Encoder triggered line laser sensor lumber global scanning positioning detection system

Abstract

The present application relates to the technical field, specifically to an encoder trigger type line laser sensor wood global scanning positioning detection system, which comprises a wood global parameter acquisition module, an encoder trigger parameter adaptation module, a line laser scanning parameter regulation module, a point cloud acquisition deviation correction module and a defect positioning feature extraction module.In the present application, the core physical parameters of wood are collected, the coincidence degree and the deviation value are calculated in combination with the defect susceptible reference parameters, the defect susceptible area distribution value is generated, the encoder trigger parameters are adapted according to the distribution value, the line laser scanning parameters are regulated, the deviation value is calculated by calling real-time parameters to generate a correction coefficient, the global point cloud data is optimized by relying on the coefficient, the defect positioning characteristic value is extracted by screening and matching parameters, the scanning parameter differentiation adaptation and the point cloud deviation accurate correction are realized, the susceptible area detection is focused, the point cloud quality and the feature extraction efficiency are optimized, the uniform scanning limitation is avoided, the defect detection accuracy and the pertinence are improved, and the feature recognition effectiveness is strengthened.

Description

Technical Field

[0001] The present invention relates to the technical field of wood defect recognition, and particularly to an encoder-triggered line laser sensor wood global scanning and positioning detection system. Background Art

[0002] The technical field of wood defect recognition includes related technical directions such as the detection, recognition, scanning, imaging, and data processing of wood surface and internal defects. Its core content focuses on the research and application of detection-related technologies for natural and processing defects of wood. Natural defects include cracks, knots, insect holes, decay, etc., which are defects generated during the growth process. Processing defects include burrs, saw marks, hot pressing cracks, etc., which are defects generated during the processing process. It comprehensively covers the entire technical chain of obtaining wood surface or internal information through various sensing devices, extracting defect features after data preprocessing, and then completing defect recognition, involving the integrated application of various technical means such as line laser scanning and point cloud processing, and widely serving the quality inspection link of the wood processing industry.

[0003] Among them, the encoder-triggered line laser sensor wood global scanning and positioning detection system refers to a scanning and positioning detection system for wood defect detection. The technical matters it addresses cover the scanning imaging and positioning of the entire wood area and the recognition of wood defects. The specific means adopted are to start the scanning by triggering the line laser sensor through an encoder, perform Gaussian filtering on the line laser point cloud data of the entire wood area obtained by the line laser sensor to complete point cloud preprocessing, use a wood defect recognition model constructed based on the random forest algorithm to identify defects in the preprocessed point cloud data, and at the same time achieve positioning during the scanning process through the signal feedback of the encoder.

[0004] The prior art conducts global scanning of wood using fixed scanning parameters, without adjusting the parameters in combination with the physical parameters and defect characteristics of the wood. It only performs general point cloud filtering preprocessing, without special correction for scanning deviation. It relies on a fixed algorithm to identify defects. The scanning is affected by the differences in wood parameters, resulting in acquisition deviation. The defect extraction lacks pertinence, missing defect information in susceptible areas, generating redundant scanning data, reducing the accuracy of defect recognition, increasing the burden of data processing, and being unable to adapt to the differentiated detection requirements of wood. In addition, the prior art also has the following deficiencies: Manual detection relies on the experience of operators, and can only achieve a detection efficiency of 20 pieces per minute, with a missed detection and false detection rate exceeding 15%; Traditional laser detection equipment uses low-precision single-point laser scanning, unable to completely reconstruct the three-dimensional contour of the wood, lacking the ability to identify 0.1mm-level micro cracks; Commercial vision detection systems and laser 3D cameras have not optimized the algorithm for the complex texture characteristics of wood, with a point cloud processing efficiency lower than 200,000 points per second, unable to meet the requirements of online detection; Although the SLK series of line laser sensors have the technical advantages of 1456-point contour acquisition and a repeatability accuracy of 0.5 - 10μm, they have not been combined with AI algorithms to form an integrated solution for the wood detection production line. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and propose an encoder-triggered line laser sensor wood full-area scanning positioning and detection system.

[0006] To achieve the above objectives, the present invention employs the following technical solution: an encoder-triggered line laser sensor wood full-area scanning positioning and detection system, the system comprising: Wood global parameter acquisition module: acquires wood profile dimensions, surface roughness, and moisture content parameters, calls wood defect susceptibility feature benchmark parameters, calculates the overlap between profile dimension parameters and benchmark parameters, the deviation value between roughness parameters and parameters, and generates wood defect susceptibility area distribution values. Encoder trigger parameter adaptation module: Based on the distribution value of wood defect-prone areas, obtain the encoder trigger reference value, calculate the step size adjustment, and generate a partition encoder trigger parameter table; Line laser scanning parameter control module: Based on the trigger parameter table and distribution value of the partition encoder, obtain the line laser scanning reference value, compare it with the threshold to calculate the adjustment amount, and generate the partition line laser scanning parameter table; Point cloud acquisition deviation correction module: calls the partition encoder trigger parameter table and the line laser scanning parameter table to obtain the real-time trigger step size and scanning angle, calculates the deviation value between the real-time parameters and the reference parameters, and generates the point cloud acquisition deviation correction coefficient. The defect location feature extraction module acquires full-domain point cloud data based on the point cloud acquisition deviation correction coefficient, extracts parameters, filters matching data, and generates wood defect location feature values.

[0007] As a further embodiment of the present invention, the system includes a wood global parameter acquisition module, an encoder trigger parameter adaptation module, a line laser scanning parameter control module, a point cloud acquisition deviation correction module, and a defect location feature extraction module. The wood defect susceptibility area distribution values ​​include contour overlap partition values, surface roughness deviation partition values, and defect susceptibility probability distribution values. The encoder trigger parameter table includes region encoding information, trigger step size adjustment values, and trigger frequency setting values. The line laser scanning parameter table includes region matching encoding, scanning point spacing setting values, and laser power configuration values. The point cloud acquisition deviation correction coefficient includes trigger step size deviation correction values ​​and scanning angle deviation correction values. The wood defect location feature values ​​include a defect area coordinate set, a matching point cloud grayscale value set, and a defect boundary feature point set.

[0008] As a further aspect of the present invention, the wood global parameter acquisition module further includes: Parameter acquisition submodule: acquires parameters such as wood profile dimensions, surface roughness, and moisture content, calls the benchmark parameters of wood defect susceptibility characteristics, integrates the acquired parameters and benchmark parameters to form a parameter system, and generates a set of basic parameters for the entire wood domain; The benchmark calculation submodule is based on the wood global basic parameter set. It extracts the contour size parameters and performs a coincidence calculation with the benchmark parameters to obtain the coincidence degree. It extracts the surface roughness parameters and performs a deviation calculation with the benchmark parameters to obtain the deviation value. It integrates the calculation data and generates wood defect parameter matching values. Region generation submodule: Based on the matching values ​​of wood defect parameters, combined with the comprehensive calculation of moisture content parameters, the module correlates the degree of overlap, deviation value and moisture content parameter relationship, maps the wood location parameter characteristics, and generates the distribution value of wood defect susceptible areas.

[0009] As a further aspect of the present invention, the encoder trigger parameter adaptation module further includes: Reference value acquisition submodule: acquires the distribution value of wood defect-prone areas, calculates encoder trigger step size and frequency reference values ​​based on its numerical characteristics, and generates a set of partitioned reference parameters; The adjustment amount calculation submodule: Based on the partition baseline parameter set, it retrieves the distribution value of defect-sensitive areas, calculates the corresponding area encoder trigger step size adjustment amount according to the value, and generates the partition step size adjustment parameter set; The parameter table generation submodule calls two types of parameter sets, integrates numerical information, arranges parameters according to partitioning rules, and generates a partition encoder trigger parameter table.

[0010] As a further aspect of the present invention, the line laser scanning parameter control module further includes: Reference parameter acquisition submodule: acquires the trigger parameter table of the partition encoder and the distribution value of the defect-sensitive area, calculates the line laser scanning point spacing and laser power reference value, and collects the scanning laser reference parameter set; Partition parameter calculation submodule: Based on the scanning laser reference parameter set and resolution adaptation threshold, compare the distribution value with the threshold, calculate the parameter correction amount of the high-susceptibility zone, calculate the parameter range of the medium and low-susceptibility zone, and generate a set of partition parameter correction values; The parameter table generation submodule calls two types of parameter sets, collects baseline and correction parameters, integrates data according to partitioning rules, and generates a partitioned line laser scanning parameter table.

[0011] As a further aspect of the present invention, the point cloud acquisition deviation correction module further includes: Parameter retrieval submodule: retrieves two types of parameter tables, extracts the real-time encoder trigger step size and laser scanning angle, obtains the corresponding reference values, and generates a real-time reference parameter set; Deviation value calculation submodule: calls the real-time benchmark parameter set, calculates the difference between the real-time and benchmark parameters respectively, completes the two-dimensional difference calculation, and generates two-dimensional deviation values; Correction coefficient generation submodule: Based on the two-dimensional deviation values, the step size and angle deviation values ​​are weighted and calculated, and combined with the parameter ratio conversion values, the point cloud acquisition deviation correction coefficient is generated.

[0012] As a further aspect of the present invention, the defect location feature extraction module further includes: Point cloud correction and acquisition submodule: Obtain the point cloud acquisition deviation correction coefficient, retrieve the original point cloud data of the wood, correct the acquisition deviation with the correction coefficient, integrate the point data, and generate the full-domain point cloud data of the wood. Parameter extraction and integration submodule: Based on the full-domain point cloud data of wood, retrieve the spatial and grayscale information of the points, extract the coordinate and grayscale value parameters, collect them to form a parameter system, and generate a full-domain feature parameter set of wood. Defect Feature Generation Submodule: Calls the global feature parameter set, filters data that match the coordinate parameters and distribution values, and integrates the grayscale value parameters to generate wood defect location feature values.

[0013] As a further aspect of the present invention, the system further includes a pipeline coordination module, which further includes: Conveying adapter sub-module: Equipped with speed-regulating roller conveyor, pneumatic clamp and encoder to realize uniform speed conveying of wood at 1m / s and synchronous triggering of scanning unit. It can be replaced by chain conveyor line to meet the conveying needs of super heavy logs with a single weight of >50kg. Sorting execution submodule: Equipped with Siemens S7-1200PLC and pneumatic push rod, it can be replaced by a gantry-type truss robot or a hydraulic push rod sorting device to receive the location feature value of wood defects and complete the accurate sorting of qualified and defective wood. The central control traceability submodule integrates an industrial touchscreen and a MySQL database to display real-time testing data and equipment operating status, enabling traceability of testing quality. It supports querying testing records by wood number and testing time, as well as closed-loop adjustment of process parameters. Compared with the prior art, the advantages and positive effects of the present invention are as follows: This invention collects core physical parameters of wood to generate defect-prone area distribution values, adapts encoder trigger parameters and line laser scanning parameters (matching the characteristics of professional sensors), and optimizes point cloud data using correction coefficients and optimization algorithms to quickly generate a complete 3D model and improve point cloud processing efficiency. It integrates a deep learning model to achieve accurate identification of minute defects and high-precision dimensional deviation detection. A new assembly line collaboration module is added to achieve uniform wood conveying, rapid sorting, full-process data traceability, and closed-loop process adjustment, constructing an automated detection system. It supports flexible replacement of sensors, algorithms, and conveying and sorting modules to adapt to different materials, heavy wood, and various processing scenarios. This invention achieves differentiated adaptation of scanning parameters and accurate correction of point cloud deviations, focusing on vulnerable area detection and improving the accuracy and targeting of defect detection. It also addresses the pain points of low integration, insufficient efficiency, and poor adaptability of existing equipment, perfectly matching the production rhythm of the assembly line, while possessing intelligent traceability and continuous optimization capabilities to meet the quality control needs of high-end wood processing. Attached Figure Description

[0014] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0015] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0016] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0017] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0018] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0019] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0020] Please see Figure 1 This invention provides a technical solution: an encoder-triggered line laser sensor wood full-area scanning positioning and detection system, the system comprising: Wood global parameter acquisition module: acquires wood profile size parameters, surface roughness parameters, and moisture content parameters, calls wood defect susceptibility feature benchmark parameters, calculates the overlap between profile size parameters and wood defect susceptibility feature benchmark parameters, calculates the deviation between surface roughness parameters and wood defect susceptibility feature benchmark parameters, and generates wood defect susceptibility area distribution values. Encoder trigger parameter adaptation module: Based on the distribution value of wood defect susceptibility areas, obtain the encoder trigger step size reference value and encoder trigger frequency reference value, calculate the encoder trigger step size adjustment amount corresponding to the distribution value of wood defect susceptibility areas in different regions, and generate a partition encoder trigger parameter table. Line laser scanning parameter control module: Based on the zone encoder trigger parameter table and the distribution value of wood defect-prone areas, obtain the baseline value of the line laser sensor scanning point spacing and the baseline value of the line laser sensor laser power, compare the distribution value of wood defect-prone areas in different regions with the resolution adaptation threshold, calculate the amount of reduction in scanning point spacing and increase in laser power in high-susceptibility areas, calculate the adjustment range of scanning point spacing and the setting range of laser power in medium and low-susceptibility areas, and generate a zoned line laser scanning parameter table; Point cloud acquisition deviation correction module: Calls the partition encoder trigger parameter table and partition line laser scanning parameter table to obtain the real-time encoder trigger step size and real-time line laser scanning angle, calculates the deviation between the real-time encoder trigger step size and the encoder trigger step size reference value, calculates the deviation between the real-time line laser scanning angle and the line laser scanning angle reference value, and generates point cloud acquisition deviation correction coefficient. Defect localization feature extraction module: Based on the point cloud acquisition deviation correction coefficient, it acquires the full-domain point cloud data of the wood, extracts the coordinate parameters and grayscale parameters of the full-domain point cloud data, filters the point cloud data whose coordinate parameters match the distribution values ​​of the wood defect-prone areas, and generates wood defect localization feature values.

[0021] The system includes a wood global parameter acquisition module, an encoder trigger parameter adaptation module, a line laser scanning parameter control module, a point cloud acquisition deviation correction module, and a defect location feature extraction module. The wood defect susceptibility area distribution values ​​include contour overlap partition values, surface roughness deviation partition values, and defect susceptibility probability distribution values. The encoder trigger parameter table includes region encoding information, trigger step size adjustment values, and trigger frequency setting values. The line laser scanning parameter table includes region matching encoding, scanning point spacing setting values, and laser power configuration values. The point cloud acquisition deviation correction coefficient includes trigger step size deviation correction values ​​and scanning angle deviation correction values. The wood defect location feature values ​​include defect area coordinate set, matching point cloud gray value set, and defect boundary feature point set.

[0022] Please see Figure 1 The timber global parameter acquisition module also includes: Parameter acquisition submodule: acquires parameters such as wood profile dimensions, surface roughness, and moisture content, calls the benchmark parameters of wood defect susceptibility characteristics, integrates the acquired parameters and benchmark parameters to form a parameter system, and generates a set of basic parameters for the entire wood domain; The wood profile dimensions were obtained by scanning a 2000mm×300mm×50mm solid wood board with a laser rangefinder. 20 / 6 / 5 measurement points were set in the length / width / thickness directions, and the calculated average values ​​were 1999.8mm, 299.9mm, and 49.8mm, respectively. Surface roughness parameters were obtained by measuring Ra values ​​in 10 selected areas on the wood surface, with an average value of 3.0-3.4μm. Moisture content parameters were obtained, with an average value of 11.7%-12.2% measured at 8 points. The wood defect susceptibility characteristic benchmark parameters were retrieved. These parameters were determined through measurements on 100 groups of defect-free wood. Table 1 lists the corresponding benchmark values. A data matrix was constructed by integrating various collected parameters with the benchmark parameters to form a complete parameter system and generate a comprehensive set of basic parameters for the entire wood surface.

[0023] The benchmark calculation submodule is based on the wood global basic parameter set. It extracts the contour size parameters and performs a coincidence calculation with the benchmark parameters to obtain the coincidence degree. It extracts the surface roughness parameters and performs a deviation calculation with the benchmark parameters to obtain the deviation value. It integrates the calculation data and generates wood defect parameter matching values. Based on the global set of basic parameters for wood, the actual values ​​of the contour dimensions are extracted and their coincidence calculation is performed with the benchmark values ​​of defect susceptibility features. The coincidence degree is calculated as 1 - |actual value - benchmark value| / benchmark value, yielding coincidence degrees of 0.9999, 0.9997, and 0.996 for length, width, and thickness, respectively. The actual value of surface roughness is extracted and its deviation is calculated with the benchmark value of 3.2 μm, yielding a deviation value of -0.2 to 0.2 μm. The coincidence degree of the contour dimensions and the deviation value of the surface roughness are integrated to form a dataset, generating matching values ​​for wood defect parameters.

[0024] Region generation submodule: Based on the matching values ​​of wood defect parameters, combined with the comprehensive calculation of moisture content parameters, the module correlates the degree of overlap, deviation value and moisture content parameter relationship, maps the wood location parameter characteristics, and generates the distribution value of wood defect susceptible areas.

[0025] Based on the matching values ​​of wood defect parameters, a comprehensive calculation is carried out in combination with the moisture content parameter. First, the deviation value of moisture content from the benchmark value of 12.0% is calculated to be -0.3% to 0.2%. Then, the product operation of the contour dimension overlap, surface roughness deviation value and moisture content deviation value is performed to establish the correlation between the three. The wood is divided into 5 regions according to the correlation value range of -0.00006 to 0.00014, and the characteristics of each position parameter are mapped to generate the distribution value of wood defect susceptible areas.

[0026] Please see Figure 1 The encoder trigger parameter adaptation module also includes: Reference value acquisition submodule: acquires the distribution value of wood defect-prone areas, calculates encoder trigger step size and frequency reference values ​​based on its numerical characteristics, and generates a set of partitioned reference parameters; Obtain the distribution values ​​of wood defect-prone areas. Based on their numerical characteristics, calculate the step size baseline value of region 5 as 0.66 mm and region 10.86 mm according to the linear fitting relationship step size baseline value = 0.8 - 1000 × susceptible area distribution value; calculate the frequency baseline value of region 5 as 1515 Hz and region 11163 Hz according to 1000 / step size baseline value. Collect the two baseline values ​​by region to generate the zoning baseline parameter set.

[0027] The adjustment amount calculation submodule: Based on the partition baseline parameter set, it retrieves the distribution value of defect-sensitive areas, calculates the corresponding area encoder trigger step size adjustment amount according to the value, and generates the partition step size adjustment parameter set; Based on the zonal reference parameter set, the distribution value of the wood defect-prone area is retrieved. According to the rule that the step size adjustment amount decreases by 0.02mm for every 0.00002 increase in the distribution value, the encoder trigger step size adjustment amount for each area is calculated. The adjustment amount for area 3 is -0.02mm, and for area 4 it is -0.06mm. The calculation is completed for the entire area in sequence to generate the zonal step size adjustment parameter set.

[0028] The parameter table generation submodule calls two types of parameter sets, integrates numerical information, arranges parameters according to partitioning rules, and generates a partition encoder trigger parameter table.

[0029] The partition reference parameter set and partition step size adjustment parameter set are called, and the two types of parameter values ​​are integrated and arranged according to the susceptible area number. The actual trigger step size is obtained by summing the step size reference value and the adjustment amount. The actual trigger step size is 50.58mm for the area and 10.88mm for the area. The corresponding frequency reference value is retained simultaneously to form a parameter list and generate the partition encoder trigger parameter table.

[0030] Please see Figure 1 The line laser scanning parameter control module also includes: Reference parameter acquisition submodule: acquires the trigger parameter table of the partition encoder and the distribution value of the defect-sensitive area, calculates the line laser scanning point spacing and laser power reference value, and collects the scanning laser reference parameter set; Obtain the trigger parameter table of the partition encoder and the distribution value of the wood defect-prone area. Calculate the area as 50.66mm and the area as 10.86mm based on the reference value of the point spacing = the reference value of the encoder step size. Set the laser power reference value to 25W based on the actual measured 35% laser reflectivity of the wood. Collect the two reference value data sets to obtain the scanning laser reference parameter set.

[0031] Partition parameter calculation submodule: Based on the scanning laser reference parameter set and resolution adaptation threshold, compare the distribution value with the threshold, calculate the parameter correction amount of the high-susceptibility zone, calculate the parameter range of the medium and low-susceptibility zone, and generate a set of partition parameter correction values; Based on the scanning laser reference parameter set and resolution adaptation threshold (the threshold was determined to be 0.00005 through actual measurement), the distribution values ​​of susceptible areas were compared with the threshold. When the distribution values ​​exceeded the threshold, the reduction in the point spacing and the increase in power in high-susceptibility areas were calculated. For area 5, the reduction was 0.42 mm and the increase was 16.1 W. When the threshold was not exceeded, the adjustment range of the point spacing in medium and low-susceptibility areas was calculated to be ±0.05 mm and the power to be 25 W ±3 W, and a set of correction values ​​for the partition parameters was generated.

[0032] The parameter table generation submodule calls two types of parameter sets, collects baseline and correction parameters, integrates data according to partitioning rules, and generates a partitioned line laser scanning parameter table.

[0033] The scanning laser reference parameter set and the partition parameter correction value set are called up, and the reference parameters and correction values ​​of each partition are collected. The calculation data are integrated according to the partition rules. The actual parameters are obtained by subtracting the reduction amount and adding the enhancement amount from the reference value of the high-susceptibility area. The spacing of 5 points in the area is 0.24mm and the power is 41.1W. The values ​​of the medium and low-susceptibility areas are taken according to the range. The spacing of 2 points in the area is 0.80mm and the power is 24W. The data are integrated into a list to generate the partition line laser scanning parameter table.

[0034] Please see Figure 1 The point cloud acquisition deviation correction module also includes: Parameter retrieval submodule: retrieves two types of parameter tables, extracts the real-time encoder trigger step size and laser scanning angle, obtains the corresponding reference values, and generates a real-time reference parameter set; Retrieve the partition encoder trigger parameter table and partition line laser scanning parameter table, extract the real-time encoder trigger step size of 0.78mm and the real-time line laser scanning angle of 89.5° for region 3, obtain the step size reference value of 0.76mm and the angle reference value of 90.0° for this region, and combine the real-time and reference parameters in the step size-angle order to generate the real-time reference parameter set.

[0035] Deviation value calculation submodule: calls the real-time benchmark parameter set, calculates the difference between the real-time and benchmark parameters respectively, completes the two-dimensional difference calculation, and generates two-dimensional deviation values; The real-time reference parameter set is called, and the step size of the real-time encoder is subtracted from the reference step size to calculate the step size deviation value = 0.78 - 0.76 = 0.02 mm; the real-time line laser scanning angle is subtracted from the reference angle to calculate the angle deviation value = 89.5 - 90.0 = -0.5°. The two difference calculations are completed, the two-dimensional data are integrated, and the two-dimensional deviation value is generated.

[0036] Correction coefficient generation submodule: Based on the two-dimensional deviation values, the step size and angle deviation values ​​are weighted and calculated, and combined with the parameter ratio conversion values, the point cloud acquisition deviation correction coefficient is generated.

[0037] Based on the two-dimensional deviation values, the step size and angle deviation values ​​are integrated and weighted. After actual measurement, the step size weight is set to 0.6 and the angle weight is set to 0.4. The weighted deviation = 0.02×0.6+(-0.5)×0.4=-0.188. Combined with the parameter association ratio conversion of 0.5, the correction coefficient = -0.188×0.5=-0.094. The numerical calculation is completed, and the point cloud acquisition deviation correction coefficient is generated.

[0038] Please see Figure 1 The defect location feature extraction module also includes: Point cloud correction and acquisition submodule: Obtain the point cloud acquisition deviation correction coefficient, retrieve the original point cloud data of the wood, correct the acquisition deviation with the correction coefficient, integrate the point data, and generate the full-domain point cloud data of the wood. Obtain the point cloud acquisition deviation correction coefficient, retrieve the original point cloud data of the wood, which contains the three-dimensional coordinates of 10,000 measuring points, and calculate the corrected coordinates using the correction coefficient as follows: corrected coordinates = original coordinates + original coordinates × correction coefficient. For example, the original coordinates (100, 50, 20) are corrected to (90.6, 45.3, 18.12) mm. Integrate all the corrected point data to generate the full-domain point cloud data of the wood.

[0039] Parameter extraction and integration submodule: Based on the full-domain point cloud data of wood, retrieve the spatial and grayscale information of the points, extract the coordinate and grayscale value parameters, collect them to form a parameter system, and generate a full-domain feature parameter set of wood. Based on the global point cloud data of the wood, the spatial location and grayscale sensing information of each point are retrieved. The grayscale value is equal to the reflected light intensity × 10. The coordinate parameters and grayscale value parameters are extracted one by one. The coordinate parameters retain three-dimensional values, and the grayscale value parameters retain integer values. The two types of parameters are collected to construct a point index-type parameter system and generate a global feature parameter set of the wood.

[0040] Defect Feature Generation Submodule: Calls the global feature parameter set, filters data that match the coordinate parameters and distribution values, and integrates the grayscale value parameters to generate wood defect location feature values.

[0041] The system calls up the full-domain feature parameter set of the wood, extracts coordinate parameters and matches them with the distribution values ​​of the wood defect-prone areas. If the coordinate point falls within the susceptible area, a match is determined. The matching parameter data is retained, and combined with the corresponding grayscale value parameters, the system performs one-to-one calculations according to the point location to generate the wood defect location feature value.

[0042] Please see Figure 1 The pipeline collaboration module also includes: Conveying adapter sub-module: Equipped with speed-regulating roller conveyor, pneumatic clamp and encoder to realize uniform speed conveying of wood at 1m / s and synchronous triggering of scanning unit. It can be replaced by chain conveyor line to meet the conveying needs of super heavy logs with a single weight of >50kg. Equipped with a speed-regulating roller conveyor, pneumatic clamps, and encoders, the pneumatic clamps center and hold the wood in place to prevent deviation. The speed-regulating roller conveyor is precisely matched to a conveying speed of 1m / s through frequency conversion control. The encoder collects the wood position signal in real time and generates a trigger signal when the wood reaches the preset area, achieving precise synchronization between scanning and conveying. For ultra-heavy logs weighing more than 50kg, a high-strength chain conveyor line (forged from 45# steel, with a pitch of 200mm) can be used, equipped with a geared motor and torque amplification device to ensure conveying stability and adapt to large log processing scenarios.

[0043] Sorting execution submodule: Equipped with Siemens S7-1200PLC and pneumatic push rod, it can be replaced by a gantry-type truss robot or a hydraulic push rod sorting device to receive the location feature value of wood defects and complete the accurate sorting of qualified and defective wood. Equipped with a Siemens S7-1200 PLC, it receives defect location feature values ​​(defect type, size deviation, etc.) in real time. When a severe crack, knot exceeding the threshold, or size deviation exceeding ±0.01mm is detected, a pneumatic push rod (stroke 150mm, response time ≤0.3s) is driven to complete the sorting. Small and medium-sized processing plants can replace it with a hydraulic push rod (working pressure 10-15MPa). For heavy-duty or high-precision scenarios, it can be replaced with a gantry-type truss robot (repeat positioning accuracy ≤±0.05mm) to achieve classified conveying of qualified and defective wood.

[0044] Central control traceability submodule: integrates industrial touch screen and MySQL database to display test data and equipment operating status in real time, realize test quality traceability, support query test records by wood number and test time, and close-loop adjustment of process parameters.

[0045] It integrates a 10.1-inch high-definition industrial touch screen and a MySQL database to display real-time inspection data (inspection time, wood specifications, defect information, etc.) and equipment operating status; the database adopts a master-slave architecture, stores data in JSON format, and supports multi-condition combined queries; it has a closed-loop adjustment function for process parameters, allowing operators to adjust inspection benchmark parameters and scanning thresholds based on historical data, dynamically optimize the inspection process, and improve accuracy and adaptability.

[0046] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An encoder-triggered line laser sensor-based wood full-area scanning positioning and detection system, characterized in that, The system includes: Wood global parameter acquisition module: acquires wood profile dimensions, surface roughness, and moisture content parameters, calls wood defect susceptibility feature benchmark parameters, calculates the overlap between profile dimension parameters and benchmark parameters, the deviation value between roughness parameters and parameters, and generates wood defect susceptibility area distribution values. Encoder trigger parameter adaptation module: Based on the distribution value of wood defect-prone areas, obtain the encoder trigger reference value, calculate the step size adjustment, and generate a partition encoder trigger parameter table; Line laser scanning parameter control module: Based on the trigger parameter table and distribution value of the partition encoder, obtain the line laser scanning reference value, compare it with the threshold to calculate the adjustment amount, and generate the partition line laser scanning parameter table; Point cloud acquisition deviation correction module: calls the partition encoder trigger parameter table and the line laser scanning parameter table to obtain the real-time trigger step size and scanning angle, calculates the deviation value between the real-time parameters and the reference parameters, and generates the point cloud acquisition deviation correction coefficient. Defect location feature extraction module: Based on the point cloud acquisition deviation correction coefficient, it acquires full-domain point cloud data, extracts parameters, filters matching data, and generates wood defect location feature values. Production line collaboration module: Adapted to conveying single heavy logs, receiving the location feature value of wood defects, completing the accurate sorting of qualified and defective wood, realizing quality traceability, supporting querying test records by wood number and test time, and closed-loop adjustment of process parameters.

2. The encoder-triggered line laser sensor wood full-area scanning positioning and detection system according to claim 1, characterized in that: The system includes a wood global parameter acquisition module, an encoder trigger parameter adaptation module, a line laser scanning parameter control module, a point cloud acquisition deviation correction module, a defect location feature extraction module, and a pipeline collaboration module. The wood defect susceptibility area distribution values ​​include contour overlap partition values, surface roughness deviation partition values, and defect susceptibility probability distribution values. The encoder trigger parameter table includes region encoding information, trigger step size adjustment values, and trigger frequency setting values. The line laser scanning parameter table includes region matching encoding, scanning point spacing setting values, and laser power configuration values. The point cloud acquisition deviation correction coefficient includes trigger step size deviation correction values ​​and scanning angle deviation correction values. The wood defect location feature values ​​include a defect area coordinate set, a matching point cloud grayscale value set, and a defect boundary feature point set.

3. The encoder-triggered line laser sensor wood full-area scanning positioning and detection system according to claim 2, characterized in that: The wood global parameter acquisition module also includes: Parameter acquisition submodule: acquires parameters such as wood profile dimensions, surface roughness, and moisture content, calls the benchmark parameters of wood defect susceptibility characteristics, integrates the acquired parameters and benchmark parameters to form a parameter system, and generates a set of basic parameters for the entire wood domain; The benchmark calculation submodule is based on the wood global basic parameter set. It extracts the contour size parameters and performs a coincidence calculation with the benchmark parameters to obtain the coincidence degree. It extracts the surface roughness parameters and performs a deviation calculation with the benchmark parameters to obtain the deviation value. It integrates the calculation data and generates wood defect parameter matching values. Region generation submodule: Based on the matching values ​​of wood defect parameters, combined with the comprehensive calculation of moisture content parameters, the module correlates the degree of overlap, deviation value and moisture content parameter relationship, maps the wood location parameter characteristics, and generates the distribution value of wood defect susceptible areas.

4. The encoder-triggered line laser sensor wood full-area scanning positioning and detection system according to claim 3, characterized in that: The encoder trigger parameter adaptation module also includes: Reference value acquisition submodule: acquires the distribution value of wood defect-prone areas, calculates encoder trigger step size and frequency reference values ​​based on its numerical characteristics, and generates a set of partitioned reference parameters; The adjustment amount calculation submodule: Based on the partition baseline parameter set, it retrieves the distribution value of defect-sensitive areas, calculates the corresponding area encoder trigger step size adjustment amount according to the value, and generates the partition step size adjustment parameter set; The parameter table generation submodule calls two types of parameter sets, integrates numerical information, arranges parameters according to partitioning rules, and generates a partition encoder trigger parameter table.

5. The encoder-triggered line laser sensor wood full-area scanning positioning and detection system according to claim 4, characterized in that: The line laser scanning parameter control module also includes: Reference parameter acquisition submodule: acquires the trigger parameter table of the partition encoder and the distribution value of the defect-sensitive area, calculates the line laser scanning point spacing and laser power reference value, and collects the scanning laser reference parameter set; Partition parameter calculation submodule: Based on the scanning laser reference parameter set and resolution adaptation threshold, compare the distribution value with the threshold, calculate the parameter correction amount of the high-susceptibility zone, calculate the parameter range of the medium and low-susceptibility zone, and generate a set of partition parameter correction values; The parameter table generation submodule calls two types of parameter sets, collects baseline and correction parameters, integrates data according to partitioning rules, and generates a partitioned line laser scanning parameter table.

6. The encoder-triggered line laser sensor wood full-area scanning positioning and detection system according to claim 2, characterized in that: The point cloud acquisition deviation correction module also includes: Parameter retrieval submodule: retrieves two types of parameter tables, extracts the real-time encoder trigger step size and laser scanning angle, obtains the corresponding reference values, and generates a real-time reference parameter set; Deviation value calculation submodule: calls the real-time benchmark parameter set, calculates the difference between the real-time and benchmark parameters respectively, completes the two-dimensional difference calculation, and generates two-dimensional deviation values; Correction coefficient generation submodule: Based on the two-dimensional deviation values, the step size and angle deviation values ​​are weighted and calculated, and combined with the parameter ratio conversion values, the point cloud acquisition deviation correction coefficient is generated.

7. The encoder-triggered line laser sensor wood full-area scanning positioning and detection system according to claim 2, characterized in that: The defect location feature extraction module also includes: Point cloud correction and acquisition submodule: Obtain the point cloud acquisition deviation correction coefficient, retrieve the original point cloud data of the wood, correct the acquisition deviation with the correction coefficient, integrate the point data, and generate the full-domain point cloud data of the wood. Parameter extraction and integration submodule: Based on the full-domain point cloud data of wood, retrieve the spatial and grayscale information of the points, extract the coordinate and grayscale value parameters, collect them to form a parameter system, and generate a full-domain feature parameter set of wood. Defect Feature Generation Submodule: Calls the global feature parameter set, filters data that match the coordinate parameters and distribution values, and integrates the grayscale value parameters to generate wood defect location feature values.

8. The encoder-triggered line laser sensor wood full-area scanning positioning and detection system according to claim 2, characterized in that: The system also includes a pipeline coordination module, which further includes: Conveying adapter sub-module: Equipped with speed-regulating roller conveyor, pneumatic clamp and encoder to realize uniform speed conveying of wood at 1m / s and synchronous triggering of scanning unit. It can be replaced by chain conveyor line to meet the conveying needs of super heavy logs with a single weight of >50kg. Sorting execution submodule: Equipped with Siemens S7-1200PLC and pneumatic push rod, it can be replaced by a gantry-type truss robot or a hydraulic push rod sorting device to receive the location feature value of wood defects and complete the accurate sorting of qualified and defective wood. Central control traceability submodule: integrates industrial touch screen and MySQL database to display test data and equipment operating status in real time, realize test quality traceability, support query test records by wood number and test time, and close-loop adjustment of process parameters.

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