A total station prism that can be automatically adjusted based on image recognition and its usage method

Abstract

The present invention relates to the field of automatic adjustment of total station prisms, and discloses a total station prism capable of automatic adjustment based on image recognition and its usage method, including: installing the total station prism and initializing it, calibrating the total station prism through multi-module linkage, analyzing the initialization situation of the total station prism and giving feedback; after initialization, obtaining the scene image and depth image of the wall surface through the image acquisition module, combining and analyzing to obtain the wall surface plane equation, and establishing a wall surface geometric model; orthogonalizing the reflecting surface of the total station prism, and performing measurement preprocessing according to the type of the wall surface; after the measurement preprocessing is completed, measuring the wall surface, dynamically correcting the total station prism constant through environmental parameters to obtain the prism correction constant and measuring to obtain the wall surface measurement data; performing refined processing on the wall surface measurement data, fusing the wall surface measurement data and eliminating the deviated data, and optimizing and generating a report based on the wall surface measurement data after the elimination is completed.

Description

Technical Field

[0001] The present invention relates to the technical field of total station prism automatic adjustment, and particularly relates to a total station prism capable of automatic adjustment based on image recognition and a using method thereof. Background Art

[0002] In the completion survey, it is often necessary to measure the coordinates of the building corner points. Using a total station, the measurement accuracy is relatively high, stable and reliable; the total station and the prism are respectively erected directly above two points, that is, the measurement reference axis passes through the measurement point and is perpendicular to the horizontal plane. The measurement reference axis is a virtual axis. For the prism equipment in the prior art, it is generally calibrated by the axis of the centering rod. That is, the centering rod is set at the measurement point and the centering rod is made vertical. The total station emits a laser signal to the prism and receives the signal reflected by the prism. Thus, the distance between the total station and the prism surface is measured. The distance between the prism reflection surface and the measurement reference axis of the prism is the prism constant. According to the distance and the prism constant, the distance between the two points can be determined.

[0003] In the prior art, due to the certain thickness and width of the prism itself, when measuring a wall surface or a wall corner, even if the prism is placed closely against the wall surface or the wall corner, it is still impossible to make the measurement reference axis of the prism closely adhere to the wall surface or the wall corner. In this case, the distance data measured by the total station is actually the distance between the total station and the measurement reference axis of the prism, and there is still a certain error value from the actual distance between the total station and the wall surface or the wall corner to be measured. Obtaining the prism constant by measuring the distance between the prism reflection surface and the measurement reference axis of the prism cannot effectively compensate for the measurement errors brought by different types of wall surfaces or wall corners. It is necessary to dynamically correct the prism constant under different types of wall surfaces or wall corners in combination with environmental parameters to ensure the accuracy of the measurement results, and automatically compare the deviation between the wall measurement data and the design drawing data, eliminate the identified abnormal wall measurement data, and optimize the generation of reports to ensure the authenticity and accuracy of the measurement results. Therefore, it is necessary to provide a total station prism capable of automatic adjustment based on image recognition and a using method thereof. Summary of the Invention

[0004] The purpose of the present invention is to provide a total station prism capable of automatic adjustment based on image recognition and a using method thereof. To solve the above-mentioned prior art problems, the present invention is realized through the following technical solutions:

[0005] In the first aspect, the present invention provides a total station prism capable of automatic adjustment based on image recognition and a using method thereof, including the following steps:

[0006] Install the total station prism and perform initialization, calibrate the total station prism through multi-module linkage, analyze the initialization situation of the total station prism and give feedback;

[0007] After initialization is completed, the scene image and depth image of the wall are obtained through the image acquisition module, the wall plane equation is obtained through combined analysis, and a wall geometric model is established.

[0008] Based on the wall geometric model, the reflecting surface of the total station prism is orthogonally processed, and measurement preprocessing is performed according to the type of the wall.

[0009] After the measurement preprocessing is completed, the wall is measured, the prism constant of the total station is dynamically corrected through environmental parameters to obtain the prism correction constant, and the wall measurement data is obtained.

[0010] The wall measurement data is refined, the wall measurement data is fused and the deviated data is eliminated, and a report is optimized and generated based on the wall measurement data after the elimination is completed.

[0011] In a second aspect, the present invention provides a total station prism operating system based on image recognition and capable of automatic adjustment, including the following modules:

[0012] Initialization module: Send an initialization signal, the microprocessor self-checks each component, and connects to the total station to establish a data transmission channel.

[0013] Intelligent calibration module: A piezoelectric ceramic damper is integrated at the bottom of the rod to suppress external vibration and the inverse piezoelectric effect is used to cancel the vibration, the white balance of the image acquisition module is calibrated, the motor drive system is self-checked, and zero reset parameters are loaded.

[0014] Image acquisition module: Collect the scene image and depth image of the measured wall for inspection and calibration.

[0015] Feature analysis module: Based on the collected scene image, edge detection is performed, and the detection algorithm locates the corner points.

[0016] Measurement preprocessing module: Obtain the initial inclination angle, establish an angle compensation function to adjust the prism angle to the target angle, realize the orthogonalization of the reflecting surface, set different rotation angles according to the type of the corner of the wall, and optimize the stress distribution of the L-shaped connecting piece through finite element analysis.

[0017] Measurement correction module: Measure the wall, dynamically correct the prism constant of the total station through environmental parameters to obtain the prism correction constant, and obtain the wall measurement data.

[0018] Analysis and generation module: Refine the wall measurement data, fuse the wall measurement data and eliminate the deviated data, and optimize and generate a report based on the wall measurement data after the elimination is completed.

[0019] The beneficial effects of the present invention:

[0020] 1. The upper prism assembly, the middle connecting assembly and the centering rod assembly can be disassembled and combined, which is convenient for carrying and adapting to different measurement scenarios. Through the L-shaped connecting assembly and the rotatable connecting piece, the prism can be embedded into the internal and external corners of the building corner, breaking through the limitation that traditional prisms are only applicable to planes, and reducing the measurement error in complex environments. By utilizing the direct and inverse piezoelectric effects, vibrations are monitored and cancelled in real time. Compared with traditional counterweights for passive vibration damping, active compensation for dynamic interference significantly improves measurement stability. The vibration energy is analyzed, and the reverse acting force is precisely matched to optimize the vibration damping effect.

[0021] 2. By combining visible light images and depth images, multi-dimensional analysis of the geometric features of the wall surface is achieved, providing edge contours, locating key points, and fitting the plane equation of the wall surface, complementarily improving the model accuracy. The attitude of the total station prism is dynamically adjusted through the angle compensation function to ensure that the reflecting surface is orthogonal to the wall surface. Differentiated strategies are formulated for internal corners, external corners, and non-standard angles, and the mechanical stability of the L-shaped connecting piece is optimized by combining FEA. The influence of temperature on the total station prism constant is calculated in real time according to the change of temperature, and thus compensation is carried out. Through comprehensive calculation and analysis of the three parts, the corrected total station prism constant is obtained , which is used for distance measurement to improve the accuracy and reliability of measurement;

[0022] 3. By dynamically adjusting the time series weights, the timeliness of recent data is given priority, avoiding errors caused by data time series. Based on the calculation of the standard deviation of the weighted average, outliers are automatically identified and removed, triggering the retest mechanism. Through attribute tags, precise positioning and traceability of data are realized, and the measured value is automatically compared with the designed value, and the over-limit area is automatically marked and fed back. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for description in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0024] Figure 1 FIG. 17 is a step flow chart of a total station prism capable of automatic adjustment based on image recognition and its usage method provided in Embodiment 1 of the present invention;

[0025] Figure 2 FIG. 21 is a structural schematic diagram of an operating system of a total station prism capable of automatic adjustment based on image recognition provided in Embodiment 2 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0026] To enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solution in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0027] Embodiment 1

[0028] As Figure 1 shown, a total station prism capable of automatic adjustment based on image recognition and its usage method provided by an embodiment of the present invention specifically include the following steps:

[0029] Step 1: Install the total station prism and initialize it, calibrate the total station prism through multi-module linkage, analyze the initialization situation of the total station prism and give feedback;

[0030] Specifically, the specific method for installing the total station prism and initializing it is as follows:

[0031] Set up the total station and perform preliminary leveling to make the total station in a stable measurement state;

[0032] Install the total station prism on the centering rod through the lower component, and use the centering device of the centering rod to accurately position the prism directly above the measurement point;

[0033] The total station prism includes: an upper prism component, a middle connection component, and a centering rod component;

[0034] The upper prism component includes: a prism and a prism bracket. The prism is rotatably connected to the top of the prism bracket. A prism bracket level is installed on the prism bracket, and a first fixed column is provided at the bottom of the prism bracket;

[0035] The middle connection component is an L-shaped connection component, which is convenient for embedding the internal and external corners of the building corner. The bottom of the first fixed column is connected to the top of the second fixed column through a rotatable connector. The rotatable connector is used to realize the rotatable adjustment and fixation of the upper prism component above the middle connection component. Conversion connecting rods are provided on both sides of the second fixed column;

[0036] The centering rod component includes: a lower support component and a centering rod;

[0037] Turn on the total station, the image acquisition module, the microprocessor, the motor drive system, the electronic bubble sensor, and the piezoelectric ceramic damper on the total station prism;

[0038] The total station sends an initialization signal to the total station prism, and the microprocessor conducts self-checks on each component to ensure the normal operation of the device; searches for and connects to the total station to establish a data transmission channel;

[0039] Function 1: The upper prism assembly, the middle connecting assembly, and the centering rod assembly can be disassembled and combined, which is convenient for carrying and adapting to different measurement scenarios. Through the L-shaped connecting assembly and the rotatable connecting piece, the prism can be embedded into the internal and external corners of the building corner, breaking through the limitation that traditional prisms are only applicable to planes and reducing measurement errors in complex environments;

[0040] Specifically, the specific method for calibrating the total station prism through multi-module linkage is as follows:

[0041] Integrate a piezoelectric ceramic damper at the bottom of the total station prism rod to suppress external vibrations;

[0042] Specifically, when external vibrations occur, the prism rod is affected by the vibrations and undergoes displacement or acceleration changes. The piezoelectric ceramic material in the piezoelectric ceramic damper has the piezoelectric effect. When the piezoelectric ceramic is subjected to mechanical stress, the polarization state inside it changes, thereby generating electric charges on the surface of the piezoelectric ceramic, converting the mechanical vibration signal into a vibration electrical signal;

[0043] The piezoelectric ceramic damper is connected to a control circuit, and the control circuit will receive the vibration electrical signal generated by the piezoelectric ceramic and perform band-pass filtering to eliminate environmental noise;

[0044] The control circuit judges the frequency and amplitude characteristics of the vibration based on the received vibration electrical signal through processing and analysis;

[0045] Specifically, convert the time-domain signal of the vibration electrical signal to the frequency domain and extract the dominant vibration frequency to obtain the vibration energy through Parseval's theorem;

[0046] It should be noted that Parseval's theorem represents Parseval's theorem, indicating that the energy of a function in the time domain is equal to the energy in the frequency domain, reflecting the idea of energy conservation;

[0047] Based on the comparison between the obtained vibration energy and the preset vibration energy threshold, if the vibration energy is greater than or equal to the preset vibration energy threshold, the control circuit will apply a reverse electrical signal to the piezoelectric ceramic;

[0048] It should be noted that due to the inverse piezoelectric effect of the piezoelectric ceramic, when the piezoelectric ceramic is subjected to an electrical signal, it will generate a mechanical deformation in the opposite direction to the original vibration, thereby generating a reverse acting force;

[0049] The reverse force generated by the piezoelectric ceramic acts on the rod in the prism, canceling out the force generated by the external vibration;

[0050] Exemplarily, when the external vibration causes the rod to displace upward, the reverse force generated by the piezoelectric ceramic damper causes the rod to move downward, thereby reducing or eliminating the vibration displacement of the rod;

[0051] The image acquisition module performs white balance calibration;

[0052] Based on the completion of white balance calibration, the motor drive system is started for self-check to examine the hardware status of the system, including: whether the power supply is stable, whether the sensor is working properly, and whether there is a short circuit or open circuit in the motor winding;

[0053] If an abnormality is detected during self-check, the system will issue an alarm and stop the reset operation, waiting for maintenance personnel to handle it;

[0054] Based on the end of the self-check program, the drive system loads the parameters related to zero reset preset in advance. The parameters related to zero reset include but are not limited to: reset speed, direction, and preset error range;

[0055] It should be noted that the parameters related to zero reset are set by professionals in the field of the present invention according to the type of the motor, application scenarios, and control requirements;

[0056] Specifically, the system controls the motor to start running at a preset low speed to ensure the smooth operation of the motor and confirm the zero reference signal;

[0057] A limit switch is installed at the zero position. When the motor runs to the zero position, the limit switch is triggered, and the limit switch sends a zero reference signal to the drive system, indicating that it is near the zero point;

[0058] Based on the obtained zero reference signal, the motor reduces its speed based on the preset low speed to determine the position approaching the zero point, and the system adjusts the position of the motor according to the accurate position data of the encoder;

[0059] By comparing the deviation between the current position and the zero position, the rotation angle of the motor is adjusted to make the motor stop at the zero position;

[0060] Based on the obtained zero position, the drive system records the value of the encoder and marks it as the zero position reference value;

[0061] Based on the completion of the calibration of the total station prism, a calibration completion signal is generated, indicating that the calibration and reset are successful;

[0062] Function 2: Utilize the direct and inverse piezoelectric effects to monitor and cancel vibrations in real time. Compared with traditional counterweights for passive vibration damping, it actively compensates for dynamic disturbances, significantly improves measurement stability, analyzes vibration energy, precisely matches the reverse force, and optimizes the vibration damping effect;

[0063] Step 2: After initialization, use the image acquisition module to obtain the scene image and depth image of the wall surface, combine and analyze to obtain the wall surface plane equation, and establish a wall surface geometric model;

[0064] Specifically, the specific method for combining and analyzing to obtain the wall surface plane equation and establish a wall surface geometric model is as follows:

[0065] Use a visible light camera to collect the scene image, and the obtained image data will be used for edge detection and corner location;

[0066] Specifically, use the Canny algorithm to perform edge detection on the visible light image;

[0067] It should be noted that the Canny algorithm is a classic edge detection algorithm. It smooths the image through Gaussian filtering to reduce the influence of noise, calculates the gradient magnitude and direction of the image, applies non-maximum suppression to refine the edges, uses a double-threshold algorithm to determine the true edge points and connect them into edge lines. Through the Canny algorithm, the edge information of the objects in the image can be accurately extracted, providing a basis for subsequent analysis;

[0068] Use the Harris corner detection algorithm to locate corners in the visible light image; The Harris corner detection is based on the change of local gray level in the image to detect corners;

[0069] If at a certain pixel point, when the window moves in two mutually perpendicular directions, the gray level values change significantly, then this pixel point is considered a corner; If the gray level value changes significantly in one direction and changes little in other directions, it is considered an edge point; If the gray level values change little in all directions, it is considered a point in a flat area;

[0070] It should be noted that the Harris corner detection algorithm is a classic corner detection algorithm. A small window is selected around each pixel point in the image, and then the change of the gray level value when the window moves in different directions is observed. The accuracy of the algorithm reaches ±1 pixel, accurately determining the corner positions in the image. Corners play an important role in subsequent image matching and feature extraction tasks;

[0071] Exemplarily, for a pixel point in the image , the change of the gray level value within the small window around the pixel point is described by the following formula: , where represents the window in The gray change energy after moving in the is a Gaussian function that assigns different weights to the pixel points within the window. represents the gray value of the image at ; is the gray value of the image at ;

[0072] By performing Taylor expansion and simplification on , a matrix form is calculated as: , where represents a matrix, called the autocorrelation matrix, and its elements are: , where and are the first-order partial derivatives of the image in the and directions respectively;

[0073] The depth image information of the wall surface is obtained by using a ToF camera, and 3D point cloud data with a resolution of 640×480 is obtained; the ToF camera measures the time it takes for light to travel from the camera to the object and back, calculates the distance between the object and the camera, and thus obtains the depth information of the scene.

[0074] Based on the obtained 3D point cloud data, a local plane equation of the wall surface is constructed; using fitting algorithms such as the least squares method, by processing the point cloud data obtained from the depth image, the parameters representing the wall surface plane are analyzed and the wall surface plane equation is determined.

[0075] Based on the wall surface plane equation, the normal vector of the wall surface and the horizontal reference vector are obtained. By calculating the dot product of the two vectors, dividing it by the product of their magnitudes, and then taking the inverse cosine value, the angle between the wall surface and the horizontal reference direction can be obtained;

[0076] The formula for calculating the wall surface angle is ;

[0077] Exemplarily, the normal vector of the wall surface obtained by the point cloud fitting method is , the horizontal reference vector is in the Y-axis direction of the total station coordinate system, the magnitude of the horizontal reference vector , the magnitude of the normal vector is . Substituting into the formula for calculating the wall surface angle gives , indicating that the wall surface is inclined by relative to the horizontal reference direction;

[0078] Based on the obtained wall plane equation and the wall angle, establish a wall geometric model;

[0079] Specifically, obtain the wall data in the design drawing to determine the wall boundary. Based on the 3D modeling interface, input the wall plane equation, and generate a wall geometric model based on the wall angle, wall boundary, and wall plane equation;

[0080] Function three: Combine the visible light image and the depth image to realize the multi-dimensional analysis of the wall geometric features, provide the edge contour, locate the key points, fit the wall plane equation, and complementarily improve the model accuracy;

[0081] Step three: Based on the wall geometric model, orthogonally transform the reflecting surface of the total station prism and perform measurement preprocessing according to the type of the wall;

[0082] First specifically, the specific method for orthogonally transforming the reflecting surface of the total station prism is as follows:

[0083] Establish an angle compensation function. Through the formula obtain the angle compensation value , where represents the initial inclination angle of the total station prism, which is measured in real time by the inertial measurement unit IMU, represents the target angle determined by calculating according to the wall angle, represents the mechanical backlash caused by temperature, which affects the angle of the total station prism;

[0084] It should be noted that the inertial measurement unit senses the attitude change of the total station prism in space, and through internal sensors such as accelerometers and gyroscopes, accurately obtains the initial tilt angle information of the prism;

[0085] Adopt a harmonic reduction stepping motor as the actuator. After calculating the angle compensation value , the control system sends an adjustment instruction to the harmonic reduction stepping motor to drive the total station prism to perform angle adjustment in the pitch direction, so that the total station prism reaches the target angle, and thus achieves the purpose of orthogonalizing the reflecting surface;

[0086] Second specifically, the specific method for performing measurement preprocessing according to the type of the wall is as follows:

[0087] Based on the completion of the orthogonalization of the reflecting surface, when measuring the external corner, in order to enable the center of the total station prism to accurately align with the diagonal of the corner, set the rotation angle to , ensure that the measurement light emitted by the total station is reflected along the ideal path, and improve the measurement accuracy;

[0088] When measuring the inside corner, the total station prism is directly attached to the wall for measurement. At this time, the rotation angle is set to to make the prism closely attached to the wall and obtain accurate wall measurement data;

[0089] When measuring the non-standard angle of the corner, that is, the actual angle of the corner , according to the geometric symmetry principle, the rotation angle is set to to ensure that the prism measures at a symmetric and reasonable posture under the non-standard angle corner, minimizing the measurement error to the greatest extent;

[0090] The stress distribution of the L-shaped connector is optimized through finite element analysis (FEA). The L-shaped connector is divided into e elements. By calculating the stress and strain of each element, the mechanical properties of the entire structure are analyzed. After optimization, it is ensured that when , the maximum deformation of the L-shaped connector is less than 0.01 mm, thus ensuring the stability and measurement accuracy of the total station prism at the angle ;

[0091] Function 4: Dynamically adjust the posture of the total station prism through the angle compensation function to ensure that the reflection surface is orthogonal to the wall. Differentiated strategies are formulated for the outside corner, inside corner, and non-standard angle, and the mechanical stability of the L-shaped connector is optimized in combination with FEA;

[0092] Step 4: After the measurement preprocessing is completed, measure the wall. Dynamically correct the prism constant of the total station according to the environmental parameters to obtain the corrected prism constant and measure the wall measurement data;

[0093] In Step 4:

[0094] Specifically, the specific method for dynamically correcting the prism constant of the total station based on the environmental parameters is as follows:

[0095] The dynamic correction of the prism constant K adopts the correction formula to obtain the corrected prism constant , where is the preset initial constant of the total station prism, represents the secant function of the target angle , is the geometric projection correction value. The geometric projection correction value is due to the change in the prism angle , which causes the propagation path of light in the prism to change, thus affecting the measured distance. By calculating the product of and , the geometric projection correction value of the prism constant of the total station caused by the geometric projection change is obtained; is the temperature compensation term, is the influence coefficient of temperature on the total station prism constant, is the current ambient temperature, is the reference temperature;

[0096] Based on the calculated prism correction constant is added to the original distance measured by the total station to obtain the wall measurement data;

[0097] Function five: Calculate in real time the influence of temperature on the total station prism constant according to the change of temperature, so as to carry out compensation. Through comprehensive calculation and analysis of three parts, the corrected total station prism constant is obtained for distance measurement, improving the accuracy and reliability of measurement;

[0098] Step five: Refine the wall measurement data, fuse the wall measurement data and eliminate the deviated data, and optimize and generate a report based on the wall measurement data after elimination;

[0099] In step five:

[0100] Specifically, the specific method for refining the wall measurement data is:

[0101] Use the weighted average method to process the measurement values of consecutive P times, and assign different weight coefficients to the P measurement values according to the time series;

[0102] It should be noted that the measurement value closer to the measurement time reflects the current actual situation and is true and effective, so it is given a relatively large weight. For example: the weight of the earliest measurement value is 0.1, and the weight of the latest measurement value is 0.3;

[0103] Based on the obtained consecutive P measurement values, the weighted average measurement value is obtained through the weighted average method;

[0104] Obtain all the weighted average measurement values, and calculate the data standard deviation of the weighted average measurement value data;

[0105] According to the Pauta criterion, the deviation between a single measurement value and the weighted average value is greater than then it is determined that the measurement value is a deviated data, Set to 2mm and adjust flexibly according to the measurement accuracy requirements;

[0106] If a deviated data is detected, the system automatically triggers a retest process to obtain accurate wall measurement data, avoiding errors in subsequent analysis and application caused by measurement errors that are significantly deviated from the true value;

[0107] Specifically, the specific method for optimizing and generating a report based on the wall measurement data after elimination is:

[0108] Directly import the wall measurement data into the BIM software. During the import process, assign attribute tags to the wall measurement data. The attribute tags include but are not limited to: measurement location, measurement time, and measurement accuracy. Through the attribute tags, ensure that the wall measurement data is accurately identified and located in the BIM model;

[0109] Utilize the comparison function built into the BIM software to set the deviation threshold. The system automatically compares the wall measurement data with the corresponding position and dimension information in the design drawings point by point. If the deviation between the measured value and the designed value exceeds the preset deviation threshold range, automatically mark the area where the deviation exceeds the limit and give feedback;

[0110] The technical solution of the embodiment of the present invention is as follows: The upper prism assembly, the middle connection assembly, and the centering rod assembly can be disassembled and combined, which is convenient for carrying and adapting to different measurement scenarios. Through the L-shaped connection assembly and the rotatable connecting piece, the prism can be embedded into the internal and external corners of the room corner, breaking through the limitation that traditional prisms are only applicable to planes, and reducing the measurement error in complex environments; Utilize the direct and inverse piezoelectric effects to monitor and cancel vibrations in real time. Compared with traditional counterweights for passive vibration damping, actively compensate for dynamic interference, significantly improve measurement stability, analyze vibration energy, accurately match the reverse force, and optimize the vibration damping effect; Combine visible light images and depth images to realize multi-dimensional analysis of the geometric features of the wall, provide edge contours, locate key points, fit the wall plane equation, and complementarily improve the model accuracy; Dynamically adjust the attitude of the total station prism through the angle compensation function to ensure that the reflection surface is orthogonal to the wall. Develop differentiated strategies for internal corners, external corners, and non-standard angles, and optimize the mechanical stability of the L-shaped connecting piece in combination with FEA; Calculate the influence of temperature on the total station prism constant in real time according to the change of temperature, and then make compensation. Through the comprehensive calculation and analysis of the three parts, obtain the corrected total station prism constant , which is used for distance measurement to improve the accuracy and reliability of measurement; By dynamically adjusting the time series weight, give priority to the timeliness of recent data, avoid errors caused by data time series, calculate based on the standard deviation of the weighted average, automatically identify and eliminate outliers, trigger the retest mechanism, realize accurate data positioning and traceability through attribute tags, automatically compare the measured value with the designed value, and automatically mark and feedback the area where the limit is exceeded.

[0111] Embodiment 2

[0112] As Figure 2 shown, an automatically adjustable total station prism operating system based on image recognition provided by the embodiment of the present invention specifically includes the following modules:

[0113] Initialization module: Send an initialization signal, the microprocessor self-checks each component, and connects to the total station to establish a data transmission channel;

[0114] Intelligent calibration module: A piezoelectric ceramic damper is integrated at the bottom of the middle rod to suppress external vibrations and utilize the inverse piezoelectric effect to cancel vibrations. The white balance of the image acquisition module is calibrated, the motor drive system is self-checked, and the zero-load reset parameters are loaded;

[0115] Image acquisition module: Acquire the scene image and depth image of the measured wall for calibration inspection;

[0116] Feature analysis module: Based on the acquired scene image, perform edge detection, and the detection algorithm locates the corner points;

[0117] Measurement preprocessing module: Obtain the initial inclination angle, establish an angle compensation function to adjust the prism angle to the target angle, achieve the orthogonality of the reflection surface, set different rotation angles according to the type of wall corner, and optimize the stress distribution of the L-shaped connecting piece through finite element analysis;

[0118] Measurement correction module: Measure the wall, dynamically correct the total station prism constant through environmental parameters to obtain the prism correction constant, and measure the wall measurement data;

[0119] Analysis and generation module: Refinely process the wall measurement data, fuse the wall measurement data and eliminate the deviated data, and optimize and generate a report based on the wall measurement data after elimination.

[0120] The above has described a specific embodiment of the present invention in detail, but the content described is only the preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention; the above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by software simulation of a large amount of collected data to obtain a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation and historical experience and can be adjusted according to the actual situation; the above is only the preferred embodiment of the present invention and does not limit the present invention. Any equal changes and improvements made according to the scope of the present invention application should still fall within the scope covered by the patent of the present invention.

Claims

1. A method for using a total station prism that can be automatically adjusted based on image recognition, characterized in that: The following steps are involved: Install the total station prism and initialize it, calibrate the total station prism through multi-module linkage, analyze the initialization of the total station prism and provide feedback; The total station sends an initialization signal to the total station prism, and the microprocessor performs self-checks on the components of the total station prism to ensure the normal operation of the equipment; searches and connects to the total station and establishes a data transmission channel; The upper prism assembly comprises: a prism and a prism bracket, the prism is rotatably connected to the top of the prism bracket, a prism bracket level is installed on the prism bracket, and a first fixed column is arranged at the bottom of the prism bracket; The middle connecting assembly is an L-shaped connecting assembly, which is convenient for embedding into the inner and outer corners of the room angle. The bottom of the first fixed column is connected to the top of the second fixed column through a rotatable connecting piece. The rotatable connecting piece is used to realize the rotatable adjustment and fixation of the upper prism assembly above the middle connecting assembly. Conversion connecting rods are arranged on both sides of the second fixed column. The centering rod assembly includes: a lower support assembly and a centering rod; The process of multi-module linkage calibration of the total station prism is as follows: The mechanical vibration signal generated by the vibration of the prism middle rod is converted into a vibration electrical signal through piezoelectric ceramics, the time domain signal of the vibration electrical signal is converted into the frequency domain, and the dominant vibration frequency is extracted to calculate the vibration energy; based on the comparison between the obtained vibration energy and the preset vibration energy threshold, the reverse force generated by the piezoelectric ceramics acts on the prism middle rod, and cancels out the force generated by the external vibration; After initialization, the scene image and depth image of the wall are obtained through the image acquisition module, and the plane equation of the wall is obtained by combined analysis, and the wall geometric model is established; Based on the wall geometry model, the reflection surface of the total station prism is orthogonalized, and measurement preprocessing is performed according to the type of wall; After the measurement preprocessing is completed, the wall surface is measured, and the prism constant of the total station is dynamically corrected by the environmental parameters to obtain the prism correction constant and measure the wall surface measurement data; The wall measurement data is processed in a refined manner, the wall measurement data is integrated and the deviated data is eliminated, and a report is generated based on the optimized wall measurement data after elimination.

2. The method for using the total station prism that can be automatically adjusted based on image recognition according to claim 1, characterized in that: The process of combining the analysis to obtain the wall plane equation is: The scene image and depth image of the wall are collected, edge detection is performed and corner points are located, the local plane equation of the wall is constructed, and the least squares fitting algorithm is used to process the point cloud data obtained based on the depth image to obtain the parameters representing the wall plane and determine the wall plane equation.

3. The method for using the total station prism that can be automatically adjusted based on image recognition according to claim 1, characterized in that: The process of establishing the wall geometry model is as follows: Based on the wall plane equation, get the wall normal vector and the horizontal reference vector , the wall angle is obtained by calculation , obtain the wall data in the design drawing to determine the wall boundary, based on the 3D modeling interface, input the wall plane equation, and generate the wall geometry model based on the wall angle, wall boundary and wall plane equation.

4. The method for using the total station prism that can be automatically adjusted based on image recognition according to claim 1, characterized in that: The measurement preprocessing process is as follows: The initial inclination angle of the total station prism is obtained, and the prism angle is adjusted to reach the target angle by establishing an angle compensation function to achieve orthogonalization of the reflection surface. Different rotation angles are set according to the type of wall corner, and the stress distribution of the L-shaped connector is optimized through finite element analysis.

5. The method for using the total station prism that can be automatically adjusted based on image recognition according to claim 1, characterized in that: The process of dynamic correction of the total station prism constant is as follows: The target wall is measured based on measurement preprocessing, the total station prism constant obtained by measurement preprocessing is dynamically corrected according to environmental parameters, and the corrected prism correction constant is calculated using a compensation formula.

6. The method for using the total station prism that can be automatically adjusted based on image recognition according to claim 1, characterized in that: The process of fusing the wall measurement data and eliminating the deviating data is as follows: The weighted average method is used to process continuous measurement values, the data standard deviation is calculated, the deviating data is eliminated according to the Laida criterion, and the re-measurement process is triggered based on the deviating data.

7. The method for using the total station prism that can be automatically adjusted based on image recognition according to claim 1, characterized in that: The process of optimizing and generating reports is as follows: Import the wall measurement data into the BIM software, assign attribute labels, and use the BIM software comparison function to mark the areas where the deviation exceeds the limit and provide feedback.

8. An automatic adjustable total station prism operating system based on image recognition, applied to a method for using an automatic adjustable total station prism based on image recognition as claimed in any one of claims 1 to 7, characterized in that: include: Initialization module: Sends initialization signal, the microprocessor self-checks each component, connects to the total station to establish a data transmission channel; Intelligent calibration module: The piezoelectric ceramic damper at the bottom of the middle pole suppresses external vibration and uses the inverse piezoelectric effect to offset vibration, the image acquisition module white balance calibration, the motor drive system self-checks, and loads the zero point reset parameters; Image acquisition module: collects scene images and depth images of the measurement wall for verification and calibration; Feature analysis module: performs edge detection based on the acquired scene images, and uses detection algorithms to locate corner points; Measurement preprocessing module: obtain the initial inclination angle, establish an angle compensation function to adjust the prism angle to the target angle, realize the orthogonality of the reflection surface, set different rotation angles according to the wall angle type, and optimize the stress distribution of the L-shaped connector through finite element analysis; Measurement correction module: measure the wall surface, dynamically correct the prism constant of the total station through environmental parameters to obtain the prism correction constant and measure the wall surface measurement data; Analysis and generation module: refine the wall measurement data, fuse the wall measurement data and eliminate the deviated data, and generate a report based on the optimized wall measurement data after elimination.

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