Measurement matrix lofting method based on Internet of Things

Abstract

The invention relates to the technical field of measurement lofting, in particular to a measurement matrix lofting method based on the Internet of Things. According to the application, firstly, a plurality of measuring robots and an environment sensor are connected with an Internet of Things control unit to form a measuring system, and real-time data transmission between equipment is realized; then a control instruction is sent through the Internet of Things cloud platform, and operations such as station setting and control point re-checking are automatically completed; then, meteorological correction is carried out based on real-time data collected by an environment sensor, and the measurement precision is improved; finally, the target position is automatically adjusted according to the corrected data until the precision requirement is met.

Description

Technical Field

[0001] The present application relates to the technical field of measurement and layout, and in particular to a measurement matrix layout method based on the Internet of Things. Background Art

[0002] Total station is a high-precision measuring instrument, which is widely used in engineering surveying, topographic mapping, construction, roads, bridges, etc. It integrates functions such as angle measurement, distance measurement, and data processing, and can achieve high-precision coordinate measurement.

[0003] The existing total station survey and layout simplifies the layout process of spatial plane positions during construction through steps such as spatial plane partitioning, extraction and input of three-dimensional coordinates, data inspection, manual station preparation and manual control point review. However, the existing technology still belongs to the traditional total station survey and layout, which requires two people to cooperate, one to operate the prism and the other to operate the total station, and import the data into the computer for processing and analysis. The operation is cumbersome and inefficient.

[0004] The existing total station survey and layout not only requires professionals to perform on-site operations, but also data processing and transmission usually require manual intervention, which is prone to errors; at the same time, remote control cannot be achieved, which limits its application in complex environments or remote control scenarios. In the case of tight construction schedules and complex scenarios, rapid survey and layout of remote control scenarios need to be achieved. Traditional operation methods cannot meet the measurement requirements, and this situation needs to be further improved. Summary of the invention

[0005] In order to solve the problems of low efficiency, multi-person collaboration and lack of automatic verification conditions in the existing total station measurement and layout methods, this application provides a measurement matrix layout method based on the Internet of Things, which adopts the following technical solutions: In a first aspect, the present application provides a measurement matrix layout method based on the Internet of Things, comprising the following steps: Connecting multiple measuring robots and environmental sensors to an IoT control unit to obtain a measuring system; Send station setting instructions and station setting parameters to the measurement system through the Internet of Things cloud platform, control the robot matrix to perform automatic search and lock the target, and obtain the station setting completion status; According to the station setting completion status, a control point review instruction is sent to obtain the measured coordinates and environmental parameters to obtain the control point review result; According to the control point review results, the layout instructions and target point coordinates are sent to obtain real-time measurement data; Perform meteorological correction according to the real-time measurement data and the environmental parameters to obtain layout guidance data; The target position is adjusted to within a set error range according to the layout guidance data to complete the layout.

[0006] By adopting the above technical solution, during the construction of large bridges, rapid changes in environmental factors such as temperature and air pressure will lead to reduced measurement accuracy. At the same time, on-site personnel need to frequently travel back and forth between the instrument and the target point to make adjustments, which seriously affects construction efficiency. This application first connects multiple measuring robots and environmental sensors to the Internet of Things control unit to form a measurement system to achieve real-time data transmission between devices. Then, control instructions are sent through the Internet of Things cloud platform to automatically complete operations such as station setting and control point review. Next, meteorological corrections are performed based on real-time data collected by environmental sensors to improve measurement accuracy. Finally, the target position is automatically adjusted according to the corrected data until the accuracy requirements are met.

[0007] Optionally, sending station setting instructions and station setting parameters to the measurement system through the Internet of Things cloud platform, controlling the robot matrix to perform automatic search and lock the target, and obtaining the station setting completion status, specifically includes the following steps: Sending station setting instructions and station setting coordinate parameters to the measurement system through the Internet of Things cloud platform to obtain initial station setting data; According to the initial station setting data, the robot matrix is ​​controlled to perform centering and leveling; According to the robot matrix centering and leveling state, the back view point coordinates are sent to the measurement system; According to the rear-view point coordinates, control the robot matrix to search for and lock the rear-view prism; Measure backsight angle and distance data; According to the angle and distance data, the orientation angle and the station coordinate data are calculated to obtain the station setting completion status.

[0008] By adopting the above technical solution, in tunnel construction measurement, the operator needs to repeatedly adjust the instrument position for centering and leveling, and manually aim at the backsight point and record data, which is not only time-consuming and error-prone, but also difficult to ensure the quality of station setting, especially in environments with insufficient light or limited vision. The present application first sends station setting instructions and coordinate parameters through the cloud platform to automatically complete centering and leveling; then automatically searches and locks the prism based on the backsight point coordinates; finally, by accurately measuring the angle and distance of the backsight point, the orientation angle and station coordinates are automatically calculated, which not only eliminates the uncertainty of manual operation, but also realizes remote control and real-time monitoring through the Internet of Things technology, greatly improving the efficiency and accuracy of station setting.

[0009] Optionally, obtaining measured coordinates and environmental parameters to obtain control point review results specifically includes the following steps: sending control point coordinate data to the measurement system according to the control point review instruction; According to the control point coordinate data, the robot matrix is ​​controlled to automatically search for the control point prism and lock it; According to the prism locking state, the angle and distance data of the control point are collected multiple times to obtain the measured coordinates; Collect temperature, air pressure and humidity data from environmental sensors to obtain environmental parameters; The spatial position of the control point is calculated according to the measured coordinates and the environmental parameters to obtain a control point verification result.

[0010] By adopting the above technical scheme, in the measurement of high-rise building construction, due to the complex and changeable environmental conditions, a single measurement is easily affected by factors such as temperature and air pressure and produces errors, and the manual recording of environmental parameters often has a lag, resulting in insufficient reliability of the control point verification results; the present application first realizes automatic search and prism locking according to the control point coordinates; then uses multiple measurements to collect angle and distance data, and at the same time obtains parameters such as temperature, air pressure and humidity in real time through environmental sensors; finally, the measured coordinates and environmental parameters are comprehensively analyzed to calculate the accurate spatial position, realizing the coordinated collection and processing of measurement data and environmental parameters, which not only improves the reliability of control point verification, but also significantly improves the measurement accuracy through multiple measurements and environmental compensation mechanism.

[0011] Optionally, the calculation of the control point coordinate data specifically includes the following steps: Calculate the horizontal distance D, Among them, (X a ,Y a ) is the site coordinate, (X b ,Y b ) is the backsight point coordinate; Calculate the coordinate azimuth H, where When Y b -Y a >0,X b -X a >0, H=arctan((Y b -Y a ) / (X b -X a )), When Y b -Y a >0,X b -X a <0, H = 180°-arctan((Y b -Y a ) / (X b -X a )), When Y b -Y a <0,X b -X a <0, H=180°+arctan((Y b-Y a ) / (X b -X a )), When Y b -Y a <0,X b -X a >0, H=360°-arctan((Y b -Y a ) / (X b -X a )), Calculate the vertical angle V,

[0012] By adopting the above technical solution, the present application first establishes a spatial distance calculation model based on three-dimensional coordinates; then processes the coordinate azimuth calculation in different quadrants through piecewise functions, effectively avoiding the angle calculation errors caused by cross-quadrants; finally, the vertical angle is accurately solved based on the elevation difference, which not only ensures the accuracy of the calculation results in the entire space, but also improves the calculation efficiency through the optimization of the mathematical model.

[0013] Optionally, calculating the spatial position of the control point according to the measured coordinates and the environmental parameters to obtain a control point review result specifically includes the following steps: Obtaining the azimuth, vertical angle and horizontal distance information in the measured coordinates to obtain original observation data; Calculating correction parameters according to the environmental parameters; Correcting the horizontal distance according to the correction parameter to obtain a corrected horizontal distance; Calculate the three-dimensional coordinates of the control point according to the corrected horizontal distance, azimuth and vertical angle; The calculated coordinates are compared with the known control point coordinates, the coordinate difference is calculated, and it is determined whether the verification accuracy requirements are met based on the coordinate difference.

[0014] By adopting the above technical scheme, in precision engineering measurements in all regions, the correction coefficient is abnormal due to inaccurate temperature, air pressure and humidity obtained inside the instrument and equipment, and the traditional fixed correction coefficient method cannot adapt to complex meteorological conditions, resulting in significant errors in the measurement results. The present application first extracts basic measurement data such as horizontal angle, vertical angle and slant distance from the measured coordinates, and then uses the temperature, air pressure and humidity data collected in real time by the environmental sensor to calculate the correction parameters and accurately correct the distance measurement results. The corrected data obtains the actual three-dimensional coordinates of the control point through spatial coordinate calculation, and automatically compares them with the theoretical coordinates to ensure that the control point position meets the engineering requirements. It not only realizes the full automation of the control point review process, but also significantly improves the reliability of the review results by introducing a real-time correction mechanism for environmental parameters.

[0015] Optionally, a correction parameter is calculated according to the environmental parameter, Among them, ΔD is the correction parameter, P is the atmospheric pressure value, t is the temperature data, h is the humidity data, and α is the atmospheric expansion coefficient.

[0016] By adopting the above technical solution, this application substitutes atmospheric pressure, temperature and humidity into the correction formula based on the principles of atmospheric physics, and introduces the atmospheric expansion coefficient for comprehensive calculation to obtain an accurate correction coefficient, thereby achieving comprehensive consideration of environmental factors and improving the accuracy of correction, especially under extreme environmental conditions.

[0017] Optionally, according to the control point review result, a layout instruction and target point coordinates are sent to obtain real-time measurement data, which specifically includes the following steps: Check whether the control point review result is within the allowable error range to obtain a test result; According to the inspection result, a layout instruction is sent to the measurement system through the Internet of Things cloud platform to obtain a layout initial state; according to the layout initial state, the coordinates of the target point are sent to the measurement system to obtain target positioning data; According to the target positioning data, the robot matrix is ​​controlled to rotate to the target direction to obtain a rotation completion state; According to the rotation completion state, searching and locking the target prism to obtain a target locking state; According to the target locking state, the angle and distance data of the target prism are measured to obtain real-time measurement data.

[0018] By adopting the above technical scheme, in road construction stakeout, operators often directly stake out target points and ignore control point verification, or continue construction when the control point accuracy is unqualified, resulting in the gradual expansion of cumulative errors, which ultimately affects the quality of the project; this application first performs error inspection on the control point review results to ensure the reliability of the benchmark points; then gradually sends stakeout instructions and target point coordinates through the Internet of Things cloud platform to establish a strict state feedback mechanism; finally, through automatic rotation, search, locking and other steps, accurate measurement of the target points is achieved, and full quality control and intelligent execution of the stakeout process are achieved, which not only ensures the reliability of the measurement benchmark, but also achieves seamless connection of each step through the state feedback mechanism, significantly improving the efficiency and accuracy of stakeout.

[0019] Optionally, adjusting the target position to within a set error range according to the layout guidance data to complete the layout specifically includes the following steps: Obtaining coordinate difference values ​​in the layout guidance data to obtain position deviation data; Calculate the moving direction and distance of the target point according to the position deviation data to obtain adjustment guidance parameters; Control the movement of the target point position according to the adjustment guidance parameters to obtain an adjusted position; Measuring the real-time coordinates of the adjusted position to obtain verification data; Comparing the difference between the verification data and the design coordinates to obtain an error check result; It is determined whether the error check result is within the set error range. If so, the setting out is completed.

[0020] By adopting the above technical scheme, in the layout of precision equipment foundation construction, operators often make position adjustments based on experience, lack of scientific guidance, and due to the lack of strict verification process, it is easy for the adjusted position to still exceed the error range, resulting in frequent rework and serious impact on construction efficiency; this application first analyzes the coordinate difference to obtain the position deviation; then calculates the precise moving direction and distance of the target point; then moves the position according to the adjustment parameters; then performs real-time measurement and verification of the adjusted position; finally, ensures that the position accuracy meets the requirements through error inspection, which not only provides scientific adjustment guidance, but also ensures the layout quality through real-time verification.

[0021] Optionally, obtaining the coordinate difference in the layout guidance data to obtain the position deviation data specifically includes the following steps: Among them, (X a ,Y a ) is the site coordinate, (X 实测 , Y 实测 ) is the current measured data, (X, Y) is the design coordinates.

[0022] By adopting the above technical solution, the present application first calculates the distance deviation based on the verification data and the design coordinates; then uses the spatial geometric relationship between the measuring station, verification point and design point to calculate the angle deviation, thereby achieving a comprehensive evaluation of the error and realizing a three-dimensional inspection of the layout error.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: 1. This application first connects multiple measurement robots and environmental sensors to the IoT control unit to form a measurement system to achieve real-time data transmission between devices; then sends control instructions through the IoT cloud platform to automatically complete operations such as station setting and control point review; then performs meteorological correction based on the real-time data collected by the environmental sensors to improve measurement accuracy; finally, automatically adjusts the target position according to the corrected data until the accuracy requirements are met; 2. This application first issues station setting instructions and coordinate parameters through the cloud platform to automatically complete centering and leveling; then automatically searches and locks the prism based on the backsight point coordinates; finally, by accurately measuring the angle and distance of the backsight point, the orientation angle and station coordinates are automatically calculated, which not only eliminates the uncertainty of manual operation, but also realizes remote control and real-time monitoring through the Internet of Things technology, greatly improving the efficiency and accuracy of station setting; 3. This application first realizes automatic search and prism locking according to the control point coordinates; then uses multiple measurements to collect angle and distance data, and at the same time obtains parameters such as temperature, air pressure and humidity in real time through environmental sensors; finally, the measured coordinates and environmental parameters are comprehensively analyzed to calculate the accurate spatial position, realizing the coordinated collection and processing of measurement data and environmental parameters, which not only improves the reliability of control point review, but also significantly improves the measurement accuracy through multiple measurements and environmental compensation mechanisms. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flow chart of a measurement matrix layout method based on the Internet of Things according to an embodiment of the present application; Figure 2 It is a schematic diagram of an Internet of Things system in a measurement matrix layout method based on the Internet of Things in an embodiment of the present application; Figure 3 It is a schematic diagram of a hardware system in a measurement matrix layout method based on the Internet of Things in an embodiment of the present application; Figure 4 It is a flowchart of step S200 in a measurement matrix layout method based on the Internet of Things in an embodiment of the present application; Figure 5 It is a flowchart of step S300 in a measurement matrix layout method based on the Internet of Things in an embodiment of the present application; Figure 6 It is a flowchart of step S350 in a measurement matrix layout method based on the Internet of Things in an embodiment of the present application; Figure 7 It is a flowchart of step S400 in a measurement matrix layout method based on the Internet of Things in an embodiment of the present application; Figure 8 It is a flowchart of step S600 in a measurement matrix layout method based on the Internet of Things in an embodiment of the present application. DETAILED DESCRIPTION

[0025] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0026] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0027] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0028] In the first aspect, the present application provides a measurement matrix layout method based on the Internet of Things, referring to Figure 1 , including the following steps: S100, connecting a plurality of measuring robots and environmental sensors to an Internet of Things control unit to obtain a measuring system.

[0029] In this embodiment, multiple measuring robots and environmental sensors are connected to the Internet of Things control unit through a network interface to form a complete intelligent measurement system. The environmental sensors include temperature sensors, air pressure sensors, and humidity sensors, which are used to collect meteorological parameters of the measurement environment. The measuring robot has automatic search and locking functions, which can realize remote control and automated measurement.

[0030] Specifically, prepare multiple measuring robots, which are mainly used to execute the measurement and layout instructions of the midpoint coordinates of the spatial plane. Pay attention to the distance and vertical angle limitations when using the measuring robot for measurement and layout. For example, the final plane construction height difference is allowed to be ±2cm, then the distance between the measuring point and the layout surface should be within 200m, and the vertical angle should be within 5 degrees. When the requirements are low during the initial layout of the project, the distance and vertical angle will be looser. Prepare an environmental sensor QTHPB temperature, humidity and pressure sensor with a measuring range of -40-60°C, 0-100%RH humidity and 10-110kPa (100-1100hPa). It is used to monitor the temperature, humidity and atmospheric pressure of the current space as a basis for correcting the measurement results of the measuring robot to improve the measurement accuracy. Build an Internet of Things system, such as Figure 2As shown, the MCU adopts the stm32f103 series, the serial port 2 of the MCU is connected to a 4g module, the serial port 3 is configured with an RS-232 interface, the serial port 5 is configured with an RS-485 interface, and the serial port 1 is used to download and debug programs. The measuring robot uses the RS-232 interface to connect to the IoT system, and the environmental sensor uses the RS-485 interface to connect to the IoT system. After completing the hardware system connection, download the MCU program, connect the system, start the system, and upload the system data to the cloud platform.

[0031] S200, sending station setting instructions and station setting parameters to the measurement system through the Internet of Things cloud platform, controlling the robot matrix to perform automatic search and lock the target, and obtaining the station setting completion status.

[0032] In this embodiment, the IoT cloud platform sends station setting instructions and station setting parameters to the measurement system, including the coordinates of the measuring station point, the coordinates of the rear-view point, and the instrument height. After receiving the instructions, the system controls the robot matrix to enter the automatic search mode, identify and lock the rear-view prism, and complete the instrument orientation.

[0033] Specifically, the transmission of station setting parameters adopts JSON format, and the data contains information such as station number, coordinate value (X, Y, Z), instrument height, etc. For example, in the construction layout of bridge piers, first input the coordinates of station K1 (1000.000, 2000.000, 100.000) and instrument height 1.500m on the cloud platform, and the coordinates of backsight point K2 (1100.000, 2000.000, 100.000), the system automatically calculates the backsight direction, controls the robot matrix rotation and locks the target.

[0034] S300: According to the station setting completion status, a control point verification instruction is sent to obtain the measured coordinates and environmental parameters, and a control point verification result is obtained.

[0035] In this embodiment, the system automatically enters the control point verification stage according to the station setting completion status. By sending the control point verification instruction, the system automatically searches and locks the control point prism, collects angle and distance data, and obtains environmental parameters to verify the control point position.

[0036] Specifically, the control point verification process uses multiple measurements, and the system automatically performs 5 measurements and takes the average value. For example, in tunnel construction measurement, when the system verifies the control point, it first locks the control point prism, then continuously collects 5 sets of data, and records environmental parameters such as the current temperature of 24°C, air pressure of 101.2kPa, and relative humidity of 65%, and calculates the actual spatial position of the control point.

[0037] S400, according to the control point review result, send the layout instruction and the target point coordinates to obtain real-time measurement data.

[0038] In this embodiment, after confirming that the control point review result is qualified, the system enters the layout stage. By sending the layout instruction and the target point coordinates, the robot matrix is ​​controlled to automatically rotate and position, search and lock the target prism, and obtain real-time measurement data.

[0039] Specifically, the transmission of the layout data is in batches, with the coordinate information of one target point being sent each time. For example, when staking out the foundation of a plant, the system first sends the coordinates of the pile point P1 (1050.000, 2050.000, 98.000), and the robot matrix automatically rotates to the calculated direction, searches for and locks the prism installed on the layout pole, and collects angle and distance data in real time.

[0040] S500: Perform meteorological correction according to the real-time measurement data and environmental parameters to obtain layout guidance data.

[0041] In this embodiment, the system performs meteorological correction on the measurement results according to the real-time measurement data and environmental parameters, and corrects the distance measurement data by calculating the correction parameters to obtain accurate spatial position information, providing guidance for layout adjustment.

[0042] Specifically, the meteorological correction adopts real-time calculation, and the system updates the environmental parameters every 10 seconds. For example, when the temperature change exceeds 2°C during the foundation laying of precision equipment, the system automatically recalculates the correction coefficient and corrects the measurement data in real time to ensure the accuracy of the laying.

[0043] S600, adjusting the target position to within the set error range according to the layout guidance data, and completing the layout.

[0044] In this embodiment, the system displays the position deviation of the target point in real time according to the layout guidance data, and guides the operator to adjust the position. The layout work is completed through continuous measurement and comparison until the target position enters the set error range.

[0045] Specifically, the position adjustment adopts a graphical indication method, and the system indicates the moving direction and distance through arrows. For example, in the precision equipment installation layout, when the system detects that the target point needs to be moved 8mm to the north and 5mm to the east, the adjustment indication graphic is displayed through the mobile phone App, and the operator makes fine adjustments according to the prompts until the deviation is close to 0, for example, less than ±2mm, and the system automatically confirms that the layout is completed.

[0046] In one embodiment, referring to Figure 4 In step S200, the station setting instruction and station setting parameters are sent to the measurement system through the IoT cloud platform to control the measurement robot to perform automatic search and lock the target, and obtain the station setting completion status, which specifically includes the following steps: S210, sending station setting instructions and station setting coordinate parameters to the measurement system through the Internet of Things cloud platform to obtain initial station setting data.

[0047] In this embodiment, the IoT cloud platform sends station setting instructions and station setting coordinate parameters to the measurement system through an encrypted communication channel. After receiving the instructions, the system first verifies the data integrity and then writes the station setting parameters into the control unit cache to prepare for subsequent operations.

[0048] Specifically, the data of the set-out points are sorted out and the station setting data is determined. For example, in the foundation setting of an industrial plant, the surveyor inputs the coordinates of the station K1 (1000.000, 2000.000, 100.000) and the instrument height of 1.550m through the cloud platform. The system automatically checks the data format and validity and saves the verified station setting parameters to the control unit. Station setting is a crucial link in the process of spatial plane measurement and setting out. The accuracy and reliability of parameter transmission can be ensured through the Internet of Things.

[0049] S220: Control the robot matrix to perform centering and leveling according to the initial station setting data.

[0050] In this embodiment, the state of the tilt compensator of the measuring robot is obtained to ensure that the compensator is in the on state, and the horizontal angle correction function is turned on. The system controls the measuring robot to perform automatic centering and leveling, and monitors the instrument state in real time through the electronic level.

[0051] Specifically, the centering and leveling process adopts an automated control method. For example, in tunnel measurement, the system first checks the state of the tilt compensator, then controls the electric foot screws for automatic leveling, monitors the state of the horizontal and vertical bubbles in real time, and automatically confirms that the leveling is completed when the leveling accuracy is better than 10″. At the same time, the atmospheric correction parameters are set to prepare for subsequent measurements. If in a manual operation environment, the measuring robot is installed on a tripod, and the tripod is preliminarily adjusted to roughly level the measuring robot. Then use an optical plummet or a laser plummet for precise centering. The optical plummet aligns the crosshairs in the field of view with the mark on the ground, while the laser plummet directly aims at the ground mark point through the laser beam. Fine-tune the tripod position to ensure that the center of the plummet coincides with the station mark to achieve high-precision centering. Use the leveling screws of the measuring robot for detailed leveling. Adjust each leveling screw separately to gradually move the horizontal bubble to the center position, ensure that the horizontal axis of the measuring robot is in a horizontal state, and provide an accurate horizontal and vertical angle reference for the subsequent measurement.

[0052] S230. Send the backsight point coordinates to the measurement system according to the robot matrix centering and leveling state.

[0053] In this embodiment, after the system confirms that the instrument is in a qualified centering and leveling state, it sends the backsight point coordinates c (Xc, Yc, Zc) and the prism height h1 to the measurement system through the cloud platform. The system automatically calculates the backsight direction and provides basic data for target search.

[0054] Specifically, the backsight point data is transmitted in a standard format. For example, in road construction measurement, the system sends the coordinates of the backsight point BS01 (1100.000, 2000.000, 100.000) and the prism height of 1.600m, and automatically calculates the approximate azimuth to the measuring station as the search starting direction.

[0055] S240. According to the rear-view point coordinates, control the robot matrix to search for and lock the rear-view prism.

[0056] In this embodiment, the system controls the robot matrix to start the ATR automatic target recognition function according to the calculated rear-view direction. The measuring robot performs a search every time it rotates a certain horizontal angle until the rear-view prism is successfully locked.

[0057] Specifically, the search process adopts an intelligent control strategy. For example, in building layout, the system controls the measurement robot to use 30° as the search sector, conduct precise search within the range of ±15° in the expected direction, identify the prism reflection signal, and lock the target when the signal strength reaches the threshold.

[0058] S250, measuring rear view point angle and distance data.

[0059] In this embodiment, after the system locks the rearview prism, the telescope crosshairs are accurately aligned with the target center, and the angle and distance observation are automatically performed. The measurement adopts a multiple observation method to record the horizontal angle, vertical angle and slant distance data.

[0060] Specifically, the measurement data collection process is strictly controlled. For example, in precision engineering measurement, the system performs double-sided observation, records the observation values ​​of the left and right sides of the face, ensures the observation quality through data comparison and analysis, and takes the average value as the final result.

[0061] S260: Calculate the orientation angle and station coordinate data based on the angle and distance data to obtain the station setting completion status.

[0062] In this embodiment, the system calculates the orientation angle and coordinates of the measuring station according to the measurement data and known coordinate information, and completes the instrument orientation by transmitting the station setting horizontal angle H and the station coordinate a to the measuring robot, and obtains the station setting completion state.

[0063] Specifically, the orientation calculation uses a rigorous mathematical model. For example, in the measurement of large equipment installation, the system uses the least squares method to calculate the optimal orientation angle and evaluate the orientation accuracy. When the orientation angle difference is less than 5", it automatically confirms that the station setting is completed.

[0064] In one embodiment, referring to Figure 5 In step S300, the measured coordinates and environmental parameters are obtained to obtain the control point verification result, which specifically includes the following steps: S310. Send control point coordinate data to the measurement system according to the control point review instruction.

[0065] In this embodiment, the theoretical angle values ​​V and H of the control point to be measured are calculated by the site coordinates a (Xa, Ya) and the check point coordinates b (Xb, Yb). The system sends the calculated angle parameters and coordinate data to the measurement system according to the control point check instruction.

[0066] Wherein, step S310 includes calculating the horizontal distance, coordinate azimuth and vertical angle. Calculate the horizontal distance D, Among them, (X a ,Y a ) is the site coordinate, (X b ,Y b ) is the backsight point coordinate; calculate the coordinate azimuth H, where Y b -Y a >0,X b -X a >0, H=arctan((Y b -Y a ) / (X b -X a )), when Y b -Y a >0,X b -X a <0, H = 180°-arctan((Y b -Y a ) / (X b -X a )), when Y b -Y a <0,X b -X a <0, H=180°+arctan((Y b -Y a ) / (X b -X a )), when Y b -Y a <0,X b -X a >0, H=360°-arctan((Y b -Y a ) / (X b -X a)) Calculate the vertical angle V, vertical angle V = 90°-Lα, where Lα is the vertical disk reading. In the spatial rectangular coordinate system, Represents the horizontal distance, that is, the projection distance between two points on the horizontal plane, ((Z b -Z a ) represents the elevation difference, which forms a right triangle with a vertical angle Horizontal distance Dab = Sab*cosV, Dab is the horizontal distance between the station and the backsight point, that is, the horizontal distance D, Sab is the slant distance between the station and the backsight point, Hab = Sab*sinV, Hab is the height difference between the station and the backsight point, X a =X b +Dab*cosα,Y a =Y b +Dab*cosα,X a is the X coordinate of the site, Y a is the Y coordinate of the station, and α is the azimuth between the station and the backsight point.

[0067] Specifically, the horizontal angle H is calculated according to the quadrant position. For example, when the control point B is located in the first quadrant (Yb-Ya>0, Xb-Xa>0), H=arctan(Yb-Ya / Xb-Xa).

[0068] S320. According to the control point coordinate data, the robot matrix is ​​controlled to automatically search for the control point prism and lock it.

[0069] In this embodiment, the measurement system checks the tilt compensator status and ensures that it is in the on state, and turns on the horizontal angle correction function. The system controls the measurement robot to rotate to the calculated V and H angle positions, sets it to the precise positioning mode, and activates the ATR automatic target recognition function.

[0070] Specifically, the search process adopts an intelligent control strategy. For example, in bridge construction measurement, the system controls the measurement robot to turn to the calculated angle position, and then conducts precise search within the range of ±5°. When the prism reflection signal is recognized, it automatically enters the precise tracking mode to achieve precise locking of the target.

[0071] S330. According to the prism locking state, collect the angle and distance data of the control point multiple times to obtain the measured coordinates.

[0072] In this embodiment, after the measuring robot accurately aligns the telescope crosshairs with the target center, the system starts the multiple observation mode, and simultaneously starts the distance measurement, angle measurement and inclination measurement functions, and records the complete data of each observation.

[0073] Specifically, the observation process adopts standardized procedures. For example, in precision engineering measurement, the system automatically performs three rounds of observation, each round includes observations on the left and right sides of the disk, records horizontal angles, vertical angles and slope distances, removes suspicious values ​​through data analysis, and calculates the average value as the final measured result.

[0074] S340: Collect temperature, air pressure and humidity data from environmental sensors to obtain environmental parameters.

[0075] In this embodiment, the system collects environmental sensor data in real time to obtain the temperature, air pressure and humidity parameters of the measurement environment. These parameters are used to calculate the atmospheric correction value to improve the measurement accuracy.

[0076] Specifically, the environmental parameter collection adopts a multi-point monitoring method. For example, in the tunnel section measurement, the system simultaneously collects environmental parameters at the measuring station and the target, with a temperature accuracy of 0.1°C, an air pressure accuracy of 0.1hPa, and a relative humidity accuracy of 1%, and obtains the final environmental correction parameters through data averaging.

[0077] S350. Calculate the spatial position of the control point according to the measured coordinates and environmental parameters to obtain the control point verification result.

[0078] In this embodiment, the system calculates the actual spatial position of the control point based on the measured coordinates and environmental parameters, and evaluates the stability and reliability of the control point by comparing the measured results with the known coordinates.

[0079] In one embodiment, referring to Figure 6 In step S350, the spatial position of the control point is calculated according to the measured coordinates and environmental parameters to obtain the control point verification result, which specifically includes the following steps: S351. Obtain the azimuth, vertical angle and horizontal distance information in the measured coordinates to obtain original observation data.

[0080] During the control point verification process, after the cloud platform sends a verification command to the measurement system, the measurement robot first detects and turns on the tilt compensator to ensure that the horizontal angle correction function works properly. The measurement robot accurately locates the target prism through the ATR mode and collects basic measurement data such as horizontal angle H, vertical angle V and slant distance (horizontal distance D).

[0081] S352. Calculate correction parameters according to environmental parameters.

[0082] The environmental parameters include atmospheric pressure, temperature and humidity. Before the measurement begins, the instrument height h0 and prism height h1 of the measuring robot are set, and the temperature t, air pressure P and humidity h data are collected in real time through environmental sensors.

[0083] Specifically, the correction parameters are calculated based on the environmental parameters. Among them, ΔD is the correction parameter, P is the atmospheric pressure value, t is the temperature data, h is the humidity data, and α is the atmospheric expansion coefficient, which is generally 1 / 273.16.

[0084] S353. Correct the slant distance according to the correction parameter to obtain the corrected horizontal distance.

[0085] Specifically, the calculated correction parameters are used to correct the measured slant distance. If it is 3.5km / mm and the measured distance D is 1000m, the correction formula is as follows: 大气补偿 =D+ΔD*(D / 1000).

[0086] S354. Calculate the three-dimensional coordinates of the control point according to the corrected horizontal distance, azimuth and vertical angle.

[0087] The corrected horizontal distance ' and the observed horizontal angle H and vertical angle V are substituted into the spatial coordinate forward calculation formula to calculate the actual three-dimensional coordinates (X', Y', Z') of the control point.

[0088] S355. Compare the calculated coordinates with the known control point coordinates, calculate the coordinate difference, and determine whether the verification accuracy requirements are met.

[0089] Specifically, the system automatically calculates the difference ΔX, ΔY, ΔZ between the measured coordinates and the known control point coordinates, and makes a judgment based on the accuracy standard required by the project. If the coordinate difference is within the allowable range, the control point position is confirmed to be qualified; otherwise, it is necessary to re-measure or check whether there is any abnormality in the measurement environment.

[0090] In one embodiment, referring to Figure 7 In step S400, according to the control point review result, the layout instruction and the target point coordinates are sent to obtain real-time measurement data, which specifically includes the following steps: S410, check whether the control point review result is within the allowable error range and obtain the inspection result.

[0091] The system automatically determines whether the coordinate differences ΔX, ΔY, and ΔZ calculated during the control point review process meet the accuracy requirements specified in the project. If they meet the requirements, the subsequent layout process will be entered; if they do not meet the requirements, the control points need to be reviewed again.

[0092] S420. According to the inspection result, a layout instruction is sent to the measurement system through the Internet of Things cloud platform to obtain the initial layout state.

[0093] Specifically, when the control points are reviewed and qualified, the cloud platform sends a layout instruction to the measurement system, activates the layout function of the measurement robot, and confirms that the system is in a ready state.

[0094] S430, according to the initial state of the layout, the target point coordinates are sent to the measurement system to obtain the target positioning data.

[0095] S440. According to the target positioning data, the robot matrix is ​​controlled to rotate to the target direction to obtain a rotation completion state.

[0096] Specifically, the measurement robot matrix automatically rotates according to the calculated azimuth angle H and vertical angle V to point the telescope to the theoretical target position. After the system confirms that the instrument has rotated into place, it proceeds to the next step.

[0097] S450, searching and locking the target prism according to the rotation completion state, and obtaining the target locking state.

[0098] Specifically, the measurement robot starts the ATR automatic target recognition function and searches for a prism in the target direction. When the prism is found, the system automatically performs precise aiming and locking; if the prism is not found, an error message is returned.

[0099] S460: According to the target locking state, the angle and distance data of the target prism are measured to obtain real-time measurement data.

[0100] Specifically, the system measures the angle and distance of the locked prism to obtain real-time horizontal angle, vertical angle and slant distance data. At the same time, it collects temperature, air pressure and humidity data from environmental sensors to provide basic data for subsequent position calculation and deviation analysis.

[0101] In one embodiment, referring to Figure 8 In step S600, the target position is adjusted to within the set error range according to the layout guidance data to complete the layout, which specifically includes the following steps: S610, obtaining coordinate differences in the layout guidance data to obtain position deviation data.

[0102] Wherein, step S650 includes calculating the distance deviation and the angle deviation. Angle deviation Among them, (X a ,Y a ,Z a ) is the site coordinate, (X 实测 , Y 实测 , Z 实测 ) is the verification data of the adjusted position, and (X, Y, Z) is the design coordinates.

[0103] S620: Calculate the moving direction and distance of the target point according to the position deviation data to obtain adjustment guidance parameters.

[0104] S630: Control the movement of the target point position according to the adjustment guidance parameters to obtain an adjusted position.

[0105] S640: Measure the real-time coordinates of the adjusted position to obtain verification data.

[0106] S650, comparing the difference between the verification data and the design coordinates to obtain an error check result.

[0107] S660, determine whether the error check result is within the set error range, and complete the layout.

[0108] If the error check result is within the set error range, the layout is completed; if it does not meet the requirements, return to step S630 to continue adjusting the position.

[0109] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0110] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A measurement matrix layout method based on the Internet of Things, comprising the following steps: Connecting multiple measuring robots and environmental sensors to an IoT control unit to obtain a measuring system; Send station setting instructions and station setting parameters to the measurement system through the Internet of Things cloud platform, control the robot matrix to perform automatic search and lock the target, and obtain the station setting completion status; According to the station setting completion status, a control point review instruction is sent to obtain the measured coordinates and environmental parameters to obtain the control point review result; According to the control point review results, the layout instructions and target point coordinates are sent to obtain real-time measurement data; Perform meteorological correction according to the real-time measurement data and the environmental parameters to obtain layout guidance data; The target position is adjusted to within a set error range according to the layout guidance data to complete the layout.

2. The measurement matrix lofting method based on the Internet of Things according to claim 1 is characterized in that: Sending station setting instructions and station setting parameters to the measurement system through the IoT cloud platform, controlling the robot matrix to perform automatic search and lock the target, and obtaining the station setting completion status, specifically includes the following steps: Sending station setting instructions and station setting coordinate parameters to the measurement system through the Internet of Things cloud platform to obtain initial station setting data; According to the initial station setting data, the robot matrix is ​​controlled to perform centering and leveling; According to the robot matrix centering and leveling state, the back view point coordinates are sent to the measurement system; According to the rear-view point coordinates, control the robot matrix to search for and lock the rear-view prism; Measure backsight angle and distance data; According to the angle and distance data, the orientation angle and the station coordinate data are calculated to obtain the station setting completion status.

3. The measurement matrix lofting method based on the Internet of Things according to claim 1 is characterized in that: Obtain the measured coordinates and environmental parameters and obtain the control point verification results, which specifically includes the following steps: sending control point coordinate data to the measurement system according to the control point review instruction; According to the control point coordinate data, the robot matrix is ​​controlled to automatically search for the control point prism and lock it; According to the prism locking state, the angle and distance data of the control point are collected multiple times to obtain the measured coordinates; Collect temperature, air pressure and humidity data from environmental sensors to obtain environmental parameters; The spatial position of the control point is calculated according to the measured coordinates and the environmental parameters to obtain a control point verification result.

4. The measurement matrix lofting method based on the Internet of Things according to claim 3 is characterized in that: The calculation of the control point coordinate data specifically includes the following steps: Calculate the horizontal distance D, D = √((X b -X a )2+(Y b -Y a )2, where (X a ,Y a ) is the site coordinate, (X b ,Y b ) is the backsight point coordinate; Calculate the coordinate azimuth H, where When Y b -Y a > 0, X b -X a > 0, H = arctan((Y b -Y a )) / (X b -X a )) When Y b -Y a > 0, X b -X a < 0, H = 180° - arctan((Y b -Y a )) / (X b -X a )) When Y b -Y a <0, X b -X a <0, H = 180° + arctan((Y b -Y a )) / (X b -X a )) When Y b -Y a < 0, X b -X a > 0, H = 360° - arctan((Y b -Y a )) / (X b -X a )) Calculate the vertical angle V, V = 90° - Lα, where Lα is the vertical disk reading of the measuring robot.

5. The measurement matrix lofting method based on the Internet of Things according to claim 4 is characterized in that: According to the measured coordinates and the environmental parameters, the spatial position of the control point is calculated to obtain the control point verification result, which specifically includes the following steps: Obtaining the azimuth, vertical angle and horizontal distance information in the measured coordinates to obtain original observation data; Calculating correction parameters according to the environmental parameters; Correcting the horizontal distance according to the correction parameter to obtain a corrected horizontal distance; Calculate the three-dimensional coordinates of the control point according to the corrected horizontal distance, azimuth and vertical angle; The calculated coordinates are compared with the known control point coordinates, the coordinate difference is calculated, and it is determined whether the verification accuracy requirements are met based on the coordinate difference.

6. The measurement matrix lofting method based on the Internet of Things according to claim 5 is characterized in that: Calculate correction parameters according to the environmental parameters, Among them, ΔD is the correction parameter, P is the atmospheric pressure value, t is the temperature data, h is the humidity data, α is the atmospheric expansion coefficient, 7. The measurement matrix lofting method based on the Internet of Things according to claim 1 is characterized in that: According to the control point review result, the layout instruction and the target point coordinates are sent to obtain real-time measurement data, which specifically includes the following steps: Check whether the control point review result is within the allowable error range to obtain a test result; According to the inspection result, a layout instruction is sent to the measurement system through the Internet of Things cloud platform to obtain the layout initial state; According to the initial state of the lofting, the coordinates of the target point are sent to the measurement system to obtain target positioning data; According to the target positioning data, the robot matrix is ​​controlled to rotate to the target direction to obtain a rotation completion state; According to the rotation completion state, searching and locking the target prism to obtain a target locking state; According to the target locking state, the angle and distance data of the target prism are measured to obtain real-time measurement data.

8. The measurement matrix lofting method based on the Internet of Things according to claim 1 is characterized in that: Adjust the target position to within the set error range according to the layout guidance data to complete the layout, which specifically includes the following steps: Obtaining coordinate difference values ​​in the layout guidance data to obtain position deviation data; Calculate the moving direction and distance of the target point according to the position deviation data to obtain adjustment guidance parameters; Control the movement of the target point position according to the adjustment guidance parameters to obtain an adjusted position; Measuring the real-time coordinates of the adjusted position to obtain verification data; Comparing the difference between the verification data and the design coordinates to obtain an error check result; It is determined whether the error check result is within the set error range. If so, the setting out is completed.

9. The measurement matrix lofting method based on the Internet of Things according to claim 8 is characterized in that: Obtaining the coordinate difference in the layout guidance data to obtain position deviation data specifically includes the following steps: Calculate distance deviation Calculate the angle deviation Among them, (X a ,Y a ) is the site coordinate, (X 实测 , Y 实测 ) is the current measured data, (X, Y) is the design coordinates.

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