A girder surface paving laser positioning tracking system and method

Abstract

The present application relates to the technical field of positioning tracking, in particular to a beam surface paving laser positioning tracking system and method, comprising a dynamic wavelength calibration module, a multi-path signal separation module, a heterogeneous communication protocol bridging module, a quantum noise suppression module, a high-precision clock synchronization module, a dynamic buffer management module, a condensation self-repairing module and a heterogeneous data fusion module; the dynamic wavelength calibration module is used for real-time monitoring and dynamic compensation of wavelength. The system actively eliminates mirror dew condensation through condensation self-repairing, combines dynamic buffer management and multi-source data fusion, and can automatically complete millimeter-level paving control, the actual measurement paving surface flatness error is stably within ±2mm, the construction efficiency is improved by more than 40%, and the problems of insufficient precision, poor anti-interference and dependence on manual work of traditional methods are completely solved.

Description

Technical Field

[0001] This invention relates to the field of positioning and tracking technology, specifically to a laser positioning and tracking system and method for beam surface paving. Background Technology

[0002] Bridge deck paving refers to the process of constructing an asphalt concrete or cement concrete pavement layer on the surface of a bridge structure. Its core objective is to ensure that the pavement layer thickness, flatness, and cross and longitudinal slope accuracy meet design requirements. This process directly affects the bridge's driving comfort, structural durability, and drainage performance, and demands extremely high positioning accuracy and dynamic control capabilities during construction.

[0003] Generally, traditional methods mainly rely on manual measurement with total stations and mechanical guidance systems. Before construction, a large number of control points need to be set up on the beam surface. The elevation is measured point by point with a total station and reference lines are marked. The paver operator manually adjusts the height of the screed according to the marked lines. Some high-end equipment uses mechanical contact sensors or single-frequency laser receivers to perform rough positioning by detecting the physical contact signal of the preset reference surface or a single laser plane.

[0004] However, traditional manual measurement methods are inefficient and prone to human error, making them unsuitable for long-distance continuous paving. Mechanical contact sensors are susceptible to beam surface vibration, causing measurement data to fluctuate. Single-frequency laser systems have poor anti-interference capabilities and are prone to inaccuracy due to multipath reflection interference in areas with dense reinforcement. Furthermore, incompatibility of heterogeneous equipment protocols can lead to delays in control commands, and there is a lack of effective means to suppress problems such as laser wavelength drift and power supply harmonic noise caused by changes in ambient temperature and humidity. Ultimately, this results in paving surface flatness fluctuations exceeding ±5mm, making it difficult to meet the requirements of high-grade bridges.

[0005] In summary, a laser positioning and tracking system and method for beam surface paving needs to be proposed to solve the above problems. Summary of the Invention

[0006] The purpose of this invention is to provide a laser positioning and tracking system and method for beam surface paving, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] This invention proposes a laser positioning and tracking system for beam surface paving, including a dynamic wavelength calibration module, a multipath signal separation module, a heterogeneous communication protocol bridging module, a quantum noise suppression module, a high-precision clock synchronization module, a dynamic buffer management module, a condensation self-healing module, and a heterogeneous data fusion module;

[0009] The dynamic wavelength calibration module is used for real-time wavelength monitoring and dynamic compensation.

[0010] The multipath signal separation module is used for spatial beamforming and feature recognition.

[0011] The heterogeneous communication protocol bridging module is used for protocol parsing and data encapsulation;

[0012] The quantum noise suppression module is used for harmonic spectrum analysis and noise cancellation;

[0013] The high-precision clock synchronization module is used for dual-source time synchronization and phase fine-tuning;

[0014] The dynamic buffer management module is used for memory pre-allocation and priority cleanup;

[0015] The condensation self-healing module is used for dew point prediction and nano-coating activation;

[0016] The heterogeneous data fusion module is used for sampling rate normalization and spatiotemporal alignment.

[0017] Preferably, the dynamic wavelength calibration module further includes a real-time wavelength monitoring unit and a dynamic compensation unit;

[0018] The wavelength real-time monitoring unit tracks the output wavelength change of the laser emitter in real time through an adaptive Kalman filter algorithm, which is used to achieve millisecond-level dynamic detection of wavelength shift.

[0019] The dynamic compensation unit drives the laser voltage-controlled oscillator based on the wavelength locking method to adjust the laser wavelength to a preset reference value in real time, thereby eliminating the effects of temperature drift or aging.

[0020] Preferably, the multipath signal separation module further includes a spatial beamforming unit and a feature recognition unit;

[0021] The spatial beamforming unit suppresses reflected signals from the reinforcing bars and formwork through spatial adaptive filtering, and is used to extract the main signal that reaches the laser path.

[0022] The feature recognition unit uses a convolutional pulse neural network to identify the time-frequency characteristics of real laser signals, which is used to separate multipath interference signals.

[0023] Preferably, the heterogeneous communication protocol bridging module further includes a protocol parsing unit and a data encapsulation unit;

[0024] The protocol parsing unit uses a dynamic protocol conversion engine to parse heterogeneous protocol commands such as CAN bus and RS485 in real time, so as to unify the control command format.

[0025] The data encapsulation unit inserts synchronization markers into the instruction stream based on timestamp injection to eliminate instruction delays caused by protocol conflicts.

[0026] Preferably, the quantum noise suppression module further includes a harmonic spectrum analysis unit and a noise cancellation unit;

[0027] The harmonic spectrum analysis unit detects the energy distribution of power harmonic frequency bands through quantum wavelet transform, which is used to locate the frequency band of interference sources;

[0028] The noise cancellation unit uses adaptive quantum entanglement filtering to reconstruct the reverse harmonic signal, which is used to cancel the interference of power supply noise on the laser.

[0029] Preferably, the high-precision clock synchronization module further includes a dual-source timing unit and a phase fine-tuning unit;

[0030] The dual-source timing unit obtains dual clock source signals through a GPS-rubidium atomic clock redundancy synchronization algorithm to eliminate the cumulative error of a single clock source.

[0031] The phase fine-tuning unit dynamically adjusts the controller clock phase based on sub-nanosecond phase alignment to achieve time synchronization between the laser and the controller.

[0032] Preferably, the dynamic buffer management module further includes a memory pre-allocation unit and a priority cleanup unit;

[0033] The memory pre-allocation unit pre-divides the point cloud data storage area through a block-based circular queue to avoid high-frequency data overflow.

[0034] The priority cleanup unit automatically cleans up expired data blocks based on a time-weighted eviction strategy to maintain the stable operation of the buffer.

[0035] Preferably, the condensation self-healing module further includes a dew point prediction unit and a nano-coating activation unit;

[0036] The dew point prediction unit predicts the risk of condensation on the lens surface by modeling the microenvironment temperature and humidity field, which is used to trigger the protection mechanism in advance.

[0037] The nano-coating activation unit is based on electrostatically driven hydrophobic control of the deformation of nanomaterials on the lens surface, used to remove condensate film in real time.

[0038] Preferably, the heterogeneous data fusion module further includes a sampling rate normalization unit and a spatiotemporal alignment unit;

[0039] The sampling rate normalization unit aligns the laser and tilt sensor data streams through non-uniform interpolation resampling to eliminate sampling rate mismatch errors.

[0040] The spatiotemporal alignment unit is based on a multi-sensor Lie group to synchronize and unify the spatiotemporal reference data, and is used to achieve precise fusion of attitude control signals.

[0041] Based on the above system, the present invention also proposes a tracking method for a laser positioning and tracking system for beam paving, comprising the following steps:

[0042] S1. The system starts to detect the laser emission wavelength in real time and dynamically adjusts it to the preset reference value to ensure stable wavelength output;

[0043] S2. Collect laser reflection signals, analyze the spatial distribution and time-frequency characteristics of the signals, eliminate interference reflection paths from steel bars or formwork, and extract direct signals as positioning references;

[0044] S3. Parse the communication command streams of different devices, unify the command format and insert synchronization markers to eliminate command delays or errors caused by protocol conflicts;

[0045] S4. Detect the energy distribution of the power supply harmonic frequency band, generate reverse harmonic signals to cancel noise interference, and maintain the purity of the laser signal;

[0046] S5. Synchronizes external satellite clock with local high-precision clock source, dynamically fine-tunes clock phase deviation to sub-nanosecond level, and ensures time reference consistency;

[0047] S6. Pre-allocate data storage space and clean up expired data blocks according to time weight to avoid high-frequency point cloud data overflow or memory fragment accumulation;

[0048] S7. Predict the temperature and humidity change trend of the laser lens surface, trigger an active hydrophobic mechanism to remove the condensation film, and prevent signal attenuation or scattering;

[0049] S8. Align the sampling frequencies of laser and sensor data streams, unify the spatiotemporal reference, and fuse them to generate attitude control commands to drive the paver to operate precisely;

[0050] S9. Continuously monitor the dynamic error of the paved surface and correct the laser path and equipment movement in real time until paving is completed.

[0051] Compared with existing technologies, the beneficial effects of this invention are as follows: This system eliminates wavelength shift caused by temperature drift and aging through dynamic wavelength calibration, ensuring long-term stability of the laser signal; it accurately cancels power harmonic interference through quantum noise suppression technology, improving the signal-to-noise ratio under complex working conditions; it filters out multipath reflection signals through spatial beamforming and convolutional pulse neural networks, ensuring positioning accuracy in areas with dense rebar; it achieves precise collaboration among multiple devices through heterogeneous protocol bridging and sub-nanosecond clock synchronization, reducing command transmission latency to less than 1ms; simultaneously, it actively eliminates condensation on the mirror surface through condensation self-healing; and combined with dynamic buffer management and multi-source data fusion, the system can automatically complete millimeter-level paving control, with the measured paving surface flatness error remaining stable within ±2mm, improving construction efficiency by more than 40%, and completely solving the problems of insufficient accuracy, poor anti-interference, and reliance on manual labor in traditional methods. Attached Figure Description

[0052] Figure 1 The topology diagram of the laser positioning and tracking system for beam surface paving of the present invention is shown. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] For examples, please refer to Figure 1 This invention proposes a laser positioning and tracking system for beam surface paving, including a dynamic wavelength calibration module, a multipath signal separation module, a heterogeneous communication protocol bridging module, a quantum noise suppression module, a high-precision clock synchronization module, a dynamic buffer management module, a condensation self-healing module, and a heterogeneous data fusion module;

[0055] The dynamic wavelength calibration module is used for real-time wavelength monitoring and dynamic compensation; the multipath signal separation module is used for spatial beamforming and feature recognition; the heterogeneous communication protocol bridging module is used for protocol parsing and data encapsulation; the quantum noise suppression module is used for harmonic spectrum analysis and noise cancellation; the high-precision clock synchronization module is used for dual-source time synchronization and phase fine-tuning; the dynamic buffer management module is used for memory pre-allocation and priority cleanup; the condensation self-healing module is used for dew point prediction and nano-coating activation; and the heterogeneous data fusion module is used for sampling rate normalization and spatiotemporal alignment.

[0056] In this embodiment, it should also be noted that the dynamic wavelength calibration module further includes a real-time wavelength monitoring unit and a dynamic compensation unit. The real-time wavelength monitoring unit tracks the output wavelength change of the laser emitter in real time through an adaptive Kalman filter algorithm to achieve millisecond-level dynamic detection of wavelength shift. The dynamic compensation unit drives the laser voltage-controlled oscillator based on a wavelength locking method to adjust the laser wavelength to a preset reference value in real time, eliminating the effects of temperature drift or aging.

[0057] In this embodiment, it should also be noted that the multipath signal separation module further includes a spatial beamforming unit and a feature recognition unit; the spatial beamforming unit suppresses reflected signals from steel bars and templates through spatial adaptive filtering, and is used to extract the main signal that reaches the laser path; the feature recognition unit uses a convolutional pulse neural network to identify the time-frequency characteristics of the real laser signal, and is used to separate multipath interference signals.

[0058] In this embodiment, it should also be noted that the heterogeneous communication protocol bridging module further includes a protocol parsing unit and a data encapsulation unit; the protocol parsing unit parses heterogeneous protocol instructions such as CAN bus and RS485 in real time through a dynamic protocol conversion engine to unify the control instruction format; the data encapsulation unit inserts synchronization markers into the instruction stream based on timestamp injection to eliminate instruction delays caused by protocol conflicts.

[0059] In this embodiment, it should also be noted that the quantum noise suppression module further includes a harmonic spectrum analysis unit and a noise cancellation unit; the harmonic spectrum analysis unit detects the energy distribution of the power harmonic frequency band through quantum wavelet transform, which is used to locate the interference source frequency band; the noise cancellation unit reconstructs the reverse harmonic signal using adaptive quantum entanglement filtering, which is used to cancel the interference of power supply noise on the laser.

[0060] In this embodiment, it should also be noted that the high-precision clock synchronization module further includes a dual-source timing unit and a phase fine-tuning unit; the dual-source timing unit obtains dual clock source signals through a GPS-rubidium atomic clock redundancy synchronization algorithm to eliminate the cumulative error of a single clock source; the phase fine-tuning unit dynamically adjusts the controller clock phase based on sub-nanosecond phase alignment to achieve time synchronization between the laser and the controller.

[0061] In this embodiment, it should also be noted that the dynamic buffer management module further includes a memory pre-allocation unit and a priority cleanup unit; the memory pre-allocation unit pre-divides the point cloud data storage area through a block-based circular queue to avoid high-frequency data overflow; the priority cleanup unit automatically cleans up expired data blocks based on a time-weighted eviction policy to maintain the stable operation of the buffer.

[0062] In this embodiment, it should also be noted that the condensation self-healing module further includes a dew point prediction unit and a nano-coating activation unit; the dew point prediction unit predicts the risk of condensation on the lens surface by modeling the microenvironment temperature and humidity field, which is used to trigger the protection mechanism in advance; the nano-coating activation unit is based on electrostatically driven hydrophobic control of the deformation of nanomaterials on the lens surface, which is used to remove the condensate film in real time.

[0063] In this embodiment, it should also be noted that the heterogeneous data fusion module further includes a sampling rate normalization unit and a spatiotemporal alignment unit; the sampling rate normalization unit aligns the laser and tilt sensor data streams through non-uniform interpolation resampling to eliminate sampling rate mismatch errors; the spatiotemporal alignment unit is based on a multi-sensor Lie group to synchronize and unify the spatiotemporal reference of the data, and is used to achieve accurate fusion of attitude control signals.

[0064] In practical applications, a tracking method for a laser positioning and tracking system for beam paving based on the above system specifically includes the following steps:

[0065] S1. Dynamic laser wavelength calibration:

[0066] S1.1. Initialize the laser emitter, load the preset wavelength reference value (1550nm), and start the wavelength monitoring sensor;

[0067] S1.2. Acquire laser spectral data using a high-speed photodetector and extract instantaneous wavelength values ​​using the sliding window method;

[0068] S1.3. Input the real-time wavelength data into the adaptive Kalman filter to predict the wavelength drift trend at the next moment;

[0069] S1.4. Drive the voltage-controlled oscillator according to the prediction results, and adjust the laser cavity temperature or current to bring the wavelength error to within ±0.01nm.

[0070] S1.5. Continuous iterative calibration process until the wavelength stability reaches the preset threshold (fluctuation <0.05nm within 10 minutes);

[0071] S2. Multipath interference signal separation:

[0072] S2.1. Deploy a multi-channel laser receiving array to acquire a mixed waveform containing direct signals and signals reflected from the rebar / formwork;

[0073] S2.2. Perform spatial beamforming calculations on the received signal and estimate the direction angle of the interference signal using the covariance matrix;

[0074] S2.3. Construct a spatial domain filtering weight vector to suppress signal energy in non-main path directions (attenuation > 30dB);

[0075] S2.4. Perform a short-time Fourier transform on the filtered signal to extract the time-frequency domain peak features (pulse width < 5ns, bandwidth > 10GHz);

[0076] S2.5. Using a pre-trained convolutional spiking neural network model, match the fingerprint features of real laser signals and output the interference-free positioning reference signal;

[0077] S3. Heterogeneous Protocol Command Synchronization:

[0078] S3.1. Monitor the CAN bus and RS485 port to capture raw command data packets (including protocol headers and checksums) from different devices;

[0079] S3.2. Based on the dynamic protocol library, match the instruction format and parse out the key fields of device type, instruction type, and parameter value;

[0080] S3.3. Convert heterogeneous instructions into a unified intermediate format (JSON-LD semantic description) and refactor them into standardized control instructions;

[0081] S3.4. Based on the rubidium atomic clock timestamp, insert nanosecond-level synchronization markers (accuracy ±50ns) into the instruction stream;

[0082] S3.5. Send standardized instructions through a priority queue scheduler to ensure that the timing alignment error of multiple device actions is <1ms;

[0083] S4. Quantum noise suppression processing:

[0084] S4.1. Acquire the power bus voltage waveform and record 10 consecutive power frequency cycles of data at a sampling rate of 1MHz;

[0085] S4.2. Perform quantum wavelet transform (QWT) on the voltage signal to decompose it into 21 frequency bands (including the 3rd to 50th harmonics);

[0086] S4.3. Calculate the quantum entanglement entropy value of each frequency band and identify the harmonic interference frequency band with energy abrupt change (23rd harmonic exceeds the standard);

[0087] S4.4. Generate a cancellation signal with opposite amplitude and phase based on the interference frequency band parameters (error <2%).

[0088] S4.5. Inject reverse harmonics into the power supply filter circuit through a power amplifier to achieve interference cancellation (suppression ratio > 40dB);

[0089] S5. Sub-nanosecond clock synchronization:

[0090] S5.1. Receive GPS satellite pulse-second (1PPS) signals and measure their phase difference with the rubidium atomic clock 1PPS (accuracy ±5ns);

[0091] S5.2. The least squares method is used to fit the clock drift curve to predict the cumulative time deviation in the next 10 seconds;

[0092] S5.3. Control the voltage-controlled crystal oscillator (VCXO) to adjust the local clock frequency in 0.1 ppb steps;

[0093] S5.4. Fine-tune the clock phase using a digital delay line to compensate for residual deviations to the sub-nanosecond level (<0.3 ns);

[0094] S5.5. Perform closed-loop calibration every 30 seconds to maintain long-term clock synchronization stability (24-hour error <1μs);

[0095] S6. Data buffer optimization:

[0096] S6.1. Based on the point cloud data rate (100kpoints / s), pre-calculate the memory requirements and divide the storage into 8 ring-shaped blocks;

[0097] S6.2. Allocate independent read / write pointers for each block and use a double buffering mechanism to avoid access conflicts;

[0098] S6.3. Add timestamp tags to data blocks to record the acquisition time (accuracy 1μs) and data priority (level 0 to 3);

[0099] S6.4. Monitor buffer fill rate and initiate cleanup when usage > 85%.

[0100] Data blocks with lower weights are eliminated by sorting them according to the time-weighted formula (weight = priority × e^(-0.1.t)).

[0101] S6.5. Periodically perform memory defragmentation, merge consecutive free blocks, and maintain storage efficiency >95%;

[0102] S7. Condensation Self-Healing Control:

[0103] S7.1. Deploy a miniature temperature and humidity sensor array (resolution 0.1℃ / 0.1%RH) around the laser lens;

[0104] S7.2. Establish a three-dimensional unsteady heat transfer model and solve for the dew point temperature distribution on the lens surface (mesh size 0.5 mm);

[0105] S7.3. When the predicted condensation probability is >60%, apply a 200V pulse voltage (pulse width 10ms) to the nano-coated electrode;

[0106] S7.4. By altering the surface morphology of hydrophobic materials (contact angle > 150°) through electrostatic actuation, a micron-scale protrusion structure is formed to repel water droplets;

[0107] S7.5. Use an infrared thermal imager to verify the dryness of the mirror surface. If the thickness of the residual water film is >1μm, trigger a secondary cleaning process.

[0108] S8. Multi-source data fusion control:

[0109] S8.1. Acquire laser ranging data (100Hz) and tilt sensor data (50Hz), and mark their respective timestamps;

[0110] S8.2. Perform cubic spline interpolation on the low-frequency tilt angle data to generate virtual sampling points with the same frequency as the laser data;

[0111] S8.3. Calculate the time alignment error between the two data streams and use the Lie group SE(3) model to compensate for the spatial coordinate system deviation;

[0112] S8.4. The fused data is input into the PID controller to generate two-dimensional adjustment commands for cross slope and longitudinal slope;

[0113] S8.5. Control commands are sent via CAN bus at 10ms cycles to drive the hydraulic actuator to achieve a paving elevation error of <±2mm;

[0114] S9. Dynamic error closed-loop correction:

[0115] S9.1. Use a linear CCD camera to continuously photograph the paved surface and extract the surface elevation contour line (sampling interval 5cm);

[0116] S9.2. Compare the measured profile with the design model, and calculate the root mean square error (RMS) and the maximum peak / trough value;

[0117] S9.3. If RMS > 3mm, initiate error source analysis: separate the laser positioning error, mechanical execution error, and material settlement error components;

[0118] S9.4. Adjust parameters according to error type: positioning error triggers wavelength recalibration, mechanical error corrects PID gain, and settlement error compensates for paving thickness;

[0119] S9.5. Perform a full system health check after every 5 meters of paving length is completed, and update the calibration coefficients and control strategies.

[0120] Through the above steps, this system eliminates wavelength shifts caused by temperature drift and aging through dynamic wavelength calibration, ensuring long-term stability of the laser signal. It accurately cancels power harmonic interference through quantum noise suppression technology, improving the signal-to-noise ratio under complex working conditions. It filters out multipath reflection signals through spatial beamforming and convolutional pulse neural networks, ensuring positioning accuracy in areas with dense reinforcement. It achieves precise collaboration among multiple devices through heterogeneous protocol bridging and sub-nanosecond clock synchronization, reducing command transmission latency to less than 1ms. At the same time, it actively eliminates condensation on the mirror surface through condensation self-healing. Combined with dynamic buffer management and multi-source data fusion, the system can automatically complete millimeter-level paving control. The measured paving surface flatness error is stable within ±2mm, and the construction efficiency is improved by more than 40%, completely solving the problems of insufficient accuracy, poor anti-interference, and reliance on manual labor in traditional methods.

[0121] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A laser positioning and tracking system for beam surface paving, characterized in that, It includes a dynamic wavelength calibration module, a multipath signal separation module, a heterogeneous communication protocol bridging module, a quantum noise suppression module, a high-precision clock synchronization module, a dynamic buffer management module, a condensation self-healing module, and a heterogeneous data fusion module; The dynamic wavelength calibration module is used for real-time wavelength monitoring and dynamic compensation. The multipath signal separation module is used for spatial beamforming and feature recognition; the multipath signal separation module also includes a spatial beamforming unit and a feature recognition unit. The spatial beamforming unit suppresses reflected signals from the reinforcing bars and formwork through spatial adaptive filtering, and is used to extract the main signal that reaches the laser path. The feature recognition unit uses a convolutional pulse neural network to identify the time-frequency characteristics of real laser signals, which is used to separate multipath interference signals. The heterogeneous communication protocol bridging module is used for protocol parsing and data encapsulation; The quantum noise suppression module is used for harmonic spectrum analysis and noise cancellation; The high-precision clock synchronization module is used for dual-source time synchronization and phase fine-tuning; The dynamic buffer management module is used for memory pre-allocation and priority cleanup; The condensation self-healing module is used for dew point prediction and nano-coating activation; The heterogeneous data fusion module is used for sampling rate normalization and spatiotemporal alignment.

2. The laser positioning and tracking system for beam surface paving according to claim 1, characterized in that: The dynamic wavelength calibration module also includes a real-time wavelength monitoring unit and a dynamic compensation unit; The wavelength real-time monitoring unit tracks the output wavelength change of the laser emitter in real time through an adaptive Kalman filter algorithm, which is used to achieve millisecond-level dynamic detection of wavelength shift. The dynamic compensation unit drives the laser voltage-controlled oscillator based on the wavelength locking method to adjust the laser wavelength to a preset reference value in real time, thereby eliminating the effects of temperature drift or aging.

3. The laser positioning and tracking system for beam surface paving according to claim 2, characterized in that: The heterogeneous communication protocol bridging module also includes a protocol parsing unit and a data encapsulation unit; The protocol parsing unit uses a dynamic protocol conversion engine to parse CAN bus and RS485 heterogeneous protocol commands in real time, so as to unify the control command format. The data encapsulation unit inserts synchronization markers into the instruction stream based on timestamp injection to eliminate instruction delays caused by protocol conflicts.

4. The laser positioning and tracking system for beam surface paving according to claim 3, characterized in that: The quantum noise suppression module also includes a harmonic spectrum analysis unit and a noise cancellation unit; The harmonic spectrum analysis unit detects the energy distribution of power harmonic frequency bands through quantum wavelet transform, which is used to locate the frequency band of interference sources; The noise cancellation unit uses adaptive quantum entanglement filtering to reconstruct the reverse harmonic signal, which is used to cancel the interference of power supply noise on the laser.

5. The laser positioning and tracking system for beam surface paving according to claim 4, characterized in that: The high-precision clock synchronization module also includes a dual-source timing unit and a phase fine-tuning unit; The dual-source timing unit obtains dual clock source signals through a GPS-rubidium atomic clock redundancy synchronization algorithm to eliminate the cumulative error of a single clock source. The phase fine-tuning unit dynamically adjusts the controller clock phase based on sub-nanosecond phase alignment to achieve time synchronization between the laser and the controller.

6. The laser positioning and tracking system for beam surface paving according to claim 5, characterized in that: The dynamic buffer management module also includes a memory pre-allocation unit and a priority cleanup unit; The memory pre-allocation unit pre-divides the point cloud data storage area through a block-based circular queue to avoid high-frequency data overflow. The priority cleanup unit automatically cleans up expired data blocks based on a time-weighted eviction strategy to maintain the stable operation of the buffer.

7. The laser positioning and tracking system for beam surface paving according to claim 6, characterized in that: The condensation self-healing module also includes a dew point prediction unit and a nano-coating activation unit; The dew point prediction unit predicts the risk of condensation on the lens surface by modeling the microenvironment temperature and humidity field, which is used to trigger the protection mechanism in advance. The nano-coating activation unit is based on electrostatically driven hydrophobic control of the deformation of nanomaterials on the lens surface, used to remove condensate film in real time.

8. The laser positioning and tracking system for beam surface paving according to claim 7, characterized in that: The heterogeneous data fusion module also includes a sampling rate normalization unit and a spatiotemporal alignment unit; The sampling rate normalization unit aligns the laser and tilt sensor data streams through non-uniform interpolation resampling to eliminate sampling rate mismatch errors. The spatiotemporal alignment unit is based on a multi-sensor Lie group to synchronize and unify the spatiotemporal reference data, and is used to achieve precise fusion of attitude control signals.

9. A laser positioning and tracking method for beam surface paving, comprising a laser positioning and tracking system for beam surface paving according to claim 8, characterized in that, Includes the following steps: S1. The system starts to detect the laser emission wavelength in real time and dynamically adjusts it to the preset reference value to ensure stable wavelength output; S2. Collect laser reflection signals, analyze the spatial distribution and time-frequency characteristics of the signals, eliminate interference reflection paths from steel bars or formwork, and extract direct signals as positioning references; S3. Parse the communication command streams of different devices, unify the command format and insert synchronization markers to eliminate command delays or errors caused by protocol conflicts; S4. Detect the energy distribution of the power supply harmonic frequency band, generate reverse harmonic signals to cancel noise interference, and maintain the purity of the laser signal; S5. Synchronizes external satellite clock with local high-precision clock source, dynamically fine-tunes clock phase deviation to sub-nanosecond level, and ensures time reference consistency; S6. Pre-allocate data storage space and clean up expired data blocks according to time weight to avoid high-frequency point cloud data overflow or memory fragment accumulation; S7. Predict the temperature and humidity change trend of the laser lens surface, trigger an active hydrophobic mechanism to remove the condensation film, and prevent signal attenuation or scattering; S8. Align the sampling frequencies of laser and sensor data streams, unify the spatiotemporal reference, and fuse them to generate attitude control commands to drive the paver to operate precisely; S9. Continuously monitor the dynamic error of the paved surface and correct the laser path and equipment movement in real time until paving is completed.

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