A method, system, device and medium for monitoring a track of a rammer

Abstract

A ramming track monitoring method, system, device and medium, wherein the method comprises: acquiring construction monitoring data, real-time state parameters and environmental parameters of a rammer, the construction monitoring data comprising underwater acoustic signals, the real-time state parameters comprising circumferential pressure data and perpendicularity; determining a sinking track of the rammer in water; constructing an underwater pressure gradient distribution map of the rammer based on the circumferential pressure data; analyzing spatial attitude change characteristics of the rammer based on the underwater pressure gradient distribution map, the perpendicularity and the environmental parameters; determining an actual ramming position sequence of a target ramming point based on the spatial attitude change characteristics and the sinking track, and calculating an overlapping area of the rammer and the target ramming point; calculating the compaction degree of each target actual ramming position in the actual ramming position sequence; and constructing a ramming track feature map of the rammer according to the overlapping area, each target actual ramming position and the compaction degree corresponding to each target actual ramming position. The application can improve the accuracy of ramming track monitoring.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ramming track monitoring, and particularly relates to a ramming track monitoring method, system, device and medium. BACKGROUND

[0002] In the fields of infrastructure construction, port engineering and underwater foundation treatment, heavy hammer ramming is widely used in the reinforcement of soft ground and the improvement of engineering foundation stability as an important means of foundation reinforcement. This type of construction usually involves free falling a heavy rammer from a certain height, repeatedly ramming the soil or riprap body in the target area through impact energy, so as to achieve the purpose of compaction and reinforcement. In complex construction environments, especially in underwater or semi-underwater environments, the working state of the rammer is directly related to the uniformity of the ramming effect and the effectiveness of the foundation treatment.

[0003] In the related art, the position information of the rammer is obtained through a positioning device such as an underwater sonar positioning module installed on the rammer, and the ramming operation track of the rammer is monitored and recorded in combination with the preset ramming point arrangement parameters.

[0004] However, relying only on the position information of the rammer for ramming track monitoring is difficult to fully reflect the real movement path of the rammer in the ramming process and the contact state with the bed. Especially in underwater environments, due to factors such as the medium characteristics of the water body, the hammer posture change and the surrounding environmental interference, the movement track of the rammer in the falling process may deviate, tilt or be unstable in posture, etc. Relying only on the position information of the rammer for ramming track monitoring is difficult to reveal the details of these dynamic behaviors, reducing the accuracy of the ramming track monitoring. SUMMARY

[0005] The present application provides a ramming track monitoring method, system, device and medium for improving the accuracy of ramming track monitoring.

[0006] The first aspect of the application provides a method for monitoring the tamping track, applied to a server, the method comprising: obtaining construction monitoring data, real-time state parameters of a tamper and environmental parameters, wherein the construction monitoring data comprises underwater acoustic signals, the real-time state parameters comprise circumferential pressure data and verticality; determining the sinking track of the tamper in water based on the underwater acoustic signals, the real-time state parameters and the environmental parameters; constructing an underwater pressure gradient distribution map of the tamper based on the circumferential pressure data; analyzing the spatial attitude change characteristics of the tamper based on the underwater pressure gradient distribution map, the verticality and the environmental parameters; determining the actual tamping position sequence of the target tamping point based on the spatial attitude change characteristics and the sinking track, and calculating the overlapping area of the tamper and the target tamping point; calculating the compaction degree of each target actual tamping position in the actual tamping position sequence; and constructing the tamping track feature map of the tamper according to the overlapping area, each target actual tamping position and the corresponding compaction degree of each target actual tamping position.

[0007] Optionally, the determination of the sinking track of the tamper in water based on the underwater acoustic signals, the real-time state parameters and the environmental parameters comprises: constructing a dynamic frequency spectrum envelope of the underwater acoustic signals based on the frequency distribution characteristics of the underwater acoustic signals and the water flow velocity and water turbulence degree in the environmental parameters, determining the energy attenuation gradient of the underwater acoustic signals based on the dynamic frequency spectrum envelope; determining the deviation degree of the dynamic frequency spectrum envelope from the preset standard underwater acoustic propagation characteristics, determining the water turbulence intensity corresponding to the real-time position of the center of gravity of the tamper based on the deviation degree; analyzing the time sequence correspondence between the water turbulence intensity and the circumferential pressure data, identifying the cavity effect interval of the tamper in the sinking process, and determining the continuous sinking section and the resistance section of the tamper according to the duration of the cavity effect interval; calculating the sinking speed of the tamper based on the energy attenuation gradient corresponding to the continuous sinking section, the water turbulence intensity corresponding to the resistance section, the initial water entry speed of the tamper and the mass parameters of the tamper; and time sequence fusion of the sinking speed, the position coordinates in the real-time state parameters and the verticality to obtain the sinking track.

[0008] Optionally, the sinking speed of the rammer is calculated based on the energy attenuation gradient corresponding to the continuous sinking section, the water body turbulence intensity corresponding to the retardation section, the initial water entry speed of the rammer, and the mass parameter of the rammer, and specifically comprises: constructing a speed calculation function of the rammer based on the energy attenuation gradient corresponding to the continuous sinking section; determining a correction coefficient of an energy attenuation gradient term in the speed calculation function based on the water body turbulence intensity corresponding to the retardation section, and correcting the speed calculation function based on the correction coefficient to obtain a target speed calculation function; and calculating the sinking speed of the rammer based on the target speed calculation function, the initial water entry speed, and the mass parameter.

[0009] Optionally, the actual ramming position sequence of the target ramming point is determined based on the spatial posture change feature and the sinking trajectory, and the overlap area of the rammer and the target ramming point is calculated, and specifically comprises: determining a contact feature sequence of the rammer and the riprap bed based on the bed reflection wave data in the construction monitoring data; performing time domain matching on the spatial posture change feature and the contact feature sequence to determine a posture change time of the rammer; determining a speed change sequence of the rammer based on the sinking trajectory, combining the speed change sequence and the posture change time to determine a bottom touch time of the rammer, and determining an actual ramming position based on a position coordinate corresponding to the bottom touch time; determining an actual ramming position sequence of the target ramming point based on a plurality of actual ramming positions in a preset range of the target ramming point and the bottom touch time; and calculating the overlap area of the rammer and the target ramming point based on the contact feature sequence and the actual ramming position sequence.

[0010] Optionally, the overlap area of the rammer and the target ramming point is calculated based on the contact feature sequence and the actual ramming position sequence, and specifically comprises: determining an energy distribution feature of the rammer based on the contact feature sequence; determining a compaction influence radius of each target actual ramming position in the actual ramming position sequence based on the energy distribution feature, and determining a compaction influence area of each target actual ramming position in the actual ramming position sequence according to the compaction influence radius; and performing weighted superposition on the area of the compaction influence area of each target actual ramming position to obtain the overlap area.

[0011] Optionally, the compaction degree of each target actual ramming position in the actual ramming position sequence is calculated, and specifically comprises:

[0012] The compaction degree is calculated by the following formula: , is the compaction degree of the i-th target actual ramming position, is the overlap area of the i-th target actual ramming position, an effective energy of the i-th target actual ramming position for the k-th ramming, a preset energy reference value, a contact pressure of the i-th target actual ramming position for the k-th ramming, a preset pressure reference value, a rammer posture offset angle of the i-th target actual ramming position for the k-th ramming, a ramming influence radius of the i-th target actual ramming position for the k-th ramming, a preset ramming influence radius reference value, and n is a maximum number of rammings, and i ∈ [1, n].

[0013] Optionally, the ramming track feature map of the rammer is constructed according to the overlap area, each target actual ramming position, and the compaction degree corresponding to each target actual ramming position, and specifically includes: connecting the target actual ramming positions in time sequence, and determining a coverage range circle of each target actual ramming position based on the overlap area, a radius of the coverage range circle being proportional to the overlap area, to obtain a ramming path schematic diagram; in the ramming path schematic diagram, a display contrast of the coverage range circle is determined according to the compaction degree, to obtain the ramming track feature map.

[0014] In a second aspect of the present application, a ramming track monitoring system is provided, including:

[0015] an acquisition module configured to acquire construction monitoring data, real-time state parameters of a rammer, and environmental parameters, wherein the construction monitoring data includes underwater acoustic signals, and the real-time state parameters include circumferential pressure data and verticality;

[0016] a first analysis module configured to determine a sinking track of the rammer in water based on the underwater acoustic signals, the real-time state parameters, and the environmental parameters;

[0017] a first construction module configured to construct an underwater pressure gradient distribution map of the rammer based on the circumferential pressure data;

[0018] a second analysis module configured to analyze spatial posture change characteristics of the rammer based on the underwater pressure gradient distribution map, the verticality, and the environmental parameters;

[0019] a determination module configured to determine an actual ramming position sequence of a target ramming point based on the spatial posture change characteristics and the sinking track, and calculate an overlap area of the rammer and the target ramming point;

[0020] a calculation module configured to calculate a compaction degree of each target actual ramming position in the actual ramming position sequence;

[0021] a second construction module configured to construct a ramming track feature map of the rammer according to the overlap area, each of the target actual ramming positions, and the compaction degree corresponding to each of the target actual ramming positions.

[0022] In a third aspect of the present application, an electronic device is provided, comprising a processor, a memory, a user interface, and a network interface, the memory is configured to store instructions, the user interface and the network interface are configured to communicate with other devices, and the processor is configured to execute the instructions stored in the memory to enable the electronic device to perform the method of any one of the above aspects.

[0023] In a fourth aspect of the present application, a computer-readable storage medium is provided, which stores instructions that, when executed, perform the method of any one of the above aspects.

[0024] In summary, the one or more technical solutions provided by the present application have at least the following technical effects or advantages:

[0025] 1. By obtaining construction monitoring data, real-time state parameters of the rammer, and environmental parameters, especially including underwater acoustic signals, circumferential pressure data, and verticality information, the multi-dimensional state changes of the rammer during movement in water can be more comprehensively reflected, and compared with the method of relying only on position information for ramming track monitoring, the perception ability of the actual movement track of the rammer can be improved. By fusing the underwater acoustic signals, real-time state parameters, and environmental parameters, the sinking track of the rammer in water can be determined, and further based on the circumferential pressure data, a pressure gradient distribution map can be constructed, and then combined with the verticality information and environmental parameters, the spatial attitude change characteristics of the rammer can be analyzed, so that the sinking process of the rammer is dynamically monitored, and the real movement behavior embodied by the attitude change is effectively captured. By jointly analyzing the sinking track and the attitude change characteristics, the actual ramming position sequence of the target ramming point can be determined, and based on the sequence and the overlap area between the rammer and the target ramming point, the compaction degree of each actual ramming position can be further calculated, and finally the ramming track feature map of the rammer is constructed. The feature map is no longer limited to the two-dimensional position level, but fuses multi-dimensional parameters such as attitude change, sinking path, contact state, and compaction degree, so that the spatial dynamic behavior of the rammer during actual ramming can be more accurately described. Especially in the complex underwater environment, by means of multi-source data fusion, the problem of insufficient monitoring of single position information due to the medium characteristics of water and environmental interference is solved, and the accuracy of the ramming track monitoring is improved.

[0026] 2、By introducing the frequency distribution characteristics of underwater acoustic signals and the flow velocity and water turbulence in the environmental parameters, a dynamic spectral envelope of underwater acoustic signals is constructed, and based on the dynamic spectral envelope, the energy attenuation gradient of the acoustic signals in the medium is determined, so that the energy change law in the sound wave propagation process in the complex water environment can be accurately reflected, and then the basic data support for the subsequent discrimination of the rammer sinking state is provided. By comparing the dynamic spectral envelope with the preset standard underwater acoustic propagation characteristics, the deviation degree is determined, and the water turbulence intensity corresponding to the real-time position of the rammer gravity center is calculated, which can effectively reflect the disturbance degree of the water around the rammer, realize the dynamic perception of the local water environment change. On this basis, combined with the time sequence change analysis of the circumferential pressure data, the cavity effect interval formed by the rammer in the sinking process can be identified, and based on the continuous time length of the interval, the continuous sinking section and the blocking section of the rammer are further divided, so as to more finely depict the nonlinear motion characteristics of the rammer. Combined with the energy attenuation gradient corresponding to the continuous sinking section, the water turbulence intensity corresponding to the blocking section, the initial speed and mass parameters of the rammer into the water, the present scheme can comprehensively model the dynamics of the rammer in the water, and accurately calculate the sinking speed. Finally, by time sequence fusion of the sinking speed and the position coordinates and the verticality in the real-time state parameters, the complete sinking trajectory of the rammer in the water is obtained. Compared with the traditional sinking path construction mode which only depends on the position information, the present scheme integrates the underwater acoustic response characteristics and multi-dimensional dynamic parameters, which can overcome the influence of water medium interference, attitude change and turbulence disturbance and other factors on the trajectory recognition accuracy, realize the dynamic, continuous and high-precision modeling of the real sinking process of the rammer, and significantly improve the accuracy and adaptability of the underwater rammer sinking trajectory monitoring.

[0027] 3、In the calculation process of the rammer sinking speed, by taking the energy attenuation gradient corresponding to the continuous sinking section as the key input parameter, the speed calculation function of the rammer is constructed, so that the speed calculation not only reflects the acoustic propagation characteristics of the water body where the rammer is located, but also indirectly reflects the influence of physical factors such as water density, resistance coefficient and sound energy dissipation on the motion state of the rammer. Further, after identifying the existence of the resistance section in the sinking process of the rammer, based on the water turbulence intensity corresponding to the resistance section, the correction coefficient for correcting the energy attenuation gradient term in the speed calculation function is determined, so that the function can dynamically adapt to the nonlinear mapping relationship between the sound energy attenuation and the actual resistance change under the condition of complex water disturbance, thereby improving the physical consistency and calculation accuracy of the speed model. After the initial speed calculation function is corrected to obtain the target speed calculation function, combined with the initial speed and mass parameters of the rammer, the instantaneous sinking speed of the rammer in different hydrodynamic environments can be calculated more accurately. Compared with the traditional speed calculation method using fixed water resistance model or empirical formula, by integrating the dynamic response mechanism of acoustic energy attenuation characteristics and water turbulence intensity, the adaptive adjustment ability of the sinking speed calculation model is realized, the problem of inaccurate speed estimation caused by severe resistance change in the underwater high disturbance environment is solved, thereby providing a solid data foundation for subsequent high-fidelity reconstruction of the rammer sinking trajectory, and improving the precision and stability of the underwater ramming operation monitoring. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 is a system architecture schematic diagram of a ramming trajectory monitoring system in an embodiment of the present application;

[0029] Figure 2 is a flowchart of a ramming trajectory monitoring method in an embodiment of the present application;

[0030] Figure 3 is a structural schematic diagram of a ramming trajectory monitoring system in an embodiment of the present application;

[0031] Figure 4 is a structural schematic diagram of an electronic device in an embodiment of the present application.

[0032] Marked with reference numerals: 301, acquisition module; 302, first analysis module; 303, first construction module; 304, second analysis module; 305, determination module; 306, calculation module; 307, second construction module; 401, processor; 402, communication bus; 403, user interface; 404, network interface; 405, memory. DETAILED DESCRIPTION

[0033] In order for those skilled in the art to better understand the technical solutions in the specification, the technical solutions in the specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the specification. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments.

[0034] In the description of the embodiments of the present application, the words such as "for example" or "for instance" are used to represent an example, illustration or description. Any embodiment or design scheme described as "for example" or "for instance" in the embodiments of the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the words such as "for example" or "for instance" are intended to present the relevant concept in a specific manner.

[0035] In the description of the embodiments of the present application, the term "a plurality of" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. In addition, the terms "first" and "second" are used only for the purpose of description, and should not be interpreted as indicating or implying relative importance or implicitly indicating the indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more of the features. The terms "include", "contain", "have" and their variants mean "include but are not limited to", unless otherwise specifically emphasized.

[0036] Figure 1 A system architecture diagram of a track monitoring system for ramming is shown.

[0037] As Figure 1 shown, the system architecture 100 can include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 can include various connection types, such as wired, wireless communication links or optical fiber cables, etc. Users can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications can be installed on the terminal devices 101, 102, 103, such as model training applications, video recognition applications, web browser applications, social platform software, etc.

[0038] The terminal device 101, 102, 103 can be hardware or software. When the terminal device 101, 102, 103 is hardware, it can be various electronic devices with a display screen, including but not limited to a smart phone, a tablet computer, an e-book reader, an MP3 (Moving Picture Experts Group Audio Layer III) player, an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop computer, a desktop computer, and the like. When the terminal device 101, 102, 103 is software, it can be installed in the above-listed electronic devices. It can be implemented as multiple software or software modules (for example, multiple software or software modules for providing distributed services) or as a single software or software module. No specific limitation is made herein.

[0039] When the terminal device 101, 102, 103 is hardware, a video acquisition device can also be installed thereon. The video acquisition device can be various devices capable of acquiring video, such as a camera, a sensor, and the like. A user can acquire video by using the video acquisition device on the terminal device 101, 102, 103. The server 105 can be a server providing various services, for example, a background server for processing data displayed on the terminal device 101, 102, 103. The background server can analyze and process received data, and can feed back the processing result (for example, a recognition result) to the terminal device. It should be understood that Figure 1 The number of terminal devices, networks, and servers in FIG. 1 is merely illustrative. According to the needs of implementation, there can be any number of terminal devices, networks, and servers. In particular, in the case where target data does not need to be acquired from a remote place, the above system architecture can not include a network, but only include a terminal device or a server.

[0040] Figure 2 FIG. 1 is a flow diagram of a method for monitoring a ramming track according to an embodiment of the present application.

[0041] Referring to FIG. 1, Figure 2 A method for monitoring a ramming track according to an embodiment of the present application is applied to a server, and the method includes:

[0042] S201, acquiring construction monitoring data, real-time state parameters of a rammer, and environmental parameters, the construction monitoring data including underwater acoustic signals, the real-time state parameters including circumferential pressure data and perpendicularity;

[0043] In step S201, in order to realize the trajectory monitoring of the rammer tamping process, the construction monitoring data, the real-time state parameters of the rammer and the environmental parameters need to be obtained. The underwater acoustic signal in the construction monitoring data is collected by the underwater acoustic sensing device arranged in the water body in the construction area, which can be a multi-channel hydrophone or a wideband acoustic receiving array, which functions to receive the sound wave signals generated in the falling process of the rammer in real time, and convert the sound wave signals into electrical signals for digital processing. Since the rammer will excite obvious acoustic disturbance in the local water body during the water entry and sinking process, the underwater acoustic signal can reflect the sound wave propagation characteristics generated by the rammer at different depths and different attitudes in the water, thereby providing acoustic characteristic basis for analyzing the motion path and stress state of the rammer.

[0044] In the present embodiment, in addition to the underwater acoustic signal used to identify the sinking behavior of the rammer, the base bed reflection wave data is further introduced to obtain the response characteristics of the rammer in the process of approaching or contacting the riprap base bed. The base bed reflection wave refers to the sound wave emitted by the rammer in the sinking process or the water body disturbance sound wave excited thereby, which is reflected after propagating to the riprap base bed of the water bottom, and the echo signal is received by the acoustic receiving array collecting device arranged in the water. The essence is the energy feedback signal generated by the reflection of sound waves on the medium interface. By analyzing the characteristic parameters such as the amplitude, frequency change and arrival time delay of the reflection wave, the relative proximity, contact state and contact duration between the rammer and the riprap base bed can be judged. Specifically, in the implementation process, the collection of base bed reflection wave data depends on a high-sensitivity underwater acoustic receiving equipment, which is arranged around the sinking path of the rammer and is data-linked with the server system. When the rammer gradually approaches the base bed area of the water bottom, due to the significant change of the reflection coefficient of sound waves on the interface between water body and riprap medium, the reflection wave signal formed will show regular changes in energy distribution. The server can identify the dynamic process of the reflection wave from weak to strong and from scattered to concentrated by analyzing the sound pressure level change curve of the echo in the continuous time period, which corresponds to the state evolution of the rammer from far away to contact the base bed.

[0045] The real-time state parameters of the rammer mainly include the circumferential pressure data and the verticality information. The circumferential pressure data is collected by a group of pressure sensors installed on the surface of the peripheral structure of the rammer. These sensors are uniformly arranged around the hammer body at certain angles, which can obtain the water pressure changes in each direction on the surface of the rammer in real time during the sinking process of the rammer, thereby reflecting the stress distribution state of the rammer in different directions. The verticality information is obtained by a high-precision attitude sensor or an inertial measurement unit, which is usually installed near the central axis of the rammer. Its function is to measure the deflection angle of the rammer relative to the theoretical vertical direction in real time, and then judge the attitude stability and inclination trend of the rammer in the sinking process.

[0046] The environmental parameters include water flow velocity, water turbulence, water temperature, water depth, and water density in the construction area, and the like. The parameters are collected by a multi-point hydrological monitoring device arranged in the construction area. For example, a Doppler flow meter is used to measure the water velocity distribution at different depths, and a turbulence sensor is used to evaluate the degree of local water disturbance. The acquisition of the environmental parameters helps to restore the fluid dynamic environment of the water area where the rammer is located, and provides necessary boundary conditions for subsequent analysis of the underwater sound wave propagation path and the motion state of the rammer.

[0047] S202, determining a sinking trajectory of the rammer in water based on the underwater acoustic signal, the real-time state parameter, and the environmental parameter;

[0048] In order to realize dynamic reconstruction of the real sinking trajectory of the rammer in water, three types of multi-source data, i.e., underwater acoustic signal, real-time state parameter of the rammer, and environmental parameter, are comprehensively utilized to construct a dynamic physical model of the complex motion process of the rammer in water. Due to multiple factors such as water flow disturbance, turbulence interference, and attitude change of the rammer itself in the underwater environment, it is difficult to accurately reveal the real sinking path of the rammer by relying on single-dimensional data only, and therefore a multi-dimensional data fusion method is needed to deeply model the sinking behavior of the rammer. It can include steps S2021-S2025:

[0049] S2021, constructing a dynamic spectral envelope of the underwater acoustic signal based on the frequency distribution characteristics of the underwater acoustic signal and the water flow velocity and water turbulence in the environmental parameter, and determining an energy attenuation gradient of the underwater acoustic signal based on the dynamic spectral envelope;

[0050] The dynamic spectral envelope refers to a short time period sampling interval dynamically divided based on the sampling frequency of the acoustic signal and the sinking speed of the rammer, with the starting time of the rammer entering water as the starting point. The time window is usually a sliding window between 10 milliseconds and 200 milliseconds, and the window length is controlled by a system preset parameter. The setting principle is to ensure that the frequency response of the acoustic signal remains stable enough in each window period to enable effective frequency domain analysis. The basis for selecting the time window is the proportional relationship between the sound wave propagation speed in water (about 1500 meters / second) and the sinking speed of the rammer (usually 1-3 meters / second), so as to ensure that the relative position change of the rammer in each window is within a controllable range, avoid confusing the spectral response characteristics of different depth horizons, and fit the envelope profile of the frequency distribution intensity of the acoustic signal with time change trend. The dynamic spectral envelope can reflect the attenuation speed of the sound wave energy at different frequency bands and the coupling relationship with water disturbance.

[0051] By matching the dynamic spectral envelope with the actual water flow velocity and turbulence intensity, the energy attenuation gradient in the process of sound wave propagation can be deduced. As an indicator of the interaction strength between the rammer and the surrounding water, the energy attenuation gradient can be used to characterize the resistance of the rammer in different depth environments. Specifically, the system first performs frequency-domain transformation on the acoustic signal within a continuous sliding time window starting from the rammer's water entry time, extracts the energy distribution characteristics in the frequency-time-depth three-dimensional space, and constructs a spectral energy response tensor: , , wherein: represents the energy amplitude of the jth frequency band at the kth depth layer in the ith time window, T, F, and D are the discrete sets of time, frequency, and depth, respectively, characterizes the energy time-frequency distribution changes of the sound wave at different depths. At the same time, the system synchronously acquires the real-time environmental parameters of each depth layer, including the water flow velocity field and the turbulence intensity field, and jointly models the water flow velocity field, the turbulence intensity field, and the spectral energy response tensor to construct the following nonlinear coupling mapping function: , wherein: represents the spectral energy perturbation response function of frequency band j at depth d, represents the energy response sequence of frequency band j at depth d for all time windows, and ϕ(·) is a nonlinear fitting function, which can take the form of Gaussian mixture, radial basis function, or deep regression network, v(d) and τ(d) are the water flow velocity and turbulence intensity corresponding to the depth, respectively. Based on the above definition, the system derives the perturbation response function of all frequency bands at each depth point d, and further constructs the energy attenuation gradient function : The energy attenuation gradient is the average value of the perturbation response function of all frequency bands with respect to the depth gradient in the frequency domain, and can comprehensively reflect the propagation loss trend of sound energy in different depth environments due to hydrodynamic disturbance.

[0052] S2022, determining the deviation degree of the dynamic spectral envelope from the preset standard underwater acoustic propagation characteristics, and determining the turbulence intensity of the water body corresponding to the real-time position of the center of gravity of the rammer based on the deviation degree;

[0053] The standard propagation characteristics are reference curves established according to the sound wave propagation model measured in static or ideal water bodies, which are used to describe the attenuation law of sound waves under undisturbed conditions. When the deviation between the integral energy value of the current dynamic spectral envelope and the energy value of the corresponding frequency band of the standard propagation curve exceeds the preset energy deviation threshold in the same frequency band range, it indicates that there is strong disturbance in the sound wave propagation path. The preset energy deviation threshold is a statistical parameter obtained by fitting a large amount of experimental data, which is usually clustered and analyzed based on the acoustic data sets collected in different turbulence conditions in historical construction sites, and finally forms a multi-level threshold library suitable for the target water environment.

[0054] Further, the system inversely deduces the water turbulence intensity at the current location of the rammer through the spectral deviation degree, which is based on the coupling relationship between the sound energy propagation model and the turbulence energy consumption model. In the specific implementation process, the system first determines the energy deviation value ΔE of the dynamic spectral envelope line and the standard curve in a specific frequency band (such as low frequency 50-500Hz), and then calculates the turbulence intensity according to the following formula : , wherein is the spectral energy deviation value (unit: dB), is the current water flow velocity, and a and β are calibration parameters obtained through experimental regression fitting, reflecting the coupling relationship between sound energy loss and flow velocity. The system compares the calculated with the calibrated turbulence intensity level table in the environmental database, so as to quantitatively determine the water turbulence intensity value at the current location of the rammer, which is m 2 / s 3 (complying with the international standard notation of turbulence dissipation rate).

[0055] S2023, analyze the time sequence correspondence between the water turbulence intensity and the circumferential pressure data, identify the cavity effect interval of the rammer in the sinking process, and determine the continuous sinking section and the blocking section of the rammer according to the duration of the cavity effect interval;

[0056] The cavity effect refers to the local low-pressure area formed at the bottom or both sides of the rammer when it sinks at high speed, so that the water cannot be filled in time, forming a bubble-like cavity structure, and then causing the sinking resistance to decrease sharply or change suddenly. By analyzing the time sequence of the circumferential pressure data collected by the pressure sensor and combining the mutation trend of the water turbulence intensity, the starting and ending time of the cavity effect can be identified, and then the continuous sinking section and the blocking section of the rammer in the sinking process can be divided. For example, if the circumferential pressure instantaneously decreases and the turbulence intensity suddenly rises in a certain period of time, it may indicate that the rammer enters the cavity area, and this period of time can be determined as the continuous sinking section; when the pressure fluctuates sharply and the turbulence degree is unstable, it can be determined as the blocking section.

[0057] S2024, calculate the sinking speed of the rammer based on the energy attenuation gradient corresponding to the continuous sinking section, the water turbulence intensity corresponding to the blocking section, the initial speed of the rammer into the water, and the mass parameters of the rammer;

[0058] In a complex water environment, the actual sinking speed of the rammer is not only affected by the basic action of gravity and buoyancy, but also by fluid resistance, turbulent disturbance and water body acoustic energy dissipation and other nonlinear factors. Therefore, the traditional speed calculation model based on ideal flow field conditions often cannot accurately reflect the speed change of the rammer in the real sinking process. Therefore, the energy attenuation gradient corresponding to the continuous sinking section and the water body turbulence intensity corresponding to the resistance section are taken as the core input variables, and the speed calculation model with dynamic adaptability and physical consistency is constructed by combining the initial speed and mass parameters of the rammer into the water, so as to realize the physical modeling of the instantaneous speed of the rammer. It can include the following steps: based on the energy attenuation gradient corresponding to the continuous sinking section, the speed calculation function of the rammer is constructed; based on the water body turbulence intensity corresponding to the resistance section, the correction coefficient of the energy attenuation gradient term in the speed calculation function is determined, and the speed calculation function is corrected based on the correction coefficient to obtain the target speed calculation function; based on the target speed calculation function, the initial speed and mass parameters into the water, the sinking speed of the rammer is calculated.

[0059] Specifically, the system constructs the speed calculation function of the rammer based on the energy attenuation gradient corresponding to the continuous sinking section. The energy attenuation gradient reflects the rate of acoustic energy loss caused by water resistance, density change and interface reflection in the sinking path of the rammer. Since the attenuation of acoustic energy is positively correlated with the resistance of water to the rammer, the energy attenuation gradient can be used as an indirect indicator of the strength of fluid resistance experienced by the rammer. The system establishes the following functional relationship through experimental calibration: wherein, represents the theoretical speed of the rammer in the continuous sinking section, is the gravity experienced by the rammer, is the energy attenuation gradient, is the acoustic energy resistance mapping coefficient, and m is the mass of the rammer. The speed calculation function establishes a quantitative coupling between acoustic energy consumption and sinking resistance from the perspective of mechanics, so that the speed calculation process can reflect the energy interaction between the rammer and the water.

[0060] The system dynamically corrects the energy attenuation gradient term in the above speed calculation function based on the water body turbulence intensity corresponding to the resistance section, in order to improve the adaptability of the speed calculation function to complex disturbance conditions. The water body turbulence intensity is a disturbance intensity index calculated by comprehensively calculating the acoustic spectrum deviation and water flow velocity, with the unit of m 2 / s 3 The value directly affects the fluctuation and trend of the sinking speed of the rammer. The system corrects the energy attenuation gradient term by constructing a correction coefficient μ, and the correction relationship is as follows: wherein, is the water body turbulence intensity, is the turbulence correction coefficient. The corrected speed function is denoted as the target speed calculation function: By introducing a correction coefficient μ, not only is the velocity function made to account for the indirect influence of water disturbance on sound wave propagation, but a reasonable prediction of the significant decreasing trend of the ram's velocity in high turbulence zones is also achieved. For example, when the ram enters a highly turbulent region, The increase is significant, μ increases, and the corresponding The increased energy decay term leads to a decrease in the hammer speed, which is consistent with actual physical phenomena.

[0061] After obtaining the target velocity calculation function, the system, based on this function and in conjunction with the initial entry velocity and mass parameters of the rammer, calculates the sinking velocity of the rammer within any given time period. (Initial entry velocity) It is obtained through high frame rate image recognition or initial acceleration integration, and the quality parameter m is a known constant of the device. The system will As initial boundary conditions, the target velocity calculation function is integrated over time to obtain the velocity variation curves of the hammer at various depths in the water, and its velocity-time function curve is constructed accordingly: acceleration For example, in the first 2 seconds after entering the water, the ram is in a low turbulence environment and its speed rises slowly. After 2 to 3 seconds, it enters a high disturbance zone, the correction coefficient increases and the speed drops significantly. The system can reflect this change process in real time.

[0062] S2025. The sinking speed is fused with the position coordinates and verticality in the real-time status parameters to obtain the sinking trajectory.

[0063] In step S2025, the sinking velocity calculated in the previous step is fused with the position coordinates and verticality in the real-time state parameters, thereby mapping the velocity, position, and attitude information to the same temporal reference system to form a sinking trajectory with temporal continuity and spatial geometric consistency. Since the rammer sinks in water not only with velocity changes but also with attitude shifts and trajectory skew, relying solely on velocity or coordinate information cannot fully reflect its true motion path; therefore, multi-dimensional data fusion processing is necessary to achieve dynamic trajectory reconstruction.

[0064] In the specific implementation process, the system first integrates the instantaneous sinking velocity of the rammed hammer over time based on the principle of velocity integration to obtain a preliminary vector displacement sequence. The integration process is implemented using numerical integration algorithms, such as trapezoidal integration or the Runge-Kutta method, to improve the integration accuracy under non-uniform sampling conditions. The velocity at the initial time point is the initial velocity upon entering the water, and the corresponding position coordinates are obtained by the high-precision positioning module. The system uses this as the starting condition for iterative integration to form the foundation displacement path driven by velocity.

[0065] While acquiring the basic displacement path, the system extracts position coordinate data from real-time state parameters, which are usually provided by an underwater positioning system and have a certain sampling period and error range. Due to the influence of factors such as sound wave refraction and water flow disturbance in the underwater environment, the position information of the positioning system has a certain drift and jump, so the system uses Kalman filtering algorithm to fuse the velocity integral displacement and positioning coordinates, uses the dynamic continuity of the velocity data to correct the random error of the positioning data, and at the same time, through the position observation value, the deviation of the velocity estimation is constrained in the opposite direction, and the spatial accuracy and time consistency of the fusion result are improved.

[0066] At the same time, the system introduces the verticality data of the rammer into the trajectory fusion process. The verticality data is provided by the internal attitude sensor of the rammer (such as gyroscope, accelerometer), which is used to describe the deflection angle of the rammer at any time relative to the ideal vertical line direction. In trajectory reconstruction, the system uses verticality as an attitude correction factor to adjust the velocity vector and displacement direction through a rotation transformation matrix, ensuring that the movement path of the rammer when the attitude is inclined can be correctly projected into the three-dimensional coordinate system. This attitude correction mechanism effectively avoids the misjudgment of trajectory deviation caused by the inclination of the rammer, so that the final trajectory is more consistent with the actual physical movement process.

[0067] After completing velocity integration, coordinate correction and attitude adjustment, the system generates a three-dimensional sinking trajectory sequence of the rammer in time sequence. This trajectory not only contains the spatial position of the rammer at different time points, but also reflects its attitude change trend and motion stability. For example, if the trajectory gradually deviates from the vertical direction and the verticality continuously decreases in a certain period of time, it can be judged that the rammer has an unstable attitude phenomenon, and the system can prompt the construction risk or correct the ramming parameter configuration accordingly.

[0068] S203, constructing an underwater pressure gradient distribution map of the rammer based on the circumferential pressure data;

[0069] The underwater pressure gradient distribution map is used to describe the spatial variation of static pressure and dynamic pressure of the rammer at different circumferential angles and depth positions, and can directly reflect the uneven pressure phenomenon caused by factors such as attitude deviation, water flow disturbance or structural asymmetry during the sinking process of the rammer. It is a basic data model for analyzing the spatial attitude evolution and sinking stability of the rammer.

[0070] In implementation, the system first acquires real-time circumferential pressure data from a plurality of pressure sensors arranged on the surface of the rammer peripheral structure. Such pressure sensors are high-frequency response underwater micro-pressure sensors, usually installed in an equiangular distribution around the circumference of the rammer, for example, one set every 30 degrees, a total of 12 sets, forming a 360-degree full-coverage pressure acquisition array. Each set of sensors acquires the water pressure value at the position of the sensor in real time, forming a multi-channel pressure time series data set. The data is subjected to low-pass filtering in the preprocessing stage to eliminate high-frequency interference, and is subjected to normalization processing to eliminate the static water pressure baseline difference caused by depth changes.

[0071] Subsequently, the system constructs a three-dimensional data array according to the circumferential angle and time dimension with the attitude angle and depth of the rammer at the moment as the reference baseline, and applies a radial interpolation algorithm or a high-order spline fitting method to continuously map the pressure values in each direction, generating a pressure distribution image in two-dimensional polar coordinate form. The image takes angle as the horizontal axis, water depth as the vertical axis, and pressure value as the color distribution, and represents the pressure gradient corresponding to different angles and depths through color scale changes. Further, the system calculates the pressure difference in adjacent angle directions and the pressure increment rate at different depth points in the same direction, thereby forming a complete pressure gradient distribution map, which essentially reflects the non-uniform fluid force field acting on the rammer in the water body.

[0072] In order to improve the sensitivity of the distribution map to attitude changes, the system also introduces a normalized pressure gradient factor, i.e., the pressure difference ratio of each sampling point relative to the symmetry axis, which is used to strengthen the identification of whether the rammer has lateral tilt or eccentric motion. For example, when the pressure on one side is always higher than that on the opposite side, and the difference continues to expand with increasing depth, the system will determine that the rammer has a stable tilting trend, and mark it as a gradient anomaly area in the distribution map.

[0073] By constructing the underwater pressure gradient distribution map, the system not only realizes the visual expression of the circumferential stress state of the rammer, but also provides a key input for subsequent spatial attitude feature extraction. The map can be used to identify the force symmetry, attitude stability and coupling behavior with the surrounding water flow field of the rammer during sinking. For example, if the map shows that the pressure on the front direction of the rammer suddenly increases, while the pressure on the rear direction suddenly decreases within a certain time period, combined with the verticality change trend, it can be further analyzed whether there is a front-in-water or local rotation trend. The pressure gradient distribution map as a direct manifestation of physical response enhances the system's structured understanding ability of the dynamic attitude and trajectory deviation behavior of the rammer.

[0074] S204, analyzing the spatial attitude change characteristics of the rammer based on the underwater pressure gradient distribution map, the verticality and the environmental parameters;

[0075] The attitude change feature is not only used for describing the inclination amplitude, deflection direction and attitude stability of the rammer at different depths and different time periods, but also provides a key criterion for subsequent identification of actual ramming position sequences and calculation of overlapping areas, and constitutes a core intermediate variable in the identification chain of rammer motion behavior.

[0076] In specific implementation, the system first extracts the circumferential pressure difference sequence at the same depth layer from the underwater pressure gradient distribution map, and converts it into a planar vector field model based on polar coordinate transformation. In this model, the pressure difference in different angular directions is mapped as the size and direction of the vector, forming a spatial map of uneven force on the rammer. The system extracts the principal axis direction vector representing the main inclination direction and force deflection trend of the rammer by principal component analysis or tensor decomposition of the vector field. If the principal axis direction deviates stably from the theoretical vertical axis and the angle deviation continues to expand, the system judges that there is a persistent attitude deflection of the rammer.

[0077] At the same time, the system obtains the verticality data of the rammer from the real-time state parameters, which is derived from the three-axis inertial measurement unit (IMU) installed at the center of the rammer shaft. This device outputs the pitch angle, roll angle and yaw angle of the rammer relative to the gravity direction in real time through the joint solution of accelerometer, gyroscope and magnetometer. In spatial attitude change analysis, the system matches the verticality data with the principal axis direction extracted from the pressure vector field. If the deviation trends of the two are consistent, the system further confirms that the attitude change of the rammer has structural consistency, i.e. the external pressure distribution and the internal attitude measurement results form a logical closed loop, improving the accuracy and robustness of attitude judgment.

[0078] The environmental parameters are mainly used to correct the external disturbance influence of the water body on the attitude change of the rammer in the analysis process. The system introduces the flow velocity, water turbulence intensity and flow direction angle as disturbance compensation factors, which are coupled into the attitude change model to avoid misjudgment of short-time attitude disturbance caused by water flow impact as structural deflection of the rammer itself. For example, when the system detects a short-time attitude deflection but the flow velocity suddenly changes, the system can identify it as a transient change caused by external disturbance through the model, and does not include it in the spatial attitude feature change trend.

[0079] After the fusion of the three types of data, the system constructs the spatial attitude change feature sequence of the rammer in the entire sinking process, which is indexed by time and records the main inclination angle, deflection direction, attitude change rate and attitude stability level of the rammer at each time point. This feature sequence is not only continuous in the time dimension, but also has three-axis attitude decomposition capability in the spatial dimension, which can accurately reflect the attitude change pattern of the rammer in different depth intervals. For example, in a certain time period, the system records that the pitch angle of the rammer gradually increases, the main inclination direction changes from north-east to east, and the attitude change rate increases, which indicates that there is a cumulative trend of water entry angle deviation of the rammer in this stage, which may cause the ramming point to deviate.

[0080] S205, determining the actual ramming position sequence of the target ramming point based on the spatial attitude change feature and the subsidence trajectory, and calculating the overlapping area between the rammer and the target ramming point;

[0081] In step S205, based on the spatial attitude change feature and the subsidence trajectory obtained in the previous steps, the real hitting position of the rammer during the contact with the riprap bed is further identified, and the overlapping area between the rammer and the target ramming point is calculated by counting the distribution of multiple actual ramming positions in the range of the target ramming point. This step is not only used to determine whether the rammer completes effective ramming in the design area, but also used to analyze whether there is overlap, offset or empty hitting between the ramming points, which is a key link for evaluating the uniformity of ramming and controlling the compaction quality. To achieve this goal, the system aligns the attitude change, speed change and bed contact feature of the rammer in time and space, constructs the actual ramming position sequence, and calculates the overlapping area accordingly. It can include steps S2051-S2055:

[0082] S2051, determining the contact feature sequence of the rammer and the riprap bed based on the bed reflection wave data in the construction monitoring data;

[0083] The bed reflection wave data is a low-frequency acoustic wave generated by the rammer excitation or its own structure reflection, which forms a reflection signal after propagating to the riprap bed surface and is collected by the underwater acoustic receiving array in real time. By analyzing the amplitude, arrival time delay and spectral characteristics of the echo signal, the system identifies the change process of the reflection wave from weak to strong, from dispersion to concentration and then to attenuation, and takes the peak time as the reference point of the rammer contacting the bed to form the contact feature sequence. The contact feature sequence records all the time nodes and corresponding signal intensities of the effective acoustic reflection between the rammer and the bed, which can be used to accurately identify whether the ramming bottom behavior occurs and the frequency.

[0084] S2052, time domain matching the spatial attitude change feature and the contact feature sequence to determine the attitude change time of the rammer;

[0085] Specifically, the system takes the reflection wave peak time in the contact feature sequence as the anchor point, finds the attitude parameters of the adjacent time period in the attitude change sequence, and judges whether the rammer is in a stable attitude state at the bottom touching moment by comparing the pitch angle, roll angle and their change rates before and after the contact time. For example, when the attitude angle changes less than a preset threshold before and after the contact time, the system determines that this ramming is stable, otherwise it is marked as a biased ramming. This matching process helps to exclude non-effective ramming records caused by dramatic attitude changes, and improves the accuracy of actual ramming position judgment.

[0086] S2053, determine a speed change sequence of the rammer based on the sinking trajectory, determine a bottom-touching moment of the rammer by combining the speed change sequence and the attitude change moment, determine an actual ramming position based on a position coordinate corresponding to the bottom-touching moment;

[0087] The speed change sequence is generated by the target speed calculation function in the previous step, and records the speed change trend of the rammer in the entire sinking process. The system sets a speed threshold, when the speed drops below the threshold and the contact signal intensity reaches the peak, it is judged as the bottom-touching moment. Further, the system extracts the spatial position coordinate of this moment in the sinking trajectory as the actual ramming position. Through this fusion judgment method, the system avoids the false judgment of the bottom-touching moment caused by the fluctuation of a single data source, and improves the stability of the ramming position recognition.

[0088] S2054, determine an actual ramming position sequence of the target ramming point based on a plurality of actual ramming positions and bottom-touching moments within a preset range of the target ramming point;

[0089] The system takes the preset range of the target ramming point as a spatial constraint condition, and counts all actual ramming positions corresponding to the bottom-touching moments within the range to construct the actual ramming position sequence of the target ramming point. The preset range is usually a boundary rectangular or circular area marked in the design drawing, which is defined in the form of two-dimensional plane coordinates in the system. When the actual ramming position falls within the boundary range, the system will include it in the actual ramming record of the current target ramming point. In this way, the system can determine whether a ramming target is covered multiple times, whether there is a rammer offset strike behavior, etc.

[0090] S2055, calculate the overlap area of the rammer and the target ramming point based on the contact feature sequence and the actual ramming position sequence.

[0091] To quantitatively calculate the overlap area between the tamping hammer and the target impact point, step S2055 no longer relies solely on the geometric overlap of the actual impact locations. Instead, it further incorporates the impact energy distribution characteristics and the derived compaction influence zone, constructing a physical superposition model based on energy diffusion and impact coverage effects. This approach more accurately reflects the actual impact range of the tamping on the riprap subgrade, avoiding misjudgments of the effective tamping area due to slight deviations in the tamping hammer's sinking path, thereby improving the accuracy of tamping quality assessment. To achieve this goal, the system uses the contact feature sequence as input, extracts the energy release characteristics of the tamping hammer during each impact, calculates the compaction influence radius based on this, constructs the compaction influence zone, and obtains the total overlap area through weighted superposition of multiple zones. The steps may include: determining the energy distribution characteristics of the tamping hammer based on the contact feature sequence; determining the compaction influence radius of each target's actual tamping position in the actual tamping position sequence based on the energy distribution characteristics; determining the compaction influence area of ​​each target's actual tamping position in the actual tamping position sequence based on the compaction influence radius; and weighting and superimposing the areas of the compaction influence areas of each target's actual tamping position to obtain the overlap area.

[0092] In this embodiment, the system determines the energy distribution characteristics of the tamping hammer based on the contact feature sequence. The purpose is to transform the acoustic contact response into a physically meaningful energy diffusion spectrum, which characterizes the spatial propagation range and directional distribution of the energy released by the tamping hammer onto the riprap bed during each tamping process. The energy distribution characteristics of the tamping hammer are an energy action model of each tamping event in two-dimensional or three-dimensional space, usually represented as a spatial function with energy weights, used for the subsequent construction of the compaction influence area and the superposition calculation of the overlap area. To obtain these energy distribution characteristics, the system starts from acoustic reflection data and establishes the energy spatial distribution function for each tamping impact through three processes: kinetic energy estimation, normalized diffusion modeling, and attitude coupling correction.

[0093] In the specific implementation process, the system first extracts the acoustic reflection wave signal of each impact event from the contact feature sequence. The reflection wave signal is acquired by a multi-channel underwater acoustic receiving array deployed in the water body. The system performs short-time energy calculation on the original sound pressure time series and obtains the total reflected acoustic energy of each impact using the following integral formula. : Where p(t) is the sound pressure signal, The effective duration of the reflected wave. As an indicator of the acoustic energy generated after the tamper contacts the foundation bed. Total reflected acoustic energy. The higher the value, the stronger the impact kinetic energy or the more concentrated the energy release.

[0094] Subsequently, the system uses a preset acoustic-kinetic energy conversion function to map the total reflected acoustic energy into the equivalent impact kinetic energy of the tamping hammer. The function is calibrated by the initial experiment of construction, and the form is: wherein and are fitting coefficients. The ramming kinetic energy is taken as the total energy input to drive the construction of the energy distribution function.

[0095] To realize the modeling of energy in space, the system constructs a two-dimensional energy diffusion model centered on the actual ramming position. The model adopts a Gaussian distribution form, with the actual ramming point as the center point, and the energy diffuses outward in the horizontal plane. The mathematical expression is: wherein is the coordinate of the rammer bottom, , are the diffusion scale parameters of energy in the x-axis and y-axis directions, respectively, representing the energy decay rate. The asymmetric Gaussian form here is used to describe the difference in energy directional release caused by the rammer posture deviation.

[0096] To improve the modeling accuracy, the system introduces a posture correction factor to couple the pitch angle and roll angle obtained in the previous step into the diffusion scale parameters. When the rammer has a significant tilt, the system increases the diffusion scale parameter in the main direction of the tilt, for example: wherein is the standard diffusion scale, is the tilt angle, is an empirical coefficient. Through this correction mechanism, the system can construct an asymmetric distribution diagram of the energy diffusion range of the rammer under different postures. Finally, the system saves the energy distribution function in the above two-dimensional or three-dimensional form as the energy distribution feature of the current ramming event. This feature not only records the total intensity of energy, but also describes its diffusion trend, coverage range, and directional deviation in space.

[0097] In the foregoing steps, the system has constructed the energy distribution feature of each ramming of the rammer, i.e., a two-dimensional energy diffusion model centered on the actual ramming position , which describes the diffusion behavior of the rammer kinetic energy on the bed surface and reflects the intensity of ramming energy received by unit area at different spatial positions. To further quantify the compaction effect of ramming in space, the system needs to determine the compaction influence radius of each ramming based on the energy distribution function and determine the compaction influence area accordingly, thereby providing a spatial basis for the superposition calculation of the subsequent lap area. Specifically, the system first identifies the maximum value of each energy distribution function at the actual ramming position , which is equal to the energy density of the equivalent kinetic energy of ramming at the spatial center point. Subsequently, the system sets an energy threshold ratio ρ, usually 5%, i.e., when the energy density at a certain position decays to 5% of the maximum value, the position is considered as the boundary point of the compaction effect. The system solves the equation The corresponding spatial boundary. If the energy distribution function is symmetric, the system uses the distance from the boundary point to the impact center as the compaction influence radius and constructs a circular compaction area with this radius as the scale; if the energy distribution is asymmetric, that is, there are different diffusion rates in the x-axis and y-axis directions, the system calculates the compaction influence radius in both directions separately and constructs an elliptical compaction influence area centered on the actual impact point, forming the actual range of action of each impact in space.

[0098] After the compaction influence area is determined, the system enters the overlap area calculation stage. Within the preset boundary range of each target compaction point, the system loads the compaction influence areas corresponding to all actual compaction locations within that area and calculates the overlap area between each compacted area and the target boundary. To avoid misjudgment due to equal-weighted superposition caused by simple overlap, the system introduces an energy weighting mechanism, that is, assigning different weight coefficients to the compacted areas based on the equivalent kinetic energy of each compaction. This weight is calculated by the ratio of the equivalent kinetic energy value of that compaction to the sum of the kinetic energy of all compactions, reflecting the relative degree of contribution of that compaction to the compaction of the target area. The system performs a weighted summation of the intersection areas of all compacted areas within the target boundary to finally obtain the weighted overlap area of ​​the target compaction point.

[0099] S206. Calculate the compaction degree of each target actual compaction location in the actual compaction location sequence;

[0100] In step S206, based on the actual compaction location sequence identified in the previous steps and corresponding key data such as energy distribution characteristics, attitude change characteristics, and overlap area information, the system further quantitatively evaluates the compaction effect of each compaction point, i.e., calculates the compaction degree of each target's actual compaction location. The core purpose of step S206 is to establish a mathematical mapping relationship between the compaction behavior of the tamping hammer under different positions, energies, and attitudes and its compaction effect on the subgrade, thereby achieving a spatialized and indexed expression of compaction quality. By constructing a composite compaction degree calculation model that includes energy factors, contact pressure factors, attitude correction factors, and action distance attenuation factors, the system can accurately reflect the compaction effect of each target point under multiple overlapping compaction actions, providing key data support for compaction quality control and compaction uniformity evaluation. This may include the following steps: calculating the compaction degree using the following formula: , Let be the compaction degree at the actual impact location of the i-th target. Let be the overlap area of ​​the actual impact location of the i-th target. Let be the effective energy of the k-th impact at the actual impact location of the i-th target. As a preset energy reference value, Let K be the contact pressure of the k-th impact at the actual impact position of the i-th target. a preset compaction degree reference value, and n is a maximum number of ramming, i∈[1, n]. a rammer posture offset angle of the i-th target actual ramming position for the k-th ramming, a ramming influence radius of the i-th target actual ramming position for the k-th ramming, a preset ramming influence radius reference value, and n is a maximum number of ramming, i∈[1, n].

[0101] In specific implementation, the system calculates the compaction degree of each target actual ramming position by using a compaction degree calculation expression. The model introduces a multi-factor weighting mechanism to describe the comprehensive compaction effect of a target position under the action of multiple rammings. In the formula, represents the compaction degree of the i-th target actual ramming position, is the corresponding lap area of the position, which is used as a normalization coefficient to standardize the total compaction contribution to unit area compaction effect. The system considers that the factors affecting the compaction effect include the effective energy , the contact pressure , the ramming posture offset angle, and the action distance of the ramming point relative to the target point .

[0102] The system first extracts the effective energy of each ramming event, which is obtained from the energy distribution feature described above and reflects the kinetic energy value actually transmitted by the rammer to the base bed in the k-th ramming. Subsequently, the system obtains the contact pressure of the ramming from the contact feature sequence, which is derived from the amplitude and spectrum of the sound wave reflection feature and represents the instantaneous normal action intensity of the rammer and the base bed. The system normalizes the energy and pressure to and , respectively, where is a preset energy reference value, i.e., a reference energy set in the construction stage, is a preset pressure reference value, i.e., a reference contact pressure, for unifying the dimension and order of magnitude.

[0103] In order to reflect the influence of the rammer posture on the compaction effect, the system introduces as a correction factor, where is the posture offset angle of the ramming, which is obtained by the inertial measurement unit. This term reflects the reduction of compaction efficiency caused by non-vertical ramming. The greater the deviation from the vertical direction, the lower the compaction efficiency. The system also introduces the action distance between the ramming point and the target point, and establishes an attenuation model through to represent the weakening trend of the compaction energy with the spatial distance, where is a preset standard action radius, which is used to build a comparative reference for distance attenuation.

[0104] The system takes the product of the above energy factor, pressure factor, attitude factor and distance factor as the unit contribution value of a single ramming to the compaction degree of the target point, sums up all the ramming sequences falling into the overlapping area of the target point, and then divides by the overlapping area to obtain the total compaction degree of the target point. This compaction degree index can more finely reflect the actual physical changes and spatial distribution characteristics in the ramming process compared to the traditional rough evaluation based on the number of strikes or the total energy.

[0105] S207, according to the overlapping area, each target actual ramming position and the compaction degree corresponding to each target actual ramming position, a ramming trajectory feature map of the rammer is constructed.

[0106] After completing the identification of the actual ramming position of the rammer, the calculation of the overlapping area and the evaluation of the compaction degree, step S207 further integrates these spatial and physical parameters to construct a ramming trajectory feature map of the rammer in the entire operation process. The ramming trajectory feature map not only visually displays the time sequence movement trajectory and ramming distribution of the rammer, but also superimposes the coverage range and compaction effect information of each ramming, which is an important achievement carrier for realizing the visual management of ramming quality, the backtracking of construction process and the analysis of compaction uniformity. Therefore, the system combines time series, overlapping area and compaction degree in this step to complete the graphical drawing of the ramming path of the rammer and the visual expression of the compaction effect.

[0107] In the specific implementation process, the system first sorts all the actual ramming positions in the order of collection time, and connects them in turn to form a polyline structure, which constitutes a ramming path schematic diagram of the rammer in the target area. This path schematic diagram can reflect the spatial movement trend of the rammer in the operation process, such as from east to west, from periphery to center, etc., which helps to identify whether the construction organization method is reasonable. In order to further express the spatial coverage degree of each ramming to the target area in the diagram, the system constructs a coverage range circle with each target actual ramming position as the center, and the radius of the coverage range circle is determined by the corresponding overlapping area, following the physical logic that the larger the coverage area, the more sufficient the effect on the target point. Specifically, the system maps the overlapping area value to the radius value through normalization processing, for example, sets the maximum circle radius corresponding to the maximum overlapping area as 1 meter, and the rest is scaled in proportion, thereby forming a spatial coverage layer with uniform scale.

[0108] After the path and coverage range are constructed, the system performs contrast coding on each coverage range circle in the graph to express the compaction effect at the position. Specifically, the compaction degree value is mapped to a gray scale or transparency level, and the area with a higher compaction degree is displayed darker or less transparent, and vice versa, a lighter visual coding is used, so as to intuitively reflect the compaction effect distribution through visual contrast. The system can set multiple compaction degree level thresholds, such as 0.8 or less for light gray (insufficient compaction), 0.8-1.2 for medium gray (normal compaction), and 1.2 or more for dark gray or black (sufficient compaction), and is labeled in combination with a legend. The finally generated image is the rammer tamping track feature map, which integrates the three types of information of the operation track, coverage range and compaction effect, and is the core carrier for the transformation of construction data into engineering quality information.

[0109] Referring to Figure 3 A structure schematic diagram of a tamping track monitoring system provided for an embodiment of the present application, a tamping track monitoring system 300 specifically includes:

[0110] The acquisition module 301 is configured to acquire construction monitoring data, real-time state parameters and environmental parameters of the rammer, the construction monitoring data including underwater acoustic signals, the real-time state parameters including circumferential pressure data and verticality; the first analysis module 302 is configured to determine the sinking track of the rammer in water based on the underwater acoustic signals, the real-time state parameters and the environmental parameters; the first construction module 303 is configured to construct an underwater pressure gradient distribution map of the rammer based on the circumferential pressure data; the second analysis module 304 is configured to analyze the spatial attitude change characteristics of the rammer based on the underwater pressure gradient distribution map, the verticality and the environmental parameters; the determination module 305 is configured to determine the actual tamping position sequence of the target tamping point based on the spatial attitude change characteristics and the sinking track, and calculate the overlapping area of the rammer and the target tamping point; the calculation module 306 is configured to calculate the compaction degree of each target actual tamping position in the actual tamping position sequence; and the second construction module 307 is configured to construct a tamping track feature map of the rammer based on the overlapping area, each target actual tamping position and the compaction degree corresponding to each target actual tamping position.

[0111] Optionally, the first analysis module 302 is specifically configured to: based on the frequency distribution characteristics of the underwater acoustic signal and the flow velocity and the water body turbulence degree in the environmental parameters, construct a dynamic spectrum envelope line of the underwater acoustic signal, determine an energy attenuation gradient of the underwater acoustic signal based on the dynamic spectrum envelope line; determine a deviation degree of the dynamic spectrum envelope line from a preset standard underwater acoustic propagation characteristic, determine a water body turbulence intensity corresponding to the real-time position of the gravity center of the rammer based on the deviation degree; analyze a time sequence corresponding relationship between the water body turbulence intensity and the circumferential pressure data, identify a cavity effect interval of the rammer in the sinking process, and determine a continuous sinking section and a blocking section of the rammer according to a duration of the cavity effect interval; calculate a sinking speed of the rammer based on the energy attenuation gradient corresponding to the continuous sinking section, the water body turbulence intensity corresponding to the blocking section, the initial water entry speed of the rammer and the mass parameters of the rammer; and perform time sequence fusion on the sinking speed and the position coordinates and the verticality in the real-time state parameters to obtain a sinking trajectory.

[0112] Optionally, the first analysis module 302 is further specifically configured to: construct a speed calculation function of the rammer based on the energy attenuation gradient corresponding to the continuous sinking section; determine a correction coefficient of the energy attenuation gradient term in the speed calculation function based on the water body turbulence intensity corresponding to the blocking section, and correct the speed calculation function based on the correction coefficient to obtain a target speed calculation function; and calculate the sinking speed of the rammer based on the target speed calculation function, the initial water entry speed and the mass parameters.

[0113] Optionally, the determination module 305 is specifically configured to: determine a contact feature sequence of the rammer and the riprap bed based on the bed reflection wave data in the construction monitoring data; perform time domain matching on the spatial attitude change feature and the contact feature sequence to determine an attitude change moment of the rammer; determine a speed change sequence of the rammer based on the sinking trajectory, determine a bottom-touching moment of the rammer in combination with the speed change sequence and the attitude change moment, determine an actual ramming position based on a position coordinate corresponding to the bottom-touching moment; determine an actual ramming position sequence of the target ramming point based on a plurality of actual ramming positions in a preset range of the target ramming point and the bottom-touching moment; and calculate an overlapping area of the rammer and the target ramming point based on the contact feature sequence and the actual ramming position sequence.

[0114] Optionally, the determination module 305 is further specifically configured to: determine an energy distribution characteristic of the rammer based on the contact feature sequence; determine a compaction influence radius of each target actual ramming position in the actual ramming position sequence based on the energy distribution characteristic, and determine a compaction influence area of each target actual ramming position in the actual ramming position sequence according to the compaction influence radius; and perform weighted superposition on areas of the compaction influence areas of each target actual ramming position to obtain the overlapping area.

[0115] Optionally, the calculation module 306 is specifically configured to: calculate the compaction degree by the following formula: , a compaction degree of the i-th target actual ramming position, an overlap area of the i-th target actual ramming position, an effective energy of the k-th ramming of the i-th target actual ramming position, a preset energy reference value, a contact pressure of the k-th ramming of the i-th target actual ramming position, a preset pressure reference value, a rammer posture offset angle of the k-th ramming of the i-th target actual ramming position, a ramming influence radius of the k-th ramming of the i-th target actual ramming position, a preset ramming influence radius reference value, and n is a maximum number of rammings, and i∈[1, n].

[0116] Optionally, the second construction module 307 is specifically configured to: connect the target actual ramming positions in time sequence, and determine a coverage range circle of each target actual ramming position based on the overlap area, a radius of the coverage range circle being proportional to the overlap area, to obtain a ramming path schematic diagram; and determine a display contrast of the coverage range circle according to the compaction degree in the ramming path schematic diagram, to obtain a ramming track feature map.

[0117] It should be noted that the apparatus provided in the above embodiments is only used as an example for dividing the above functional modules in realizing its functions, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above described functions. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process is detailed in the method embodiments, which will not be repeated here.

[0118] The embodiment further discloses an electronic device, referring to Figure 4 The electronic device can include at least one processor 401, at least one communication bus 402, a user interface 403, a network interface 404, and at least one memory 405. The communication bus 402 is used to realize the connection and communication between the components. The user interface 403 can include a display screen (Display) and a camera (Camera), and the optional user interface 403 can further include a standard wired interface and a wireless interface. The network interface 404 can optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0119] The processor 401 can include one or more processing cores. The processor 401 connects various parts within the server through various interfaces and lines, performs various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 405, and calling data stored in the memory 405. Alternatively, the processor 401 can be implemented in at least one of a hardware form of a digital signal processing (DSP), a field-programmable gate array (FPGA), and a programmable logic array (PLA). The processor 401 can integrate a combination of one or more of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. Among them, the CPU mainly processes operating systems, user interfaces, and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; and the modem is used for processing wireless communication. It can be understood that the above-mentioned modem can also not be integrated into the processor 401, but can be realized by a separate chip.

[0120] The memory 405 can include a random access memory (RAM) and a read-only memory (ROM). Alternatively, the memory 405 includes a non-transitory computer-readable storage medium. The memory 405 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 can include a program storage area and a data storage area, wherein the program storage area can store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 405 can alternatively be at least one storage device located away from the aforementioned processor 401. As shown, the memory 405 as a computer storage medium can include an operating system, a network communication module, a user interface module, and an application program of a ramming track monitoring method. Figure 4 As shown, the memory 405 as a computer storage medium can include an operating system, a network communication module, a user interface module, and an application program of a ramming track monitoring method.

[0121] It should be noted that, for the aforementioned method embodiments, for the sake of simple description, they are all described as a series of action combinations, but those skilled in the art should know that the present application is not limited to the action sequence described, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0122] In the above embodiments, the description of each embodiment is focused on, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0123] The above are only exemplary embodiments of the present disclosure, and cannot limit the scope of the present disclosure. That is, any equivalent changes and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. Other embodiments of the present disclosure will be readily apparent to those skilled in the art upon considering the disclosure herein. The present application is intended to cover any variations, uses, or adaptive changes of the present disclosure that follow the general principles of the present disclosure and include common knowledge or conventional technical means in the art not described in the present disclosure. The scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method of monitoring a tamping trajectory, characterized by, Applied in a server, the method comprises: Obtaining construction monitoring data, real-time state parameters of the rammer and environmental parameters, wherein the construction monitoring data comprises underwater acoustic signals, and the real-time state parameters comprise circumferential pressure data and verticality; Based on the underwater acoustic signals, the real-time state parameters and the environmental parameters, determining the sinking trajectory of the rammer in water; Based on the circumferential pressure data, constructing the underwater pressure gradient distribution map of the rammer; Based on the underwater pressure gradient distribution map, the verticality and the environmental parameters, analyzing the spatial attitude change characteristics of the rammer; Based on the spatial attitude change characteristics and the sinking trajectory, determining the actual ramming position sequence of the target ramming point, and calculating the overlapping area of the rammer and the target ramming point; Calculating the compaction degree of each target actual ramming position in the actual ramming position sequence; According to the overlapping area, each target actual ramming position and the compaction degree corresponding to each target actual ramming position, constructing the ramming trajectory feature map of the rammer; The method based on the underwater acoustic signals, the real-time state parameters and the environmental parameters, and determining the sinking trajectory of the rammer in water, specifically comprises: Based on the frequency distribution characteristics of the underwater acoustic signals and the flow velocity and water turbulence degree in the environmental parameters, constructing the dynamic frequency spectrum envelope line of the underwater acoustic signals, and based on the dynamic frequency spectrum envelope line, determining the energy attenuation gradient of the underwater acoustic signals; Determining the deviation degree of the dynamic frequency spectrum envelope line from the preset standard underwater acoustic propagation characteristics, and based on the deviation degree, determining the water turbulence intensity corresponding to the real-time position of the center of gravity of the rammer; Analyzing the time sequence corresponding relationship between the water turbulence intensity and the circumferential pressure data, identifying the cavity effect interval of the rammer in the sinking process, and according to the duration of the cavity effect interval, determining the continuous sinking section and the resistance section of the rammer; Based on the energy attenuation gradient corresponding to the continuous sinking section, the water turbulence intensity corresponding to the resistance section, the initial water entry speed of the rammer and the mass parameters of the rammer, calculating the sinking speed of the rammer; Time sequence fusion of the sinking speed and the position coordinates in the real-time state parameters and the verticality is carried out to obtain the sinking trajectory; The method based on the energy attenuation gradient corresponding to the continuous sinking section, the water turbulence intensity corresponding to the resistance section, the initial water entry speed of the rammer and the mass parameters of the rammer to calculate the sinking speed of the rammer, specifically comprises: Based on the energy attenuation gradient corresponding to the continuous sinking section, constructing the speed calculation function of the rammer; Based on the water turbulence intensity corresponding to the resistance section, determining the correction coefficient of the energy attenuation gradient term in the speed calculation function, and based on the correction coefficient, modifying the speed calculation function to obtain the target speed calculation function; Based on the target speed calculation function, the initial water entry speed and the mass parameters, calculating the sinking speed of the rammer; The method for calculating the compaction degree of each target actual ramming position in the actual ramming position sequence, specifically comprises: The compaction degree is calculated by the following formula: , is the compaction degree of the i-th target actual ramming position, is the overlap area of the i-th target actual ramming position, is the effective energy of the k-th ramming of the i-th target actual ramming position, is a preset energy reference value, is the contact pressure of the k-th ramming of the i-th target actual ramming position, is a preset pressure reference value, is the rammer posture offset angle of the k-th ramming of the i-th target actual ramming position, is the ramming influence radius of the k-th ramming of the i-th target actual ramming position, is a preset ramming influence radius reference value, and n is the maximum number of rammings, i∈[1, n].

2. The method of claim 1, wherein, The actual ramming position sequence of the target ramming point is determined based on the spatial posture change feature and the subsidence trajectory, and an overlap area of the rammer and the target ramming point is calculated, specifically comprising: The contact feature sequence of the rammer and the riprap bed is determined based on the bed reflected wave data in the construction monitoring data; The posture change time of the rammer is determined by time domain matching the spatial posture change feature and the contact feature sequence; The velocity change sequence of the rammer is determined based on the subsidence trajectory, and the bottom touch time of the rammer is determined by combining the velocity change sequence and the posture change time, and the actual ramming position is determined based on the position coordinates corresponding to the bottom touch time; The actual ramming position sequence of the target ramming point is determined based on the actual ramming positions in the preset range of the target ramming point and the bottom touch time; The overlap area of the rammer and the target ramming point is calculated based on the contact feature sequence and the actual ramming position sequence.

3. The method of claim 2, wherein, The overlap area of the rammer and the target ramming point is calculated based on the contact feature sequence and the actual ramming position sequence, specifically comprising: The energy distribution feature of the rammer is determined based on the contact feature sequence; The compaction influence radius of each target actual ramming position in the actual ramming position sequence is determined based on the energy distribution feature, and the compaction influence area of each target actual ramming position in the actual ramming position sequence is determined according to the compaction influence radius; The areas of the compaction influence areas of each target actual ramming position are weighted and superimposed to obtain the overlap area.

4. The method of claim 1, wherein, The ramming trajectory feature map of the rammer is constructed according to the overlap area, each target actual ramming position and the corresponding compaction degree of each target actual ramming position, specifically comprising: The target actual ramming positions are connected in time sequence, and the coverage range circle of each target actual ramming position is determined based on the overlap area, the radius of the coverage range circle is proportional to the overlap area, and a ramming path schematic diagram is obtained; In the ramming path schematic diagram, the display contrast of the coverage range circle is determined according to the compaction degree, and the ramming trajectory feature map is obtained.

5. A track monitoring system for a rammer, the system comprising: It comprises: An acquisition module is configured to acquire construction monitoring data, real-time state parameters and environmental parameters of a rammer, wherein the construction monitoring data comprises underwater acoustic signals, and the real-time state parameters comprise circumferential pressure data and verticality; A first analysis module is configured to determine a subsidence trajectory of the rammer in water based on the underwater acoustic signals, the real-time state parameters and the environmental parameters; A first construction module is configured to construct an underwater pressure gradient distribution map of the rammer based on the circumferential pressure data; A second analysis module is configured to analyze a spatial posture change feature of the rammer based on the underwater pressure gradient distribution map, the verticality and the environmental parameters; A determination module is configured to determine an actual ramming position sequence of a target ramming point based on the spatial posture change feature and the subsidence trajectory, and to calculate an overlap area of the rammer and the target ramming point. a calculation module, configured to calculate a compaction degree of each target actual ramming position in the actual ramming position sequence; a second construction module, configured to construct a ramming track feature map of the rammer according to the overlap area, each target actual ramming position, and the compaction degree corresponding to each target actual ramming position; the first analysis module is specifically configured to construct a dynamic frequency spectrum envelope line of the underwater acoustic signal based on the frequency distribution characteristics of the underwater acoustic signal and the flow velocity and the water turbulence degree in the environmental parameters, determine an energy attenuation gradient of the underwater acoustic signal based on the dynamic frequency spectrum envelope line, determine a water turbulence intensity corresponding to the real-time position of the center of gravity of the rammer based on a deviation degree of the dynamic frequency spectrum envelope line from a preset standard underwater acoustic propagation characteristic, analyze a time sequence corresponding relationship between the water turbulence intensity and the circumferential pressure data, identify an air cavity effect interval of the rammer in the sinking process, and determine a continuous sinking section and a resistance section of the rammer according to a duration of the air cavity effect interval; determine a sinking speed of the rammer based on the energy attenuation gradient corresponding to the continuous sinking section, the water turbulence intensity corresponding to the resistance section, an initial water entry speed of the rammer, and a mass parameter of the rammer; time sequence fuse the sinking speed with the position coordinates in the real-time state parameter and the verticality to obtain the sinking track; the first analysis module is also specifically configured to construct a speed calculation function of the rammer based on the energy attenuation gradient corresponding to the continuous sinking section; determine a correction coefficient of an energy attenuation gradient term in the speed calculation function based on the water turbulence intensity corresponding to the resistance section, correct the speed calculation function based on the correction coefficient to obtain a target speed calculation function, and calculate the sinking speed of the rammer based on the target speed calculation function, the initial water entry speed, and the mass parameter; comprises: one or more processors and a memory; the memory is coupled with the one or more processors, and the memory is configured to store computer program codes, the computer program codes comprising computer instructions, and the one or more processors invoke the computer instructions to enable the electronic device to perform the method in any one of claims 1-4. The computing module is specifically configured to calculate the compaction degree according to the following formula: , is the compaction degree of the i th target actual ramming position, is the overlapping area of the i th target actual ramming position, is the effective energy of the k th ramming of the i th target actual ramming position, is a preset energy reference value, is the contact pressure of the k th ramming of the i th target actual ramming position, is a preset pressure reference value, is the rammer posture offset angle of the k th ramming of the i th target actual ramming position, is the ramming influence radius of the k th ramming of the i th target actual ramming position, is a preset ramming influence radius reference value, and n is the maximum number of rammings, i ∈ [1, n].

6. An electronic device, comprising: when the instructions run on the electronic device, enable the electronic device to perform the method in any one of claims 1-4. ​ ​ 7. A computer-readable storage medium comprising instructions, characterized in that, ​

Images