Intelligent guiding and data tracing system and method for whole process of construction lofting

Abstract

The invention discloses an intelligent guiding and data tracing system and method for the whole process of construction lofting, and relates to the technical field of engineering surveying construction. The system comprises a data preprocessing module, an intelligent guiding module, a real-time monitoring module, a data tracing module and an interaction terminal, lofting reference data is optimized through a multi-source data fusion calibration algorithm, precise guidance of construction point locations is realized in combination with a space coordinate dynamic guiding model, and full-process data is recorded by synchronously utilizing a block chain time sequence evidence storage technology. According to the method, through the steps of reference data calibration, dynamic guide lofting, real-time deviation correction and block chain evidence storage tracing, the problems that traditional lofting is low in efficiency, large in deviation and non-traceable in data are solved. The innovation point of the method lies in collaborative design of multi-source data fusion calibration, space dynamic guidance and block chain tracing, the lofting precision and the flow traceability are greatly improved, and the method is suitable for various engineering construction scenes.

Description

Technical Field

[0001] This invention relates to the field of engineering surveying and construction technology, specifically to an intelligent guidance and data traceability system and method for the entire construction layout process. Background Technology

[0002] Construction layout is the process of measuring the plan position and elevation of buildings or structures on the design drawings and transferring them to the actual site using surveying instruments and methods. This provides a precise basis for construction and is widely used in various engineering projects such as roads, bridges, buildings, and water conservancy.

[0003] With the continuous expansion of engineering construction scale and the increasing demands for construction precision, traditional construction layout techniques are no longer sufficient to meet actual needs. Currently, traditional construction layout mainly relies on manual operation of surveying equipment such as total stations and levels. Layout work is completed by manually reading data, calculating coordinates, and marking points, which has many shortcomings. Traditional layout is inefficient, with cumbersome manual procedures requiring the collaboration of multiple technicians. For complex projects with multiple layout points, it often consumes a significant amount of time. Secondly, layout accuracy is greatly affected by human factors. The operator's professional skills, operational proficiency, and sense of responsibility directly affect the measurement results, easily leading to human error and causing layout point deviations to exceed the allowable range. Furthermore, traditional layout data records are mostly in paper documents or simple spreadsheets, resulting in scattered data storage, chaotic management, and a lack of effective traceability mechanisms.

[0004] Meanwhile, although some existing layout technologies have incorporated satellite positioning and automated measurement techniques, improving layout efficiency to some extent, significant shortcomings remain. For example, some systems only utilize a single data source, failing to consider the fusion and calibration of multi-source data, resulting in insufficient accuracy of the benchmark data; some systems lack dynamic guidance functions, unable to adjust guidance strategies in real time according to actual site conditions; and some systems lack a comprehensive data traceability system, making data security and traceability difficult to guarantee. These problems severely restrict the development of construction layout technology, affecting the efficiency and quality of engineering construction. Therefore, developing a construction layout system and method with high precision, high efficiency, real-time guidance, and full traceability has become an urgent need in the current field of engineering surveying and construction. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent guidance and data traceability system and method for the entire construction layout process, which solves the problems mentioned in the background section.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution: an intelligent guidance and data traceability system for the entire construction layout process, including a data preprocessing module, an intelligent guidance module, a real-time monitoring module, a data traceability module, and an interactive terminal, wherein each module establishes bidirectional data communication through an industrial Ethernet; The data preprocessing module receives design drawing data, site topographic data, and satellite positioning data, and outputs accurate layout benchmark data through a multi-source data fusion calibration algorithm. The intelligent guidance module constructs a dynamic spatial coordinate guidance model based on the benchmark data and sends real-time guidance commands to the construction equipment. The real-time monitoring module collects actual coordinate data of construction points and performs deviation analysis with the benchmark data. The data traceability module uses blockchain time-series evidence storage technology to encrypt, store, and manage the traceability of data throughout the layout process. The interactive terminal is used for data visualization, command input, and traceability query.

[0007] Optionally, the data preprocessing module includes a data receiving unit, a data cleaning unit, a coordinate transformation unit, and a fusion calibration unit; The data receiving unit supports the simultaneous reception of CAD format design drawings, GPS / BeiDou satellite positioning data, and lidar terrain scanning data; the data cleaning unit removes invalid data using an outlier detection algorithm based on the Laida criterion, which first calculates the mean of the dataset. and standard deviation Set the data deviation threshold to 3. When a single data point satisfy When an outlier is detected, it is automatically removed. Simultaneously, the collection time, collection device, and data content of the outlier data are recorded for subsequent traceability and analysis. The coordinate transformation unit converts the Cartesian coordinates of the design drawings into the geodetic coordinates of the construction site. The transformation process uses a seven-parameter coordinate transformation model and achieves accurate mapping between different coordinate systems through Bursa's formula, as follows: in, The transformed geodetic coordinates are... Original Cartesian coordinates, For coordinate translation parameters, As a scale factor, The rotation parameter is used; the fusion calibration unit performs fusion processing on multi-source data based on the Kalman filter algorithm, and dynamically corrects data bias through the state equation and observation equation. The state equation is as follows: The observation equation is as follows: in for The state vector at time t, Here is the state transition matrix. The system noise driving matrix, For system noise, For the observation vector, The observation matrix maps the state vector to the observation vector. To detect noise, the filtering process is carried out iteratively in two steps: prediction and update. The prediction step predicts the state vector and covariance matrix at the current time based on the state estimate at the previous time step. The update step combines the current observation value to correct the prediction result and obtain the optimal state estimate. Finally, high-precision stakeout benchmark data is output.

[0008] Optionally, the intelligent guidance module includes a model building unit, a path planning unit, and an instruction sending unit; The model building unit constructs a three-dimensional spatial coordinate dynamic guidance model based on the construction point coordinates, site terrain elevation data, and construction equipment parameters from the benchmark data. The model uses a triangular mesh interpolation algorithm to generate a three-dimensional terrain surface of the construction area. First, the terrain data is divided into triangular meshes according to rules. The elevation of any point within the triangular mesh is calculated by interpolating the elevation values ​​of adjacent terrain points. Then, the coordinates of the stakeout points are embedded into the surface model. Combined with the operating range and motion constraints of the construction equipment, a visual guidance path is formed. The path planning unit uses the A* algorithm to plan the optimal guidance path based on the mobility of the construction equipment, the distribution of obstacles on site, and the order of the stakeout points. The algorithm uses a heuristic function... Evaluate path costs, where From the starting point to the node The actual cost, For nodes The estimated cost to reach the destination; The instruction sending unit uses a wireless communication protocol to send real-time guidance instructions to the execution mechanism of the construction equipment.

[0009] Optionally, the real-time monitoring module includes a coordinate acquisition unit, a deviation analysis unit, and an early warning unit; The coordinate acquisition unit integrates high-precision positioning equipment, distance measurement equipment and attitude sensor to collect the actual three-dimensional coordinates of the construction point and the attitude data of the equipment in real time. The deviation analysis unit compares the actual coordinate data with the reference data point by point to calculate the three-dimensional coordinate deviation value. The deviation value is calculated using the Euclidean distance formula as follows: in As the reference coordinates, These are the actual coordinates.

[0010] Optionally, the data traceability module includes a data acquisition unit, an encrypted storage unit, a traceability query unit, and an access control unit; the data acquisition unit collects data from the entire layout process in real time, including baseline data, guidance instruction data, actual measurement data, deviation correction data, operator information, and equipment operating parameters, with the timestamp accuracy of the collected data being at the millisecond level; The encrypted storage unit uses blockchain technology to build a distributed evidence storage network. Each data block contains the hash value of the previous data block, the current data content, the timestamp, and node information. The data is encrypted using the SHA-256 encryption algorithm. The SHA-256 algorithm converts input data of any length into a 256-bit hash value, which is collision resistant and irreversible, ensuring that the data cannot be tampered with. The source tracing query unit supports multi-dimensional query and traceability of data. The query process ensures data integrity through hash value chain verification. First, the target data block is located according to the query conditions. Then, the previous data block is traced through the hash value of the data block. The process is repeated until the initial data block is reached, forming a complete data flow trajectory. The query results are displayed in the form of visual charts. The permission management unit adopts a role-based access control strategy, which divides users into different roles and assigns different data access permissions to different roles.

[0011] Optionally, the interactive terminal includes a hardware terminal and a software interface. The hardware terminal is an industrial-grade tablet computer. The software interface adopts a layered design, including a data display layer, an instruction input layer, and a traceability query layer.

[0012] Optionally, it also includes a device adaptation module, which has a built-in library of communication protocols for various construction equipment. It enables data interaction between the system and different devices through protocol conversion without the need for hardware modification of existing construction equipment. At the same time, it supports the extended access of communication protocols for new devices. New protocols can be added and adapted through a protocol configuration tool, which provides a visual configuration interface.

[0013] The method of the intelligent guidance and data traceability system for the entire construction layout process includes the following steps: S1. Receive design drawing data, site topographic data and satellite positioning data through the data preprocessing module. After cleaning, coordinate transformation and multi-source data fusion calibration, output accurate layout benchmark data. S2. The intelligent guidance module constructs a dynamic spatial coordinate guidance model based on benchmark data, plans the optimal guidance path, sends real-time guidance instructions to the construction equipment, and guides the construction equipment to accurately locate the target point. S3. The real-time monitoring module continuously collects the actual coordinate data of the construction points and performs deviation analysis with the benchmark data. When a deviation occurs, a correction instruction is generated and fed back to the intelligent guidance module to adjust the guidance strategy until the deviation meets the requirements. S4, the data traceability module, collects and encrypts the data of the entire layout process in real time, forming tamper-proof blockchain evidence data, and supports multi-dimensional traceability queries.

[0014] Optionally, the specific process of multi-source data fusion calibration in step S1 is as follows: S101. The data cleaning unit uses the Laida criterion to remove invalid data and calculates the mean of the dataset. and standard deviation This will exceed 3 Data within the specified range was identified as outliers and removed. S102. Using a seven-parameter coordinate transformation model through a coordinate transformation unit, the transformation parameters are solved using the least squares method to convert the design coordinates into geodetic coordinates. S103. The Kalman filter algorithm is used to fuse satellite positioning data and terrain scanning data through the fusion calibration unit. The state vector, covariance matrix, system noise covariance matrix and observation noise covariance matrix are initialized. The state prediction value and covariance prediction matrix at the current time are obtained through the prediction step. The optimal state estimate value is obtained by combining the observation value and updating the step. When the deviation change is less than the set threshold for three consecutive iterations, the iteration is stopped and the final reference data is output.

[0015] Optionally, the specific process of blockchain evidence storage and traceability in step S4 is as follows: S401. The data acquisition unit collects the entire layout process data in chronological order. A data block is generated at each set time interval. Each data block contains the hash value of the previous data block, all data in the current time period, timestamp, and acquisition node information. The data block is encrypted using the SHA-256 encryption algorithm. S402. The encrypted data block is sent to each authorized node of the blockchain consortium chain. The nodes verify the data block using the practical Byzantine fault tolerance algorithm. After verification, the data block is added to the blockchain. S403. When traceability queries are required, users input query conditions through an interactive terminal. The traceability query unit retrieves relevant data blocks in the blockchain based on the conditions, verifies data integrity through hash value chaining, and feeds back the query results to the user in the form of a visual chart. At the same time, it records the query operation log to ensure that the traceability process is traceable.

[0016] This invention provides an intelligent guidance and data traceability system and method for the entire construction layout process, which has the following beneficial effects: The system integrates design drawing data, satellite positioning data, and terrain scanning data. Through data cleaning, coordinate transformation, and Kalman filter fusion algorithms, it effectively eliminates invalid data and corrects data deviations. Data cleaning uses the Laida criterion to accurately identify outliers. Coordinate transformation uses a seven-parameter model combined with the least squares method to achieve accurate coordinate system mapping. The Kalman filter algorithm dynamically optimizes the data through a prediction-update iteration process. The synergistic effect of these three processes ensures that the output benchmark data has extremely high accuracy. This solves the problems of insufficient accuracy and limitation by a single data source in traditional layout benchmark data, providing a reliable foundation for subsequent accurate layout and ensuring that the accuracy of the construction point surveying meets engineering requirements. Secondly, the spatial coordinate dynamic guidance model and path planning design of the intelligent guidance module realize efficient and accurate guidance for construction layout; the system constructs a three-dimensional dynamic guidance model based on benchmark data, restores the terrain surface through triangular mesh interpolation algorithm, and forms a visual guidance path by combining construction equipment parameters; the path planning adopts the A* algorithm combined with Bézier curve optimization, which ensures the optimal path while taking into account smoothness, and ensures the smooth movement of construction equipment. Furthermore, the system accurately calculates the three-dimensional coordinate deviation value using the Euclidean distance formula, and at the same time uses a linear regression algorithm to construct a deviation trend model to predict the direction of deviation development. When the deviation exceeds the threshold or shows an increasing trend, an early warning is triggered in time and a correction instruction is generated to ensure that the deviation during the layout process is always controlled within the allowable range, effectively avoiding engineering rework caused by deviation. In addition, the system uses the SHA-256 encryption algorithm combined with a consortium blockchain architecture to ensure that the data is immutable; it uses the Byzantine fault tolerance algorithm to achieve node consensus and ensure the consistency of data storage; and it uses multi-dimensional traceability queries combined with hash value chain verification to ensure that the data can be accurately traced. Finally, the system's device adaptation module design enables seamless integration with various construction equipment without requiring hardware modifications to existing equipment, reducing system deployment costs. It also supports extended access to new device protocols, enhancing the system's versatility and compatibility, making it suitable for various engineering construction scenarios such as roads, bridges, buildings, and water conservancy. Attached Figure Description

[0017] Figure 1 This is a flowchart of the system of the present invention; Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0019] Please see Figure 1The present invention provides a technical solution: an intelligent guidance and data traceability system for the entire construction layout process, including a data preprocessing module, an intelligent guidance module, a real-time monitoring module, a data traceability module and an interactive terminal, wherein each module establishes bidirectional data communication through an industrial Ethernet; The data preprocessing module receives design drawing data, site topographic data, and satellite positioning data, and outputs accurate layout benchmark data through a multi-source data fusion calibration algorithm. The data preprocessing module includes a data receiving unit, a data cleaning unit, a coordinate transformation unit, and a fusion calibration unit; The data receiving unit supports the simultaneous reception of CAD format design drawings, GPS / BeiDou satellite positioning data, and LiDAR terrain scanning data; the data cleaning unit removes invalid data through an outlier detection algorithm, which is based on the Laida criterion and first calculates the mean of the dataset. and standard deviation Set the data deviation threshold to 3. When a single data point satisfy When an outlier is detected, it is automatically removed. The time of data collection, the equipment used for collection, and the data content are recorded for subsequent traceability and analysis. The coordinate transformation unit converts the Cartesian coordinates from the design drawings to the geodetic coordinates used in the construction site. The transformation process employs a seven-parameter coordinate transformation model and utilizes Bursa's formula to achieve accurate mapping between different coordinate systems. Bursa's formula is as follows: in, The transformed geodetic coordinates are... Original Cartesian coordinates, For coordinate translation parameters, As a scale factor, For the rotation parameters, the least squares method is used to solve the parameters. An error equation is established using the coordinate data of multiple known common points, and the parameter values ​​that minimize the overall error are solved. The fusion calibration unit uses the Kalman filter algorithm to fuse multi-source data and dynamically corrects data biases through state equations and observation equations. The state equations are as follows: The observation equation is as follows: in for The state vector at any given time contains parameters such as coordinates and velocity. The state transition matrix is ​​set according to the characteristics of data change. The system noise driving matrix, The system noise follows a Gaussian distribution. , Let be the system noise covariance matrix. The observation vector is the measured value from the multi-source data. The observation matrix maps the state vector to the observation vector. To observe the noise, it follows a Gaussian distribution. , To observe the noise covariance matrix, the filtering process is carried out iteratively in two steps: prediction and update. The prediction step predicts the state vector and covariance matrix at the current time based on the state estimate at the previous time step, and the update step corrects the prediction result based on the current observation value to obtain the optimal state estimate value. Finally, high-precision stakeout benchmark data is output. The intelligent guidance module constructs a dynamic spatial coordinate guidance model based on benchmark data and sends real-time guidance commands to the construction equipment. The intelligent guidance module includes a model building unit, a path planning unit, and a command sending unit. The model building unit constructs a three-dimensional spatial coordinate dynamic guidance model based on the construction point coordinates, site terrain elevation data, and construction equipment parameters from the benchmark data. The model uses a triangular mesh interpolation algorithm to generate a three-dimensional terrain surface of the construction area. First, the terrain data is divided into triangular meshes according to rules. The elevation of any point within the triangular mesh is calculated by interpolating the elevation values ​​of adjacent terrain points. Then, the coordinates of the stakeout points are embedded into the surface model. Combined with the operating range and motion constraints of the construction equipment, a visual guidance path is formed. The path planning unit uses the A* algorithm to plan the optimal guidance path based on the mobility of the construction equipment, the distribution of obstacles on site, and the order of the stakeout points. The algorithm uses a heuristic function... Evaluate path costs, where From the starting point to the node The actual cost is calculated using the Euclidean distance between nodes. For nodes The estimated cost to the destination is calculated using Manhattan distance or Chebyshev distance. Explorable and explored nodes are managed through open and closed lists. The path with the lowest cost is iteratively selected, while also considering path smoothness. The planned path is optimized using Bézier curves to avoid sharp bends or abrupt changes, ensuring smooth movement of the construction equipment. The command sending unit uses a wireless communication protocol to send real-time guidance commands to the execution mechanism of the construction equipment. These commands include direction adjustment parameters, distance correction parameters, and attitude control parameters. The command content is dynamically adjusted based on the path planning results and the real-time status of the equipment to ensure that the construction equipment accurately follows the guidance path. The real-time monitoring module collects the actual coordinate data of the construction points and performs deviation analysis with the benchmark data. The real-time monitoring module includes a coordinate acquisition unit, a deviation analysis unit, and an early warning unit; The coordinate acquisition unit integrates high-precision positioning equipment, distance measurement equipment, and attitude sensor. The three work together to collect the actual three-dimensional coordinates of the construction site and the attitude data of the equipment in real time. The deviation analysis unit compares the actual coordinate data with the reference data point by point, and calculates the three-dimensional coordinate deviation value. The deviation value is calculated using the Euclidean distance formula as follows: in As the reference coordinates, Using actual coordinates, and analyzing the trend of deviation changes, a deviation trend model is constructed using a linear regression algorithm, with the deviation value set as the dependent variable. Time is the independent variable. Establish a linear regression equation ,in The slope The intercept is used to solve the equation parameters using the least squares method. When this occurs, it indicates that the deviation is showing a continuous increasing trend. When this occurs, it indicates that the deviation is showing a continuous decreasing trend. When this time, it indicates that the deviation tends to stabilize; The early warning unit has a preset deviation threshold, which is set according to the accuracy requirements of the engineering construction. When the deviation value exceeds the threshold or the deviation trend shows a continuous increase, an audible and visual early warning is immediately triggered. The early warning signal is simultaneously sent to the interactive terminal and construction equipment to remind the operators to make timely corrections. The data traceability module uses blockchain time-series evidence storage technology to encrypt, store, and manage the traceability of data throughout the entire layout process. The data traceability module includes a data acquisition unit, an encrypted storage unit, a traceability query unit, and an access control unit. The data acquisition unit collects data from the entire layout process in real time, including baseline data, guidance instruction data, actual measurement data, deviation correction data, operator information, and equipment operating parameters. The timestamp accuracy of the collected data is at the millisecond level. The encrypted storage unit uses blockchain technology to build a distributed evidence storage network. Each data block contains the hash value of the previous data block, the current data content, a timestamp, and node information. The data is encrypted using the SHA-256 encryption algorithm, which converts input data of any length into a 256-bit hash value. This algorithm is collision resistant and irreversible, ensuring that the data cannot be tampered with. The blockchain nodes adopt a consortium blockchain architecture, where only authorized nodes can participate in data storage and verification. Nodes achieve data consistency through a consensus mechanism that uses a practical Byzantine fault-tolerant algorithm. A data block can only be added to the blockchain when more than 2 / 3 of the authorized nodes verify the data as valid. The traceability query unit supports querying traceability data by multiple dimensions such as time, construction location, and operator. The query process ensures data integrity through hash value chain verification. First, the target data block is located according to the query conditions, and then the previous data block is traced through the hash value of the data block. This process is repeated until the initial data block is reached, forming a complete data flow trajectory. The query results are displayed in the form of visual charts, including data content, timestamps, and related data. The access control unit adopts a role-based access control strategy, dividing users into different roles such as administrators, operators, and supervisors. Different roles are assigned different data access permissions. Administrators have full access permissions, including data entry, modification, deletion, and permission allocation. Operators can only query data related to their own operations. Supervisors can query all construction data but do not have modification permissions. Access verification is achieved through dual authentication of username and password + dynamic verification code. The dynamic verification code is pushed to the user terminal via SMS or APP, effectively preventing unauthorized access. Interactive terminals are used for data visualization, command input, and traceability queries; The interactive terminal comprises a hardware terminal and a software interface. The hardware terminal uses an industrial-grade tablet PC, which is waterproof, dustproof, and drop-proof, and supports touch operation and handwriting input. The software interface adopts a layered design, including a data display layer, a command input layer, and a traceability query layer. The data display layer displays real-time information such as baseline coordinates, actual coordinates, deviation values, and guide paths, using a dual display method of 3D graphics and numerical values. The 3D graphics are zoomable and rotatable for easy viewing by operators. The command input layer allows operators to manually input adjustment commands, set parameter thresholds, and confirm operation results, with input methods including touch input, handwriting input, and voice input. The traceability query layer provides multi-condition query entry points, supports data export and report generation functions, and export formats include Excel, PDF, and CSV.

[0020] The system also includes an equipment adaptation module, which has built-in libraries of various construction equipment communication protocols, including CAN bus protocol, Modbus protocol, and TCP / IP protocol. It supports seamless integration with various construction surveying and operation equipment such as total stations, levels, pavers, and road rollers. Through protocol conversion, the system can achieve data interaction with different devices without the need for hardware modifications to existing construction equipment, thus reducing system deployment costs. At the same time, it supports the expansion and access of new device communication protocols. New protocols can be added and adapted through the protocol configuration tool, which provides a visual configuration interface. Users can complete the protocol parameter settings through drag-and-drop and selection operations without writing complex code.

[0021] Please see Figure 2 This invention provides a technical solution: a method for an intelligent guidance and data traceability system for the entire construction layout process, comprising the following steps: S1. Receive design drawing data, site topographic data and satellite positioning data through the data preprocessing module. After cleaning, coordinate transformation and multi-source data fusion calibration, output accurate layout benchmark data. The specific process of multi-source data fusion calibration is as follows: S101. The data cleaning unit uses the Laida criterion to remove invalid data and calculates the mean of the dataset. and standard deviation This will exceed 3 Data within the specified range was identified as outliers and removed. S102. Using a seven-parameter coordinate transformation model through a coordinate transformation unit, the transformation parameters are solved using the least squares method to convert the design coordinates into geodetic coordinates. S103. The Kalman filter algorithm is used to fuse satellite positioning data and terrain scanning data through the fusion calibration unit. The state vector, covariance matrix, system noise covariance matrix and observation noise covariance matrix are initialized. The state prediction value and covariance prediction matrix at the current time are obtained through the prediction step. The optimal state estimate value is obtained by combining the observation value through the update step. When the deviation change is less than the set threshold for three consecutive iterations, the iteration is stopped and the final reference data is output. S2. The intelligent guidance module constructs a dynamic spatial coordinate guidance model based on benchmark data, plans the optimal guidance path, sends real-time guidance instructions to the construction equipment, and guides the construction equipment to accurately locate the target point. S3. The real-time monitoring module continuously collects the actual coordinate data of the construction points and performs deviation analysis with the benchmark data. When a deviation occurs, a correction instruction is generated and fed back to the intelligent guidance module to adjust the guidance strategy until the deviation meets the requirements. S4. The data traceability module collects and encrypts the data of the entire layout process in real time, forming tamper-proof blockchain evidence data that supports multi-dimensional traceability queries. The specific process of blockchain-based evidence storage and traceability is as follows: S401. The data acquisition unit collects the entire layout process data in chronological order. A data block is generated at each set time interval. Each data block contains the hash value of the previous data block, all data in the current time period, timestamp, and acquisition node information. The data block is encrypted using the SHA-256 encryption algorithm. S402. The encrypted data block is sent to each authorized node of the blockchain consortium chain. The nodes verify the data block using the practical Byzantine fault tolerance algorithm. After verification, the data block is added to the blockchain. S403. When traceability queries are required, users input query conditions through an interactive terminal. The traceability query unit retrieves relevant data blocks in the blockchain based on the conditions, verifies data integrity through hash value chaining, and feeds back the query results to the user in the form of a visual chart. At the same time, it records the query operation log to ensure that the traceability process is traceable.

[0022] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A smart guidance and data traceability system for the entire construction layout process, characterized in that: It includes a data preprocessing module, an intelligent guidance module, a real-time monitoring module, a data traceability module, and an interactive terminal. Each module establishes bidirectional data communication through an industrial Ethernet network. The data preprocessing module receives design drawing data, site topographic data, and satellite positioning data, and outputs accurate layout benchmark data through a multi-source data fusion calibration algorithm. The intelligent guidance module constructs a dynamic spatial coordinate guidance model based on the benchmark data and sends real-time guidance commands to the construction equipment. The real-time monitoring module collects actual coordinate data of construction points and performs deviation analysis with the benchmark data. The data traceability module uses blockchain time-series evidence storage technology to encrypt, store, and manage the traceability of data throughout the layout process. The interactive terminal is used for data visualization, command input, and traceability query.

2. The intelligent guidance and data traceability system for the entire construction layout process according to claim 1, characterized in that, The data preprocessing module includes a data receiving unit, a data cleaning unit, a coordinate transformation unit, and a fusion calibration unit. The data receiving unit supports the simultaneous reception of CAD format design drawings, GPS / BeiDou satellite positioning data, and lidar terrain scanning data; the data cleaning unit removes invalid data using an outlier detection algorithm based on the Laida criterion, which first calculates the mean of the dataset. and standard deviation Set the data deviation threshold to 3. When a single data point satisfy When an outlier is detected, it is automatically removed. Simultaneously, the collection time, collection device, and data content of the outlier data are recorded for subsequent traceability and analysis. The coordinate transformation unit converts the Cartesian coordinates of the design drawings into the geodetic coordinates of the construction site. The transformation process uses a seven-parameter coordinate transformation model and achieves accurate mapping between different coordinate systems through Bursa's formula, as follows: in, The transformed geodetic coordinates are... Original Cartesian coordinates, For coordinate translation parameters, As a scale factor, The rotation parameter is used; the fusion calibration unit performs fusion processing on multi-source data based on the Kalman filter algorithm, and dynamically corrects data bias through the state equation and observation equation. The state equation is as follows: The observation equation is as follows: in for The state vector at time t, Here is the state transition matrix. The system noise driving matrix, For system noise, For the observation vector, The observation matrix maps the state vector to the observation vector. To detect noise, the filtering process is carried out iteratively in two steps: prediction and update. The prediction step predicts the state vector and covariance matrix at the current time based on the state estimate at the previous time step. The update step corrects the prediction result by combining the current observation value to obtain the optimal state estimate, and finally outputs high-precision stakeout benchmark data.

3. The intelligent guidance and data traceability system for the entire construction layout process according to claim 1, characterized in that, The intelligent guidance module includes a model building unit, a path planning unit, and an instruction sending unit; The model building unit constructs a three-dimensional spatial coordinate dynamic guidance model based on the construction point coordinates, site terrain elevation data, and construction equipment parameters from the benchmark data. The model uses a triangular mesh interpolation algorithm to generate a three-dimensional terrain surface of the construction area. First, the terrain data is divided into triangular meshes according to rules. The elevation of any point within the triangular mesh is calculated by interpolating the elevation values ​​of adjacent terrain points. Then, the coordinates of the stakeout points are embedded into the surface model. Combined with the operating range and motion constraints of the construction equipment, a visual guidance path is formed. The path planning unit uses the A* algorithm to plan the optimal guidance path based on the mobility of the construction equipment, the distribution of obstacles on site, and the order of the stakeout points. The algorithm uses a heuristic function... Evaluate path costs, where From the starting point to the node The actual cost, For nodes The estimated cost to reach the destination; The instruction sending unit uses a wireless communication protocol to send real-time guidance instructions to the execution mechanism of the construction equipment.

4. The intelligent guidance and data traceability system for the entire construction layout process according to claim 1, characterized in that, The real-time monitoring module includes a coordinate acquisition unit, a deviation analysis unit, and an early warning unit; The coordinate acquisition unit integrates high-precision positioning equipment, distance measurement equipment and attitude sensor to collect the actual three-dimensional coordinates of the construction point and the attitude data of the equipment in real time. The deviation analysis unit compares the actual coordinate data with the reference data point by point to calculate the three-dimensional coordinate deviation value. The deviation value is calculated using the Euclidean distance formula as follows: in As the reference coordinates, These are the actual coordinates.

5. The intelligent guidance and data traceability system for the entire construction layout process according to claim 1, characterized in that, The data traceability module includes a data acquisition unit, an encrypted storage unit, a traceability query unit, and an access control unit. The data acquisition unit collects data from the entire layout process in real time, including baseline data, guidance instruction data, actual measurement data, deviation correction data, operator information, and equipment operating parameters. The timestamp accuracy of the collected data is at the millisecond level. The encrypted storage unit uses blockchain technology to build a distributed evidence storage network. Each data block contains the hash value of the previous data block, the current data content, the timestamp, and node information. The data is encrypted using the SHA-256 encryption algorithm. The SHA-256 algorithm converts input data of any length into a 256-bit hash value, which is collision resistant and irreversible, ensuring that the data cannot be tampered with. The source tracing query unit supports multi-dimensional query and traceability of data. The query process ensures data integrity through hash value chain verification. First, the target data block is located according to the query conditions. Then, the previous data block is traced through the hash value of the data block. The process is repeated until the initial data block is reached, forming a complete data flow trajectory. The query results are displayed in the form of visual charts. The permission management unit adopts a role-based access control strategy, which divides users into different roles and assigns different data access permissions to different roles.

6. The intelligent guidance and data traceability system for the entire construction layout process according to claim 1, characterized in that, The interactive terminal includes a hardware terminal and a software interface. The hardware terminal is an industrial-grade tablet computer. The software interface adopts a layered design, including a data display layer, an instruction input layer, and a traceability query layer.

7. The intelligent guidance and data traceability system for the entire construction layout process according to claim 1, characterized in that, It also includes a device adaptation module, which has a built-in library of communication protocols for various construction equipment. Through protocol conversion, the system can achieve data interaction with different devices without the need for hardware modification of existing construction equipment. At the same time, it supports the extended access of communication protocols for new devices. New protocols can be added and adapted through a protocol configuration tool, which provides a visual configuration interface.

8. A method for the intelligent guidance and data traceability system for the entire construction layout process as described in claims 1 to 7, characterized in that, Includes the following steps: S1. Receive design drawing data, site topographic data and satellite positioning data through the data preprocessing module. After cleaning, coordinate transformation and multi-source data fusion calibration, output accurate layout benchmark data. S2. The intelligent guidance module constructs a dynamic spatial coordinate guidance model based on benchmark data, plans the optimal guidance path, sends real-time guidance instructions to the construction equipment, and guides the construction equipment to accurately locate the target point. S3. The real-time monitoring module continuously collects the actual coordinate data of the construction points and performs deviation analysis with the benchmark data. When a deviation occurs, a correction instruction is generated and fed back to the intelligent guidance module to adjust the guidance strategy until the deviation meets the requirements. S4, the data traceability module, collects and encrypts the data of the entire layout process in real time, forming tamper-proof blockchain evidence data, and supports multi-dimensional traceability queries.

9. The intelligent guidance and data traceability method for the entire construction layout process according to claim 8, characterized in that, The specific process of multi-source data fusion calibration in step S1 is as follows: S101. The data cleaning unit uses the Laida criterion to remove invalid data and calculates the mean of the dataset. and standard deviation This will exceed 3 Data within the specified range was identified as outliers and removed. S102. Using a seven-parameter coordinate transformation model through a coordinate transformation unit, the transformation parameters are solved using the least squares method to convert the design coordinates into geodetic coordinates. S103. The Kalman filter algorithm is used to fuse satellite positioning data and terrain scanning data through the fusion calibration unit. The state vector, covariance matrix, system noise covariance matrix and observation noise covariance matrix are initialized. The state prediction value and covariance prediction matrix at the current time are obtained through the prediction step. The optimal state estimate value is obtained by combining the observation value and updating the step. When the deviation change is less than the set threshold for three consecutive iterations, the iteration is stopped and the final reference data is output.

10. The intelligent guidance and data traceability method for the entire construction layout process according to claim 8, characterized in that, The specific process of blockchain evidence storage and traceability in step S4 is as follows: S401. The data acquisition unit collects the entire process data of the layout in chronological order. A data block is generated at each set time interval. Each data block contains the hash value of the previous data block, all data in the current time period, timestamp and acquisition node information. The data block is encrypted using the SHA-256 encryption algorithm. S402. The encrypted data block is sent to each authorized node of the blockchain consortium chain. The nodes verify the data block using the practical Byzantine fault-tolerant algorithm. After verification, the data block is added to the blockchain. S403. When traceability queries are required, users input query conditions through an interactive terminal. The traceability query unit retrieves relevant data blocks in the blockchain based on the conditions, verifies data integrity through hash value chaining, and feeds back the query results to the user in the form of a visual chart. At the same time, it records the query operation log to ensure that the traceability process is traceable.

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