Method for detecting machining precision of special-shaped stone

Abstract

The invention discloses a special-shaped stone machining precision detection method, and belongs to the technical field of special-shaped stone quality detection.The special-shaped stone is subjected to spiral / Z-shaped track scanning and real-time modeling through a handheld three-dimensional laser scanner, collected STL data and a design model are subjected to three-dimensional alignment comparison in Polyworks software, and the accuracy of the special-shaped stone machining precision is detected. And a color deviation graph is generated to visually display the machining error, and finally a quantitative detection report is output, so that rapid visual evaluation of the machining precision of the special-shaped stone is realized. The method has the advantages of high efficiency, accuracy, standardization and the like, has a wide popularization prospect, and can remarkably improve the stone processing quality management level. Therefore, the method for detecting the machining precision of the special-shaped stone solves the technical problem of how to improve the detection efficiency of the machining precision of the special-shaped stone.

Description

Technical Field

[0001] This invention relates to the technical field of quality inspection of irregularly shaped stone, and in particular to a method for testing the processing precision of irregularly shaped stone. Background Technology

[0002] Stone curtain wall components refer to building envelope components made from natural or artificial stone. They can be reliably connected to the main building structure through metal connectors to form a non-load-bearing exterior wall system that combines decoration and functionality. The core components of the stone curtain wall typically include stone panels, a steel / aluminum alloy supporting keel system, connecting brackets such as back bolts and short grooves, sealing materials, and insulation layers. They must meet the physical performance requirements of building structures, such as wind pressure resistance, waterproofing, and earthquake resistance, while also fulfilling the aesthetic expression of the building facade.

[0003] As architectural design increasingly leans towards complex curved surfaces and free-form shapes, the shapes of stone curtain wall components are also becoming more diverse. This is particularly evident in high-end public building projects, where irregularly shaped curved stone products are being adopted due to their unique visual appeal. However, compared to traditional flat stone, irregularly shaped curved stone requires higher dimensional accuracy during processing and installation, and its inspection is significantly more challenging.

[0004] Based on this, Chinese patent document CN115342714B discloses a device for detecting the flatness of lace-patterned stone. It includes a base, a detection seat mounted on the base, a detection rod slidably mounted vertically on the detection seat, an elastic element connecting the detection rod and the detection seat, and a detection head mounted on the lower end of the detection rod. The detection head has an ink-extrusion channel extending from its outlet end to the middle of its bottom end. The detection head is connected to an ink supply hose fixed to the side wall of the detection rod via the ink-extrusion channel. The end of the ink supply hose away from the ink-extrusion channel is connected to an ink supply system. An ink-extrusion component is mounted on the detection seat to flatten the ink supply hose on the adjacent side wall of the detection rod onto the detection rod. A clearance groove is provided on the side of the detection rod near the ink-extrusion component for complete embedding of the ink supply hose. When the detection head is pressed against the standard surface of the plane to be measured, the clearance groove aligns with the ink-extrusion component. The technical solution disclosed in this patent document has the effect of detecting the flatness of stone and automatically marking it with ink.

[0005] However, the aforementioned decorative stone flatness testing device still has a technical problem: it cannot detect the core dimensions of curved stone. Specifically, 3D laser scanning technology, as a rapidly developing non-contact three-dimensional measurement method in recent years, has been widely used in industries such as automotive, aerospace, mold making, and machinery manufacturing. Its high efficiency, high precision, and visualization features make it an important tool for quality inspection. Although this technology is maturely applied in the industrial field, its use in the stone industry is still in its early stages, especially in the research and practice related to the processing precision inspection of irregularly shaped curved stone. For curved stone, traditional quality inspection methods, such as vernier calipers, tape measures, and template comparison, are insufficient to meet the quality inspection requirements of high precision and complex geometries. Summary of the Invention

[0006] Therefore, it is necessary to provide a method for detecting the processing accuracy of irregularly shaped stones, addressing the technical issue of how to improve the detection efficiency of irregularly shaped stone processing accuracy.

[0007] A method for detecting the processing precision of irregularly shaped stone, comprising the following steps: S1: Inspection preparation, a. Prepare the irregularly shaped stone to be inspected and place it on the platform, and set up the marker points at the same time; b. Connect and calibrate the handheld 3D laser scanner according to the preset line, and then set the scanner according to the preset working parameters; S2: Scan the object to collect data. Use a scanner to scan the stone using a spiral or Z-shaped trajectory, and simultaneously perform detailed scanning and real-time modeling. S3: Data processing, exporting the data collected by the scanner into an STL format file for later reference; S4: Comparison and Analysis, a. In the Polyworks software, set the comparison parameters according to the preset parameters and import the scanned model of the stone from the previous steps; at the same time, import the design model corresponding to the detected stone into the Polyworks software; b. In the Polyworks software, align the scanned model of the stone with the design model, then calculate the deviation between the two models, and finally generate a color deviation map; S5: Output the results. Edit the measurement report according to the preset parameters, and then export the color deviation map and test report of the stone. This completes the test of the processing parameters of the irregular stone.

[0008] Furthermore, an infrared band is added to the existing blue laser to compensate for the reflective interference on the stone surface through dual wavelengths, thereby improving the point cloud integrity of high light-absorbing materials such as dark marble. At the same time, an adaptive power adjustment module is developed to dynamically optimize the laser intensity.

[0009] Furthermore, the specific steps for using multispectral laser fusion scanning to optimize reflective interference on the stone surface are as follows: S11: Equipment modification, modifying the existing handheld 3D laser scanner by adding an infrared laser and an adaptive power adjustment module; S12: Parameter settings. Set the dual-wavelength scanning mode in the software and adjust the power ratio of blue laser and infrared laser to adapt to different types of stone. S13: Data Acquisition. Start the scanner to emit blue and infrared lasers simultaneously to acquire point cloud data of the stone surface. S14: Data fusion, which involves data fusion processing on edge computing terminals or cloud servers, using dual-wavelength data complementarity to improve point cloud integrity; S15: Quality assessment. Based on the fused point cloud data, automatically assess the scan quality and prompt for additional scanning areas if necessary.

[0010] Furthermore, in step S12, for dark-colored stone, the power of the infrared laser is increased to 1.5-2 times that of the blue laser; for light-colored stone, the power of the blue laser accounts for more than 70% of the total power of the two lasers.

[0011] Furthermore, in the multispectral laser fusion scanning process, before scanning the stone, a low-power test beam with a power set to 10mW is emitted; then, the reflection intensity is measured using an APD sensor, and the material reflectivity ratio is calculated using the formula: P 1550 =K*(R 450 / R 1550 )*P 450 In the formula, k is the material coefficient, and P 1550 P is the power of the infrared laser. 450 The power of the blue laser is set; finally, the power of both lasers is dynamically adjusted based on reflectivity.

[0012] Furthermore, in the multispectral laser fusion scanning process, the adaptive control process is as follows: S111: Initial settings, default ratio 1:1, 100mW for each wavelength; S112: Adjustment during scanning. The power ratio is updated every 5ms. When the deviation of the power ratio exceeds ±15%, the parameter optimization process is automatically triggered.

[0013] Furthermore, the scanning control process of the spectral laser fusion scanning system is as follows: A [Initiate Dual-Wavelength Alternating Scan] --> B [Real-Time Reflectivity Analysis] B-->C {Determine if reflectivity is <30%} C --> |Yes|D [Switch to mode using 1550nm infrared laser as the main scanning wavelength] C --> | No | E [Mainly maintain the mode of using 450nm blue laser as the primary scanning wavelength] D&E --> F [Point Cloud Data Fusion] F-->G [Generate a composite 3D model].

[0014] Furthermore, a method for integrating an NVIDIA Jetson edge computing unit into the scanning handle of a handheld 3D scanner to achieve real-time point cloud preprocessing, dynamic evaluation of scan quality, and direct transmission of on-site data to the cloud includes the following steps: S21: Hardware integration, embedding the NVIDIA Jetson edge computing unit inside the scanning handle of the 3D scanner, and connecting the edge computing unit to the laser scanning module and camera; S22: Control method, through preset edge computing software, enables it to have point cloud preprocessing algorithm, scan quality assessment algorithm and 5G communication module driver; S23: Preprocessing process: During the scanning process, the edge computing unit receives point cloud data in real time and performs noise reduction and filtering operations. S24: Quality assessment. Based on the preprocessed point cloud data, dynamically assess the scanning quality and automatically suggest areas for additional scanning. S25: Data Upload. The preprocessed point cloud data is uploaded to the cloud server in real time via the 5G module for subsequent analysis.

[0015] In summary, the present invention provides a method for detecting the processing accuracy of irregularly shaped stone. This method utilizes a handheld 3D laser scanner to perform spiral / Z-shaped trajectory scanning and real-time modeling of the irregularly shaped stone. The collected STL data is then compared with the design model in Polyworks software using 3D alignment, generating a color deviation map to visually display processing errors. Finally, a quantitative inspection report is output, achieving rapid and visual assessment of the processing accuracy of irregularly shaped stone. This method offers advantages such as high efficiency, accuracy, and standardization, and has broad prospects for widespread application, significantly improving the quality management level of stone processing. In the embodiment of hyperboloid stone strip inspection, the handheld 3D laser scanner demonstrates high precision, high efficiency, and strong adaptability in stone strip processing accuracy detection. By comparing point cloud data with the design model, it can quickly and accurately determine processing accuracy, meeting the quality inspection needs of complex curved stone surfaces. Therefore, this technology has enormous potential for application in the stone industry and other fields, and is expected to drive the transformation and upgrading of traditional quality inspection methods. Thus, the present invention provides a method for detecting the processing accuracy of irregularly shaped stone, solving the technical problem of how to improve the detection efficiency of irregularly shaped stone processing accuracy. Attached Figure Description Figure 1 This is a flowchart of a method for detecting the processing precision of irregularly shaped stone according to the present invention; Figure 2 This is a schematic diagram of a test report output by a specific embodiment of the method for testing the processing precision of irregularly shaped stone according to the present invention; Figure 3 This is a partial circuit control schematic diagram of the multispectral laser fusion scanning method used in the method for detecting the processing accuracy of irregularly shaped stone in this invention. Detailed Implementation

[0016] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0017] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0018] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0019] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0020] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0021] It should be noted that when an element is referred to as being "fixed to" or "set on" another element, it can be directly on the other element or there may be an intervening element. When an element is considered to be "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "upper," "lower," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0022] For details, please refer to Figure 1 and Figure 2 The present invention discloses a method for detecting the processing precision of irregularly shaped stone, which includes the following steps: S1: Inspection preparation, a. Prepare the irregularly shaped stone to be inspected and place it on the platform, and set up the marker points at the same time; b. Connect and calibrate the handheld 3D laser scanner according to the preset line, and then set the scanner according to the preset working parameters; S2: Scan the object to collect data. Use a scanner to scan the stone using a spiral or Z-shaped trajectory, and simultaneously perform detailed scanning and real-time modeling. S3: Data processing, exporting the data collected by the scanner into an STL format file for later reference; S4: Comparison and Analysis, a. In the Polyworks software, set the comparison parameters according to the preset parameters and import the scanned model of the stone from the previous steps; at the same time, import the design model corresponding to the detected stone into the Polyworks software; b. In the Polyworks software, align the scanned model of the stone with the design model, then calculate the deviation between the two models, and finally generate a color deviation map; S5: Output the results. Edit the measurement report according to the preset parameters, and then export the color deviation map and test report of the stone. This completes the test of the processing parameters of the irregular stone.

[0023] Specifically, in the method for detecting the processing precision of irregularly shaped stone in this invention, the handheld device used can be the HEXAGON RigelScan Ultra, which consists of two CCD cameras and four blue lasers. Moreover, this handheld scanner can perform dynamic and free-moving scanning without the need for marking points, relying on self-positioning technology. Its scanning speed is up to 1,350,000 points / second, and its maximum precision can reach 0.01mm. While scanning, it can generate a triangular mesh model (STL format file) in real time, providing basic data for subsequent comparative analysis.

[0024] Specifically, in the method for detecting the processing accuracy of irregularly shaped stone in this invention, the principle of the applied three-dimensional comparison analysis is as follows: using Polyworks software, the scanned point cloud data is registered with the original design 3D model, and then the point cloud and model are aligned using the least squares method. The deviation is calculated and a color deviation map is generated. Finally, reports such as the maximum deviation and the mean deviation are output, and the processing quality is judged based on these reports. The specific process is as follows: S41: Data preparation stage: Point cloud processing, after importing the scan data, perform "noise filtering" with a control threshold of 0.1mm, and use adaptive sampling to control the point cloud density at 200 points / cm²; Design model optimization, convert the CAD model to a lightweight format, which can usually be converted to 3dxml format, and remove non-detection features on the design model. S42: Intelligent Registration Process: Coarse Registration: Manually select 3 pairs of feature points, usually the intersection of edges, and establish an initial coordinate system based on them; Fine Registration: Enable the "Best Fit Alignment" function, set the number of iterations to 100, and the convergence tolerance to 0.005mm; Validation: Use the "deviation histogram" to check the registration quality, and the RMS value should be <0.02mm. S43: Deviation Analysis Module, Calculation Settings: Calculate using the least squares method, activate the "Curvature Compensation" option; Chromatographic Mapping: Customize 7 tolerance zones, such as: ±0.1 / 0.3 / 0.5 / 1.0 / 1.5 / 2.0 / >2.0mm; Dynamic Analysis: Generate cross-sectional deviation curves and vector deviation arrow diagrams with 10mm intervals. S44: Report Generation System: Statistical Parameters: Automatically extracts MaxDeviation / MinDeviation / MeanDeviation; Output Content: Includes 3D chromatograms, critical section deviation curves, and coordinate tables of out-of-tolerance areas. Format Selection: Supports dual-format output of PDF (vector graphics) + Excel (raw data).

[0025] Specifically, compared with traditional stone testing methods, the method for detecting the processing precision of irregularly shaped stone according to this invention offers higher accuracy and efficiency. It supports dynamic scanning, has no size limitations, and adapts to complex curved surfaces and various on-site environments. Point cloud data completely records the three-dimensional morphology of the stone strips, and deviation chromatograms visually display processing errors. Although the initial investment is high, the long-term cost is low, resulting in significant economic benefits. Therefore, it can be widely applied to the precision testing of irregularly shaped stone products, improving quality inspection efficiency and reliability. Furthermore, it can be applied to fields such as building curtain walls and sculptures, supporting batch testing. Its advantages, including high precision, flexibility, data compatibility, intelligence, and automation, make it suitable for large-scale project applications.

[0026] Furthermore, in a specific embodiment of the method for detecting the processing precision of irregularly shaped stone according to the present invention, it is applied to the detection of curtain wall stone strips. The type of stone strip is a hyperboloidal irregularly shaped stone strip, 50mm thick, with 73 strips in total. The length and width of the strips vary, for example, the length is from 200mm to 1300mm, and the width is from 50mm to 108mm. During the detection process, the scanning time is 1 minute per piece, including the time for saving the scanned model file, and the comparison time is 2 minutes per piece, including the time for generating the detection report. The equipment has a maximum scanning accuracy of 0.01mm, and the color deviation mark is set within the acceptable range, i.e., it is marked by the green mark, with a range of 0 to -0.5mm. This meets the maximum design accuracy requirement of 0 to -1mm for stone strip processing, reaches and exceeds the measurement accuracy of vernier calipers, and completes the measurement of curved surfaces and curves that vernier calipers cannot achieve. The detection efficiency is the same as that of conventional measurement, and it can generate a visual document, i.e., a PDF inspection report, which is helpful for later rectification and traceability.

[0027] Furthermore, the detection method for the processing precision of irregularly shaped stone of the present invention is compared with the traditional detection method, as shown in Table 1 below.

[0028] Table 1: Comparison of the effects of the embodiments of the present invention with traditional detection methods

[0029] Therefore, the method for detecting the processing precision of irregularly shaped stone materials of the present invention can be widely applied to the precision detection of irregularly shaped stone products, such as curved slabs and carved pieces, replacing traditional inefficient methods and improving quality inspection efficiency and reliability. In addition, the present invention can also be extended to the fields of building curtain walls and sculptures, and is especially suitable for non-contact detection of complex geometric shapes. The automated interface supports integration with robots to achieve batch detection.

[0030] Furthermore, the method for detecting the processing accuracy of irregularly shaped stone can be optimized by using multispectral laser fusion scanning to improve the technical problem of reflection interference on the stone surface during scanning. Specifically, an infrared band, namely the 1550nm band, is added to the existing blue laser. By compensating for reflection interference on the stone surface with dual wavelengths, the point cloud integrity of high light-absorbing materials such as dark marble is improved. At the same time, an adaptive power adjustment module is developed to dynamically optimize the laser intensity.

[0031] Specifically, the steps for optimizing the method for detecting the processing accuracy of irregularly shaped stone using multispectral laser fusion scanning are as follows: S11: Equipment modification, modifying the existing handheld 3D laser scanner by adding an infrared laser and an adaptive power adjustment module; S12: Parameter Settings. In the software, set the dual-wavelength scanning mode and adjust the power ratio of the blue laser and infrared laser to adapt to different types of stone. For example, for dark-colored stone, such as black granite, the power of the infrared laser (1550nm) needs to be increased to 1.5-2 times that of the blue laser (450nm) because it has a high absorption rate of visible light and stronger penetration in the infrared band. For light-colored stone, such as white marble, the power of the blue laser should account for more than 70% of the total power of the two lasers to obtain surface details using its high reflectivity, while the infrared laser assists in compensating for internal structural information. S13: Data Acquisition. Start the scanner to emit blue and infrared lasers simultaneously to acquire point cloud data of the stone surface. S14: Data fusion, which involves data fusion processing on edge computing terminals or cloud servers, using dual-wavelength data complementarity to improve point cloud integrity; S15: Quality assessment. Based on the fused point cloud data, automatically assess the scan quality and prompt for additional scanning areas if necessary.

[0032] Specifically, in the aforementioned multispectral laser fusion scanning scheme, a low-power test beam is emitted before scanning. At this time, the power of both wavelengths is set to 10mW. The reflection intensity is measured by an APD sensor, and the material reflectivity ratio is calculated, as shown in Equation 1 below: According to Equation 1, the power is dynamically adjusted based on the reflectivity: P 1550 =K*(R 450 / R 1550 )*P 450 ; In Equation 1, k is the material coefficient, such as k=0.8 for granite and k=1.2 for marble; P 1550 P is the power of the infrared laser. 450 This represents the power of the blue laser.

[0033] Specifically, in the aforementioned multispectral laser fusion scanning scheme, the adaptive control process is as follows: S111: Initial settings, default ratio 1:1, 100mW for each wavelength; S112: Adjustment during scanning. The power ratio is updated every 5ms. If the deviation of the power ratio exceeds ±15%, the parameter optimization process is automatically triggered.

[0034] Specifically, a typical material parameter comparison table is shown in Table 2 below: Table 2: Typical Material Parameters

[0035] Specifically, in the multispectral laser fusion scanning scheme, reflectivity feedback and dynamic algorithms achieve a scanning accuracy improvement of over 20%, compared to a fixed-power scheme. In practical applications, it can be used in conjunction with edge computing terminals to process sensor data in real time.

[0036] Furthermore, in the method for detecting the processing accuracy of irregularly shaped stone, the present invention can also be optimized by an embedded edge computing terminal. Specifically, an NVIDIA Jetson edge computing unit can be integrated into the handle of the 3D scanner to achieve: real-time point cloud preprocessing to achieve noise reduction / filtering effects, dynamic evaluation of scanning quality to automatically prompt for additional scanning areas, and support for direct transmission of on-site data to the cloud via a 5G module.

[0037] Specifically, in the present invention, a method for detecting the processing precision of irregularly shaped stone includes a method that integrates an NVIDIA Jetson edge computing unit into the scanning handle to achieve real-time point cloud preprocessing, dynamic evaluation of scanning quality, and direct transmission of on-site data to the cloud. This method comprises the following steps: S21: Hardware integration, embedding the NVIDIA Jetson edge computing unit inside the scanning handle of the 3D scanner, and connecting the edge computing unit to sensors such as laser scanning modules and cameras; S22: Software development, developing adapted edge computing software, including point cloud preprocessing algorithms, scan quality assessment algorithms, and 5G communication module drivers; S23: Preprocessing process. During the scanning process, the edge computing unit receives point cloud data in real time and performs preprocessing operations such as noise reduction and filtering. S24: Quality assessment. Based on the preprocessed point cloud data, dynamically assess the scanning quality, such as point cloud density and noise level, and automatically suggest areas for additional scanning.

[0038] S25: Data Upload. The preprocessed point cloud data is uploaded to the cloud server in real time via communication modules such as 5G modules for subsequent analysis.

[0039] Specifically, in the method for detecting the processing accuracy of irregularly shaped stone according to the present invention, the detailed method based on multispectral laser fusion scanning and embedded edge computing terminal is as follows: A. Equipment Modification and Integration Step 1: Select a suitable infrared laser (1550nm) and adaptive power adjustment module; Step 2: Disassemble the existing handheld 3D laser scanner and reserve installation positions for the infrared laser and power adjustment module; Step 3: Perform circuit connection and debugging to ensure normal communication between the infrared laser and the scanner's main control board; Step 4: Embed the NVIDIA Jetson edge computing unit inside the scanning handle and connect it to sensors such as the laser scanning module and camera; B. Software Development and Parameter Setting Step 1: Develop control software for the dual-wavelength scanning mode, and set parameters such as the power ratio and scanning speed of the blue laser and infrared laser; Step 2: Develop edge computing software, including point cloud preprocessing algorithms (noise reduction, filtering), scan quality assessment algorithms, and 5G communication module drivers; Step 3: Deploy the software on the edge computing unit and conduct functional tests to ensure that all functions are operating normally; C. Data Acquisition and Fusion Processing Step 1: Start the scanner, which simultaneously emits blue and infrared lasers to scan the stone surface; Step 2: The edge computing unit receives dual-wavelength point cloud data in real time and performs preliminary data synchronization and calibration; Step 3: Utilize the complementary characteristics of dual-wavelength data to perform data fusion processing on edge computing units or cloud servers to improve point cloud integrity; D. Quality Assessment and Data Upload Step 1: Based on the fused point cloud data, the edge computing unit dynamically evaluates the scanning quality, such as point cloud density and noise level; Step 2: If the scan quality is not up to standard, the system will automatically prompt for areas to be scanned, and the operator can then perform the rescanning according to the prompts. Step 3: Upload the preprocessed point cloud data to the cloud server in real time via the 5G module for subsequent analysis; E. Cloud-based analytics and report generation Step 1: The cloud server receives the uploaded point cloud data and uses algorithms such as deep learning for further analysis and processing; Step 2: Generate processing error prediction reports, quality traceability reports, etc., for user reference; Step 3: Users can view the report through the web interface or mobile application and perform subsequent operations based on the report results.

[0040] Specifically, in the method for detecting the processing precision of irregularly shaped stone according to the present invention, the implementation scheme of the multispectral laser fusion scanning system is as follows: Hardware Architecture Design: The laser emission module employs a dual-wavelength laser, namely a 450nm blue laser and a 1550nm infrared laser, and integrates an adaptive power adjustment circuit to dynamically adjust the laser intensity based on the material's reflectivity, providing a control module adjustable from 0-300mW. Optical Receiving Module: A dual-channel APD sensor receives blue light and infrared reflected signals respectively, equipped with bandpass filters, such as 450±10nm / 1550±20nm bandpass filters, to suppress ambient light interference.

[0041] Specifically, the scanning control process of the multispectral laser fusion scanning system is as follows: graphTD A [Initiate Dual-Wavelength Alternating Scan] --> B [Real-Time Reflectivity Analysis] B-->C {Determine if reflectivity is <30%} C --> |Yes|D [Switch to 1550nm main scan] C --> | No | E [Main scan at 450nm] D&E --> F [Point Cloud Data Fusion] F --> G [Generate composite 3D model] Specifically, in the method for detecting the processing accuracy of irregularly shaped stone in this invention, a reflectivity compensation algorithm can be used to establish a database of stone material-wavelength-power correspondence to achieve automatic matching of scanning parameters; while multispectral registration technology can use feature point matching to achieve spatial alignment of dual-wavelength point clouds with an error controlled within ±0.05mm.

[0042] For the implementation plan of the embedded edge computing terminal, the hardware configuration is as follows: main control unit: NVIDIA Jetson AGX Orin, 32 TOPS AI computing power; expansion module, 5G communication: Quectel RM500Q-GL module, supporting Sub-6GHz; local storage: 1TB NVMe SSD, with a continuous write speed of up to 3GB / s; power management: 6S lithium battery pack, 50Wh and fast charging PD protocol.

[0043] For the implementation plan of the embedded edge computing terminal, its real-time processing algorithm flow is as follows: Point cloud preprocessing: noise filtering is achieved based on the DBSCAN clustering algorithm, and edge features are preserved by using bilateral filtering; Quality assessment model: a lightweight YOLOv5s network is constructed to achieve defect detection; Develop a scan integrity assessment index, and trigger a rescan prompt when the coverage is ≥98%.

[0044] For the implementation plan of the embedded edge computing terminal, its system integration solution includes: mechanical structure: magnesium alloy handle shell, achieving an IP54 protection level; heat dissipation design: heat dissipation combined with heat dissipation of heat dissipation plate and micro turbine fan; human-computer interaction: 2.4-inch OLED touch screen and three-color LED status indicator.

[0045] For details, please continue reading. Figure 3 In an edge computing terminal, the core circuit modules include: main control unit circuit, sensor interface circuit, communication and storage circuit, and power supply and protection circuit.

[0046] Specifically, in the main control unit circuit, the processor selection can be a multi-core ARM architecture SoC, such as NVIDIA Jetson AGX Orin or RK3588, integrating an NPU to achieve a computing power of ≥6 TOPS and a Mali-G610 GPU. Peripheral circuit design: Power management: 12V input → multiple DC-DC converters, with core voltages of 0.8V / 1.8V / 3.3V, which can be dynamically adjusted using PMIC chips such as TPS548B22. Clock synchronization: The Si5332A clock generator provides multiple differential clocks of 156.25MHz / 100MHz, with jitter <100fs11.

[0047] In the sensor interface circuit, multispectral data acquisition includes: a laser drive circuit: a MAX3946 driver chip controls a dual-wavelength laser, namely lasers with wavelengths of 450nm and 1550nm, supporting 0-300mW dynamic power adjustment. An APD receiving circuit: a transimpedance amplifier, such as the AD8015, can convert photocurrent, and works with the AD8602 operational amplifier to achieve low-noise signal conditioning. A camera interface: four MIPI-CSI channels, each 6Gbps, for connecting to a multispectral camera; an SN65LVDS324 deserializer performs signal conversion.

[0048] In the communication and storage circuitry, the 5G module interface: a Mini PCIe slot connects to the Quectel RM500Q-GL module, communicating with the main controller via a PCIe 3.0×1 interface. High-speed storage: an NVMe SSD interface, PCIe 3.0×4, supporting up to 4TB capacity; eMMC 5.1 is used for system boot.

[0049] In the power supply and protection circuit, wide input voltage is achieved using the MP2315 buck-boost controller, supporting operation from -40℃ to 85℃ with an input voltage of 6-36V. ESD protection is provided by a TPD2E007 bidirectional TVS diode deployed on the Ethernet / USB interface, providing ±8kV contact discharge protection.

[0050] Therefore, in the method for detecting the processing precision of irregularly shaped stone in this invention, the collaborative design of multispectral laser fusion scanning and embedded edge computing terminal enables precise and intelligent three-dimensional scanning of stone. The hardware employs a dynamic power adjustment module to adapt to the reflective characteristics of different materials, coupled with real-time point cloud processing by NVIDIA Jetson; the software combines deep learning error prediction and an improved ICP registration algorithm, ultimately forming a closed-loop solution through AR quality inspection and blockchain traceability. This improves scanning efficiency by more than 40% and achieves a defect recognition rate of over 98% compared to traditional methods.

[0051] In summary, the present invention provides a method for detecting the processing accuracy of irregularly shaped stone. This method utilizes a handheld 3D laser scanner to perform spiral / Z-shaped trajectory scanning and real-time modeling of the irregularly shaped stone. The collected STL data is then compared with the design model in Polyworks software using 3D alignment, generating a color deviation map to visually display processing errors. Finally, a quantitative inspection report is output, achieving rapid and visual assessment of the processing accuracy of irregularly shaped stone. This method offers advantages such as high efficiency, accuracy, and standardization, and has broad prospects for widespread application, significantly improving the quality management level of stone processing. In the embodiment of hyperboloid stone strip inspection, the handheld 3D laser scanner demonstrates high precision, high efficiency, and strong adaptability in stone strip processing accuracy detection. By comparing point cloud data with the design model, it can quickly and accurately determine processing accuracy, meeting the quality inspection needs of complex curved stone surfaces. Therefore, this technology has enormous potential for application in the stone industry and other fields, and is expected to drive the transformation and upgrading of traditional quality inspection methods. Thus, the present invention provides a method for detecting the processing accuracy of irregularly shaped stone, solving the technical problem of how to improve the detection efficiency of irregularly shaped stone processing accuracy.

[0052] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0053] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for detecting the processing precision of irregularly shaped stone, characterized in that, It includes the following steps: S1: Inspection preparation, a. Prepare the irregularly shaped stone to be inspected and place it on the platform, and set up the marker points at the same time; b. Connect and calibrate the handheld 3D laser scanner according to the preset line, and then set the scanner according to the preset working parameters; S2: Scan the object to collect data. Use a scanner to scan the stone using a spiral or Z-shaped trajectory, and simultaneously perform detailed scanning and real-time modeling. S3: Data processing, exporting the data collected by the scanner into an STL format file for later reference; S4: Comparison and Analysis, a. In the Polyworks software, set the comparison parameters according to the preset parameters and import the scanned model of the stone from the previous steps; at the same time, import the design model corresponding to the detected stone into the Polyworks software; b. In the Polyworks software, align the scanned model of the stone with the design model, then calculate the deviation between the two models, and finally generate a color deviation map; S5: Output the results. Edit the measurement report according to the preset parameters, and then export the color deviation map and test report of the stone. This completes the test of the processing parameters of the irregular stone.

2. The method for detecting the processing precision of irregularly shaped stone according to claim 1, characterized in that: By adding an infrared band to the existing blue laser, the point cloud integrity of high-light-absorbing materials such as dark marble is improved by compensating for the reflective interference on the stone surface through dual wavelengths. At the same time, an adaptive power adjustment module is developed to dynamically optimize the laser intensity.

3. The method for detecting the processing precision of irregularly shaped stone according to claim 2, characterized in that: The specific steps for using multispectral laser fusion scanning to optimize reflective interference on stone surfaces are as follows: S11: Equipment modification, modifying the existing handheld 3D laser scanner by adding an infrared laser and an adaptive power adjustment module; S12: Parameter settings. Set the dual-wavelength scanning mode in the software and adjust the power ratio of blue laser and infrared laser to adapt to different types of stone. S13: Data Acquisition. Start the scanner to emit blue and infrared lasers simultaneously to acquire point cloud data of the stone surface. S14: Data fusion, which involves data fusion processing on edge computing terminals or cloud servers, using dual-wavelength data complementarity to improve point cloud integrity; S15: Quality assessment. Based on the fused point cloud data, automatically assess the scan quality and prompt for additional scanning areas if necessary.

4. The method for detecting the processing precision of irregularly shaped stone according to claim 3, characterized in that: In step S12, for dark-colored stone, the power of the infrared laser is increased to 1.5-2 times that of the blue laser; for light-colored stone, the power of the blue laser accounts for more than 70% of the total power of the two lasers.

5. The method for detecting the processing precision of irregularly shaped stone according to claim 4, characterized in that: In the multispectral laser fusion scanning process, before scanning the stone, a low-power test beam with a power set to 10mW is emitted. Then, the reflection intensity is measured using an APD sensor, and the material reflectivity ratio is calculated using the formula: P 1550 =K*(R 450 / R 1550 )*P 450 In the formula, k is the material coefficient, and P 1550 P is the power of the infrared laser. 450 The power of the blue laser is set; finally, the power of both lasers is dynamically adjusted based on reflectivity.

6. The method for detecting the processing precision of irregularly shaped stone according to claim 5, characterized in that: In the multispectral laser fusion scanning process, the adaptive control process is as follows: S111: Initial settings, default ratio 1:1, 100mW for each wavelength; S112: Adjustment during scanning. The power ratio is updated every 5ms. When the deviation of the power ratio exceeds ±15%, the parameter optimization process is automatically triggered.

7. The method for detecting the processing precision of irregularly shaped stone according to claim 6, characterized in that: The scanning control process of the spectral laser fusion scanning system is as follows: A [Initiate Dual-Wavelength Alternating Scan] --> B [Real-Time Reflectivity Analysis] B-->C {Determine if reflectivity is <30%} C --> |Yes|D [Switch to mode using 1550nm infrared laser as the main scanning wavelength] C --> | No | E [Mainly maintain the mode of using 450nm blue laser as the primary scanning wavelength] D&E --> F [Point Cloud Data Fusion] F-->G [Generate a composite 3D model].

8. The method for detecting the processing precision of irregularly shaped stone according to claim 1, characterized in that: A method for integrating an NVIDIA Jetson edge computing unit into the scanning handle of a handheld 3D scanner to achieve real-time point cloud preprocessing, dynamic scan quality assessment, and direct transmission of on-site data to the cloud includes the following steps: S21: Hardware integration, embedding the NVIDIA Jetson edge computing unit inside the scanning handle of the 3D scanner, and connecting the edge computing unit to the laser scanning module and camera; S22: Control method, through preset edge computing software, enables it to have point cloud preprocessing algorithm, scan quality assessment algorithm and 5G communication module driver; S23: Preprocessing process: During the scanning process, the edge computing unit receives point cloud data in real time and performs noise reduction and filtering operations. S24: Quality assessment. Based on the preprocessed point cloud data, dynamically assess the scanning quality and automatically suggest areas for additional scanning. S25: Data Upload. The preprocessed point cloud data is uploaded to the cloud server in real time via the 5G module for subsequent analysis.

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