main data acquisition components within the distributed wireless sensing node 1 are a vibration acceleration sensor 9 and a pore water pressure sensor 10. Its underground housing 5 is divided by a horizontal plate 6 into an electrical cavity 12, a first detection cavity 13, and a second detection cavity 14 arranged from top to bottom. The vibration acceleration sensor 9 is located in the first detection cavity 13 to collect vibration signals from the soil, while the pore water pressure sensor 10 is located in the second detection cavity 14 to collect pore water pressure in deep soil. To ensure accurate collection of pore water pressure data, an opening 15 is provided on the side wall of the second detection cavity 14, allowing the pore water pressure sensor 10 to directly contact the underground soil and collect pore water pressure data. The pore water pressure data and vibration acceleration data can be transmitted via a wireless signal transmitter 7 to a regional signal relay receiver 2, and then monitored and alerted by the data processing center 3.

[0020] During the precursory phase of an earthquake, pore water pressure can exhibit significant abrupt changes earlier in deep soil and rock masses during seismic wave propagation. It is more sensitive to deep dynamic responses than vibration signals. Therefore, when a sudden change in pore water pressure data is detected, the system can enter an alert state. When the vibration signal collected by the subsequent vibration acceleration sensor 9 also shows a sharp change, it indicates a high probability of an earthquake, and an official alarm can be issued through the early warning terminal 4. By using pore water pressure as the primary indicator during the precursory phase, supplemented by vibration signals collected by the vibration acceleration sensor 9, earthquake monitoring and early warning can be conducted, improving the accuracy and timeliness of monitoring and early warning. This approach is suitable for earthquake monitoring and early warning scenarios in areas prone to sand liquefaction, major engineering sites, and densely populated areas.

[0021] Preferably, the early warning terminal 4 includes an audible and visual alarm, an emergency broadcast system, and a mobile terminal.

[0022] The early warning terminal 4 can be set up in the monitoring area or near the data processing center 3. It can also be a mobile terminal. When it is determined that an earthquake is likely to occur, early warning can be issued through sound and light prompts, broadcast notifications, and mobile phone push notifications.

[0023] Preferably, the data processing center 3 includes: The wavelet packet energy analysis module 16 is used to select an appropriate wavelet basis function, decompose the signals collected by the vibration acceleration sensor 9 and the pore water pressure sensor 10 into multiple frequency subspaces, calculate the energy value of each subspace, construct an energy feature vector, and then calculate the change amplitude of the energy feature vector per unit time to obtain the real-time energy change. The threshold warning judgment module 17 is used to set graded thresholds based on the background vibration data and historical earthquake precursor data of the monitoring area. When the real-time energy change reaches different graded thresholds, it outputs multi-level warning instructions. The wavelet packet energy analysis module 16 is connected to the regional signal relay collector 2 and the threshold early warning judgment module 17, respectively. The threshold early warning judgment module 17 is connected to the early warning terminal 4.

[0024] The data processing center 3 includes a wavelet packet energy analysis module 16 and a threshold early warning judgment module 17. The wavelet packet energy analysis module 16 can decompose the vibration acceleration data and pore water pressure data, construct energy feature vectors, and calculate the corresponding real-time energy change. The real-time energy change can then be sent to the threshold early warning judgment module 17. By comparing it with different graded thresholds, corresponding multi-level early warning instructions are obtained, and corresponding measures are taken based on different early warning instructions.

[0025] Preferably, the execution steps of the threshold warning judgment module 17 include: Background vibration data and historical earthquake precursor data under the same geological conditions of the monitoring area were acquired and preprocessed. Then, the 95% confidence interval method was used to set the first-level attention threshold, the second-level early warning threshold, and the first- and third-level alarm thresholds. When the real-time energy change of the pore water pressure sensor 10 reaches the first-level concern threshold, a first-level concern command is generated, and the sampling and analysis frequency of the vibration acceleration sensor 9 signal is increased. When the real-time energy change of vibration acceleration sensor 9 reaches the secondary warning threshold, a secondary warning command is generated; When the real-time energy change of the pore water pressure sensor 10 and the real-time energy change of the vibration acceleration sensor 9 both reach the level 3 alarm threshold, a level 3 alarm command is generated and sent to the early warning terminal 4.

[0026] The threshold warning judgment module 17 sets three thresholds using the 95% confidence interval method: a first-level attention threshold, a second-level warning threshold, and a third-level alarm threshold. Since pore water pressure will show significant changes relatively early during the propagation of seismic waves, the first-level attention threshold is used to compare with the real-time energy change calculated from the pore water pressure data collected by the pore water pressure sensor 10. When the real-time energy change is greater than the first-level attention threshold, a first-level attention command can be output, and the entire system will enter an alarm state. At the same time, the sampling and analysis frequency of the vibration acceleration sensor 9 signal is increased to improve the accuracy and reliability of monitoring.

[0027] After the Level 1 concern command is issued, the real-time energy change of the vibration acceleration sensor 9 is continuously compared with the Level 2 warning threshold. When the Level 2 warning threshold is reached, it is determined that there are clear earthquake precursor characteristics, thereby generating a Level 2 warning command and triggering the Level 2 warning.

[0028] After the secondary warning is triggered, the real-time energy change of the pore water pressure sensor 10 and the real-time energy change of the vibration acceleration sensor 9 can be compared with the third-level alarm threshold. When both exceed the preset third-level alarm threshold, a third-level alarm command is generated and an alarm is triggered through the warning terminal 4, thereby buying time for emergency evacuation in the monitored area.

[0029] Preferably, the data processing center 3 further includes: The multi-parameter collaborative analysis module 18 is used to distinguish between effective signals and interference signals based on the data collected by the vibration acceleration sensor 9 and the pore water pressure sensor 10, and to dynamically adjust the grading threshold. The multi-parameter collaborative analysis module 18 is connected to the regional signal relay receiver 2 and the threshold early warning judgment module 17 respectively. The execution steps of the multi-parameter collaborative analysis module 18 include: Extract the temporal characteristics of energy change in pore water pressure data and vibration acceleration data collected by vibration acceleration sensor 9 and pore water pressure sensor 10 within the same time window and the same frequency subspace; Based on the time-series characteristics of energy change, the wavelet packet cross-spectral coherence coefficient and phase difference are calculated. When the coherence coefficient is lower than the preset threshold and the phase difference does not conform to the propagation law of seismic waves in the soil, it is determined to be noise interference, and a graded threshold adjustment instruction is sent to the threshold early warning judgment module 17.

[0030] To ensure the accuracy and reliability of earthquake monitoring, a multi-parameter collaborative analysis module 18 is also set up in the data processing center 3. This module can extract the energy change time-series characteristics of the pore water pressure data and vibration acceleration data collected by the vibration acceleration sensor 9 and the pore water pressure sensor 10. Based on the energy change time-series characteristics, it calculates the coherence coefficient and phase difference. When the coherence coefficient is lower than the preset threshold and the phase difference does not conform to the propagation law of seismic waves, it is judged as noise interference. This allows for the differentiation between valid signals and interference signals. After the interference signal is identified, it is fed back to the threshold warning judgment module 17. The threshold warning judgment module 17 dynamically adjusts the graded thresholds to improve the accuracy of the warning, further verify the earthquake precursor characteristics, reduce the false alarm rate, and adapt to the real-time changes in the field environment.

[0031] Preferably, the regional signal relay receiver 2 includes a filtering unit 19 and a multi-hop networking unit 20. The filtering unit 19 is connected to the vibration acceleration sensor 9, the pore water pressure sensor 10 and the multi-hop networking unit 20 respectively. The multi-hop networking unit 20 is connected to the data processing center 3.

[0032] The filtering unit 19 is used to remove noise signals such as vehicle vibration and construction disturbance, and improve the quality of the original signal. The multi-hop networking unit 20 can realize multi-level intermediate transmission of the sensing nodes, expand the monitoring coverage, and finally the regional signal relay receiver 2 can forward to the data processing center 3 through the 5G network.

[0033] Reference Figure 5 In the second embodiment shown, the distributed wireless sensing node 1 further includes a vertical plate 21, a calibration pressure core 22, a miniature piezoelectric actuator 23, an elastic diaphragm 24, and a conductive medium 25. The vertical plate 21 is disposed in the second detection cavity 14, dividing the second detection cavity 14 into a measurement cavity 26 and a calibration cavity 27. An opening 15 is disposed on one side of the measurement cavity 26. The pore water pressure sensor 10 is disposed in the measurement cavity 26, with its measuring end facing the opening 15. The reference end of the pore water pressure sensor 10 extends into the calibration cavity 27. The calibration pressure core 22, the miniature piezoelectric actuator 23, and the elastic diaphragm 24 are all disposed in the calibration cavity 27. The reference end of the calibration pressure core 22 is vacuum sealed. The elastic diaphragm 24 is located on one side of the miniature piezoelectric actuator 23. The conductive medium 25 fills the calibration cavity 27. The wireless signal transmitter 7 is connected to the calibration pressure core 22 and the miniature piezoelectric actuator 23 for data transmission.

[0034] In this embodiment, the second detection cavity 14 is divided into a measurement cavity 26 and a calibration cavity 27 by a vertical plate 21. A pore water pressure sensor 10 is installed in the measurement cavity 26. It is a piezoresistive MEMS chip type, including a measuring end and a reference end. The measuring end faces the opening 15, through which pore water enters the measurement cavity 26. The pore water pressure is collected, and the difference between the pore water pressure data and the standard pressure at the reference end is calculated. Finally, the pressure difference is converted into an electrical signal and sent to the wavelet packet energy analysis module 16. Since the distributed wireless sensing node 1 is deeply buried... In order to achieve in-situ calibration, inert silicone oil is filled in calibration chamber 27 as a conductive medium 25. When an electrical signal is sent to the micro piezoelectric actuator 23, it can generate controllable micro-displacement, which pushes the elastic diaphragm 24 to undergo quantitative deformation, compresses the inert silicone oil sealed in calibration chamber 27, and generates a uniform and controllable standard pressure. The reference end of the pore water pressure sensor 10 is directly placed in the silicone oil medium in calibration chamber 27, and can sense the standard pressure in real time, thereby changing the pressure difference between its measuring end and the reference end, and completing the zero point and sensitivity calibration of pore water pressure sensor 10.

[0035] Reference Figure 6In the third embodiment shown, the distributed wireless sensing node 1 further includes a filter plate 11, a trough 28, an electrically controlled door 29, an air reservoir 30, and a spike 31. The filter plate 11 is disposed inside the opening 15. The trough 28 is disposed on the top surface of the measuring cavity 26, with its bottom open. The electrically controlled door 29 is rotatably disposed on the bottom surface of the trough 28. The air reservoir 30 is disposed inside the trough 28. The spike 31 is disposed on the bottom surface of the measuring cavity 26 and located below the air reservoir 30. The air reservoir 30 stores high-pressure inert gas. The wireless signal transmitter 7 is data-connected to the electrically controlled door 29.

[0036] By installing a filter plate 11 at the opening 15, most mud and sand impurities can be filtered out. Pore water can still enter the measuring chamber 26 and come into contact with the pore water pressure sensor 10, preventing mud and sand from wearing down the pore water pressure sensor 10. However, during long-term testing, mud and sand will clog the filter plate 11, affecting the flow of pore water. Therefore, an air storage bladder 30 is installed above the measuring chamber 26, which stores high-pressure inert gas. When the filter plate 11 is clogged, the electric control door 29 can be activated to open downwards, allowing the air storage bladder 30 to fall out of the tank 28 and be punctured by the spike 31. The high-pressure inert gas in the air storage bladder 30 can then move towards the filter plate 11, thereby pushing out the clogged mud and sand, achieving self-cleaning of the filter plate 11, and ensuring the accuracy of the pore water pressure data acquisition results.

[0037] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A sand site liquefaction monitoring and early warning system, characterized by, The system includes distributed wireless sensor nodes, a regional signal relay receiver, a data processing center, and an early warning terminal. Each distributed wireless sensor node comprises a buried housing, a horizontal plate, a wireless signal transmitter, a power supply device, a vibration acceleration sensor, and a pore water pressure sensor. The buried housing is installed underground in the monitoring area. The horizontal plate divides the interior of the buried housing into an electrical cavity, a first detection cavity, and a second detection cavity. The wireless signal transmitter and power supply device are located in the electrical cavity. The vibration acceleration sensor is located in the first detection cavity, and the pore water pressure sensor is located in the second detection cavity. The second detection cavity has an opening on its side wall. The power supply device powers the wireless signal transmitter, the vibration acceleration sensor, and the pore water pressure sensor. The wireless signal transmitter is connected to the regional signal relay receiver, the vibration acceleration sensor, and the pore water pressure sensor for data transmission. The data processing center is connected to the regional signal relay receiver and the early warning terminal for data transmission.

2. The sand site liquefaction monitoring and early warning system according to claim 1, wherein, The early warning terminal includes an audible and visual alarm, an emergency broadcast system, and a mobile terminal.

3. The sand site liquefaction monitoring and warning system according to claim 1, wherein, The data processing center includes: The wavelet packet energy analysis module is used to select a suitable wavelet basis function, decompose the signals collected by the vibration acceleration sensor and the pore water pressure sensor into multiple frequency subspaces, calculate the energy value of each subspace, construct an energy feature vector, and then calculate the change amplitude of the energy feature vector per unit time to obtain the real-time energy change. The threshold warning judgment module is used to set graded thresholds based on the background vibration data and historical earthquake precursor data of the monitoring area. When the real-time energy change reaches different graded thresholds, it outputs multi-level warning instructions. The wavelet packet energy analysis module is connected to the regional signal relay collector and the threshold early warning judgment module, respectively. The threshold early warning judgment module is connected to the early warning terminal.

4. The sand site liquefaction monitoring and early warning system according to claim 3, wherein, The execution steps of the threshold warning judgment module include: Background vibration data and historical earthquake precursor data under the same geological conditions of the monitoring area were acquired and preprocessed. Then, the 95% confidence interval method was used to set the first-level attention threshold, the second-level early warning threshold, and the first- and third-level alarm thresholds. When the real-time energy change of the pore water pressure sensor reaches the first-level concern threshold, a first-level concern command is generated, and the sampling and analysis frequency of the vibration acceleration sensor signal is increased. When the real-time energy change of the vibration acceleration sensor reaches the secondary warning threshold, a secondary warning command is generated. When the real-time energy change of the pore water pressure sensor and the real-time energy change of the vibration acceleration sensor both reach the level 3 alarm threshold, a level 3 alarm command is generated and sent to the early warning terminal.

5. The sand site liquefaction monitoring and warning system according to claim 3, wherein The data processing center also includes: The multi-parameter collaborative analysis module is used to distinguish between valid signals and interference signals based on the data collected by the vibration acceleration sensor and the pore water pressure sensor, and to dynamically adjust the grading threshold. The multi-parameter collaborative analysis module is connected to the regional signal relay receiver and the threshold early warning judgment module respectively.

6. A sand site liquefaction monitoring and warning system according to claim 5, wherein The execution steps of the multi-parameter collaborative analysis module include: Extract the temporal characteristics of energy change in pore water pressure data and vibration acceleration data collected by vibration acceleration sensor and pore water pressure sensor within the same time window and frequency subspace; Based on the temporal characteristics of energy change, the wavelet packet cross-spectral coherence coefficient and phase difference are calculated. When the coherence coefficient is lower than the preset threshold and the phase difference does not conform to the propagation law of seismic waves in the soil, it is determined to be noise interference, and a graded threshold adjustment instruction is sent to the threshold early warning judgment module.

7. A monitoring and early warning system for liquefaction of sandy soil sites according to claim 1, characterized in that, The regional signal relay receiver includes a filtering unit and a multi-hop networking unit. The filtering unit is connected to the vibration acceleration sensor, the pore water pressure sensor and the multi-hop networking unit respectively. The multi-hop networking unit is connected to the data processing center.

8. A monitoring and early warning system for liquefaction of sandy soil sites according to claim 1, characterized in that, The distributed wireless sensing node further includes a vertical plate, a calibration pressure core, a miniature piezoelectric actuator, an elastic diaphragm, and a conductive medium. The vertical plate is disposed in the second detection cavity, dividing the second detection cavity into a measurement cavity and a calibration cavity. The opening is disposed on one side of the measurement cavity. The pore water pressure sensor is disposed in the measurement cavity with its measuring end facing the opening. The reference end of the pore water pressure sensor extends into the calibration cavity. The calibration pressure core, the miniature piezoelectric actuator, and the elastic diaphragm are all disposed in the calibration cavity. The reference end of the calibration pressure core is vacuum sealed. The elastic diaphragm is located on one side of the miniature piezoelectric actuator. The conductive medium fills the calibration cavity. The wireless signal transmitter is connected to the calibration pressure core and the miniature piezoelectric actuator for data transmission.

9. A monitoring and early warning system for liquefaction of sandy soil sites according to claim 8, characterized in that, The distributed wireless sensing node also includes a filter plate, a trough, an electrically controlled door, an air reservoir, and spikes. The filter plate is located inside the opening. The trough is located on the top surface of the measuring chamber with an open bottom. The electrically controlled door is rotatably located on the bottom surface of the trough. The air reservoir is located inside the trough. The spikes are located on the bottom surface of the measuring chamber and below the air reservoir. The air reservoir stores high-pressure inert gas. The wireless signal transmitter is connected to the electrically controlled door.

Images