Comprehensive detection processing and analysis method and system for immersed tube tunnel deep foundation trench

Abstract

The application discloses a comprehensive detection processing and analysis method and system for a deep foundation trench of a immersed tunnel, and relates to the technical field of data processing. Firstly, the acoustic calibration is performed on a multi-beam array in the foundation trench area to compensate for the beam incidence angle and echo delay, so as to eliminate systematic sounding errors. Then, the corrected sounding equipment is used to perform macroscopic scanning on the foundation trench to generate a high-resolution three-dimensional point cloud, to identify abnormal elevation changes in real time and to dynamically adjust the dredging depth. Next, the silt deposits are subjected to multi-frequency acoustic detection to draw a floating mud thickness cloud map to evaluate the loose structure and to implement targeted compensation. Finally, the terrain morphology and the sediment structure change are combined for construction warning to form a closed-loop system from precision calibration to anomaly detection, to physical property diagnosis and risk warning. The closed-loop system not only significantly improves the precision and integrity of the foundation trench sounding and silt monitoring, but also can discover and correct potential risks in time during construction, to ensure the safety and efficiency of the deep foundation trench construction of the immersed tunnel.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a comprehensive detection processing and analysis method and system for a deep foundation trench of a immersed tunnel. BACKGROUND

[0002] The deep foundation trench of an immersed tunnel is a foundation pit structure excavated in advance underwater in immersed tunnel construction, which provides a precise bearing space for the sinking of prefabricated pipe sections and ensures the stable docking of the pipe sections with the foundation and the onshore section. With the continuous deepening of the utilization of urban underground space, immersed tunnels, as an important form of underwater and riverbed transportation channels, have been widely used in subway cross-sea, river crossing and port connection projects.

[0003] For example, the design of a seabed immersed tunnel foundation trench allows the calculation of over-excavation engineering quantities, which uses a certain construction stage seabed topography and a parameterized cross-section template to establish a three-dimensional foundation trench excavation model. According to the characteristics of the three-dimensional foundation trench excavation model and the allowable over-excavation conditions of the foundation trench, a rapid calculation tool for design of allowable over-excavation engineering quantities is developed.

[0004] For example, the seabed immersed tunnel foundation trench siltation three-dimensional visualization analysis method disclosed in CN115270276A, first step: establish seabed topography before and after foundation trench siltation, import water depth measurement data before foundation trench siltation, establish seabed topography before foundation trench siltation, import water depth measurement data after foundation trench siltation, establish seabed topography after foundation trench siltation; second step: establish foundation trench siltation section design interface, assign two-dimensional foundation trench siltation section centerline elevation information, establish three-dimensional foundation trench siltation section centerline, draw parameterized cross-section template of foundation trench siltation section, establish parameterized cross-section template library of foundation trench siltation section; third step: establish three-dimensional siltation thickness color difference map; fourth step: establish three-dimensional foundation trench siltation model; fifth step: three-dimensional visualization analysis of foundation trench siltation.

[0005] However, in the process of implementing the technical scheme of the present application, the above-mentioned technology at least has the following technical problems:

[0006] Because the foundation trench excavation process involves the removal of large volume of soil, the complex interaction of seabed topography and sediment characteristics, the traditional single-point detection method cannot meet the fine control requirements of ultra-wide variable cross-section foundation trench, high water pressure and rapid siltation, and cannot guarantee the accurate positioning and long-term safety of the tunnel structure. SUMMARY

[0007] To overcome the deficiencies of the prior art, the present application provides a comprehensive detection processing and analysis method and system for a deep foundation trench of an immersed tunnel, which solves the problems in the background art.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solution: a comprehensive detection, processing and analysis method for deep foundation trenches of immersed tunnels, including using a multibeam system to transmit acoustic pulses and receive multibeam array echoes in the construction area of ​​the immersed tunnel foundation trench, obtaining multibeam array echo parameters for analysis, obtaining the multibeam array echo delay characterization value of the construction area of ​​the immersed tunnel foundation trench, and compensating and correcting the incident angle of the sound beam.

[0009] A macroscopic scan of the immersed tunnel foundation trench construction area was conducted to generate a three-dimensional point cloud model of the immersed tunnel foundation trench construction area. The depth measurement data of the immersed tunnel foundation trench construction area was obtained and analyzed to identify abnormal elevation changes in the immersed tunnel foundation trench construction area and adjust the dredging depth accordingly.

[0010] Multi-frequency raw signals of silt deposits in the construction area of ​​the immersed tunnel foundation trench were collected and processed to generate a cloud map of the mud thickness in the construction area of ​​the immersed tunnel foundation trench. Measurement parameters of the backfilled sediment in the cloud map of the mud thickness in the construction area of ​​the immersed tunnel foundation trench were obtained and analyzed, and the loose structure of the silt deposits in the construction area of ​​the immersed tunnel foundation trench was compensated.

[0011] Early warning of the immersed tunnel construction process is provided by combining the topography and sediment structure of the construction area of ​​the immersed tunnel foundation trench.

[0012] Furthermore, the echo delay characterization value of the multibeam array in the construction area of ​​the immersed tunnel foundation trench is obtained. The specific process is as follows: a monitoring time period is preset, and the multibeam array echo parameters are extracted during the monitoring time period, including the average echo time offset, the average beam incident angle, and the average elevation deviation value.

[0013] The average echo time offset and the maximum echo time offset, the average beam incidence angle and the beam incidence calibration angle, and the average elevation deviation and the maximum elevation deviation are respectively analyzed by proportion, and weighting coefficients are introduced to obtain the multi-beam array echo delay characterization value of the immersed tunnel foundation trench construction area. The multi-beam array echo delay characterization value of the immersed tunnel foundation trench construction area is used to evaluate the degree of impact of beam tilt and positioning time delay on elevation accuracy.

[0014] Furthermore, the incident angle of the sound beam is compensated and corrected. The specific process is as follows: extract the echo delay characterization value of the multibeam array in the construction area of ​​the immersed tunnel foundation trench, and compare it with the incident angle offset corresponding to each interval of the multibeam array echo delay characterization value of the construction area of ​​the immersed tunnel foundation trench in the preset database to obtain the incident angle offset of the construction area of ​​the immersed tunnel foundation trench. The incident angle of the sound beam is then compensated and corrected according to the incident angle offset of the construction area of ​​the immersed tunnel foundation trench.

[0015] Furthermore, the depth measurement data of the immersed tunnel foundation trench construction area is obtained and analyzed. The specific process is as follows: the immersed tunnel foundation trench construction area is divided into sub-regions, and the depth measurement data of each sub-region is extracted, including the average elevation difference, average echo intensity, and the number of effective sonar measurement points per unit area.

[0016] The average elevation difference and the historical baseline elevation difference, the average echo intensity and the defined echo intensity, and the number of effective sonar measurement points per unit area and the number of effective sonar measurement points per unit area were analyzed by proportion. Weighting coefficients and the echo delay characterization value of the multibeam array in the immersed tunnel foundation trench construction area were introduced to obtain the abnormal elevation change characterization value of each immersed tunnel foundation trench construction sub-region. The abnormal elevation change characterization value of each immersed tunnel foundation trench construction sub-region is used to assess the degree of topographic anomaly in the deep foundation trench.

[0017] Furthermore, the process of identifying abnormal elevation changes in the immersed tunnel foundation trench construction area is as follows: The abnormal elevation change characterization value of each immersed tunnel foundation trench construction sub-region is extracted and compared with the preset abnormal elevation change characterization threshold of the immersed tunnel foundation trench construction area in the database. If the abnormal elevation change characterization value of a certain immersed tunnel foundation trench construction sub-region is higher than or equal to the abnormal elevation change characterization threshold of the immersed tunnel foundation trench construction area, then that immersed tunnel foundation trench construction sub-region is marked as an abnormal elevation change area of ​​the immersed tunnel foundation trench construction area, thus obtaining the abnormal elevation change areas of each immersed tunnel foundation trench construction area. If the abnormal elevation change characterization value of a certain immersed tunnel foundation trench construction sub-region is lower than the abnormal elevation change characterization threshold of the immersed tunnel foundation trench construction area, then it is not necessary to mark the abnormal elevation change area of ​​the immersed tunnel foundation trench construction area.

[0018] Furthermore, the dredging depth is adjusted. The specific process is as follows: extract the abnormal elevation change characterization value of the sub-region of the immersed tunnel foundation trench construction area corresponding to the abnormal elevation change area of ​​each immersed tunnel foundation trench construction area, and take the deviation between the abnormal elevation change characterization value of the sub-region of the immersed tunnel foundation trench construction area corresponding to the abnormal elevation change area of ​​each immersed tunnel foundation trench construction area and the preset abnormal elevation change characterization value threshold in the database as the dredging depth exceeding limit of each immersed tunnel foundation trench construction area. Adjust the dredging depth of the abnormal elevation change area of ​​each immersed tunnel foundation trench construction area according to the dredging depth exceeding limit of each immersed tunnel foundation trench construction area.

[0019] Furthermore, the measurement parameters of the backfilled sediment in the mud thickness cloud map of the immersed tunnel foundation trench construction area are obtained and analyzed. The specific process is as follows: the measurement parameters of the backfilled sediment in the mud thickness cloud map of each immersed tunnel foundation trench construction sub-area are extracted, including the average mud thickness deviation, the current sediment volume density deviation, and the shear wave velocity offset.

[0020] The average mud thickness deviation and the defined mud thickness deviation, the current sediment volume density deviation and the defined sediment volume density deviation, and the shear wave velocity offset and the defined shear wave velocity offset are respectively analyzed by proportion. Weighting coefficients and abnormal elevation change characterization values ​​of each immersed tunnel trench construction sub-region are introduced to obtain the physical property structure looseness characterization value of the backfilled sediment in each immersed tunnel trench construction sub-region. The physical property structure looseness characterization value of the backfilled sediment in each immersed tunnel trench construction sub-region is used to evaluate and quantify the overall structural looseness of the backfilled sediment.

[0021] Furthermore, the loose structure of the silt deposits in the immersed tunnel foundation trench construction area is compensated. The specific process is as follows: extract the loose structure characterization value of the backfilled silt in each sub-region of the immersed tunnel foundation trench construction area, and match it with the static pressure load compensation value corresponding to each interval of the loose structure characterization value of the backfilled silt in the database to obtain the static pressure load compensation value of each sub-region of the immersed tunnel foundation trench construction area. The loose structure of the silt deposits in the immersed tunnel foundation trench construction area is compensated according to the static pressure load compensation value of each sub-region of the immersed tunnel foundation trench construction area.

[0022] Furthermore, an early warning system is implemented for the immersed tunnel construction process. Specifically, the number of abnormal elevation change areas in each immersed tunnel foundation trench construction area is counted, and the static pressure load compensation value of each immersed tunnel foundation trench construction sub-area is extracted and compared with the static pressure load compensation threshold set in the database. The number of immersed tunnel foundation trench construction sub-areas whose static pressure load compensation value is higher than or equal to the static pressure load compensation threshold is counted and recorded as the number of loose physical properties in each immersed tunnel foundation trench construction sub-area.

[0023] The number of abnormal elevation change areas in each immersed tunnel foundation trench construction area and the number of loose physical structures in each immersed tunnel foundation trench construction sub-area are compared with the threshold numbers for the number of abnormal elevation change areas and the threshold numbers for the number of loose physical structures, respectively. If the number of abnormal elevation change areas in each immersed tunnel foundation trench construction area and the number of loose physical structures in each immersed tunnel foundation trench construction sub-area are both higher than or equal to the threshold numbers for the number of abnormal elevation change areas and the threshold numbers for the number of loose physical structures, then an early warning is issued for the immersed tunnel construction process; otherwise, no early warning is required for the immersed tunnel construction process.

[0024] A second aspect of the present invention also provides a comprehensive detection, processing and analysis system for deep foundation trenches of immersed tunnels, comprising: a sound beam positioning and correction module, used to transmit acoustic pulses and receive multibeam array echoes in the construction area of ​​the immersed tunnel foundation trench using a multibeam system, obtain multibeam array echo parameters for analysis, obtain the multibeam array echo delay characterization value of the construction area of ​​the immersed tunnel foundation trench, and compensate and correct the incident angle of the sound beam.

[0025] The abnormal elevation change analysis module is used to perform macroscopic scanning of the immersed tunnel foundation trench construction area, generate a three-dimensional point cloud model of the immersed tunnel foundation trench construction area, obtain and analyze the depth measurement data of the immersed tunnel foundation trench construction area, identify abnormal elevation changes in the immersed tunnel foundation trench construction area, and adjust the dredging depth.

[0026] The silt analysis module is used to collect and process multi-frequency raw signals of silt in the construction area of ​​the immersed tunnel foundation trench, generate a cloud map of the mud thickness in the construction area of ​​the immersed tunnel foundation trench, obtain and analyze the measurement parameters of the back silt in the mud thickness cloud map of the construction area of ​​the immersed tunnel foundation trench, and compensate for the loose structure of the silt in the construction area of ​​the immersed tunnel foundation trench.

[0027] The intelligent early warning module is used to provide early warnings for the construction process of immersed tunnels by combining the topography and sediment structure of the construction area of ​​the immersed tunnel foundation trench.

[0028] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0029] (1) The comprehensive detection, processing and analysis method and system for deep foundation trenches of immersed tunnels provided by the present invention firstly performs acoustic calibration of the multibeam array in the foundation trench area through a multibeam system to compensate for the beam incident angle and echo delay, so as to eliminate systematic depth measurement errors; then, based on the calibrated depth measurement equipment, the foundation trench is macroscopically scanned to generate a high-resolution three-dimensional point cloud, and abnormal elevation changes are identified in real time and the dredging depth is dynamically adjusted; next, multi-frequency acoustic detection is performed on the silt deposits, and a cloud map of the floating mud thickness is drawn to assess the loose structure and implement targeted compensation; finally, the topographic morphology and sediment structure changes are combined for construction early warning, forming a closed-loop system from accuracy calibration to anomaly detection, and then to physical property diagnosis and risk early warning. This not only significantly improves the accuracy and completeness of foundation trench depth measurement and silt monitoring, but also enables timely detection and correction of potential risks during construction, ensuring the safety and efficiency of deep foundation trench construction of immersed tunnels.

[0030] (2) By obtaining the echo delay characterization value of the multibeam array in the construction area of ​​the immersed tunnel foundation trench, the present invention can dynamically compensate and correct the real-time incident angle of the sound beam in one go. This not only minimizes the systematic error before macroscopic depth measurement, but also ensures that the subsequently generated three-dimensional terrain model has sub-centimeter accuracy, providing a solid and reliable measurement basis for subsequent abnormal elevation identification, dredging scheme adjustment and sediment property analysis.

[0031] (3) By obtaining the abnormal elevation change characterization values ​​of each sub-region of the immersed tunnel foundation trench construction area, this invention helps to identify abnormal elevation changes in the immersed tunnel foundation trench construction area and adjust the dredging depth of the corresponding sub-region accordingly. This not only achieves high-resolution positioning of the topographical changes at the bottom of the deep foundation trench, but also accurately guides the dredging operation to high-risk areas. This improves the scientificity and economy of dredging depth adjustment, saves construction costs to the maximum extent, and reduces environmental disturbance. It provides accurate, efficient and controllable comprehensive detection and analysis support for the deep foundation trench construction of immersed tunnels.

[0032] (4) This invention obtains the loose characterization values ​​of the physical properties of the backfilled sediment in each sub-area of ​​the immersed tunnel foundation trench construction, and then performs quantitative static pressure reinforcement compensation on the loose sediment accordingly. This achieves high-precision diagnosis and targeted reinforcement of the loose backfilled sediment at the bottom of the deep foundation trench, greatly improving the support stability and the safety of the tunnel section placement, optimizing the allocation of dredging and compaction resources, and improving construction efficiency. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the method of the present invention;

[0034] Figure 2 This is a schematic diagram of the logic flow of the comprehensive detection, processing and analysis method for deep foundation trenches of immersed tunnels according to the present invention;

[0035] Figure 3 This is a schematic diagram of the logic flow for adjusting the dredging depth according to the present invention;

[0036] Figure 4 This is a schematic diagram of the system of the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] In the description of this invention, it should be understood that the terms "opening", "upper", "lower", "thickness", "top", "middle", "length", "inner", "around", etc., which indicate orientation or positional relationship, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the components or elements referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as limiting this invention.

[0039] Please see Figure 1This invention provides a technical solution: a comprehensive detection, processing and analysis method for deep foundation trenches of immersed tunnels, including using a multibeam system to transmit acoustic pulses and receive multibeam array echoes in the construction area of ​​the immersed tunnel foundation trench, obtaining multibeam array echo parameters for analysis, obtaining the multibeam array echo delay characterization value of the construction area of ​​the immersed tunnel foundation trench, and compensating and correcting the incident angle of the sound beam.

[0040] It should be noted that a multibeam sonar system is an underwater acoustic tomography device, the core of which consists of a low-frequency acoustic wave transmitter, a receiving hydrophone array, and dedicated signal processing software. It emits a series of acoustic pulses of known frequencies, and by utilizing the time difference, amplitude, and phase information of the sound beams reflecting multiple times at the water-sediment interface, it can accurately analyze the thickness and density distribution of floating mud and silt without intruding on the sample.

[0041] A macroscopic scan of the immersed tunnel foundation trench construction area was conducted to generate a three-dimensional point cloud model of the immersed tunnel foundation trench construction area. The depth measurement data of the immersed tunnel foundation trench construction area was obtained and analyzed to identify abnormal elevation changes in the immersed tunnel foundation trench construction area and adjust the dredging depth accordingly.

[0042] It should be noted that when conducting macroscopic scanning of the foundation trench area, a multibeam echo sounder on a shipboard or unmanned surface platform is typically combined with a high-precision inertial attitude measurement system, such as differential positioning technology based on RTK and CORS systems. Dozens to hundreds of sound beams are emitted along a predetermined route to record depth and position in real time. The acquired raw echo data is processed by specialized software, such as Qimera, to perform slant range projection, attitude compensation, and spatiotemporal stitching, ultimately generating a 3D point cloud model of the bottom of the foundation trench. This model reflects the overall topographic contour of the construction area and provides accurate spatial reference for subsequent identification of elevation anomalies, adjustment of dredging depth, and overlay of floating mud thickness cloud maps.

[0043] Multi-frequency raw signals of silt deposits in the construction area of ​​the immersed tunnel foundation trench were collected and processed to generate a cloud map of the mud thickness in the construction area of ​​the immersed tunnel foundation trench. Measurement parameters of the backfilled sediment in the cloud map of the mud thickness in the construction area of ​​the immersed tunnel foundation trench were obtained and analyzed, and the loose structure of the silt deposits in the construction area of ​​the immersed tunnel foundation trench was compensated.

[0044] Early warning of the immersed tunnel construction process is provided by combining the topography and sediment structure of the construction area of ​​the immersed tunnel foundation trench.

[0045] It should be noted that the acoustic pulse calibration of the multibeam system and the delay characterization values ​​and incident angle compensation parameters obtained from the multibeam echo reception provide a centimeter-level accuracy benchmark for subsequent macroscopic depth sounding, enabling all terrain scans to output highly reliable 3D point clouds under actual hydrological and platform attitude conditions. Next, based on this high-precision point cloud, the system identifies each abnormal elevation area and immediately adjusts the dredging depth quantitatively according to the magnitude of the anomaly, thereby ensuring the accuracy of pipe section placement. Finally, under the dual spatial reference of "corrected terrain + high-precision acoustics," the system acquires multi-frequency signals of sediment and generates a floating mud thickness cloud. The figure shows that when extracting physical properties such as thickness deviation, bulk density, and shear wave velocity of the floating mud layer, the point cloud model can be used to determine the relative positional relationship between the thickness profile and the topographic base plate, and the depth profile adjusted by dredging can be used to accurately interpret the accumulation and loose state of sediments. From acoustic correction to morphological scanning and then to physical property analysis, they support each other on the same spatiotemporal benchmark and decision chain, realizing a closed-loop synergy of depth measurement accuracy, dredging strategy, and sediment reinforcement. This enables the deep foundation trench construction of immersed tunnels to respond quickly to changes in terrain at the macro level and to make fine compensation for sediment structure at the micro level, thereby greatly improving the safety and efficiency of construction.

[0046] It should be noted that the specific process of generating a continuous mud thickness cloud map for the entire trench involves synchronously collecting multi-frequency raw signals of mud and backfilled sediments using a tuning fork vibration response sensor, ultrasonic pulse density meter, and electromagnetic rheometer in an equally spaced array throughout the trench. After these signals are calibrated by on-site temperature and hydrostatic pressure sensors to remove environmental drift, they are fed into a pre-trained multivariate regression model to invert the accurate physical density value and map it to the same voxel grid according to the water depth coordinate. At the same time, the system combines timestamps and tide records, construction logs, and foundation pit deformation curves for spatiotemporal alignment, completing the full-domain coupling of topography and density. Then, the system calculates the density gradient on the vertical bar of each voxel and integrates the echo time difference, amplitude, and phase information of low-frequency (5–10 kHz) sound wave penetration detection to automatically calibrate the upper and lower interfaces of the mud layer, generating a continuous mud thickness cloud map for the entire trench.

[0047] Specifically, the echo delay characterization value of the multibeam array in the construction area of ​​the immersed tunnel foundation trench is obtained. The specific process is as follows: a monitoring time period is preset, and the multibeam array echo parameters are extracted during the monitoring time period, including the average echo time offset, the average beam incident angle, and the average elevation deviation value.

[0048] It should be noted that within the preset monitoring period in the database, the system first performs a time stamp comparison on each multibeam echo acquisition record. By comparing the sonar echo reception time with the timestamp of inertial navigation or differential GPS, the system calculates the delay of each echo relative to the ideal synchronization clock, and then averages all the delay values ​​to obtain the average echo time offset within the monitoring period. At the same time, each echo data is accompanied by incident angle information, which is the actual tilt angle of the sound beam incident on the seabed calculated by the attitude sensors and array geometry model on the sonar platform. The system averages these angle values ​​within the monitoring period to obtain the average beam incident angle. Finally, the platform also compares each compensated vertical depth value with the historical bathymetric benchmark at the same location, records the elevation difference of each measurement, and then averages the accumulated values ​​to obtain the average elevation deviation value.

[0049] The average echo time offset and the maximum echo time offset, the average beam incidence angle and the beam incidence calibration angle, and the average elevation deviation and the maximum elevation deviation are respectively analyzed by proportion, and weighting coefficients are introduced to obtain the multi-beam array echo delay characterization value of the immersed tunnel foundation trench construction area. The multi-beam array echo delay characterization value of the immersed tunnel foundation trench construction area is used to evaluate the degree of impact of beam tilt and positioning time delay on elevation accuracy.

[0050] It should be noted that the specific analysis conditions for the multibeam array echo delay characterization value in the immersed tunnel foundation trench construction area are as follows:

[0051] ;

[0052] In the formula, DB represents the echo delay characteristic value of the multibeam array in the construction area of ​​the immersed tunnel foundation trench, and T1 represents the average echo time offset. This indicates the maximum echo time offset set in the database. Indicates the average beam incidence angle. This indicates the beam incident calibration angle set in the database. This represents the average elevation deviation value. This represents the maximum elevation deviation value set in the database. This represents the weighting coefficient corresponding to the echo time offset set in the database. This represents the weighting coefficient corresponding to the average beam incidence angle set in the database. This represents the weighting coefficient corresponding to the average elevation deviation value set in the database.

[0053] It should be noted that in the process of assessing the quality of trench sounding data, the three key parameters—mean echo time offset, mean beam incidence angle, and mean elevation deviation—are interrelated and jointly determine the sounding accuracy and the reliability of subsequent terrain reconstruction. First, the mean echo time offset directly affects the accuracy of water depth calculation; while the mean beam incidence angle determines the geometric transformation coefficient of the slant range to vertical depth projection, and a large incidence angle deviation will amplify the vertical depth error caused by any time offset. Secondly, the combined effect of these two factors is ultimately reflected in the average elevation deviation. For example, if the beam incident angle deviates significantly from the calibration value, improper slant range projection will lead to elevation deviation. When there is an overall delay in the sonar echo relative to the inertial navigation or GNSS clock (Global Navigation Satellite System clock), even a millisecond-level offset will be amplified when projected onto the vertical depth on the edge beam with a larger incident angle, thus increasing the average elevation deviation. Conversely, if the observed elevation deviation is consistently high, it often means that the time synchronization has not been fully calibrated or the beam angle compensation is inaccurate, and both must be further adjusted. At the same time, if the incident angle itself deviates from the calibration angle, it will also change the sensitivity of the time offset to depth calculation, causing the same echo delay to produce different magnitudes of elevation error at different angles.

[0054] It should be noted that the weighting coefficients corresponding to the echo time offset, the average beam incidence angle, and the average elevation deviation are all stored in the database, and their values ​​are typically set between 0 and 1. For example, by constructing a mapping table between the echo time offset and the weighting coefficients, the real-time detected echo time offset is input to the corresponding mapping table in the database, thereby quickly obtaining the weighting coefficient corresponding to the echo time offset. Similarly, for the average beam incidence angle, by constructing a mapping table between the average beam incidence angle and the weighting coefficients, the real-time detected average beam incidence angle is input to the corresponding mapping table in the database, thereby quickly obtaining the weighting coefficient corresponding to the average beam incidence angle. For the average elevation deviation, a pre-established mapping table between the average elevation deviation and the weighting coefficients can also be used to input the real-time measured average elevation deviation value to the corresponding mapping table in the database, thereby quickly obtaining the weighting coefficient corresponding to the average elevation deviation.

[0055] Specifically, the incident angle of the sound beam is compensated and corrected. The specific process is as follows: extract the echo delay characterization value of the multibeam array in the construction area of ​​the immersed tunnel foundation trench, and compare it with the incident angle offset corresponding to each interval of the multibeam array echo delay characterization value of the construction area of ​​the immersed tunnel foundation trench in the database to obtain the incident angle offset of the construction area of ​​the immersed tunnel foundation trench. The incident angle of the sound beam is then compensated and corrected according to the incident angle offset of the construction area of ​​the immersed tunnel foundation trench.

[0056] It should be noted that the specific process for compensating and correcting the incident angle of the sound beam by the incident angle offset in the construction area of ​​the immersed tunnel foundation trench is as follows: obtain the calibrated incident angle stored in the database. If the calibrated incident angle is smaller than the real-time measured incident angle, subtract the incident angle offset from the measured incident angle. If the calibrated incident angle is larger than the measured incident angle, add the incident angle offset to the measured incident angle.

[0057] It should be noted that the echo time offset is the difference between the timestamp of the received echo and the delay between the clock record given by the inertial navigation system or differential GPS.

[0058] Specifically, the depth measurement data of the immersed tunnel foundation trench construction area is obtained and analyzed. The specific process is as follows: the immersed tunnel foundation trench construction area is divided into sub-areas, and the depth measurement data of each sub-area is extracted, including the average elevation difference, average echo intensity, and the number of effective sonar measurement points per unit area.

[0059] It should be noted that the average elevation difference is calculated by comparing the real-time seabed depth of all measuring points in the sub-region with the preset design depth in the database for the corresponding location, recording the depth difference at each location, and then summing these differences to obtain the average value for the region; the average echo intensity comes from the sonar's digital recording of the echo amplitude of each transmission and reception during the return signal processing stage, and the system accumulates the reflected amplitude values ​​and calculates the average; and the average number of effective sonar measuring points per unit area is obtained by dividing the area of ​​the sub-region by the total number of measuring points in the region where the sonar successfully obtained effective echoes, resulting in the average number of measuring points per square meter.

[0060] The average elevation difference and the historical baseline elevation difference, the average echo intensity and the defined echo intensity, and the number of effective sonar measurement points per unit area and the number of effective sonar measurement points per unit area were analyzed by proportion. Weighting coefficients and the echo delay characterization value of the multibeam array in the immersed tunnel foundation trench construction area were introduced to obtain the abnormal elevation change characterization value of each immersed tunnel foundation trench construction sub-region. The abnormal elevation change characterization value of each immersed tunnel foundation trench construction sub-region is used to assess the degree of topographic anomaly in the deep foundation trench.

[0061] It should be noted that the specific analysis conditions for the abnormal elevation changes in each sub-area of ​​the immersed tunnel foundation trench construction are as follows:

[0062] ;

[0063] In the formula, This represents the abnormal elevation change characteristic value of the i-th immersed tunnel foundation trench construction sub-region. This represents the average elevation difference of the i-th sub-region for the construction of the immersed tunnel foundation trench. Indicates the difference in historical baseline elevation. This represents the average echo intensity of the i-th sub-region of the immersed tunnel foundation trench construction area. This indicates the defined echo intensity set in the database. This represents the number of effective sonar measurement points per unit area in the i-th sub-region of immersed tunnel foundation trench construction. This indicates the number of effective sonar measurement points within a defined unit area specified in the database. This represents the echo delay characteristic value of the multibeam array in the construction area of ​​the immersed tunnel foundation trench. This represents the weighting coefficient corresponding to the average elevation difference set in the database. This represents the weighting coefficient corresponding to the average echo intensity set in the database. This represents the weighting coefficient corresponding to the number of effective sonar measurement points per unit area as defined in the database. This represents the weighting coefficient corresponding to the multibeam array echo delay characterization value of the immersed tunnel foundation trench construction area as defined in the database, where i represents the number of each immersed tunnel foundation trench construction sub-region. , where n is the total number of sub-regions for the construction of the immersed tunnel foundation trench.

[0064] It should be noted that in the quality assessment of trench sounding data, there is a close coupling relationship between the average elevation difference, the average echo intensity, and the number of effective sonar measurement points per unit area, which together determine the accuracy of terrain anomaly identification and data reliability. First, the average elevation difference reflects the vertical offset between the current point cloud and the baseline model. Its magnitude directly depends on the stability of the echo intensity and the spatial coverage of the measurement points. When the echo intensity attenuates severely or there is a large-scale intensity unevenness, the reflected signal of the sound wave at the sediment interface becomes blurred, causing fluctuations or systematic deviations in the calculation of the elevation difference. At the same time, if the number of effective measurement points per unit area is insufficient, for example, due to excessive ship speed or sound beam obstruction, the statistical average of the elevation difference will rely more on a few outliers and be more susceptible to the influence of single-point noise, thus amplifying the deviation. Secondly, the echo intensity itself is affected by the density of measurement points. For example, in dense measurement point areas, overlapping multiple echoes can verify and superimpose each other, which helps to smooth the amplitude fluctuations of a single beam, thereby improving the confidence of the average echo intensity. In sparse measurement point areas, even if the same underwater acoustic conditions are input, the echo intensity may vary significantly due to the diversity of signal paths or seabed sediments. This can cause systematic errors in the depth back-calculation at the same elevation, and further increase or decrease the average elevation difference.

[0065] It should be noted that the weighting coefficients corresponding to the average elevation difference, the average echo intensity, the number of effective sonar measurement points per unit area, and the multibeam array echo delay characterization value of the immersed tunnel foundation trench construction area are all stored in the database, and their values ​​are usually set between 0 and 1. For example, by constructing a mapping table between the average elevation difference and the weighting coefficients, the real-time detected average elevation difference is input to the corresponding mapping table in the database, thereby quickly obtaining the weighting coefficient corresponding to the average elevation difference. Similarly, for the average echo intensity, by constructing a mapping table between the average echo intensity and the weighting coefficients, the real-time detected average echo intensity is input to the corresponding mapping table in the database, thereby quickly obtaining the weighting coefficient corresponding to the average echo intensity. The number of effective sonar measurement points per unit area can also be obtained through a pre-established mapping table between the number of effective sonar measurement points per unit area and the weighting coefficients. The number of effective sonar measurement points per unit area, measured in real time, is input into the corresponding mapping table in the database, thereby quickly obtaining the weight coefficient corresponding to the number of effective sonar measurement points per unit area. Similarly, for the multibeam array echo delay characterization value of the immersed tunnel foundation trench construction area, a mapping table between the multibeam array echo delay characterization value and the weight coefficient is constructed. The real-time obtained multibeam array echo delay characterization value of the immersed tunnel foundation trench construction area is input into the corresponding mapping table in the database, thereby quickly obtaining the weight coefficient corresponding to the multibeam array echo delay characterization value of the immersed tunnel foundation trench construction area.

[0066] Specifically, the process of identifying abnormal elevation changes in the construction area of ​​the immersed tunnel foundation trench is as follows: Extract the abnormal elevation change characterization value of each sub-region of the immersed tunnel foundation trench construction area and compare it with the preset abnormal elevation change characterization threshold of the immersed tunnel foundation trench construction area in the database. If the abnormal elevation change characterization value of a certain sub-region of the immersed tunnel foundation trench construction area is higher than or equal to the abnormal elevation change characterization threshold of the immersed tunnel foundation trench construction area, then that sub-region of the immersed tunnel foundation trench construction area is marked as an abnormal elevation change area of ​​the immersed tunnel foundation trench construction area, thus obtaining the abnormal elevation change areas of each immersed tunnel foundation trench construction area. If the abnormal elevation change characterization value of a certain sub-region of the immersed tunnel foundation trench construction area is lower than the abnormal elevation change characterization threshold of the immersed tunnel foundation trench construction area, then it is not necessary to mark it as an abnormal elevation change area of ​​the immersed tunnel foundation trench construction area.

[0067] Specifically, the dredging depth is adjusted as follows: extract the abnormal elevation change characterization value of the sub-region of the immersed tunnel foundation trench construction area corresponding to the abnormal elevation change area of ​​each immersed tunnel foundation trench construction area, and take the deviation between the abnormal elevation change characterization value of the sub-region of the immersed tunnel foundation trench construction area corresponding to the abnormal elevation change area of ​​each immersed tunnel foundation trench construction area and the preset abnormal elevation change characterization value threshold in the database as the dredging depth exceeding limit of each immersed tunnel foundation trench construction area. Adjust the dredging depth of the abnormal elevation change area of ​​each immersed tunnel foundation trench construction area according to the dredging depth exceeding limit of each immersed tunnel foundation trench construction area.

[0068] It should be noted that the specific process for adjusting the dredging depth of abnormal elevation change areas in each immersed tunnel foundation trench construction area based on the excess dredging depth of each immersed tunnel foundation trench construction area is as follows: the excess dredging depth of each immersed tunnel foundation trench construction area is multiplied by the dredging depth increment coefficient obtained from on-site calibration and stored in the database in advance, so as to reflect the optimal dredging depth increase corresponding to each meter of elevation deviation under the geological conditions; finally, the obtained additional dredging depth is directly added to the original design dredging depth of the sub-area, and the new dredging target value is sent to the construction control system.

[0069] Specifically, the measurement parameters of the backfilled sediment in the mud thickness cloud map of the immersed tunnel foundation trench construction area are obtained and analyzed. The specific process is as follows: extract the measurement parameters of the backfilled sediment in the mud thickness cloud map of each immersed tunnel foundation trench construction sub-area, including the average mud thickness deviation, the current sediment volume density deviation, and the shear wave velocity offset.

[0070] It should be noted that the average mud thickness deviation is calculated by comparing the actual mud layer thickness detected by sonar or acoustic waves in each sub-region with the design average thickness of that sub-region, recording the thickness difference at each measuring point, and then summing them up to obtain the average deviation for a region. The current sediment volume density deviation is derived from multi-frequency detection equipment such as tuning fork vibration response, ultrasonic pulse density meter, and electromagnetic rheological sensor to measure sediments at multiple points and record the actual volume density value at each measuring point. Then, these measured density values ​​are subtracted from the design reference density of the sub-region one by one, and the density differences of all measuring points are averaged to obtain the current sediment volume density deviation of the sub-region. The shear wave velocity offset is obtained by using a shallow subsurface acoustic profiler to scan the shear wave velocity in the sub-region, measuring the propagation time difference of the sound wave through the sediment layer and converting it into velocity, and then comparing it with the design sound velocity value at the same depth. The difference is the offset, which reflects the changes in the elastic properties and pore structure of the medium.

[0071] The average mud thickness deviation and the defined mud thickness deviation, the current sediment volume density deviation and the defined sediment volume density deviation, and the shear wave velocity offset and the defined shear wave velocity offset are respectively analyzed by proportion. Weighting coefficients and abnormal elevation change characterization values ​​of each immersed tunnel trench construction sub-region are introduced to obtain the physical property structure looseness characterization value of the backfilled sediment in each immersed tunnel trench construction sub-region. The physical property structure looseness characterization value of the backfilled sediment in each immersed tunnel trench construction sub-region is used to evaluate and quantify the overall structural looseness of the backfilled sediment.

[0072] It should be noted that the specific analysis conditions for the loose physical properties of the backfilled sediment in each sub-area of ​​the immersed tunnel foundation trench construction are as follows:

[0073] ;

[0074] In the formula, This represents the loose physical properties of the silt deposits in the i-th sub-region of the immersed tunnel foundation trench construction area. This represents the average deviation of the floating mud thickness in the i-th sub-region of the immersed tunnel foundation trench construction area. This indicates the defined deviation in mud thickness set in the database. This represents the current sediment volume density deviation in the i-th sub-region of the immersed tunnel foundation trench construction area. This indicates the deviation in sediment volume density defined in the database. This represents the shear wave velocity offset of the i-th sub-region of the immersed tunnel foundation trench construction area. This represents the defined shear wave velocity offset specified in the database. This represents the abnormal elevation change characteristic value of the i-th immersed tunnel foundation trench construction sub-region. This represents the weighting coefficient corresponding to the average mud thickness deviation set in the database. This represents the weighting coefficient corresponding to the sediment volume density deviation set in the database. This represents the weighting coefficient corresponding to the shear wave velocity offset set in the database. This represents the weighting coefficient corresponding to the abnormal elevation change characterization value set in the database, and i represents the number of each sub-region for the immersed tunnel foundation trench construction. , where n is the total number of sub-regions for the construction of the immersed tunnel foundation trench.

[0075] It should be noted that in the assessment of floating mud properties, there is an inherent coupling relationship among the average floating mud thickness deviation, the current sediment bulk density deviation, and the shear wave velocity offset, which determines the accuracy of the judgment on the looseness of the sediment structure. First, the average floating mud thickness deviation reflects the macroscopic change in the accumulation or thinning of the floating mud layer, and this thickness itself affects the representativeness of the density measurement points: when the floating mud layer unexpectedly thickens, the measurement depth of acoustic detection and ultrasonic densitometers increases, often accompanied by a decrease in density at the measurement point and increased signal attenuation, thus leading to fluctuations in the bulk density deviation; conversely, when the floating mud is thin or there is local exposure of a hard bottom, the density measurement tends to be a mixture of suspended mud and underlying sand, which may cause the deviation to show unexpected increases or decreases. Secondly, bulk density, as a quantitative indicator of mud compaction, is closely related to shear wave velocity: increased density usually means reduced pore water and tighter particle packing, resulting in a synchronous increase in shear wave velocity, as wave velocity propagates faster in denser media. Conversely, if the bulk density deviation indicates increased looseness, the shear wave velocity offset will also shift towards negative values, reflecting a decrease in media stiffness. Elevation anomalies often directly reflect the accumulation or loss of mud and sand at the bottom of the trench, while the loose structure of the backfilled sediments determines the porosity, compressibility, and bearing capacity of these deposits or depressions. If a sub-area shows a significant elevation rise, it may mean that rapid sediment settling has formed a new layer of floating mud or silt. In this case, the sediment contains more pore space and water, inevitably corresponding to higher looseness. Conversely, in scour areas with decreased elevation, the original sediments are cut or relocated, and the remaining layer is often denser and more structurally stable, resulting in a relatively lower looseness characteristic value.

[0076] It should be noted that the weighting coefficients corresponding to the average mud thickness deviation, sediment volume density deviation, shear wave velocity offset, and abnormal elevation change characterization values ​​are all stored in the database and their values ​​are usually set between 0 and 1. For example, by constructing a mapping table between the average mud thickness deviation and weighting coefficients, the real-time detected average mud thickness deviation is input and transmitted to the corresponding mapping table in the database, thereby quickly obtaining the weighting coefficient corresponding to the average mud thickness deviation. Similarly, for sediment volume density deviation, by constructing a mapping table between sediment volume density deviation and weighting coefficients, the real-time detected sediment volume density deviation is input and transmitted to the corresponding mapping table in the database, thereby quickly obtaining the weighting coefficient corresponding to the sediment volume density deviation. For shear wave velocity offset, a pre-established mapping table between shear wave velocity offset and weighting coefficients can also be used to input the real-time measured shear wave velocity offset and transmit it to the corresponding mapping table in the database, thereby quickly obtaining the weighting coefficient corresponding to the shear wave velocity offset. Likewise, for anomalous elevation change characterization values, by constructing a mapping table between anomalous elevation change characterization values ​​and weighting coefficients, the real-time obtained anomalous elevation change characterization values ​​are input and transmitted to the corresponding mapping table in the database, thereby quickly obtaining the weighting coefficient corresponding to the anomalous elevation change characterization values.

[0077] Specifically, the loose structure of the silt deposits in the construction area of ​​the immersed tunnel foundation trench is compensated. The specific process is as follows: extract the loose structure characterization value of the backfilled silt in each sub-region of the immersed tunnel foundation trench construction area, and match it with the static pressure load compensation value corresponding to each interval of the loose structure characterization value of the backfilled silt in the database to obtain the static pressure load compensation value of each sub-region of the immersed tunnel foundation trench construction area. The loose structure of the silt deposits in the construction area of ​​the immersed tunnel foundation trench is compensated according to the static pressure load compensation value of each sub-region of the immersed tunnel foundation trench construction area.

[0078] It should be noted that the specific process of compensating for the loose structure of silt deposits in the construction area of ​​the immersed tunnel foundation trench based on the static pressure load compensation value of each sub-area of ​​the immersed tunnel foundation trench is as follows: the static pressure load compensation value of each sub-area of ​​the immersed tunnel foundation trench is added to the original static pressure load of each sub-area of ​​the immersed tunnel foundation trench.

[0079] Specifically, an early warning system is implemented for the immersed tunnel construction process. The specific process is as follows: count the number of abnormal elevation change areas in each immersed tunnel foundation trench construction area, extract the static pressure load compensation value of each immersed tunnel foundation trench construction sub-area and compare it with the static pressure load compensation threshold set in the database, count the number of immersed tunnel foundation trench construction sub-areas whose static pressure load compensation value is higher than or equal to the static pressure load compensation threshold, and record it as the number of loose physical properties in each immersed tunnel foundation trench construction sub-area.

[0080] The number of abnormal elevation change areas in each immersed tunnel foundation trench construction area and the number of loose physical structures in each immersed tunnel foundation trench construction sub-area are compared with the threshold numbers for the number of abnormal elevation change areas and the threshold numbers for the number of loose physical structures, respectively. If the number of abnormal elevation change areas in each immersed tunnel foundation trench construction area and the number of loose physical structures in each immersed tunnel foundation trench construction sub-area are both higher than or equal to the threshold numbers for the number of abnormal elevation change areas and the threshold numbers for the number of loose physical structures, then an early warning is issued for the immersed tunnel construction process; otherwise, no early warning is required for the immersed tunnel construction process.

[0081] like Figure 2 As shown, Figure 2 This is a schematic diagram of the logical flow of a comprehensive detection, processing, and analysis method for deep foundation trenches in immersed tunnels. Based on shallow profile linkage calibration, it uses multi-beam delay characterization values ​​to dynamically compensate for beam slant distance and timestamps, ensuring that the 3D point cloud generated by macroscopic depth sounding has sub-centimeter elevation accuracy. Subsequently, it combines historical data to identify elevation anomalies online and adjust dredging strategies in real time. Then, it uses multi-frequency acoustic detection to construct a mud thickness cloud map, extracting physical property parameters such as thickness deviation, bulk density, and shear wave velocity to quantify the loose structure of sediments and automatically trigger compensation schemes. Finally, it combines topographic morphology and sediment properties for intelligent early warning, providing a path for deep foundation trench construction from high-precision calibration to dynamic compensation to multi-dimensional monitoring to closed-loop optimization to intelligent early warning, significantly improving monitoring accuracy, response timeliness, and construction safety.

[0082] like Figure 3 As shown, Figure 3 The schematic diagram of the logic flow for adjusting the dredging depth shows that the overall floating mud thickness cloud map is first subdivided into several sub-areas, and the abnormal elevation change characterization value of each sub-area is obtained by comprehensively calculating the abnormal elevation change characterization value of each sub-area. Based on this, the system judges whether the sub-area exceeds the limit. Finally, the dredging is dynamically deepened on the basis of the original design depth, while the sub-areas that do not exceed the limit maintain the original dredging depth. This not only can accurately locate and quantify the terrain anomalies, but also realize the intelligent and quantitative adjustment of the dredging depth, which greatly improves the accuracy and efficiency of deep foundation trench construction of immersed tunnels.

[0083] like Figure 4 As shown, the second aspect of the present invention also provides a comprehensive detection, processing and analysis system for deep foundation trenches of immersed tunnels, including: a sound beam positioning and correction module, used to transmit acoustic pulses and receive multi-beam array echoes in the construction area of ​​the immersed tunnel foundation trench using a multi-beam system, obtain multi-beam array echo parameters for analysis, obtain the multi-beam array echo delay characterization value of the construction area of ​​the immersed tunnel foundation trench, and compensate and correct the incident angle of the sound beam.

[0084] The abnormal elevation change analysis module is used to perform macroscopic scanning of the immersed tunnel foundation trench construction area, generate a three-dimensional point cloud model of the immersed tunnel foundation trench construction area, obtain and analyze the depth measurement data of the immersed tunnel foundation trench construction area, identify abnormal elevation changes in the immersed tunnel foundation trench construction area, and adjust the dredging depth.

[0085] The silt analysis module is used to collect and process multi-frequency raw signals of silt in the construction area of ​​the immersed tunnel foundation trench, generate a cloud map of the mud thickness in the construction area of ​​the immersed tunnel foundation trench, obtain and analyze the measurement parameters of the back silt in the mud thickness cloud map of the construction area of ​​the immersed tunnel foundation trench, and compensate for the loose structure of the silt in the construction area of ​​the immersed tunnel foundation trench.

[0086] The intelligent early warning module is used to provide early warnings for the construction process of immersed tunnels by combining the topography and sediment structure of the construction area of ​​the immersed tunnel foundation trench.

[0087] The comprehensive detection, processing, and analysis system for deep foundation trenches in immersed tunnels also includes a multibeam echo sounder system: comprising a high-frequency acoustic transmitter, receiver, data processing unit, and positioning system, capable of providing high-resolution seabed topographic data and accurately reflecting seabed depth when the mud-water density is below 1.03 kg / m³; a dual-frequency echo sounder for high and low frequency depth detection during the rough excavation stage, where the low-frequency beam can penetrate the floating mud layer, and combined with high-frequency beam data, accurately reflecting the hard-bottom water depth during trench excavation; a mud density detection system, including a tuning fork densitometer, for detecting mud density and floating mud thickness within the trench, measuring density values ​​through tuning fork vibration response, and determining the density characteristics of backfilled sediments by combining echo sounder data; and an acoustic analysis system for monitoring floating mud distribution thickness, classifying floating mud thickness according to density gradients based on the penetrating power of low-frequency sound waves. This system includes acoustic sensors, a data acquisition unit, and analysis software, capable of providing high-precision measurement data of floating mud thickness. Shallow seismic profiler is used to detect the propagation characteristics of sound waves in soil and rock media, infer the structure and density of the soil and rock media, and can provide detailed information on the soil and rock structure at the bottom of the foundation trench; Elevation anomaly measurement system: combining GNSS (Global Navigation Satellite System) and CORS (Continuously Operating Reference Station System), it is used to accurately measure the elevation anomaly values ​​of the construction area to ensure the accuracy of the depth sounding data, and also includes a GNSS receiver, a data processing unit, and an elevation anomaly calculation module. The sonar pre-calibration stage involves emitting a series of acoustic pulses of known frequencies through an acoustic analysis system, receiving echo parameters from a dual-frequency sounding system, calculating the beam array echo delay characterization value for the entire area, and dynamically compensating and correcting the incident angle of the acoustic beam accordingly. The macroscopic topographic scanning utilizes a calibrated multi-beam dual-frequency sounding system with GNSS / CORS positioning to scan the entire trench area along a predetermined route, generating a high-resolution 3D point cloud model in real time. This model is then compared with historical baseline data to identify abnormal elevation changes and automatically adjusts the dredging depth based on the magnitude of the anomalies. In the subsequent sediment property analysis stage, a mud density detection system (tuning fork vibration sound) is used. The system, in conjunction with a sounding instrument and a mud monitoring module, collects multi-frequency raw acoustic signals. Simultaneously, it uses a shallow seismic profiler to detect the sound velocity and shear wave velocity of the soil and rock media, generating a mud thickness cloud map and extracting physical property parameters such as thickness deviation for quantitative compensation of loose sedimentary layers. Finally, intelligent early warning sends real-time updated topographic morphology and sediment structure data to the early warning engine, automatically triggering risk alerts based on temporal trends and multi-source thresholds. This provides integrated technical support for deep foundation trench construction of immersed tunnels, encompassing precise calibration, macroscopic identification, physical property diagnosis, closed-loop adjustment, and early warning decision-making. This significantly improves the accuracy of depth sounding and sediment analysis, making dredging and reinforcement more targeted and timely.

[0088] The preset thresholds for abnormal elevation changes, static load compensation, the number of areas with abnormal elevation changes, and the number of loose structural features in the immersed tunnel foundation trench construction area are all stored in a database, typically based on historical monitoring data and design specifications. For example, the threshold for abnormal elevation changes can be derived from the statistical distribution of multiple depth measurements during the foundation trench benchmark construction phase. This could involve statistically analyzing the average and standard deviation of elevation differences at each measuring point in the past ten routine depth measurements, and then setting the threshold to the 95th percentile. This approach effectively covers most normal fluctuations while also eliminating occasional measurement noise. Secondly, the static load compensation threshold is determined by combining the bearing capacity curves of backfill materials and support structures obtained from laboratory tests. For instance, the minimum static load required to ensure 90% of the test samples reach the design density is used as the lower limit, satisfying both construction process stability and ensuring effective sediment compaction. The threshold for the number of abnormal elevation change areas can also be determined by the actual number of problems caused by local siltation or scouring in historical projects. For example, in the past five similar projects, an average of 3 to 5 abnormal areas may have occurred within a single daily measurement cycle, leading to pipe section connection deviations. Therefore, the threshold can be set at 5 areas. Finally, the threshold for the number of loose areas in the physical structure should refer to the proportion of loose areas tested after dredging and compaction in the same batch of construction sub-areas. For example, if 10% of the sub-areas still have looseness exceeding the specification limit under reasonable dredging depth and static pressure load, the threshold can be set within a range of 10% above or below that proportion.

[0089] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0091] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0093] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0094] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A comprehensive inspection, processing and analysis method for a deep trench of a immersed tube tunnel, characterized in that, The application relates to a method for monitoring a sediment deposition state of a immersed tube tunnel foundation trench construction area. The method comprises the following steps: emitting acoustic pulses by using a multi-beam system and receiving multi-beam array echoes in the immersed tube tunnel foundation trench construction area, acquiring multi-beam array echo parameters for analysis, obtaining multi-beam array echo delay characteristic values of the immersed tube tunnel foundation trench construction area, and compensating and correcting the incident angle of the sound beam; The method comprises the following steps: performing macroscopic scanning on the immersed tube tunnel foundation trench construction area, generating a three-dimensional point cloud model of the immersed tube tunnel foundation trench construction area, acquiring sounding data of the immersed tube tunnel foundation trench construction area for analysis, identifying abnormal elevation changes of the immersed tube tunnel foundation trench construction area, and adjusting the dredging depth; The method comprises the following steps: collecting multi-frequency original signals of the sediment deposition in the immersed tube tunnel foundation trench construction area and processing the multi-frequency original signals, generating a floating mud thickness cloud map of the immersed tube tunnel foundation trench construction area, acquiring measurement parameters of the back deposition sediment in the floating mud thickness cloud map of the immersed tube tunnel foundation trench construction area for analysis, and compensating for the loose structure of the sediment deposition in the immersed tube tunnel foundation trench construction area. The method comprises the following steps: combining the topography and sediment structure of the immersed tube tunnel foundation trench construction area to give a warning for the immersed tube tunnel construction process.

2. The integrated detection process and analysis method for the deep foundation trench of the immersed tube tunnel according to claim 1, characterized in that: The method comprises the following steps: presetting a monitoring time period, extracting multi-beam array echo parameters in the monitoring time period, including average echo time offset, average beam incident angle and average elevation deviation value; The method comprises the following steps: performing proportion analysis on the average echo time offset and the maximum echo time offset, the average beam incident angle and the calibrated beam incident angle, and the average elevation deviation value and the maximum elevation deviation value, respectively, introducing a weight coefficient to obtain the multi-beam array echo delay characteristic values of the immersed tube tunnel foundation trench construction area, and the multi-beam array echo delay characteristic values of the immersed tube tunnel foundation trench construction area are used to evaluate the influence degree of the beam tilt and the positioning time lag delay on the elevation accuracy. The method comprises the following steps: extracting the multi-beam array echo delay characteristic values of the immersed tube tunnel foundation trench construction area, comparing the multi-beam array echo delay characteristic values with the preset incident angle offset of the multi-beam array echo delay characteristic values of the immersed tube tunnel foundation trench construction area in the database, obtaining the incident angle offset of the immersed tube tunnel foundation trench construction area, and compensating and correcting the incident angle of the sound beam according to the incident angle offset of the immersed tube tunnel foundation trench construction area.

3. The integrated detection process and analysis method for the deep foundation trench of the immersed tube tunnel according to claim 2, characterized in that: The method comprises the following steps: dividing the immersed tube tunnel foundation trench construction area to obtain each immersed tube tunnel foundation trench construction sub-region, extracting the sounding data in each immersed tube tunnel foundation trench construction sub-region, including average elevation difference, average echo intensity and the number of effective sonar measuring points in the average unit area; The method comprises the following steps: performing proportion analysis on the average elevation difference and the historical reference elevation difference, the average echo intensity and the defined echo intensity, and the number of effective sonar measuring points in the average unit area and the number of defined effective sonar measuring points in the unit area, respectively, introducing a weight coefficient and the multi-beam array echo delay characteristic values of the immersed tube tunnel foundation trench construction area to obtain abnormal elevation change characteristic values of each immersed tube tunnel foundation trench construction sub-region, and the abnormal elevation change characteristic values of each immersed tube tunnel foundation trench construction sub-region are used to evaluate the abnormality degree of the deep foundation trench topography.

4. The integrated detection process and analysis method for the deep foundation trench of the immersed tube tunnel according to claim 1, characterized in that: ​ ​ ​ 5. The integrated detection process and analysis method for the deep foundation trench of the immersed tube tunnel according to claim 4, characterized in that: The specific process for identifying abnormal elevation changes in the construction area of ​​the immersed tunnel foundation trench is as follows: The abnormal elevation change characterization values ​​of each sub-region of immersed tunnel foundation trench construction are extracted and compared with the preset abnormal elevation change characterization threshold of immersed tunnel foundation trench construction area in the database. If the abnormal elevation change characterization value of a certain sub-region of immersed tunnel foundation trench construction is higher than or equal to the abnormal elevation change characterization threshold of the immersed tunnel foundation trench construction area, then the sub-region of immersed tunnel foundation trench construction is marked as the abnormal elevation change area of ​​the immersed tunnel foundation trench construction area, thus obtaining the abnormal elevation change areas of each immersed tunnel foundation trench construction area. If the abnormal elevation change characterization value of a certain sub-region of immersed tunnel foundation trench construction is lower than the abnormal elevation change characterization threshold of the immersed tunnel foundation trench construction area, then it is not necessary to mark the abnormal elevation change area of ​​the immersed tunnel foundation trench construction area.

6. The integrated detection process and analysis method for the deep foundation trench of the immersed tube tunnel according to claim 5, characterized in that: The specific process for adjusting the dredging depth is as follows: Extract the abnormal elevation change characterization values ​​of the sub-regions of the immersed tunnel foundation trench construction area corresponding to the abnormal elevation change areas of each immersed tunnel foundation trench construction area, and take the deviation between the abnormal elevation change characterization values ​​of the sub-regions of the immersed tunnel foundation trench construction area corresponding to the abnormal elevation change areas of each immersed tunnel foundation trench construction area and the preset abnormal elevation change characterization value threshold in the database as the dredging depth exceeding limit of each immersed tunnel foundation trench construction area. Adjust the dredging depth of the abnormal elevation change areas of each immersed tunnel foundation trench construction area according to the dredging depth exceeding limit of each immersed tunnel foundation trench construction area.

7. The integrated detection process and analysis method for the deep foundation trench of the immersed tube tunnel according to claim 1, characterized in that: The specific process for obtaining and analyzing the measurement parameters of the backfilled sediment in the mud thickness cloud map of the immersed tunnel foundation trench construction area is as follows: Extract the measurement parameters of the backfilled sediment from the mud thickness cloud map of each sub-area of ​​the immersed tunnel foundation trench construction, including the average mud thickness deviation, the current sediment volume density deviation, and the shear wave velocity offset; The average mud thickness deviation and the defined mud thickness deviation, the current sediment volume density deviation and the defined sediment volume density deviation, and the shear wave velocity offset and the defined shear wave velocity offset are respectively analyzed by proportion. Weighting coefficients and abnormal elevation change characterization values ​​of each immersed tunnel trench construction sub-region are introduced to obtain the physical property structure looseness characterization value of the backfilled sediment in each immersed tunnel trench construction sub-region. The physical property structure looseness characterization value of the backfilled sediment in each immersed tunnel trench construction sub-region is used to evaluate and quantify the overall structural looseness of the backfilled sediment.

8. The integrated detection process and analysis method for the deep foundation trench of the immersed tunnel as claimed in claim 7, characterized in that: The specific process for compensating for the loose structure of silt deposits in the construction area of ​​the immersed tunnel foundation trench is as follows: Extract the loose physical properties of the silt deposits in each sub-region of the immersed tunnel foundation trench construction area, and match them with the static pressure load compensation values ​​corresponding to each interval of the loose physical properties of the silt deposits set in the database to obtain the static pressure load compensation values ​​for each sub-region of the immersed tunnel foundation trench construction area. Compensate for the loose structure of the silt deposits in the immersed tunnel foundation trench construction area according to the static pressure load compensation values ​​for each sub-region of the immersed tunnel foundation trench construction area.

9. The integrated detection process and analysis method for the deep foundation trench of the immersed tunnel of claim 1, wherein: The process of issuing early warnings during the construction of immersed tunnels is as follows: count the number of abnormal elevation change regions of each immersed tunnel foundation trench construction area, and compare the static pressure load compensation value of each immersed tunnel foundation trench construction sub-region with the static pressure load compensation threshold set in the database, count the number of immersed tunnel foundation trench construction sub-regions whose static pressure load compensation value is higher than or equal to the static pressure load compensation threshold, and record it as the loose structure number of each immersed tunnel foundation trench construction sub-region; Compare the number of abnormal elevation change regions of each immersed tunnel foundation trench construction area and the loose structure number of each immersed tunnel foundation trench construction sub-region with the number threshold of abnormal elevation change regions and the loose structure number threshold, respectively. If the number of abnormal elevation change regions of each immersed tunnel foundation trench construction area and the loose structure number of each immersed tunnel foundation trench construction sub-region are both higher than or equal to the number threshold of abnormal elevation change regions and the loose structure number threshold, respectively, the immersed tunnel construction process is warned, otherwise the immersed tunnel construction process does not need to be warned.

10. The system for applying the comprehensive detection processing and analysis method for immersed tunnel deep foundation trenches according to any one of claims 1-9, comprising: a sound beam positioning correction module for emitting acoustic pulses in the immersed tunnel foundation trench construction area using a multi-beam system and receiving multi-beam array echoes, obtaining multi-beam array echo parameters for analysis, and obtaining multi-beam array echo delay characterization values of the immersed tunnel foundation trench construction area to compensate and correct the incident angle of the sound beam; an abnormal elevation change analysis module for macroscopically scanning the immersed tunnel foundation trench construction area, generating a three-dimensional point cloud model of the immersed tunnel foundation trench construction area, obtaining depth measurement data of the immersed tunnel foundation trench construction area for analysis, identifying abnormal elevation changes in the immersed tunnel foundation trench construction area, and adjusting the dredging depth; a silt deposit analysis module for collecting multi-frequency original signals of silt deposits in the immersed tunnel foundation trench construction area and processing them to generate a floating mud thickness cloud map of the immersed tunnel foundation trench construction area, obtaining measurement parameters of the silt deposits in the floating mud thickness cloud map of the immersed tunnel foundation trench construction area for analysis, and compensating for the loose structure of the silt deposits in the immersed tunnel foundation trench construction area; an intelligent warning module for warning the immersed tunnel construction process in combination with the topography and sediment structure of the immersed tunnel foundation trench construction area.

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