Foundation pit measuring system and method for pipeline engineering construction

Abstract

The invention discloses a foundation pit measurement system and method for pipeline engineering construction, and relates to the technical field of measurement, and the system comprises the following components: an automatic mobile measurement platform, a distributed control module and a three-dimensional model. According to the method, the distributed control module and the three-dimensional modeling module are introduced, so that different positions of the foundation pit can be accurately measured according to a preset complex time function and a measurement path based on fractal geometric design; the neural network model is represented through the superposition state of quantum bits, real-time processing and optimization of measurement data are achieved, in addition, due to the application of a three-dimensional modeling measurement algorithm, the measurement result can be directly used for three-dimensional modeling and subsequent construction guidance of a foundation pit, and the overall quality and safety of pipeline engineering construction are greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of measurement, and particularly to a foundation pit measurement system and method for pipeline engineering construction. Background Art

[0002] With the continuous development of pipeline engineering construction, foundation pit measurement, as a key link therein, is of great significance for ensuring project quality, safety and the smooth progress of subsequent construction.

[0003] Traditional distributed control systems often adopt a single measurement path and data processing method, which are difficult to adapt to complex foundation pit environments and changing construction conditions, resulting in errors and uncertainties in measurement results. On the other hand, the measurement results of traditional 3D modeling measurement algorithms cannot be directly used for 3D modeling of foundation pits and subsequent construction guidance.

[0004] In summary, traditional distributed control and 3D modeling measurement algorithms have certain limitations in the foundation pit measurement of pipeline engineering construction and cannot meet the current project requirements for measurement accuracy, efficiency and real-time performance. Therefore, it is particularly important to develop a foundation pit measurement system and method for pipeline engineering construction. Summary of the Invention

[0005] The purpose of the present invention is to make up for the deficiencies of the prior art, and provides a foundation pit measurement system and method for pipeline engineering construction. By introducing distributed control and 3D modeling, this system realizes precise measurement of different positions of the foundation pit, improves measurement efficiency and accuracy, and provides a strong guarantee for the overall quality and safety of pipeline engineering construction.

[0006] To solve the above technical problems, the present invention provides the following technical solution: A foundation pit measurement system for pipeline engineering construction, which includes an automated mobile measurement platform, a distributed control module and a 3D modeling module;

[0007] The automated mobile measurement platform: consists of a platform base that can automatically move along a preset track and a measurement instrument bearing structure installed thereon;

[0008] Among them, the movement of the platform base is realized by a magnetic levitation drive system. A superconducting magnet array is distributed at the bottom of the platform base and is made of a superconducting material mixture with a critical temperature. Each magnet unit in the superconducting magnet array is hexagonal, and adjacent magnet units are connected by a superconducting connection bridge. The superconducting material of the superconducting connection bridge is magnesium diboride;

[0009] The electromagnetic guide rail laid along the preset track interacts with the superconducting magnet array. The electromagnetic guide rail is a multi-layer composite structure. The bottom layer is a ferromagnetic material for enhancing the magnetic field, the middle layer is a polyimide film insulation layer, and the upper layer is a copper-nickel alloy conductive layer with conductivity. The electromagnetic coil windings on the electromagnetic guide rail use Litz wire, and the number of winding turns is calculated based on the preset driving force requirements and magnetic field strength. By precisely controlling the magnitude and direction of the current in each electromagnetic coil, an alternating magnetic field interacting with the superconducting magnet array is generated, so that the platform base moves along the preset track with high precision in three-dimensional space;

[0010] The measurement instrument bearing structure is a honeycomb upper, middle and lower layer composite structure. The honeycomb unit is a regular hexagon, and the material is a carbon fiber reinforced ceramic matrix composite material. The control module of the measurement instrument is installed in the upper layer, the main body of the measurement instrument is fixed in the middle layer, and an adaptive mounting fixture is provided in each honeycomb unit, and the components related to the magnetic levitation drive system are carried in the lower layer;

[0011] The distributed control module: realizes information transmission and control functions based on the principle of quantum entanglement communication, including a quantum communication module with multiple quantum bit generation units and entangled photon emission-reception units, and a control algorithm unit based on a quantum neural network;

[0012] The quantum bit generation unit uses ion trap technology. Each unit can stably generate and manipulate calcium ion quantum bits, and its trapping potential field is generated by the combination between the radio frequency and the direct current electric field strength;

[0013] The entangled photon emission-reception unit uses a barium borate BBO crystal to generate entangled photon pairs through the spontaneous parametric down-conversion SPDC process. The cutting angle of the BBO crystal is precisely determined according to the wavelength and polarization characteristics of the required entangled photons. In communication, information transmission is realized by encoding and decoding the polarization state and frequency quantum characteristics of the entangled photons;

[0014] The control algorithm in the control algorithm unit is based on a quantum neural network. Its neuron model is represented by the superposition state of quantum bits. This control algorithm unit is communicatively connected to the measurement instrument and can measure different positions of the foundation pit according to the preset complex time function and the measurement path designed based on fractal geometry. The complex time function is used to determine the moving time interval of the platform, and its expression is: Among them, t is the construction time variable, and a, b, c, d, e, f are parameters. The value of a is determined according to the total construction period of the foundation pit and the time span of the key construction stage, and its range is between 10 and 100. The value of b is related to the change rate of the groundwater level during the foundation pit construction, and is obtained through long-term monitoring and analysis of geological and hydrological data, with a range between 0.01 and 0.1. The value of c is a constant, set according to the starting time of the project, with a range between 0 and 10. The value of d is determined according to the sampling frequency and data processing speed of the measuring instrument, with a range between 5 and 20. The value of e is related to the interference intensity of the electromagnetic environment at the construction site, and is obtained through on-site electromagnetic spectrum measurement and analysis, with a range between 1.1 and 1.5. The value of f is determined according to the probability of unexpected events that may occur during the construction process and the degree of influence on the measurement, with a range between 0.001 and 0.01. The measurement path designed based on fractal geometry is generated by the Iterated Function System (IFS). The parameters of its iterated function are determined according to the shape and size of the foundation pit and the fractal dimension of the surrounding geological structure. The fractal dimension is obtained by analyzing the ground penetrating radar scanning data through the box-counting method, with a range between 1.2 and 2.5. The generated measurement path can cover the key areas and areas with potential changes of the foundation pit;

[0015] The three-dimensional modeling module: processes the measurement data of the key feature points of the foundation pit to construct a three-dimensional model of the foundation pit. The algorithm formula is: Among them, M is the three-dimensional model of the foundation pit, and P i is the spatial coordinate vector of the i-th key feature point, n is the number of key feature points, k i is the exponent related to the spatial dimension of the i-th key feature point, d i is the vertical distance from the i-th key feature point to the preset reference plane of the foundation pit, λ is the distance attenuation coefficient, represents a custom vector fusion operation, C i is the topological connection coefficient related to the i-th key feature point, t i is the timestamp for measuring the i-th key feature point, ω is the time frequency parameter, r i is the local curvature radius centered on the i-th key feature point, S j is the j-th special geometric feature parameter, m is the number of special geometric feature parameters, γ j is the weight adjustment factor of the j-th special geometric feature parameter, represents a custom parameter combination operation, T j is the j-th time-space interaction parameter, β j is the enhancement coefficient of the j-th time-space interaction parameter.

[0016] Further, the measuring instrument bearing structure is a honeycomb upper, middle and lower layer composite structure, where:

[0017] Upper layer: Used to install the control module of the measuring instrument. Its heat dissipation channels are manufactured using micro-nano manufacturing technology. The manufacturing process is femtosecond laser processing technology, and the material is carbon fiber reinforced ceramic matrix composite. This material is formed by hot pressing sintering process, that is, mixing carbon fiber and ceramic powder and hot pressing sintering in a mold at a specific temperature and pressure;

[0018] Middle layer: Used to fix the main body of the measuring instrument, equipped with a shape memory alloy fixture. This fixture is formed by precision casting process and then the phase transition temperature and shape memory performance are adjusted by heat treatment. The material is carbon fiber reinforced ceramic matrix composite, and the forming process is the same as that of the upper layer;

[0019] Lower layer: Used to carry the components related to the magnetic levitation drive system. Its shock absorption structure is a stacked structure of graphene and elastic polymer. The stacking method is layer-by-layer self-assembly technology. The thickness of each layer and the stacking order are precisely controlled by controlling the solution conditions, pH value and assembly time. The assembly environment is constant temperature and humidity. The material is carbon fiber reinforced ceramic matrix composite, and the forming process is the same as that of the upper layer. The honeycomb unit is in a regular hexagon shape overall.

[0020] Furthermore, the distributed control module includes a quantum communication module and a control algorithm unit, which contains multiple quantum bit generation units and entangled photon emission-reception units. The quantum bit generation unit uses ion trap technology. Its electrodes are manufactured by micro-nano processing technology. First, an electrode pattern with a micron-level line width is lithographed and etched on a silicon wafer, and then a layer of gold film is physically vapor deposited on the electrode surface. The entangled photon emission-reception unit uses a barium borate BBO crystal to generate entangled photon pairs. The BBO crystal needs to be subjected to optical uniformity detection before cutting to ensure a highly uniform refractive index. In quantum communication, a photonic crystal fiber is used as the transmission medium and is connected to the quantum communication module through high-precision fiber alignment technology;

[0021] Based on a quantum neural network, its neuron model is represented by the superposition state of quantum bits. The control algorithm unit is communicatively connected to the measuring instrument and can measure different positions of the foundation pit according to a preset complex time function and a measurement path designed based on fractal geometry. The training algorithm of the quantum neural network uses a quantum simulated annealing algorithm, and the annealing time is determined according to the number of quantum bits and complexity.

[0022] Furthermore, the method for determining the parameters in the complex time function is further refined as follows: For parameter a, when determining the total construction period of the foundation pit and the time span of the key construction stage, the construction process is divided into multiple sub-stages, and each sub-stage is assigned a weight according to the construction technology and difficulty. The weight of the total construction period is 0.6, and the weight of the time span of the key construction stage is determined according to its influence degree on the measurement. The stage with a greater influence has a higher weight, ranging from 0.4 to 0.8. For the monitoring of the groundwater level change rate involved in parameter b, multiple water level sensors at different depths are used, and the spacing between the sensors is determined according to the geological stratification. The spacing is smaller in the area where the soil layer changes greatly, ranging from 0.5 to 2 meters. For parameter e, in addition to the on-site electromagnetic spectrum measurement, the measurement of the electromagnetic environment interference intensity is analyzed in combination with an electromagnetic simulation model. The electromagnetic simulation model is established based on the distribution of electrical equipment and topographic and geomorphic factors at the construction site. The electromagnetic environment distribution is obtained by solving the Maxwell equations through the finite element method, and then compared and calibrated with the measured data. The emergencies on which parameter f is based include, but are not limited to, bad weather and the discovery of underground obstacles. For different types of emergencies, a probability model is established according to their historical occurrence frequencies and influence degrees on the measurement, and the value of f is determined accordingly.

[0023] Furthermore, the special geometric feature parameter S in the three-dimensional modeling measurement algorithm j The calculation method is as follows: For the sharpness of the inner corner points of the foundation pit, based on the local extreme value principle of the high-order derivative, an adaptive threshold is introduced in the corner point detection algorithm. The threshold is adaptively adjusted according to the density and curvature change of the point cloud near the corner point. The threshold increases in the area with low point cloud density or large curvature change to improve the accuracy of corner point detection. In the calculation of the fold degree of the boundary surface, the Hodge decomposition process adopts a multi-resolution analysis method. The boundary surface is decomposed into sub-spaces with different resolutions according to its scale characteristics. The Hodge decomposition of the normal vector field is calculated separately in each sub-space, and then fused through wavelet transform to improve the sensitivity of the fold degree calculation to folds of different scales. In the calculation of the Gaussian curvature change rate of the space surface, when taking the derivatives of the first fundamental form and the second fundamental form, a numerical differential method with an adaptive step size is used. The step size is adjusted according to the local curvature of the surface and the point cloud density. The step size is smaller in the area with large curvature or high point cloud density to improve the calculation accuracy. When determining the relationship between the special geometric feature parameters and the key feature points through the shortest path algorithm and topological homotopy analysis in graph theory, the shortest path algorithm adopts an improved A* algorithm, and the weight of the special geometric feature parameters is introduced into the heuristic function to more accurately reflect their roles in three-dimensional modeling. The topological homotopy analysis combines Morse theory to determine the topological invariant by analyzing the Morse function of the foundation pit surface, and then more precisely analyzes the topological homotopy relationship.

[0024] Furthermore, the time-space interaction parameter T in the fast three-dimensional modeling measurement algorithmj The acquisition process is further optimized as follows: When setting the spatio-temporal reference points, in the optimization algorithm based on the Voronoi diagram, considering the inhomogeneity of the environment around the foundation pit, different weights are assigned to different geological conditions and underground structure areas. The weights are determined according to the soil type and groundwater level factors in the geological exploration data. The atomic clock in the spatio-temporal sensor uses a cesium atomic clock, and the three-dimensional space positioning sensor uses a combination of a laser tracker and a total station. The laser tracker is used for high-precision positioning at close range, and the total station is used for long-distance positioning. The two are seamlessly docked through a data fusion algorithm. In the tensor product spline interpolation method for spatial deformation data processing, the coefficients of the tensor product spline are adaptively adjusted according to the distribution density of the spatio-temporal reference points and the spatio-temporal correlation of the data. The adjustment amplitude of the coefficients is increased in areas where the data changes violently to improve the accuracy of interpolation. The soil mechanical equilibrium in the physical constraint conditions is analyzed by combining the discrete element method and the finite difference method, and the stability of the underground structure is evaluated by the finite element strength reduction method. The coupling of the two methods is achieved through a multi-field coupling algorithm to more accurately consider the influence of soil-structure interaction on time-space interaction parameters.

[0025] Furthermore, the topological connection coefficient C in the fast three-dimensional modeling measurement algorithm i The calculation method is improved as follows: When constructing the topological map of the foundation pit and the surrounding underground pipeline network, for the representation of nodes, in addition to the key feature points and pipeline connection points, it also includes geological structure change points. The attributes of these additional nodes are determined according to the geological exploration data. When determining the weights of the edges, in addition to considering factors such as pipeline diameter and soil conductivity, the influence of groundwater flow velocity and direction is also added. The groundwater flow velocity is determined by combining the tracer method and the flowmeter measurement, and the direction is determined by geomagnetic measurement and water flow simulation analysis. The discretization of the Laplace-Beltrami operator uses the adaptive finite element method, and the grid division density is automatically adjusted according to the local complexity of the topological map. The grid density is increased in areas where nodes and edges are densely distributed or the attributes change greatly to improve the accuracy of discretization. When calculating the eigenvalues and eigenvectors, the Lanczos algorithm is used to iteratively solve the eigenvalue problem of a large sparse matrix. The number of iterations is determined according to the required calculation accuracy and the scale of the topological map to more efficiently obtain the intrinsic properties of the topological structure and thus more accurately calculate the topological connection coefficient C. i 。

[0026] On the other hand, a foundation pit measurement method for pipeline engineering construction is characterized in that the specific steps of the method are as follows:

[0027] S101, wherein the movement of the platform base is realized by a unique magnetic levitation drive system. The superconducting magnet array is distributed at the bottom of the platform base and is made of a mixture of superconducting materials with a critical temperature. The mass ratio of yttrium barium copper oxide and bismuth strontium calcium copper oxide is 3:2. Each magnet unit in the superconducting magnet array is hexagonal, and adjacent magnet units are connected by superconducting connection bridges. The superconducting material of the superconducting connection bridges is magnesium diboride;

[0028] S102, The electromagnetic guide rails laid along the preset track interact with the superconducting magnet array. The electromagnetic guide rails are of a multi-layer composite structure. The bottom layer is a ferromagnetic material for enhancing the magnetic field, the middle layer is a polyimide film insulation layer, and the upper layer is a copper-nickel alloy conductive layer with electrical conductivity. The electromagnetic coil windings on the electromagnetic guide rails adopt Litz wire, and the number of winding turns is calculated based on the preset driving force requirements and magnetic field strength. By precisely controlling the magnitude and direction of the current in each electromagnetic coil, an alternating magnetic field interacting with the superconducting magnet array is generated, so that the platform base moves along the preset track with high precision in three-dimensional space;

[0029] S103, The measurement instrument bearing structure is a honeycomb upper, middle and lower layer composite structure. The honeycomb units are regular hexagons, and the material is a carbon fiber reinforced ceramic matrix composite material. The control module of the measurement instrument is installed in the upper layer, the main body of the measurement instrument is fixed in the middle layer, and an adaptive mounting fixture is provided in each honeycomb unit. The lower layer bears the components related to the magnetic levitation drive system;

[0030] S200, The distributed control: realizes information transmission based on the principle of quantum entanglement communication, including a quantum communication module with multiple qubit generation units and entangled photon emission-reception units. The qubit generation units adopt ion trap technology, and each unit can stably generate and manipulate calcium ion qubits. Its trapping potential field is generated by the combination between the radio frequency and the direct current electric field intensity. The entangled photon emission-reception unit uses a barium borate BBO crystal to generate entangled photon pairs through the spontaneous parametric down-conversion SPDC process. The cutting angle of the BBO crystal is precisely determined based on the wavelength and polarization characteristics of the required entangled photons. In communication, information transmission is realized by encoding and decoding the polarization state and frequency quantum characteristics of the entangled photons. The control algorithm in the control system is based on a quantum neural network, and its neuron model is represented by the superposition state of qubits. This control system is communicatively connected to the measurement instrument and can measure different positions of the foundation pit according to a preset complex time function and a measurement path designed based on fractal geometry. The complex time function is used to determine the movement time interval of the platform, and its expression is: Among them, t is the construction time variable, and a, b, c, d, e, f are parameters. The value of a is determined according to the total construction period of the foundation pit and the time span of the key construction stage, ranging from 10 to 100. The value of b is related to the change rate of the groundwater level during the construction of the foundation pit, and is obtained through long-term monitoring and analysis of geological and hydrological data, ranging from 0.01 to 0.1. The value of c is a constant, set according to the starting time of the project, ranging from 0 to 10. The value of d is determined according to the sampling frequency and data processing speed of the measuring instrument, ranging from 5 to 20. The value of e is related to the interference intensity of the electromagnetic environment at the construction site, and is obtained through on-site electromagnetic spectrum measurement and analysis, ranging from 1.1 to 1.5. The value of f is determined according to the probability of unexpected events that may occur during the construction process and the degree of influence on the measurement, ranging from 0.001 to 0.01. The measurement path designed based on fractal geometry is generated by the Iterated Function System (IFS). The parameters of its iterative function are determined according to the shape and size of the foundation pit and the fractal dimension of the surrounding geological structure. The fractal dimension is obtained by analyzing the ground penetrating radar scanning data through the box-counting method, ranging from 1.2 to 2.5. The generated measurement path can cover the key areas and areas with potential changes of the foundation pit;

[0031] S300, the three-dimensional modeling measurement algorithm: By processing the measurement data of the key feature points of the foundation pit to construct a three-dimensional model of the foundation pit, the algorithm formula is: Among them, M is the three-dimensional model of the foundation pit, P i is the spatial coordinate vector of the i-th key feature point, n is the number of key feature points, k i is the exponent related to the spatial dimension of the i-th key feature point, d i is the vertical distance from the i-th key feature point to the preset reference plane of the foundation pit, λ is the distance attenuation coefficient, represents a custom vector fusion operation, C i is the topological connection coefficient related to the i-th key feature point, t i is the timestamp for measuring the i-th key feature point, ω is the time frequency parameter, r i is the local curvature radius centered on the i-th key feature point, S j is the j-th special geometric feature parameter, m is the number of special geometric feature parameters, γ j is the weight adjustment factor of the j-th special geometric feature parameter, represents a custom parameter combination operation, T j is the j-th time-space interaction parameter, β j is the enhancement coefficient of the j-th time-space interaction parameter.

[0032] Compared with the prior art, a foundation pit measurement system and method for pipeline engineering construction have the following beneficial effects:

[0033] First, by introducing distributed control and three-dimensional modeling measurement algorithms, the present invention can accurately measure different positions of the foundation pit according to a preset complex time function and a measurement path designed based on fractal geometry. This method not only considers various factors during the foundation pit construction process but also represents the neuron model through the superposition state of quantum bits, realizing real-time processing and optimization of measurement data. In addition, the application of the three-dimensional modeling measurement algorithm enables the measurement results to be directly used for the three-dimensional modeling of the foundation pit and subsequent construction guidance, greatly improving the overall quality and safety of pipeline engineering construction.

[0034] Second, by adopting a unique magnetic levitation drive system, the present invention realizes the automatic movement of the measurement platform, which not only improves the measurement efficiency but also reduces manual intervention, thereby reducing human errors. At the same time, the interaction between the superconducting magnet array and the electromagnetic guide rail further enhances the stability and measurement accuracy of the system, providing more reliable technical support for the foundation pit measurement of pipeline engineering construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0036] Figure 1 An operation flowchart of a foundation pit measurement system for pipeline engineering construction;

[0037] Figure 2 An operation flowchart of a foundation pit measurement method for pipeline engineering construction. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0039] Embodiment 1

[0040] This embodiment describes the construction of a highway tunnel in a certain area. The tunnel passes through a region with complex geological structures, and the geological conditions are variable, including unfavorable factors such as faults and soft rock strata. Accurate measurement of the foundation pit is crucial to ensure the stability and safety of the tunnel. In addition, the climate in this region is variable, with large rainfall and significant fluctuations in the groundwater level, further increasing the difficulty of foundation pit measurement.

[0041] Around the tunnel foundation pit, according to the geological radar scanning data and the tunnel design drawings, the track positions are accurately preset, and an automated mobile measurement platform is deployed to ensure that the platform base can move smoothly and with high precision along the preset tracks. The bottom of the platform base is equipped with a superconducting magnet array, which interacts with the electromagnetic guide rails laid along the preset tracks to achieve high-precision movement. The superconducting magnet array is made of a mixture of yttrium barium copper oxide (YBCO) and bismuth strontium calcium copper oxide (BSCCO) with a mass ratio of 3:2 and is formed by powder metallurgy to ensure stable superconducting performance. The electromagnetic guide rails adopt a multi-layer composite structure, including a ferromagnetic material bottom layer, a polyimide film insulation layer, and a copper-nickel alloy conductive layer. By precisely controlling the magnitude and direction of the current in the electromagnetic coils, an alternating magnetic field that interacts with the superconducting magnet array is generated. The load-bearing structure adopts a honeycomb upper, middle, and lower layer composite structure made of carbon fiber-reinforced ceramic matrix composite material, which has the characteristics of high strength and lightweight. The control module of the measuring instrument is installed on the upper layer, the main body of the measuring instrument is fixed on the middle layer, and an adaptive mounting fixture is provided in each honeycomb unit. The lower layer bears the components related to the magnetic levitation drive system. The heat dissipation channels are manufactured using femtosecond laser processing technology to ensure the stable operation of the measuring instrument in high-temperature environments.

[0042] Based on the principle of quantum entanglement communication, rapid and accurate communication between the measurement platform and the central control system is achieved. The quantum communication module includes multiple quantum bit generation units and entanglement photon emission-reception units. Ion trap technology is used to generate and manipulate calcium ion quantum bits, and entangled photon pairs are generated through the spontaneous parametric down-conversion process of barium borate BBO crystals. The control system adopts a quantum neural network algorithm to dynamically measure the foundation pit according to the preset complex time function and measurement path. The complex time function comprehensively considers factors such as the total construction period of the tunnel construction, the time span of key construction stages, and the change rate of the groundwater level. Among them, t is the construction time variable, and a, b, c, d, e, f are parameters obtained through long-term monitoring and analysis of geological and hydrological data. The measurement path is generated by an iterated function system (IFS) and is determined according to the shape, size of the foundation pit, and the fractal dimension of the surrounding geological structure to ensure coverage of all key areas of the foundation pit.

[0043] The measurement data of the key feature points of the foundation pit are processed, including factors such as spatial coordinates, vertical distances, and topological connection coefficients. A three-dimensional modeling measurement algorithm is used to comprehensively consider factors related to the spatial coordinate vectors, quantities, and spatial dimension-related indices of the key feature points to construct a three-dimensional model of the foundation pit. Among them, M is the three-dimensional model of the foundation pit, and P i is the spatial coordinate vector of the i-th key feature point, n is the number of key feature points, and k i is the exponent related to the spatial dimension of the i-th key feature point, and d i is the perpendicular distance from the i-th key feature point to the preset reference plane of the foundation pit, λ is the distance attenuation coefficient, represents a custom vector fusion operation, and C i is the topological connection coefficient related to the i-th key feature point, and t i is the timestamp for measuring the i-th key feature point, ω is the time frequency parameter, and r i is the local curvature radius centered on the i-th key feature point, and S j is the j-th special geometric feature parameter, m is the number of special geometric feature parameters, and γ j is the weight adjustment factor of the j-th special geometric feature parameter, represents a custom parameter combination operation, and T j is the j-th time-space interaction parameter, and β j is the enhancement coefficient of the j-th time-space interaction parameter. For special geometric feature parameters such as the sharpness of the inner corner points of the foundation pit, the fold degree of the boundary surface, and the Gaussian curvature change rate of the space surface, an adaptive threshold corner detection algorithm, multi-resolution Hodge decomposition, and an adaptive step numerical differentiation method are used for calculation. The relationship between the special geometric feature parameters and the key feature points is determined by the shortest path algorithm and topological homotopy analysis in graph theory to more accurately reflect their roles in 3D modeling;

[0044] When setting the space-time reference point, in the optimization algorithm based on the Voronoi diagram, considering the non-uniformity of the environment around the foundation pit, different weights are assigned to different geological conditions and underground structure areas. A combination of a cesium atomic clock and a laser tracker + total station is used for 3D space positioning, and seamless docking is achieved through a data fusion algorithm. When calculating the topological connection coefficient, a topological map of the foundation pit and the surrounding underground pipeline network is constructed, considering the influence of additional nodes such as geological structure change points. The Laplace-Beltrami operator is discretized using the adaptive finite element method, and the eigenvalue problem of a large sparse matrix is iteratively solved by the Lanczos algorithm.

[0045] Example Two

[0046] This embodiment describes a large-scale water conservancy project aiming to construct a magnificent dam and a water diversion tunnel system to ensure the regional water resource supply and flood control safety. To ensure the structural stability and long-term safe operation of the dam and the tunnel, high-precision and real-time monitoring of the foundation pit is required. The foundation pit measurement system is deployed in the construction area, covering the dam foundation excavation area and the tunnel inlet and outlet sections, aiming to capture the tiny signals of the foundation pit deformation and geological structure changes.

[0047] On the preset tracks in the construction areas of the dam and the tunnel, electromagnetic guide rails are precisely installed to ensure that the guide rails are straight, stable, and can adapt to complex terrain changes. Wireless synchronization technology is adopted between the guide rails to ensure the continuity and accuracy of the movement of the measurement platform. An automated mobile measurement platform is deployed, using magnetic levitation technology to reduce ground friction and improve the moving speed and accuracy. Especially under adverse geological conditions such as muddy and slippery, the platform is designed with an automatic balance system to ensure stable operation at various tilt angles. The measurement instrument bearing structure adopts an intelligent adaptive installation fixture, which can automatically adjust the angle and position according to the measurement requirements to ensure the best measurement state of measurement devices such as high-precision laser rangefinders and total stations under different working conditions.

[0048] Based on the principle of quantum entanglement communication, a quantum communication module is configured to achieve ultra-high-speed and ultra-safe transmission of measurement data. Through quantum key distribution technology, information encryption during data transmission is ensured to prevent data leakage. The control system adopts a quantum neural network algorithm, combined with a preset complex time function and a measurement path designed based on fractal geometry, to achieve intelligent and high-precision measurement of the foundation pit. The system can automatically adjust the measurement strategy according to real-time data and optimize the measurement efficiency.

[0049] Using high-precision measurement instruments, three-dimensional coordinates, vertical distances, and local curvature radius data of key feature points of the foundation pit are collected. A cloud computing platform is used to preprocess the massive data, remove noise, and improve data quality. A three-dimensional modeling measurement algorithm is applied to construct a three-dimensional digital model of the foundation pit based on the collected data. where M is the three-dimensional model of the foundation pit, P i is the spatial coordinate vector of the i-th key feature point, n is the number of key feature points, k i is the exponent related to the spatial dimension of the i-th key feature point, d i is the vertical distance from the i-th key feature point to the preset reference plane of the foundation pit, λ is the distance attenuation coefficient, represents a custom vector fusion operation, C i is the topological connection coefficient related to the i-th key feature point, t i is the timestamp for measuring the i-th key feature point, ω is the time frequency parameter, r iis the local curvature radius centered on the i-th key feature point, S j is the j-th special geometric feature parameter, m is the number of special geometric feature parameters, γ j is the weight adjustment factor of the j-th special geometric feature parameter, represents a custom parameter combination operation, T j is the j-th time-space interaction parameter, β j is the enhancement coefficient of the j-th time-space interaction parameter. The model has high precision and high fidelity, and can truly reflect the geometric shape and geological structure of the foundation pit. Through the acquisition process of the time-space interaction parameters and the calculation method of the topological connection coefficient in the algorithm, the interaction mechanism between the foundation pit and the surrounding geological structure is deeply analyzed. Combining with the geomechanical model, the stability of the foundation pit is evaluated and the potential deformation trend is predicted.

[0051] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any reference signs in the claims should not be regarded as limiting the claims involved.

Claims

1. A foundation pit measurement system for pipeline engineering construction, characterized in that: The system includes an automated mobile measurement platform, a distributed control module and a three-dimensional modeling module; The automated mobile measuring platform is composed of a platform base that can automatically move along a preset track and a measuring instrument bearing structure installed thereon; The movement of the platform base is achieved by a magnetic suspension drive system. The superconducting magnet array is distributed at the bottom of the platform base and is made of a mixture of critical temperature superconducting materials. Each magnet unit in the superconducting magnet array is hexagonal, and adjacent magnet units are connected by superconducting bridges. The superconducting material of the superconducting bridge is magnesium boron. The electromagnetic rails laid along the preset track interact with the superconducting magnet array. The electromagnetic rails are multi-layer composite structures. The bottom layer is a ferromagnetic material for enhancing the magnetic field, the middle layer is a polyimide film insulation layer, and the upper layer is a copper-nickel alloy conductive layer with high conductivity. The electromagnetic coil windings on the electromagnetic rails use Litz wires, and the number of winding turns is calculated based on the preset driving force requirements and magnetic field strength. By precisely controlling the current size and direction in each electromagnetic coil, an alternating magnetic field that interacts with the superconducting magnet array is generated, so that the platform base can move along the preset track in three-dimensional space with high precision. The measuring instrument bearing structure is a honeycomb composite structure with upper, middle and lower layers. The honeycomb unit is a regular hexagon and is made of carbon fiber reinforced ceramic matrix composite material. The upper layer is used to install the control module of the measuring instrument, and the middle layer is used to fix the measuring instrument body. Each honeycomb unit is equipped with an adaptive mounting fixture, and the lower layer carries the relevant components of the magnetic suspension drive system. The distributed control module: realizes information transmission and control functions based on the principle of quantum entanglement communication, and includes a quantum communication module of multiple quantum bit generation units and entangled photon emission-receiving units, and a control algorithm unit based on quantum neural network; The quantum bit generation unit uses ion trap technology. Each unit can stably generate and manipulate calcium ion quantum bits. Its trapped potential field is generated by a combination of radio frequency and DC electric field strengths. The entangled photon transmitting and receiving unit uses barium borate BBO crystals to generate entangled photon pairs through the spontaneous parametric down-conversion SPDC process. The cutting angle of the BBO crystal is precisely determined according to the wavelength and polarization characteristics of the required entangled photons. In communication, information transmission is achieved by encoding and decoding the polarization state and frequency quantum characteristics of the entangled photons. The control algorithm in the control algorithm unit is based on a quantum neural network, and its neuron model is represented by the superposition state of quantum bits. The control algorithm unit is connected to the measuring instrument in communication, and can measure different positions of the foundation pit according to the preset complex time function and the measurement path designed based on fractal geometry. The complex time function is used to determine the moving time interval of the platform, and its expression is: Among them, t is the construction time variable, a, b, c, d, e, and f are parameters. The value of a is determined according to the total construction period of the foundation pit and the time span of the key construction stage, ranging from 10 to 100. The value of b is related to the groundwater level change rate during the foundation pit construction process, which is obtained through long-term monitoring and analysis of geological and hydrological data, ranging from 0.01 to 0.

1. The value of c is a constant, which is set according to the start time of the project, ranging from 0 to 10. The value of d is determined according to the sampling frequency and data processing speed of the measuring instrument, ranging from 5 to 20. The value of e is related to the electromagnetic environment interference intensity of the construction site, which is obtained through The on-site electromagnetic spectrum measurement and analysis showed that the range was between 1.1 and 1.

5. The value of f was determined according to the probability of emergencies that may occur during the construction process and the degree of influence on the measurement, ranging from 0.001 to 0.

01. The measurement path designed based on fractal geometry was generated by an iterative function system (IFS). The parameters of the iterative function were determined according to the shape and size of the foundation pit and the fractal dimension of the surrounding geological structure. The fractal dimension was obtained by analyzing the geological radar scanning data using the box counting method, ranging from 1.2 to 2.

5. The generated measurement path can cover the key areas of the foundation pit and areas with potential changes. The three-dimensional modeling module is used to construct a three-dimensional model of the foundation pit by processing the measurement data of the key feature points of the foundation pit. The algorithm formula is: Among them, M is the three-dimensional model of the foundation pit, P i is the spatial coordinate vector of the i-th key feature point, n is the number of key feature points, k i is the index related to the spatial dimension of the i-th key feature point, d i is the vertical distance from the i-th key feature point to the preset foundation pit reference plane, λ is the distance attenuation coefficient, Represents a custom vector fusion operation, C i is the topological connection coefficient associated with the i-th key feature point, t i is the timestamp of measuring the i-th key feature point, ω is the time frequency parameter, r i is the local curvature radius centered at the i-th key feature point, S j is the jth special geometric feature parameter, m is the number of special geometric feature parameters, γ j is the weight adjustment factor of the jth special geometric feature parameter, Indicates a custom parameter combination operation, T j is the jth time-space interaction parameter, β j is the enhancement coefficient of the jth time-space interaction parameter.

2. A foundation pit measurement system for pipeline engineering construction according to claim 1, characterized in that: The measuring instrument bearing structure is a honeycomb composite structure with upper, middle and lower layers, wherein: Upper layer: Control module for installing measuring instruments. Its heat dissipation channel is manufactured at the micro-nano level using femtosecond laser processing technology. The material is carbon fiber reinforced ceramic matrix composite material, which is formed by hot pressing and sintering process, that is, mixing carbon fiber and ceramic powder, and hot pressing and sintering in a mold at a specific temperature and pressure; Middle layer: used to fix the measuring instrument body, equipped with shape memory alloy fixture, which is formed by precision casting process and then heat treated to adjust the phase change temperature and shape memory performance. The material is carbon fiber reinforced ceramic matrix composite material, and the molding process is the same as the upper layer; Lower layer: used to carry the relevant components of the magnetic suspension drive system. Its shock-absorbing structure adopts a stacking structure of graphene and elastic polymer. The stacking method is layer-by-layer self-assembly technology. The thickness of each layer and the stacking order are precisely controlled by controlling the solution conditions, pH value and assembly time. The assembly environment is constant temperature and humidity. The material is carbon fiber reinforced ceramic-based composite material. The molding process is the same as the upper layer. The honeycomb unit is a regular hexagon as a whole.

3. A foundation pit measurement system for pipeline engineering construction according to claim 1, characterized in that: The distributed control module includes a quantum communication module and a control algorithm unit, including multiple quantum bit generation units and entangled photon emission-receiving units. The quantum bit generation unit adopts ion trap technology, and its electrodes are manufactured by micro-nano processing technology. First, an electrode pattern with a micron-level line width is photolithographically and etched on a silicon wafer, and then a layer of gold film is physically vapor deposited on the electrode surface. The entangled photon emission-receiving unit uses barium borate BBO crystals to generate entangled photon pairs. The BBO crystals need to be optically uniformly detected before cutting to ensure that the refractive index is highly uniform. Photonic crystal optical fiber is used as a transmission medium in quantum communication, and is connected to the quantum communication module through high-precision optical fiber alignment technology; Based on quantum neural networks, its neuron model is represented by the superposition state of quantum bits. The control algorithm unit is communicated with the measuring instrument. It can measure different positions of the foundation pit according to the preset complex time function and the measurement path designed based on fractal geometry. The training algorithm of the quantum neural network adopts the quantum simulated annealing algorithm, and the annealing time is determined according to the number and complexity of quantum bits.

4. A foundation pit measurement system for pipeline engineering construction according to claim 1, characterized in that: The parameter determination method in the complex time function is further refined as follows: for parameter a, when determining the total construction period of the foundation pit and the time span of the key construction stage, the construction process is divided into multiple sub-stages, and each sub-stage is weighted according to the construction process and difficulty. The weight of the total construction period is 0.6, and the weight of the time span of the key construction stage is determined according to its influence on the measurement. The stage with a large influence has a high weight, ranging from 0.4 to 0.

8. The groundwater level change rate monitoring involved in parameter b uses multiple water level sensors of different depths. The spacing between the sensors is determined according to the geological stratification. In areas with large soil layer changes, the water level sensors are used at different depths. The domain spacing is small, ranging from 0.5 to 2 meters. For parameter e, the measurement of electromagnetic environment interference intensity is not only for on-site electromagnetic spectrum measurement, but also combined with electromagnetic simulation model analysis. The electromagnetic simulation model is established according to the distribution of electrical equipment and topographic factors at the construction site. The electromagnetic environment distribution is obtained by solving Maxwell's equations by finite element method, and then compared and calibrated with the measured data. The emergencies based on parameter f include but are not limited to severe weather and underground obstacle discovery. For different types of emergencies, a probability model is established according to their historical occurrence frequency and the degree of impact on measurement to determine the value of f.

5. A foundation pit measurement system for pipeline engineering construction according to claim 1, characterized in that: The special geometric feature parameter S in the three-dimensional modeling measurement algorithm j The calculation method is as follows: For the sharpness of the corner points in the foundation pit, the corner point detection algorithm introduces an adaptive threshold based on the local extreme value principle based on high-order derivatives. The threshold is adaptively adjusted according to the density and curvature changes of the point cloud near the corner point. The threshold is increased in areas with low point cloud density or large curvature changes. In the calculation of the wrinkle degree of the boundary surface, the Hodge decomposition process adopts a multi-resolution analysis method to decompose the boundary surface into subspaces of different resolutions according to the scale characteristics of the boundary surface. The Hodge decomposition of the normal vector field is calculated in each subspace, and then fused through wavelet transform. In the calculation of the Gaussian curvature change rate of the spatial surface, the first basic form and When the second basic form is derived, a numerical differentiation method with adaptive step size is adopted. The step size is adjusted according to the local curvature of the surface and the point cloud density. The step size is small in areas with large curvature or high point cloud density. The relationship between special geometric feature parameters and key feature points is determined by the shortest path algorithm and topological homotopy analysis in graph theory. The shortest path algorithm adopts an improved A* algorithm, and the weights of special geometric feature parameters are introduced in the heuristic function to more accurately reflect their role in three-dimensional modeling. Topological homotopy analysis is combined with Morse theory to determine the topological invariants by analyzing the Morse function of the foundation pit surface, thereby more accurately analyzing the topological homotopy relationship.

6. A foundation pit measurement system for pipeline engineering construction according to claim 1, characterized in that: The time-space interaction parameter T in the fast 3D modeling and measurement algorithm j The acquisition process is further optimized as follows: when setting the spatiotemporal reference points, the optimization algorithm based on the Voronoi diagram takes into account the heterogeneity of the environment around the foundation pit, and assigns different weights to different geological conditions and underground structure areas. The weights are determined according to the soil type and groundwater level factors in the geological exploration data. The atomic clock in the spatiotemporal sensor adopts a cesium atomic clock, and the three-dimensional spatial positioning sensor adopts a combination of a laser tracker and a total station. The laser tracker is used for short-range high-precision positioning, and the total station is used for long-distance positioning. The two are seamlessly connected through a data fusion algorithm. In the tensor product spline interpolation method for spatial deformation data processing, the coefficients of the tensor product spline are adaptively adjusted according to the distribution density of the spatiotemporal reference points and the spatiotemporal correlation of the data, and the adjustment range of the coefficients is increased in areas where the data changes dramatically. The soil mechanical equilibrium in the physical constraint conditions is analyzed by combining the discrete element method and the finite difference method. The stability of the underground structure is evaluated by the finite element strength reduction method, and the coupling of the two methods is achieved through a multi-field coupling algorithm.

7. A foundation pit measurement system for pipeline engineering construction according to claim 1, characterized in that: The topological connection coefficient C in the fast three-dimensional modeling measurement algorithm i The calculation method is improved as follows: when constructing the topological map of the foundation pit and the surrounding underground pipeline network, the representation of the nodes, in addition to the key feature points and pipeline connection points, also includes the geological structure change points. The attributes of these additional nodes are determined according to the geological exploration data. In addition to considering the factors of pipeline diameter and soil conductivity, the weight determination of the edge also takes into account the influence of groundwater flow velocity and direction. The groundwater flow velocity is determined by combining the tracer method and the flow meter measurement, and the direction is determined by geomagnetic measurement and water flow simulation analysis. The discretization of the Laplace-Beltrami operator adopts the adaptive finite element method, which automatically adjusts the density of the grid division according to the local complexity of the topological map, and increases the grid density in areas where the nodes and edges are densely distributed or the attributes change greatly. When calculating the eigenvalues ​​and eigenvectors, the Lanczos algorithm is used to iteratively solve the eigenvalue problem of large sparse matrices. The number of iterations is determined according to the required calculation accuracy and the scale of the topological map, so as to more efficiently obtain the intrinsic properties of the topological structure, and then more accurately calculate the topological connection coefficient C. i .

8. A method for measuring a foundation pit for pipeline engineering construction, characterized in that: The specific steps of this method are: S100, the automated mobile measuring platform: comprises a platform base that can automatically move along a preset track and a measuring instrument bearing structure installed thereon; S101, in which the movement of the platform base is achieved by a unique magnetic suspension drive system. The superconducting magnet array is distributed at the bottom of the platform base and is made of a mixture of critical temperature superconducting materials, in which the mass ratio of yttrium barium copper oxide and bismuth strontium calcium copper oxide is 3:

2. Each magnet unit in the superconducting magnet array is hexagonal, and adjacent magnet units are connected by superconducting connecting bridges. The superconducting material of the superconducting connecting bridge is magnesium boron. S102, the electromagnetic rails laid along the preset track interact with the superconducting magnet array. The electromagnetic rails are multi-layer composite structures, the bottom layer is a ferromagnetic material for enhancing the magnetic field, the middle layer is a polyimide film insulation layer, and the upper layer is a copper-nickel alloy conductive layer with high conductivity. The electromagnetic coil windings on the electromagnetic rails use Litz wires, and the number of winding turns is calculated based on the preset driving force requirements and magnetic field strength. By precisely controlling the current size and direction in each electromagnetic coil, an alternating magnetic field that interacts with the superconducting magnet array is generated, so that the platform base can move along the preset track in three-dimensional space with high precision; S103, the measuring instrument bearing structure is a honeycomb-shaped upper, middle and lower composite structure, the honeycomb unit is a regular hexagon, and the material is a carbon fiber reinforced ceramic matrix composite material, wherein the upper layer is installed with the control module of the measuring instrument, the middle layer is fixed with the measuring instrument body, each honeycomb unit is provided with an adaptive mounting fixture, and the lower layer carries the components related to the magnetic suspension drive system; S200, the distributed control: information transmission is realized based on the principle of quantum entanglement communication, including a quantum communication module of multiple quantum bit generation units and entangled photon emission-receiving units, the quantum bit generation unit adopts ion trap technology, each unit can stably generate and manipulate calcium ion quantum bits, and its trapped potential field is generated by the combination of radio frequency and DC electric field strength, the entangled photon emission-receiving unit uses barium borate BBO crystals to generate entangled photon pairs through spontaneous parametric down conversion SPDC process, the BBO crystal cutting angle is accurately determined according to the wavelength and polarization characteristics of the required entangled photons, in communication, information transmission is realized by encoding and decoding the polarization state and frequency quantum characteristics of the entangled photons, the control algorithm in the control system is based on quantum neural network, and its neuron model is represented by the superposition state of quantum bits, the control system is connected to the measuring instrument, and can measure different positions of the foundation pit according to the preset complex time function and the measurement path designed based on fractal geometry, the complex time function is used to determine the moving time interval of the platform, and its expression is: Among them, t is the construction time variable, a, b, c, d, e, and f are parameters. The value of a is determined according to the total construction period of the foundation pit and the time span of the key construction stage, ranging from 10 to 100. The value of b is related to the groundwater level change rate during the foundation pit construction process, which is obtained through long-term monitoring and analysis of geological and hydrological data, ranging from 0.01 to 0.

1. The value of c is a constant, which is set according to the start time of the project, ranging from 0 to 10. The value of d is determined according to the sampling frequency and data processing speed of the measuring instrument, ranging from 5 to 20. The value of e is related to the electromagnetic environment interference intensity of the construction site, which is obtained through The on-site electromagnetic spectrum measurement and analysis showed that the range was between 1.1 and 1.

5. The value of f was determined according to the probability of emergencies that may occur during the construction process and the degree of influence on the measurement, ranging from 0.001 to 0.

01. The measurement path designed based on fractal geometry was generated by an iterative function system (IFS). The parameters of the iterative function were determined according to the shape and size of the foundation pit and the fractal dimension of the surrounding geological structure. The fractal dimension was obtained by analyzing the geological radar scanning data using the box counting method, ranging from 1.2 to 2.

5. The generated measurement path can cover the key areas of the foundation pit and areas with potential changes. S300, the three-dimensional modeling: constructing a three-dimensional model of the foundation pit by processing the measurement data of the key feature points of the foundation pit, and the algorithm formula is: Among them, M is the three-dimensional model of the foundation pit, P i is the spatial coordinate vector of the i-th key feature point, n is the number of key feature points, k i is the index related to the spatial dimension of the i-th key feature point, d i is the vertical distance from the i-th key feature point to the preset foundation pit reference plane, λ is the distance attenuation coefficient, Represents a custom vector fusion operation, C i is the topological connection coefficient associated with the i-th key feature point, t i is the timestamp of measuring the i-th key feature point, ω is the time frequency parameter, r i is the local curvature radius centered at the i-th key feature point, S j is the jth special geometric feature parameter, m is the number of special geometric feature parameters, γ j is the weight adjustment factor of the jth special geometric feature parameter, Indicates a custom parameter combination operation, T j is the jth time-space interaction parameter, β j is the enhancement coefficient of the jth time-space interaction parameter.

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