A laser measuring method for road and bridge construction

Abstract

This invention discloses a laser measurement method for road and bridge construction, relating to the field of laser measurement technology. The method includes benchmark setup and scene modeling, dual-wavelength refraction compensation data acquisition, occlusion adaptive scanning, vibration disturbance removal, multi-constraint joint calculation, closed-loop construction instruction generation, and audit records. This invention integrates benchmark setup, dual-wavelength refraction compensation, occlusion adaptation, and vibration disturbance removal technologies to achieve high-precision measurement in complex environments. It reduces atmospheric interference through reference optical paths and refractive index gradient calculations, ensures data continuity through backup path switching, eliminates vibration influences by combining inertial measurement, and generates three-dimensional pose results under multiple constraints. Ultimately, it forms a traceable construction instruction and quality evidence chain, significantly improving construction accuracy, safety, and intelligence.

Description

Technical Field

[0001] This invention relates to the field of laser measurement technology, and in particular to a laser measurement method for road and bridge construction. Background Technology

[0002] With the continuous expansion of road and bridge construction, the requirements for construction accuracy and safety are constantly increasing. Traditional total station surveying or single-wavelength laser ranging methods are easily affected by factors such as atmospheric refraction, construction obstructions, and equipment vibration, leading to unstable measurement results or significant deviations. Furthermore, existing methods often lack closed-loop management of the data processing process, failing to achieve end-to-end traceability from benchmark setup to construction command generation, thus limiting the intelligence and auditability of the construction process. Therefore, there is an urgent need for a laser measurement method that can achieve high accuracy, interference resistance, and traceability in complex construction environments to meet the demands of modern bridge construction for real-time accuracy control and safety monitoring.

[0003] Currently, Chinese patent application number CN202310851192.6 discloses a method for measuring the bridge deck alignment using lidar, comprising: S1: setting up lidar scanner measuring points along the longitudinal axis of the bridge; S2: acquiring data scanned by each lidar station, registering and stitching the point cloud data to obtain complete three-dimensional bridge point cloud data; S3: using a pass-through filtering algorithm to remove invalid points and outliers; after obtaining the processed three-dimensional bridge point cloud data, setting a slope threshold to extract the bridge deck point cloud data; using a farthest point sampling algorithm to downsample the obtained bridge deck point cloud data; S4: performing coordinate transformation on the bridge deck point cloud data to obtain the bridge deck alignment. Using a lidar scanner to measure the main cable alignment of a suspension bridge can improve the automation level of bridge alignment measurement, and inspection personnel do not need to set up a large number of observation points on the main cable of the suspension bridge, thus improving inspection efficiency.

[0004] The relevant technologies are difficult to overcome atmospheric refraction, shielding interference and vibration disturbance in complex construction environments and form a traceable closed-loop measurement and control system. Summary of the Invention

[0005] The technical problem solved by this invention is that existing technologies are unable to overcome atmospheric refraction, shielding interference and vibration disturbance in complex construction environments and form a traceable closed-loop measurement and control system.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] A laser measurement method for road and bridge construction includes the following steps:

[0008] Step S1, baseline setup and scene modeling;

[0009] Step S2: Acquisition of dual-wavelength refraction compensation data;

[0010] Step S3, occlusion adaptive scanning;

[0011] Step S4, vibration disturbance stripping;

[0012] Step S5: Joint solution of multiple constraints;

[0013] Step S6: Generation of closed-loop construction instructions and audit records;

[0014] Step S3 includes the following sub-steps:

[0015] Step S301: Based on the construction design model and on-site point cloud analysis, scan the visible field. The analysis combines the drift direction and the time window in the estimation results, and writes the visibility level and drift risk of each path into the coverage report to determine the priority observation path and give the switching threshold.

[0016] Step S302: When occlusion is detected, dynamically switch to the backup measurement path. During the switch, based on the path number and the corrected measurement results, synchronously compensate the distance and angle measurement results of the new path and continue to collect data, and record the correspondence between compensation and switching time.

[0017] Step S303: Identify reflection interference and automatically adjust the laser incident angle or polarization mode. The adjusted result is compared with the measurement dataset after refraction correction. If the difference in the estimated result exceeds the threshold within the time window, it is marked as an interference event and added to the database.

[0018] Preferably, step S1 includes the following sub-steps:

[0019] Step S101: Import the preset construction design model and generate a benchmark layout scheme. The construction design model includes digital design files of bridge alignment, elevation benchmark and segment assembly parameters. The benchmark layout scheme determines the spatial coordinates, installation height, installation method and number of each benchmark point based on the alignment, elevation control points and segment assembly joint opening in the digital design file under the constraints of the visual field analysis results. Output the benchmark list and visual field model.

[0020] Step S102: Deploy active targets according to the reference point list and establish a near-ground reference optical path. The active targets record unique codes, installation orientations and initial coordinate values ​​and register them in the construction design model. The near-ground reference optical path includes reflectors deployed along the bridge deck or catwalk and the spacing between reflectors, reflector heights and path markings, forming a reference observation network and a reference optical path parameter set.

[0021] Step S103: Synchronize the measurement equipment with the inertial measurement unit of the key component in time. Use a unified time source to align the equipment clock with the timestamp of the inertial measurement unit and record the initial attitude, offset and synchronization error limits, and output the initial measurement reference.

[0022] Preferably, step S2 includes the following sub-steps:

[0023] Step S201: Emit dual-wavelength coaxial laser and receive echo signals. The transmission process records the transmission power, transmission time and propagation path number of each wavelength. The reception process records the echo intensity, phase difference and return time corresponding to each wavelength and forms an original laser observation sequence. The original laser observation sequence is matched with the reference point list.

[0024] Step S202: Extract the dual-wavelength echo difference and the near-ground reference optical path signal. Perform quality screening, time alignment, and path number verification on the original laser observation sequence. Compare the echo intensity curve and phase difference sequence corresponding to each wavelength within the same time window. Identify the line-of-sight bending caused by atmospheric refraction based on the intensity variation with distance and the phase difference fluctuation amplitude. Use the return signal of the near-ground reference optical path as the low-refractive gradient baseline to establish the following calculation relationship:

[0025] Let the two wavelengths be respectively and The corresponding wave number is and The path length is The measured phase is and The phase difference is:

[0026] ;

[0027] in, For phase difference, For time, Number the path;

[0028] The path-average refractive index increment is estimated as follows:

[0029] ;

[0030] in, For path-average refractive index increment estimation;

[0031] The refractive index increment of the near-Earth reference optical path Let be the baseline, and let the average height difference between the two paths be . The refractive index gradient is estimated as follows:

[0032] ;

[0033] in, For refractive index gradient estimation;

[0034] Let the centroid offset vector of the echo spot on the image plane be denoted as... The direction unit vector of the centroid offset vector is The lateral drift of the target path relative to the baseline is:

[0035] ;

[0036] Drift direction is ;

[0037] By combining the duration and rate of change within the time window, the trend of refractive index change is determined, and the estimated result of refractive index change is output. The estimated result includes the path average refractive index increment estimate, the refractive index gradient estimate, the lateral drift of the target path relative to the baseline, the drift direction of the lateral drift of the target path relative to the baseline, the time window and the corresponding path number and timestamp.

[0038] Step S203: Convert the refractive index change results into path compensation data, and define:

[0039] The ranging compensation amount is:

[0040] ;

[0041] The angle compensation amount is:

[0042] ;

[0043] in, and The scaling factor is obtained from calibration, and the applicable time window is limited to the time window in the estimation result;

[0044] By binding the path compensation data with the original observation information, the corrected measurement results can be obtained:

[0045] ;

[0046] ;

[0047] in, This is the corrected ranging compensation amount. This is the corrected angle compensation amount. For the original distance measurement, For the original angle measurement;

[0048] Output the measurement dataset after refraction correction.

[0049] Preferably, step S4 includes the following sub-steps:

[0050] Step S401: Obtain inertial measurement unit data from the measuring equipment and the construction hanging basket. The inertial measurement unit data includes triaxial acceleration, triaxial angular velocity and corresponding timestamp information. Read the measurement dataset after refraction correction as laser observation input. Align the inertial measurement unit data and the measurement dataset after refraction correction according to the path number and timestamp.

[0051] Step S402: Establish a multi-rigid-body micro-motion model and separate vibration disturbances. The multi-rigid-body micro-motion model regards the measuring equipment and the hanging basket as coupled rigid bodies. It calculates small displacements and attitude changes through the acceleration and angular velocity of the inertial measurement unit, uses the lateral drift as an indicator of slow-varying external disturbances, and identifies high-frequency vibration components and low-frequency attitude changes by combining timestamp comparison analysis. It outputs a set of static stability parameters, and removes systematic offsets from the set of static stability parameters.

[0052] Step S403: Align the statically stable parameter set with the corrected measurement results, use a unified time source to perform time-series registration of the two types of data, match the observation points in the spatial coordinate system, establish a correspondence between the interference-removed laser measurement results and the original observation sequence, and output the statically stable measurement sequence.

[0053] Preferably, step S5 includes the following sub-steps:

[0054] Step S501: Input the assembly alignment, elevation and torsional constraints into the solver, and load the measurement dataset after refraction correction as the source of observation vectors and weights.

[0055] Step S502: Combine the corrected measurement results with the statically stable measurement sequence to perform multi-constraint solution. The solution process will uniformly match the stable dataset with the statically stable parameter set, check and correct the observation error item by item according to the constraint conditions, and generate a three-dimensional solution result. The solution process records the satisfaction status and correction amount of each constraint and forms a solution log. The refractive index gradient is used to set the observation weight and remove abnormal windows within the time window.

[0056] Step S503: Output the three-dimensional pose and deviation index of the segment. The three-dimensional pose includes translational deviation and rotational deviation. The deviation index includes the numerical difference relative to the design value, the error direction, and a mark indicating whether the allowable threshold is met or exceeded. In the result file, mark the mapping relationship between each result and the path number, time window, and refraction correction parameters used in step S2.

[0057] Preferably, step S6 includes the following sub-steps:

[0058] Step S601: The three-dimensional pose and deviation index are converted into construction instructions for jack lifting, hanging basket advancement and formwork adjustment. The instruction list references the corrected measurement results and fixes the corresponding time window and path number as the conditions for instruction application.

[0059] Step S602: Collect the construction receipt and compare it with the measurement dataset and three-dimensional solution results after refraction correction. Mark the items that meet the requirements and those that do not meet the requirements and output the verification results.

[0060] Step S603: Generate a quality evidence chain and store it as a version snapshot. The evidence chain explicitly records the estimation results, path compensation data, and the measurement dataset after refraction correction, as well as the timestamp, path number, and application location of the call in steps S1 to S5.

[0061] Preferably, the active target in step S102 has an encoding and recognition function. The encoding and recognition function is implemented by an optical encoding element and recognition algorithm built into each active target. After the occlusion is removed, the target is restored to its original position. During the restoration process, the time point when the target is re-identified, the coordinate difference before and after restoration, and the recognition confidence are recorded. The result of the restored positioning is compared with the benchmark observation network.

[0062] Preferably, in step S202, by comparing the intensity difference and phase difference of the dual-wavelength echoes and combining the return signal of the near-ground reference optical path, the refractive index gradient on the measurement path is derived and a refractive correction parameter is generated. The refractive correction parameter is used to correct the laser ranging and angle measurement data, forming a correction record that corresponds one-to-one with the original observation results.

[0063] Preferably, in step S402, the multi-rigid-body micro-motion model uses the acceleration and angular velocity data of the inertial measurement unit to establish a motion description of the coupled rigid body, identifies and separates high-frequency vibration components and low-frequency attitude changes by comparing time series data, records the vibration frequency, amplitude and duration, and outputs a set of filtered static stability parameters.

[0064] The beneficial effects of this invention are as follows: This invention integrates benchmark setup, dual-wavelength refraction compensation, occlusion adaptation, and vibration disturbance removal technologies to achieve high-precision measurement in complex environments. It reduces atmospheric interference by using a reference optical path and refractive index gradient calculation, ensures data continuity by using backup path switching, eliminates vibration effects by combining inertial measurement, and generates three-dimensional pose results under multiple constraints. Finally, it forms a traceable construction instruction and quality evidence chain, which greatly improves construction accuracy, safety, and intelligence. Attached Figure Description

[0065] Figure 1 This is a flowchart illustrating the steps of a laser measurement method for road and bridge construction, as provided in one embodiment of the present invention. Detailed Implementation

[0066] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0067] Example, refer to Figure 1 A laser measurement method for road and bridge construction is provided, comprising the following steps:

[0068] Step S1: Baseline setup and scene modeling.

[0069] Step S2: Acquisition of dual-wavelength refraction compensation data.

[0070] Step S3, occlusion adaptive scanning.

[0071] Step S4, vibration disturbance stripping.

[0072] Step S5: Joint solution of multiple constraints.

[0073] Step S6: Generation of closed-loop construction instructions and audit records.

[0074] This invention integrates benchmark setup, dual-wavelength refraction compensation, occlusion adaptation, and vibration disturbance removal technologies to achieve high-precision measurement in complex environments. It reduces atmospheric interference by using a reference optical path and refractive index gradient calculation, ensures data continuity by using backup path switching, eliminates vibration effects by combining inertial measurement, and generates three-dimensional pose results under multiple constraints. Finally, it forms a traceable construction instruction and quality evidence chain, which greatly improves construction accuracy, safety, and intelligence.

[0075] Step S1 includes the following sub-steps:

[0076] Step S101: Import the preset construction design model and generate a benchmark layout scheme. The construction design model includes digital design files of bridge alignment, elevation benchmark and segment assembly parameters. The benchmark layout scheme determines the spatial coordinates, installation height, installation method and number of each benchmark point based on the alignment, elevation control points and segment assembly joint opening in the digital design file and under the constraints of the visibility analysis results. Output the benchmark list and visibility model.

[0077] Step S101 imports the preset construction design model to generate a benchmark point layout scheme, forming a benchmark point list and a view model containing coordinates, installation methods, and numbers. The effect is to ensure that the benchmark point distribution is scientifically sound and strictly aligned with the construction design requirements, providing design consistency for subsequent observation paths and data calculations.

[0078] Step S102: Deploy active targets according to the benchmark point list and establish a near-ground reference optical path. Record the unique code, installation orientation and initial coordinate value of the active targets and register them in the construction design model. The near-ground reference optical path includes reflectors deployed along the bridge deck or catwalk and the spacing between reflectors, reflector height and path markings, forming a benchmark observation network and a reference optical path parameter set.

[0079] The active target in step S102 has a coding and recognition function. The coding and recognition function is realized by the optical coding element and recognition algorithm built into each active target. After the occlusion is removed, the target is restored to its original position. During the restoration process, the time point when the target is re-identified, the coordinate difference before and after restoration, and the recognition confidence are recorded. The result of the restored positioning is compared with the benchmark observation network.

[0080] Step S102 involves deploying active targets with coded identification capabilities at key locations and establishing a near-ground reference optical path, generating a benchmark observation network and a reference optical path parameter set. The effect is to achieve rapid target identification and localization recovery, and to provide a stable reference signal for refraction compensation and occlusion switching.

[0081] Step S103: Synchronize the measurement equipment with the inertial measurement unit of the key component in time. Use a unified time source to align the equipment clock with the timestamp of the inertial measurement unit and record the initial attitude, offset and synchronization error limits, and output the initial measurement reference.

[0082] Step S103 completes the time synchronization between the measuring equipment and the inertial measurement unit, records the initial attitude, offset, and error limits, and forms the initial measurement reference. The effect is to ensure that all types of observation data are consistent in time and coordinate system, providing spatiotemporal consistency assurance for subsequent compensation, stripping, and calculation.

[0083] Step S1 establishes a benchmark observation network and reference optical path covering the construction area through benchmark deployment and scene modeling, and synchronizes the initial time and attitude benchmarks. This step ensures that subsequent measurement data have unified spatiotemporal constraints, providing a reliable foundation for refraction compensation, occlusion switching, and vibration stripping.

[0084] Step S2 includes the following sub-steps:

[0085] Step S201: Emits dual-wavelength coaxial laser and receives echo signals. During the transmission process, the transmission power, transmission time, and propagation path number of each wavelength are recorded. During the reception process, the echo intensity, phase difference, and return time corresponding to each wavelength are recorded, and an original laser observation sequence is formed. The original laser observation sequence is matched with the list of reference points.

[0086] Step S201 involves acquiring echo intensity, phase difference, and return time through laser emission and echo reception at two different wavelengths, forming the original laser observation sequence corresponding to the benchmark list. The effect is to provide complete dual-wavelength comparison data for subsequent refraction analysis.

[0087] Step S202: Extract the dual-wavelength echo difference and the near-ground reference optical path signal. Perform quality screening, time alignment, and path number verification on the original laser observation sequence. Compare the echo intensity curve and phase difference sequence corresponding to each wavelength within the same time window. Identify the line-of-sight bending caused by atmospheric refraction based on the intensity variation with distance and the phase difference fluctuation amplitude. Use the return signal of the near-ground reference optical path as the low-refractive gradient baseline to establish the following calculation relationship:

[0088] Let the two wavelengths be respectively and The corresponding wave number is and The path length is The measured phase is and The phase difference is:

[0089] ;

[0090] in, For phase difference, For time, This is the path number.

[0091] The path-average refractive index increment is estimated as follows:

[0092] ;

[0093] in, This is an estimate of the path-average refractive index increment.

[0094] The refractive index increment of the near-Earth reference optical path Let be the baseline, and let the average height difference between the two paths be . The refractive index gradient is estimated as follows:

[0095] ;

[0096] in, This is for estimating the refractive index gradient.

[0097] Let the centroid offset vector of the echo spot on the image plane be denoted as... The direction unit vector of the centroid offset vector is The lateral drift of the target path relative to the baseline is:

[0098] ;

[0099] Drift direction is .

[0100] By combining the duration and rate of change within the time window, the trend of refractive index change is determined, and the estimated result of refractive index change is output. The estimated result includes the path average refractive index increment estimate, the refractive index gradient estimate, the lateral drift of the target path relative to the baseline, the drift direction of the lateral drift of the target path relative to the baseline, the time window and the corresponding path number and timestamp.

[0101] Step S202 compares the intensity difference and phase difference of the dual-wavelength echoes, combines the return signal from the near-ground reference optical path, derives the refractive index gradient on the measurement path, and generates refractive correction parameters. The refractive correction parameters are used to correct the laser ranging and angle measurement data, forming a correction record that corresponds one-to-one with the original observation results.

[0102] Step S202 compares the dual-wavelength echo with the near-ground reference optical path signal to derive the range, trend, and path correspondence of refractive index changes, and calculates the drift amount and direction. The effect is to accurately identify and quantify atmospheric refraction interference, providing parameter basis for generating compensation quantities.

[0103] Step S203: Convert the refractive index change results into path compensation data, and define:

[0104] The ranging compensation amount is:

[0105] ;

[0106] The angle compensation amount is:

[0107] ;

[0108] in, and The scaling factor is obtained from calibration, and the applicable time window is limited to the time window in the estimation results.

[0109] By binding the path compensation data with the original observation information, the corrected measurement results can be obtained:

[0110] ;

[0111] ;

[0112] in, This is the corrected ranging compensation amount. This is the corrected angle compensation amount. For the original distance measurement, This is the original angle measurement.

[0113] Output the measurement dataset after refraction correction.

[0114] Step S203 converts the refractive index change results into correction values ​​for distance and angle measurements, generates a corrected measurement dataset, and stores it in the database for subsequent steps. The effect is to generate refractive compensation results that correspond one-to-one with the original observations, ensuring data traceability and direct applicability for calculations.

[0115] Step S2 acquires dual-wavelength refraction compensation data to obtain the real-time impact of atmospheric refraction on laser transmission and converts refractive index changes into path compensation data. This step ensures that the measurement results are refractively corrected, providing stable and reliable data input and laying the foundation for occlusion handling, vibration stripping, and multi-constraint solutions.

[0116] Step S3 includes the following sub-steps:

[0117] Step S301: Based on the construction design model and on-site point cloud analysis, scan the visible field. The analysis combines the drift direction and the time window in the estimation results, and writes the visibility level and drift risk of each path into the coverage report to determine the priority observation path and give the switching threshold.

[0118] Step S301 generates a visibility coverage report based on the construction design model and on-site point cloud, marking path visibility and risk levels. The effect is to identify potential occlusion risks in advance, optimize observation path selection, and improve the success rate and coverage of measurement tasks.

[0119] Step S302: When an obstruction is detected, the system dynamically switches to the backup measurement path. During the switch, the distance and angle measurement results of the new path are synchronously compensated based on the path number and the corrected measurement results before the data acquisition continues. The corresponding relationship between the compensation and the switch time is recorded.

[0120] Step S302 automatically switches to the backup measurement path when occlusion occurs, inheriting the refraction compensation parameters to achieve seamless connection. This ensures that measurement data is not interrupted by occlusion, guaranteeing observation continuity and data integrity.

[0121] Step S303: Identify reflection interference and automatically adjust the laser incident angle or polarization mode. The adjusted result is compared with the measurement dataset after refraction correction. If the difference in the estimated result exceeds the threshold within the time window, it is marked as an interference event and added to the database.

[0122] Step S303 identifies reflection interference characteristics and automatically adjusts the laser incident angle or polarization mode, binding the adjustment parameters with the interference information. The effect is to effectively suppress measurement errors caused by reflection and output a stable measurement dataset for subsequent processing.

[0123] Step S3 employs occlusion-adaptive scanning to dynamically identify and handle occlusion and interference during construction, enabling real-time switching of the measurement path and ensuring signal quality. This step ensures the continuity and stability of measurement data in complex environments, providing complete and reliable input for subsequent data processing.

[0124] Step S4 includes the following sub-steps:

[0125] Step S401: Obtain inertial measurement unit data from the measuring equipment and the construction hanging basket. The inertial measurement unit data includes triaxial acceleration, triaxial angular velocity and corresponding timestamp information. Read the measurement dataset after refraction correction as the laser observation input. Align the inertial measurement unit data and the measurement dataset after refraction correction according to the path number and timestamp.

[0126] Step S401 acquires inertial measurement unit data from the measuring equipment and the construction formwork, recording acceleration, angular velocity, and timestamps. The effect is to capture the dynamic state during construction, providing complete input for subsequent vibration modeling.

[0127] Step S402: Establish a multi-rigid-body micro-motion model and separate vibration disturbances. The multi-rigid-body micro-motion model treats the measuring equipment and the hanging basket as coupled rigid bodies. It calculates small displacements and attitude changes through the acceleration and angular velocity of the inertial measurement unit. The lateral drift is used as an indicator of slow-varying external disturbances. The high-frequency vibration components and low-frequency attitude changes are identified by combining timestamp comparison analysis. The static stability parameter set is output, and systematic offsets are removed from the static stability parameter set.

[0128] In step S402, the multi-rigid-body micro-motion model uses the acceleration and angular velocity data of the inertial measurement unit to establish a motion description of the coupled rigid body. By comparing time series data, it identifies and separates high-frequency vibration components and low-frequency attitude changes, records the vibration frequency, amplitude and duration, and outputs a set of filtered static stability parameters.

[0129] Step S402 establishes a multi-rigid-body micro-motion model, separates high-frequency vibration components from low-frequency attitude changes, and outputs a set of static stability parameters. The effect is to eliminate system disturbances caused by environmental vibrations and structural swaying, while retaining stability information that reflects the actual position of the components.

[0130] Step S403: Align the statically stable parameter set with the corrected measurement results, use a unified time source to perform time-series registration of the two types of data, match the observation points in the spatial coordinate system, establish a correspondence between the interference-removed laser measurement results and the original observation sequence, and output the statically stable measurement sequence.

[0131] Step S403 aligns the statically stable parameters with the laser observation results, generating a corrected measurement sequence in a unified time and coordinate system. The effect is to create stable measurement data corrected for dynamic disturbances, serving as reliable input for multi-constraint solutions.

[0132] Step S4 separates the vibration and attitude changes of the hanging basket and equipment in the construction environment from laser observations through vibration disturbance stripping, obtaining stable static measurement results. This step ensures that the measurement data remains reliable in dynamic construction environments and provides interference-free observation input for accurate calculations.

[0133] Step S5 includes the following sub-steps:

[0134] Step S501: Input the assembly alignment, elevation, and torsional constraints into the solver, and load the measurement dataset after refraction correction as the source of observation vectors and weights.

[0135] Step S501 inputs design constraints such as assembly alignment, elevation, and torsion into the solver and correlates them with calibration data in the measurement database. This ensures the solution process is constrained by design boundary conditions, preventing results from deviating from the engineering objectives.

[0136] Step S502: Combine the corrected measurement results with the statically stable measurement sequence to perform multi-constraint solution. In the solution process, the stable dataset and the statically stable parameter set are uniformly matched. The observation error is checked and corrected item by item according to the constraint conditions to generate three-dimensional solution results. In the solution process, the satisfaction status and correction amount of each constraint are recorded and a solution log is formed. The refractive index gradient is used to set the observation weight and remove abnormal windows within the time window.

[0137] Step S502 combines the refraction-compensated measurement data with the static stability parameter set for unified calculation, verifying and correcting observation errors item by item. The effect is to effectively eliminate systematic deviations caused by refraction and vibration, ensuring the calculation results meet multiple constraints.

[0138] Step S503: Output the three-dimensional pose and deviation index of the segment. The three-dimensional pose includes translational deviation and rotational deviation. The deviation index includes the numerical difference relative to the design value, the error direction, and a mark indicating whether the allowable threshold is met or exceeded. In the result file, mark the mapping relationship between each result and the path number, time window, and refraction correction parameters used in step S2.

[0139] Step S503 outputs the segment's three-dimensional pose and deviation indices, and records the differences from the design values. The result is a file that can be directly used for construction control, along with a solution log to facilitate tracking the satisfaction of each constraint.

[0140] Step S5, through multi-constraint joint solution, comprehensively matches the refraction compensation results, dynamic disturbance correction data, and construction design constraints to generate three-dimensional pose and deviation indices that meet construction control requirements. This step achieves accurate conversion from observation data to engineering control parameters and is a crucial step in ensuring construction quality and structural safety.

[0141] Step S6 includes the following sub-steps:

[0142] Step S601: The three-dimensional pose and deviation index are converted into construction instructions for jack lifting, hanging basket advancement and formwork adjustment. The instruction list references the corrected measurement results and fixes the corresponding time window and path number as the conditions for instruction application.

[0143] Step S601 converts the positional deviation into construction instructions for jack lifting, formwork advancement, and template adjustment, specifying the equipment number, adjustment range, and time window. The effect is to transform abstract calculation data into directly executable operation instructions, achieving a precise mapping from data to construction actions.

[0144] Step S602: Collect the construction receipt and compare it with the measurement dataset and three-dimensional calculation results after refraction correction. Mark the items that meet the requirements and those that do not, and output the verification results.

[0145] Step S602 involves collecting construction feedback receipts and comparing them with the calculation results, recording the conforming and non-conforming items. The purpose is to verify whether the construction was carried out according to instructions, promptly identify and correct deviations, and ensure construction quality.

[0146] Step S603: Generate a quality evidence chain and store it as a version snapshot. The evidence chain explicitly records the estimation results, path compensation data, and the measurement dataset after refraction correction, as well as the timestamp, path number, and application location of the call in steps S1 to S5.

[0147] Step S603 generates a quality evidence chain from data processing, calculation, construction instructions, and receipts, and stores it as a version snapshot. The effect is to establish a traceable audit system, ensuring that every step of data retrieval, modification, and execution is recorded, which can be used for later quality review and accountability.

[0148] Step S6 generates closed-loop construction instructions and audit records, transforming the calculation results into executable construction operation instructions, and combines this with construction receipts to achieve comparison and evidence chain storage. This step ensures a closed loop throughout the entire process of measurement, calculation, execution, and verification, making the construction process controllable and traceable.

[0149] This invention introduces a pre-set construction design model and active target to establish a benchmark observation network and reference optical path, providing a unified spatiotemporal benchmark for subsequent measurements. By comparing dual-wavelength observation with the reference optical path, the refractive index gradient is derived and path compensation data is generated, significantly reducing atmospheric refraction errors. When obstruction occurs, a backup path can be automatically switched, and refraction correction parameters are inherited to ensure the continuity of measurement data. By fusing inertial measurement unit data through a multi-rigid-body micro-motion model, the invention effectively distinguishes between slowly varying atmospheric conditions and structural vibrations, achieving vibration separation and static stability measurement. By using multi-constraint joint calculation, refraction compensation and static stability observation are combined with construction design constraints to generate three-dimensional results that meet the requirements of alignment, elevation, and torsion control. The measurement results are directly converted into construction instructions and form a quality evidence chain with the construction receipt, achieving full traceability from data acquisition to construction execution.

[0150] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0151] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A laser measurement method for road and bridge construction, characterized in that, Includes the following steps: Step S1, baseline setup and scene modeling; Step S2: Acquisition of dual-wavelength refraction compensation data; Step S3, occlusion adaptive scanning; Step S4, vibration disturbance stripping; Step S5: Joint solution of multiple constraints; Step S6: Generation of closed-loop construction instructions and audit records; Step S3 includes the following sub-steps: Step S301: Based on the construction design model and on-site point cloud analysis, scan the visible field. The analysis combines the drift direction and the time window in the estimation results, and writes the visibility level and drift risk of each path into the coverage report to determine the priority observation path and give the switching threshold. Step S302: When an obstruction is detected, the system dynamically switches to the backup measurement path. During the switch, the system performs synchronous compensation on the distance and angle measurement results of the new path based on the path number and the corrected measurement results before continuing to collect data. The system also records the correspondence between the compensation and the switch time. Step S303: Identify reflection interference and automatically adjust the laser incident angle or polarization mode. The adjusted result is compared with the measurement dataset after refraction correction. If the difference in the estimated result exceeds the threshold within the time window, it is marked as an interference event and added to the database.

2. The laser measurement method for road and bridge construction as described in claim 1, characterized in that, Step S1 includes the following sub-steps: Step S101: Import the preset construction design model and generate a benchmark layout scheme. The construction design model includes digital design files of bridge alignment, elevation benchmark and segment assembly parameters. The benchmark layout scheme determines the spatial coordinates, installation height, installation method and number of each benchmark point based on the alignment, elevation control points and segment assembly joint opening in the digital design file under the constraints of the visual field analysis results. Output the benchmark list and visual field model. Step S102: Deploy active targets according to the reference point list and establish a near-ground reference optical path. The active targets record unique codes, installation orientations and initial coordinate values ​​and register them in the construction design model. The near-ground reference optical path includes reflectors deployed along the bridge deck or catwalk and the spacing between reflectors, reflector heights and path markings, forming a reference observation network and a reference optical path parameter set. Step S103: Synchronize the measurement equipment with the inertial measurement unit of the key component in time. Use a unified time source to align the equipment clock with the timestamp of the inertial measurement unit and record the initial attitude, offset and synchronization error limits, and output the initial measurement reference.

3. The laser measurement method for road and bridge construction as described in claim 2, characterized in that, Step S2 includes the following sub-steps: Step S201: Emit dual-wavelength coaxial laser and receive echo signals. The transmission process records the transmission power, transmission time and propagation path number of each wavelength. The reception process records the echo intensity, phase difference and return time corresponding to each wavelength and forms an original laser observation sequence. The original laser observation sequence is matched with the reference point list. Step S202: Extract the dual-wavelength echo difference and the near-ground reference optical path signal. Perform quality screening, time alignment, and path number verification on the original laser observation sequence. Compare the echo intensity curve and phase difference sequence corresponding to each wavelength within the same time window. Identify the line-of-sight bending caused by atmospheric refraction based on the intensity variation with distance and the phase difference fluctuation amplitude. Use the return signal of the near-ground reference optical path as the low-refractive gradient baseline to establish the following calculation relationship: Let the two wavelengths be respectively and The corresponding wave number is and The path length is The measured phase is and The phase difference is: ； in, For phase difference, For time, Number the path; The path-average refractive index increment is estimated as follows: ； in, For path-average refractive index increment estimation; The refractive index increment of the near-Earth reference optical path Let be the baseline, and let the average height difference between the two paths be . The refractive index gradient is estimated as follows: ； in, For refractive index gradient estimation; Let the centroid offset vector of the echo spot on the image plane be denoted as... The direction unit vector of the centroid offset vector is The lateral drift of the target path relative to the baseline is: ； Drift direction is ; By combining the duration and rate of change within the time window, the trend of refractive index change is determined, and the estimated result of refractive index change is output. The estimated result includes the path average refractive index increment estimate, the refractive index gradient estimate, the lateral drift of the target path relative to the baseline, the drift direction of the lateral drift of the target path relative to the baseline, the time window and the corresponding path number and timestamp. Step S203: Convert the refractive index change results into path compensation data, and define: The ranging compensation amount is: ； The angle compensation amount is: ； in, and The scaling factor is obtained from calibration, and the applicable time window is limited to the time window in the estimation result; By binding the path compensation data with the original observation information, the corrected measurement results can be obtained: ； ； in, This is the corrected ranging compensation amount. This is the corrected angle compensation amount. For the original distance measurement, For the original angle measurement; Output the measurement dataset after refraction correction.

4. The laser measurement method for road and bridge construction as described in claim 3, characterized in that, Step S4 includes the following sub-steps: Step S401: Obtain inertial measurement unit data from the measuring equipment and the construction hanging basket. The inertial measurement unit data includes triaxial acceleration, triaxial angular velocity and corresponding timestamp information. Read the measurement dataset after refraction correction as laser observation input. Align the inertial measurement unit data and the measurement dataset after refraction correction according to the path number and timestamp. Step S402: Establish a multi-rigid-body micro-motion model and separate vibration disturbances. The multi-rigid-body micro-motion model regards the measuring equipment and the hanging basket as coupled rigid bodies. It calculates small displacements and attitude changes through the acceleration and angular velocity of the inertial measurement unit, uses the lateral drift as an indicator of slow-varying external disturbances, and identifies high-frequency vibration components and low-frequency attitude changes by combining timestamp comparison analysis. It outputs a set of static stability parameters, and removes systematic offsets from the set of static stability parameters. Step S403: Align the statically stable parameter set with the corrected measurement results, use a unified time source to perform time-series registration of the two types of data, match the observation points in the spatial coordinate system, establish a correspondence between the interference-removed laser measurement results and the original observation sequence, and output the statically stable measurement sequence.

5. The laser measurement method for road and bridge construction as described in claim 4, characterized in that, Step S5 includes the following sub-steps: Step S501: Input the assembly alignment, elevation and torsional constraints into the solver, and load the measurement dataset after refraction correction as the source of observation vectors and weights. Step S502: Combine the corrected measurement results with the statically stable measurement sequence to perform multi-constraint solution. The solution process will uniformly match the stable dataset with the statically stable parameter set, check and correct the observation error item by item according to the constraint conditions, and generate a three-dimensional solution result. The solution process records the satisfaction status and correction amount of each constraint and forms a solution log. The refractive index gradient is used to set the observation weight and remove abnormal windows within the time window. Step S503: Output the three-dimensional pose and deviation index of the segment. The three-dimensional pose includes translational deviation and rotational deviation. The deviation index includes the numerical difference relative to the design value, the error direction, and a mark indicating whether the allowable threshold is met or exceeded. In the result file, mark the mapping relationship between each result and the path number, time window, and refraction correction parameters used in step S2.

6. The laser measurement method for road and bridge construction as described in claim 5, characterized in that, Step S6 includes the following sub-steps: Step S601: The three-dimensional pose and deviation index are converted into construction instructions for jack lifting, hanging basket advancement and formwork adjustment. The instruction list references the corrected measurement results and fixes the corresponding time window and path number as the conditions for instruction application. Step S602: Collect the construction receipt and compare it with the measurement dataset and three-dimensional solution results after refraction correction. Mark the items that meet the requirements and those that do not meet the requirements and output the verification results. Step S603: Generate a quality evidence chain and store it as a version snapshot. The evidence chain explicitly records the estimation results, path compensation data, and the measurement dataset after refraction correction, as well as the timestamp, path number, and application location of the call in steps S1 to S5.

7. The laser measurement method for road and bridge construction as described in claim 6, characterized in that, The active target in step S102 has an encoding and recognition function. The encoding and recognition function is realized by the optical encoding element and recognition algorithm built into each active target. After the occlusion is removed, the target is restored to its original position. During the restoration process, the time point when the target is re-identified, the coordinate difference before and after restoration, and the recognition confidence are recorded. The result of the restored positioning is compared with the benchmark observation network.

8. The laser measurement method for road and bridge construction as described in claim 7, characterized in that, Step S202 compares the intensity difference and phase difference of the dual-wavelength echoes, combines the return signal from the near-ground reference optical path, derives the refractive index gradient on the measurement path, and generates refractive correction parameters. These refractive correction parameters are used to correct the laser ranging and angle measurement data, forming a correction record that corresponds one-to-one with the original observation results.

9. The laser measurement method for road and bridge construction as described in claim 8, characterized in that, The multi-rigid-body micro-motion model in step S402 uses the acceleration and angular velocity data of the inertial measurement unit to establish a motion description of the coupled rigid body. By comparing time series data, it identifies and separates high-frequency vibration components and low-frequency attitude changes, records the vibration frequency, amplitude and duration, and outputs a set of filtered static stability parameters.

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