Construction beam erecting system based on laser detection

Abstract

The present application relates to the technical field of construction beam frame laser detection, and particularly relates to a construction beam frame detection system based on laser detection, which is provided with a feature recognition module, a feature preprocessing module, a feature analysis module and a laser detection adjustment module, acquires point cloud data of a construction beam frame to be detected through the feature recognition module, screens a feature area of the construction beam frame through the feature preprocessing module, determines a beam frame shape tendency category through the feature analysis module, and selects a laser detection adjustment mode through the laser detection adjustment module, which is to adjust a laser incidence direction for laser scanning on a beam frame shape fluctuation area, or to adjust a scanning path and a laser incidence direction of laser scanning, thereby realizing rapid identification of a key area of the construction beam frame, adaptively adjusting a laser detection mode according to a shape tendency of the key area of the construction beam frame, and improving detection efficiency and detection precision of the construction beam frame laser detection.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of construction beam frame laser detection, and in particular to a construction beam frame detection system based on laser detection. BACKGROUND

[0002] In the field of building construction, the beam frame as the key support structure of the building, its quality and safety are directly related to the stability and reliability of the entire building. The traditional beam frame detection method usually relies on manual visual inspection or simple measuring tools, which has many limitations, and it is difficult to find potential defects of the beam frame and problems in some concealed parts. Moreover, the inspection efficiency is low, and for large and complex construction beam frame structures, a large amount of time and manpower is needed, and it is easy to miss. Laser detection technology, as an advanced non-contact detection method, has the advantages of high precision, high speed, high resolution and the ability to obtain a large amount of three-dimensional spatial information, and has gradually been applied in the field of construction beam frame detection.

[0003] However, as the core load-bearing component in the building structure, the form and structure of the construction beam frame are becoming increasingly diversified and complex, and new structures such as special-shaped beam frames and large-span space beam frames are emerging. In the face of construction beam frames with different forms, the system lacks efficient key area identification capability. For example, in a complex beam frame system, the detection accuracy of key areas such as stress concentration points and connection nodes directly affects the overall safety of the beam frame. However, traditional systems are difficult to quickly and accurately lock these areas, resulting in a lack of targeted detection and an increase in invalid scanning time. Existing systems also cannot adaptively adjust the laser detection strategy according to the form trend characteristics of the key areas of the construction beam frame. Therefore, improving the detection efficiency and accuracy of construction beam frame laser detection is a technical problem that needs to be solved.

[0004] For example, Chinese Patent No. CN118089587B discloses a laser plane detection device and method for steel rail laser measurement. The device includes a fine adjustment platform and a verification device. The fine adjustment platform includes a platform base that can be detachably connected to the steel rail, and a rotating member that can rotate. The rotating axis of the rotating member is parallel to the extension direction of the steel rail. The verification device is a box with a light transmission hole and an observation hole, and is internally configured with a reflecting member. The observation hole is inlaid with a receiving screen, which is provided with a scale mark. The verification device can be fixed to the rotating member and can be rotated by the rotating member to multiple calibration positions. The verification device at the calibration position can receive a laser beam through the light transmission hole and reflect the laser beam to the receiving screen through the reflecting member. By rotating, laser beams from different directions are received, and the deviation between different laser beams is displayed through the scale mark.

[0005] The existing technology also has the following problems:

[0006] The prior art does not consider the diversification of the shape and structure of the construction beam frame, and different arc shapes of the arc-shaped beam frame will affect the laser detection accuracy. In the laser detection process of the construction beam frame, the prior art cannot quickly identify the key area of the construction beam frame, cannot adaptively adjust the laser detection mode according to the shape trend of the key area of the construction beam frame, and affects the detection efficiency and detection accuracy of the laser detection of the construction beam frame. SUMMARY

[0007] Therefore, the present application provides a construction beam frame detection system based on laser detection to overcome the problem that the prior art cannot quickly identify the key area of the construction beam frame in the laser detection process of the construction beam frame, cannot adaptively adjust the laser detection mode according to the shape trend of the key area of the construction beam frame, and affects the detection efficiency and detection accuracy of the laser detection of the construction beam frame.

[0008] To achieve the above-mentioned purpose, the present application provides a construction beam frame detection system based on laser detection, comprising:

[0009] a feature recognition module for laser scanning each preset acquisition point of the construction beam frame to be detected to obtain point cloud data;

[0010] a feature preprocessing module connected with the feature recognition module, for dividing the construction beam frame to be detected into a plurality of detection areas, obtaining a beam shape factor according to the point cloud data of the detection areas to determine a beam shape fluctuation parameter, and screening a construction beam feature area according to the beam shape fluctuation parameter;

[0011] a feature analysis module connected with the feature recognition module and the feature preprocessing module, for determining an arc representation coefficient of a feature sub-area according to the normal vector and the laser axis of a plurality of feature sub-areas in the construction beam feature area to determine a beam shape trend category;

[0012] a laser detection adjustment module connected with the feature recognition module, the feature preprocessing module, and the feature analysis module, for selecting a laser detection adjustment mode according to the beam shape trend category, determining a reference normal vector according to a plurality of normal vectors in the beam shape fluctuation area, and adjusting the laser incidence direction for laser scanning the beam shape fluctuation area;

[0013] or, adjusting the scanning path and the laser incidence direction of the laser scanning;

[0014] wherein, the beam shape fluctuation area is determined according to the beam shape factor of the construction beam feature area.

[0015] Further, the feature preprocessing module is used to determine the beam shape fluctuation parameter, wherein,

[0016] The feature preprocessing module determines a plurality of beam face widths in a detection region according to point cloud data, determines a maximum beam face width and a minimum beam face width in the detection region as a first beam frame shape factor and a second beam frame shape factor respectively, calculates a difference value of the first beam frame shape factor and the second beam frame shape factor, and determines the difference value as the beam frame shape fluctuation parameter.

[0017] Further, the feature preprocessing module is configured to screen a construction beam frame feature region, wherein,

[0018] If the beam frame shape fluctuation parameter of the detection region meets a feature region determination condition, the feature preprocessing module screens the detection region as the construction beam frame feature region.

[0019] The feature region determination condition is that the beam frame shape fluctuation parameter exceeds a preset beam frame shape fluctuation reference value.

[0020] Further, the feature analysis module is configured to determine an arc representation coefficient of a feature sub-region, wherein,

[0021] The feature analysis module divides the construction beam frame feature region into a plurality of feature sub-regions, and determines a normal vector and a laser axis of each feature sub-region according to point cloud data.

[0022] An included angle between a vector direction of the normal vector and a direction of the laser axis is calculated, and the included angle is determined as the arc representation coefficient of the feature sub-region.

[0023] Further, the feature analysis module is configured to determine a beam frame shape tendency category, wherein,

[0024] If a plurality of arc representation coefficients in the construction beam frame feature region meet a first beam frame shape tendency determination condition, the feature analysis module determines the construction beam frame feature region as a first beam frame shape tendency category.

[0025] If a plurality of arc representation coefficients in the construction beam frame feature region do not meet the first beam frame shape tendency determination condition, the feature analysis module determines the construction beam frame feature region as a second beam frame shape tendency category.

[0026] The first beam frame shape tendency determination condition is that a variance of the arc representation coefficient does not exceed a preset variance threshold.

[0027] Further, the laser detection adjustment module is configured to select a laser detection adjustment mode according to the beam frame shape tendency category, wherein,

[0028] If the beam shape tendency category is a first beam shape tendency category, the laser detection adjustment module selects a laser detection adjustment mode as determining a reference normal vector according to a plurality of normal vectors in the beam shape fluctuation region, so as to adjust the laser incidence direction of laser scanning on the beam shape fluctuation region.

[0029] If the beam shape tendency category is a second beam shape tendency category, the laser detection adjustment module selects a laser detection adjustment mode as adjusting the scanning path and the laser incidence direction of laser scanning according to a plurality of normal vectors in the construction beam feature region.

[0030] Further, the beam shape fluctuation region is a region surrounded by the line segment on which the first beam shape factor is located, the line segment on which the second beam shape factor is located, and the edge profile in the length direction of the construction beam to be measured.

[0031] The reference normal vector is a vector obtained by adding a plurality of normal vectors in the beam shape fluctuation region.

[0032] Further, the laser detection adjustment module is used to adjust the laser incidence direction of laser scanning on the beam shape fluctuation region, and the laser incidence direction is a parallel direction of the reference normal vector of the beam shape fluctuation region.

[0033] Further, the laser detection adjustment module is used to adjust the scanning path, wherein,

[0034] The scanning path is a path of scanning the feature sub-regions in the order of the angle values.

[0035] The angle is an angle calculated by the laser detection adjustment module between the normal vector in the construction beam feature region and the horizontal direction.

[0036] Further, the laser detection adjustment module is used to adjust the laser incidence direction of laser scanning on the feature sub-region, and the laser incidence direction is a parallel direction of the normal vector of the feature sub-region.

[0037] Compared with the prior art, the present application has the beneficial effects that the present application is provided with a feature recognition module, a feature preprocessing module, a feature analysis module, and a laser detection adjustment module, the point cloud data of the construction beam frame to be detected is obtained through the feature recognition module, the beam frame shape factor is obtained according to the point cloud data of the detection area through the feature preprocessing module to determine the beam frame shape fluctuation parameter, the construction beam frame feature area is screened, the radian representation coefficient of the feature sub-area is determined according to the normal vector and the laser axis of the feature sub-area in the construction beam frame feature area through the feature analysis module to determine the beam frame shape tendency category, the laser detection adjustment mode is selected through the laser detection adjustment module, that is, the reference normal vector is determined according to the normal vector in the beam frame shape fluctuation area to adjust the laser incidence direction of the laser scanning on the beam frame shape fluctuation area, or the scanning path and the laser incidence direction of the laser scanning are adjusted according to the normal vector in the construction beam frame feature area, thereby realizing the rapid identification of the key area of the construction beam frame in the construction beam frame laser detection process, adaptively adjusting the laser detection mode according to the shape tendency of the key area of the construction beam frame, and improving the detection efficiency and detection accuracy of the construction beam frame laser detection.

[0038] Especially, the construction beam frame feature area is screened according to the beam frame shape fluctuation parameter through the feature preprocessing module, and it can be understood that the construction beam frame feature area is the structure stress concentration and damage prone position, the potential damage can be effectively identified and evaluated more targetedly by screening the construction beam frame feature area, the detection efficiency is optimized, the detection time and detection resources are saved, and the detection efficiency can be significantly improved for large and complex construction beam frame structures in actual engineering, the construction beam frame feature area is screened according to the beam frame shape fluctuation parameter through the feature preprocessing module, thereby realizing the rapid identification of the key area of the construction beam frame in the construction beam frame laser detection process, and improving the detection efficiency and detection accuracy of the construction beam frame laser detection.

[0039] Especially, the application determines the beam shape tendency category according to the comparison of the arc representation coefficients in the characteristic region of the construction beam by the feature analysis module. It can be understood that the arc representation coefficient is the angle between the normal vector of the feature sub-region and the laser axis, representing the local curvature of the feature sub-region. The greater the variance of the arc representation coefficients of the characteristic region of the construction beam, the more obvious the curvature fluctuation of the characteristic region of the construction beam. The smaller the variance of the arc representation coefficients of the characteristic region of the construction beam, the less obvious the curvature fluctuation of the characteristic region of the construction beam. The more consistent the curvature of each feature sub-region, the detection accuracy of determining the beam shape tendency category can be improved. For different beam shape tendency categories, targeted detection adjustment is carried out to improve detection efficiency while ensuring detection accuracy and optimize overall detection accuracy. The application determines the beam shape tendency category according to the comparison of the arc representation coefficients in the characteristic region of the construction beam by the feature analysis module, and then realizes classification according to the shape trend of the key region of the construction beam in the laser detection process of the construction beam, improving the detection efficiency and accuracy of the laser detection of the construction beam.

[0040] Especially, under the condition of the first beam shape tendency category, the reference normal vector is determined according to the normal vectors in the beam shape fluctuation region to adjust the laser incidence direction for laser scanning of the beam shape fluctuation region. It can be understood that the first beam shape tendency category is that the surface curvature of the characteristic region of the construction beam changes gently. In this region, the region with beam width change is marked as the beam shape fluctuation region according to the beam width. The incidence angle is determined by calculating the normal vector vector sum of the beam shape fluctuation region, which can better adapt to the shape change in the region and ensure that the laser scanning can be carried out along the best direction, so as to more accurately capture the detailed information of the region, which also helps to improve the quality of the scanning data, reduce the noise and deviation in the data, and make the obtained data more truly reflect the actual situation of the beam shape fluctuation region. High-quality data is crucial for subsequent three-dimensional reconstruction, structure analysis and other work, which can improve the reliability and accuracy of the analysis results. Under the condition of the first beam shape tendency category, the reference normal vector is determined according to the normal vectors in the beam shape fluctuation region to adjust the laser incidence direction for laser scanning of the beam shape fluctuation region, and then the laser detection method is adaptively adjusted according to the shape trend of the key region of the construction beam in the laser detection process of the construction beam, improving the detection efficiency and accuracy of the laser detection of the construction beam.

[0041] Especially, under the condition of the second beam shape tendency category, the scanning path and the laser incidence direction of the laser scanning are adjusted according to the normal vectors in the characteristic region of the construction beam, and it can be understood that the surface curvature of the second beam shape tendency category, that is, the characteristic region of the construction beam, changes obviously, and the vector directions of the normal vectors of different characteristic sub-regions are relatively inconsistent. When the laser incidence direction is parallel to the vector direction of the normal vector, the reflection efficiency of the laser energy is the highest, the reflected signal is the strongest and the most stable. In order to accurately obtain the laser detection value of the region with obvious surface curvature change, the laser incidence direction needs to be adjusted according to the normal vector of each characteristic sub-region. However, frequent and large changes in the laser incidence direction will introduce noise, causing fluctuations or errors in the obtained data. Adjusting the scanning path of the laser scanning according to the normal vectors can effectively avoid frequent and large changes in the laser incidence direction, reduce such noise interference, improve the accuracy and reliability of the data, and make the measured beam surface characteristics more truly reflect the actual shape, thereby providing a more comprehensive and accurate data basis for subsequent beam shape analysis and defect detection. Under the condition of the second beam shape tendency category, the scanning path and the laser incidence direction of the laser scanning are adjusted according to the normal vectors in the characteristic region of the construction beam, and then, in the laser detection process of the construction beam, the laser detection mode is adaptively adjusted according to the shape tendency of the key region of the construction beam, thereby improving the detection efficiency and detection accuracy of the laser detection of the construction beam. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 The functional block diagram of the construction beam detection system based on laser detection of the embodiment of the present application is shown in the figure.

[0043] Figure 2 The logic flow chart of the characteristic preprocessing module for screening the characteristic region of the construction beam is shown in the figure.

[0044] Figure 3 The logic flow chart of the characteristic analysis module for determining the beam shape tendency category is shown in the figure.

[0045] Figure 4 The logic flow chart of the laser detection adjustment module for selecting the laser detection adjustment mode is shown in the figure. DETAILED DESCRIPTION

[0046] In order to make the purpose and advantages of the present application more clear and explicit, the present application will be further described below in combination with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present application, and do not limit the protection scope of the present application.

[0047] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application, and are not intended to limit the protection scope of the present application.

[0048] It should be noted that in the description of the present application, the terms indicating the direction or position relationship of "upper", "lower", "inner", "outer" and the like are based on the direction or position relationship shown in the drawings, which is only for the convenience of description, and does not indicate or imply that the device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the present application.

[0049] In addition, it should be noted that in the description of the present application, unless otherwise explicitly specified and limited, the terms "mounting", "connection" should be understood broadly, for example, it can be fixed connection, or detachable connection, or integral connection; it can be mechanical connection, or electrical connection; it can be direct connection, or indirect connection through intermediate medium, or internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0050] Please refer to Figure 1 The figure is a function block diagram of the construction beam frame detection system based on laser detection according to the embodiment of the present application, and the construction beam frame detection system based on laser detection of the present application comprises:

[0051] A feature recognition module is used to perform laser scanning on each preset acquisition point of the construction beam frame to be detected to obtain point cloud data of the construction beam frame to be detected.

[0052] Specifically, the specific structure of the feature recognition module is not limited in the present application, and preferably, it can be a three-dimensional laser scanner. The distance from the target point to the scanner is calculated by emitting a laser beam and measuring the time from emission to reflection, and the three-dimensional coordinates of the target point are determined by combining the angle information of the scanner. Here, no further description is given.

[0053] Specifically, the preset acquisition point can be set by those skilled in the art according to the detection accuracy of the construction beam frame. The higher the accuracy requirement, the smaller the interval distance of the preset acquisition point. The interval distance can be 30 cm.

[0054] A feature preprocessing module is connected with the feature recognition module, and is used to divide the construction beam frame to be detected into a plurality of detection regions, obtain beam frame shape factor according to the point cloud data of the detection region, determine beam frame shape fluctuation parameter, and screen construction beam frame feature region according to the beam frame shape fluctuation parameter.

[0055] Specifically, the specific structure of the feature preprocessing module is not limited in the present application, preferably, it can be a microprocessor, used to divide the detection area, determine the beam shape fluctuation parameter, and screen the construction beam feature area, which will not be repeated here.

[0056] Specifically, the division size of the detection area can be set by the skilled person according to the detection accuracy of the construction beam, the higher the accuracy requirement, the smaller the division size of the detection area, preferably, the division size of the detection area can be 2m*2m.

[0057] The feature analysis module is connected with the feature recognition module and the feature preprocessing module respectively, used to determine the radian representation coefficient of the feature sub-area according to the normal vector and the laser axis of the several feature sub-areas in the construction beam feature area, and determine the beam shape tendency category according to the comparison of the several radian representation coefficients in the construction beam feature area;

[0058] Specifically, the specific structure of the feature analysis module is not limited in the present application, preferably, it can be a processor used in a computer, used to determine the normal vector and the laser axis according to the point cloud data, so as to determine the beam shape tendency category, which will not be repeated here.

[0059] The laser detection adjustment module is connected with the feature recognition module, the feature preprocessing module, and the feature analysis module respectively, used to select the laser detection adjustment mode according to the beam shape tendency category, to determine the reference normal vector according to the several normal vectors in the beam shape fluctuation area, so as to adjust the laser incidence direction of the laser scanning on the beam shape fluctuation area;

[0060] Or, adjust the scanning path and the laser incidence direction of the laser scanning according to the several normal vectors in the construction beam feature area;

[0061] Wherein, the beam shape fluctuation area is determined according to the beam shape factor of the construction beam feature area.

[0062] Specifically, the specific structure of the laser detection adjustment module is not limited in the present application, preferably, it can be a programmable logic controller, used to select the laser detection adjustment mode, and control the feature recognition module to adjust the laser incidence direction and the scanning path of the laser scanning, which will not be repeated here.

[0063] Specifically, the feature preprocessing module is used to determine the beam shape fluctuation parameter, wherein,

[0064] The feature preprocessing module determines a plurality of beam face widths in a detection region according to point cloud data, determines a maximum beam face width and a minimum beam face width in the detection region as a first beam frame shape factor and a second beam frame shape factor respectively, calculates a difference value of the first beam frame shape factor and the second beam frame shape factor, and determines the difference value as the beam frame shape fluctuation parameter.

[0065] Specifically, the point cloud data of the detection region can be preprocessed by denoising and normalization, the point cloud can be segmented, and the beam face boundary can be determined to obtain the beam face width value, which will not be described here.

[0066] Referring to FIG. 1, Figure 2 FIG. 1 is a logic flow diagram of a feature preprocessing module screening a construction beam frame feature region according to an embodiment of the present application, and the feature preprocessing module is used to screen the construction beam frame feature region, wherein,

[0067] If the beam frame shape fluctuation parameter of the detection region meets the feature region determination condition, the feature preprocessing module screens the detection region as the construction beam frame feature region;

[0068] If the beam frame shape fluctuation parameter of the detection region does not meet the feature region determination condition, the feature preprocessing module does not screen the detection region;

[0069] The feature region determination condition is that the beam frame shape fluctuation parameter exceeds a preset beam frame shape fluctuation reference value.

[0070] Specifically, the preset beam frame shape fluctuation reference value is the product of the average value of the beam frame shape fluctuation parameter and a fluctuation factor, and the fluctuation factor can be set by a person skilled in the art according to the detection accuracy of the construction beam frame. The higher the accuracy requirement, the smaller the fluctuation factor. The value range of the fluctuation factor can be [0.5, 0.7], and preferably, the fluctuation factor can be 0.6.

[0071] Specifically, the feature preprocessing module screens the construction beam frame feature region according to the beam frame shape fluctuation parameter, and it can be understood that the construction beam frame feature region is a structure stress concentration and damage prone position. By screening the construction beam frame feature region, potential damage can be effectively identified and evaluated more targetedly, and these key regions can be detected more carefully to optimize the detection efficiency, save detection time and detection resources, and significantly improve the detection efficiency of large and complex construction beam frame structures in actual engineering. The feature preprocessing module screens the construction beam frame feature region according to the beam frame shape fluctuation parameter, and further, realizes the rapid identification of the key region of the construction beam frame in the construction beam frame laser detection process, and improves the detection efficiency and detection accuracy of the construction beam frame laser detection.

[0072] Specifically, it can be understood that the beam frame morphology fluctuation parameter is the change degree of the beam width in the detection area, the larger the beam frame morphology fluctuation parameter is, the greater the change of the beam width in the detection area is, the construction beam characteristic region, that is, the region where the beam width suddenly changes, the sudden change of the beam width will cause the sudden change of the structure geometry, under the action of the load, the force transmission path will change, so that the construction beam characteristic region is prone to stress concentration phenomenon, which will cause cracks in the concrete, and the stress of the steel bar will also be uneven, thereby affecting the bearing capacity and durability of the beam, at the same time, due to the existence of the load, the deformation of the construction beam characteristic region under the load is different from that of other regions, and local distortion, bending and other problems are prone to occur, so that the region is screened out for more accurate detection to timely find potential abnormal phenomena, and the application realizes rapid identification of the key region of the construction beam in the construction beam laser detection process, and improves the detection efficiency and detection precision of the construction beam laser detection.

[0073] Specifically, the feature analysis module is used to determine the radian representation coefficient of the feature sub-region, wherein,

[0074] The feature analysis module divides the construction beam characteristic region into a plurality of feature sub-regions, and determines the normal vector and the laser axis of each feature sub-region according to the point cloud data.

[0075] The angle between the vector direction of the normal vector and the direction of the laser axis is calculated, and the angle is determined as the radian representation coefficient of the feature sub-region.

[0076] Specifically, the feature sub-region contains a preset acquisition point for laser scanning, and the division size of the feature sub-region can be 30cm*30cm.

[0077] Specifically, the normal vector of each feature sub-region can be determined by the local surface fitting method, preferably, the least square method can be used to fit the local plane, and the normal vector is obtained by solving the linear equation set, which will not be repeated here.

[0078] Specifically, the laser axis can be determined by the point cloud distribution, the point cloud data obtained is preprocessed, the center of gravity, the main direction and other features of the point cloud are calculated to determine the direction of the laser axis, which will not be repeated here.

[0079] Please refer to Figure 3 The feature analysis module is used to determine the beam frame morphology tendency category, wherein,

[0080] If the several arc representation coefficients in the construction beam frame feature region meet the first beam frame shape tendency determination condition, the feature analysis module determines the construction beam frame feature region as the first beam frame shape tendency category;

[0081] If the several arc representation coefficients in the construction beam frame feature region do not meet the first beam frame shape tendency determination condition, the feature analysis module determines the construction beam frame feature region as the second beam frame shape tendency category;

[0082] The first beam frame shape tendency determination condition is that the arc representation coefficient variance does not exceed a preset variance threshold.

[0083] Specifically, the preset variance threshold can be set by a person skilled in the art according to the detection accuracy of the construction beam frame, the higher the accuracy requirement, the larger the variance threshold, and the value range of the variance threshold can be [0.1, 0.3], preferably, the variance threshold can be 0.2.

[0084] Specifically, the feature analysis module determines the beam frame shape tendency category according to the comparison of the several arc representation coefficients in the construction beam frame feature region, it can be understood that the arc representation coefficient is the angle between the normal vector of the feature sub-region and the laser axis, which represents the local curvature of the feature sub-region, the larger the variance of the arc representation coefficients in the construction beam frame feature region, the more obvious the curvature fluctuation of the construction beam frame feature region, the smaller the variance of the arc representation coefficients in the construction beam frame feature region, the less obvious the curvature fluctuation of the construction beam frame feature region, the more consistent the curvature of each feature sub-region, determining the beam frame shape tendency category can improve the detection accuracy, and for different beam frame shape tendency categories, targeted detection adjustment is performed, which improves the detection efficiency while ensuring the detection accuracy, and optimizes the overall detection accuracy, the feature analysis module determines the beam frame shape tendency category according to the comparison of the several arc representation coefficients in the construction beam frame feature region, and then, the construction beam frame laser detection process is classified according to the shape tendency of the key region of the construction beam frame, and the detection efficiency and detection accuracy of the construction beam frame laser detection are improved.

[0085] Please refer to Figure 4 Fig. 2 is a logic flow chart of the laser detection adjustment module selecting a laser detection adjustment mode according to the beam frame shape tendency category, the laser detection adjustment module is used to select a laser detection adjustment mode according to the beam frame shape tendency category, wherein,

[0086] If the beam frame shape tendency category is the first beam frame shape tendency category, the laser detection adjustment module selects the laser detection adjustment mode as determining a reference normal vector according to the several normal vectors in the beam frame shape fluctuation region to adjust the laser incidence direction for laser scanning of the beam frame shape fluctuation region;

[0087] If the beam shape tendency category is a second beam shape tendency category, the laser detection adjustment module selects a laser detection adjustment mode as adjusting the scanning path and the laser incidence direction of the laser scanning according to the normal vectors in the construction beam feature region.

[0088] Specifically, the beam shape fluctuation region is a region surrounded by the edge profile in the length direction of the first beam shape factor line segment, the second beam shape factor line segment, and the construction beam.

[0089] The reference normal vector is a vector obtained by adding the normal vectors in the beam shape fluctuation region.

[0090] Specifically, the laser detection adjustment module is used to adjust the laser incidence direction of the laser scanning on the beam shape fluctuation region, and the laser incidence direction is the parallel direction of the reference normal vector of the beam shape fluctuation region.

[0091] Specifically, under the condition of the first beam shape tendency category, the reference normal vector is determined according to the normal vectors in the beam shape fluctuation region to adjust the laser incidence direction of the laser scanning on the beam shape fluctuation region. It can be understood that the first beam shape tendency category is that the surface curvature of the construction beam feature region changes gently. In this region, the region with a change in beam width is marked as a beam shape fluctuation region according to the beam width. The incidence angle is determined by calculating the vector sum of the normal vectors of the beam shape fluctuation region. This can better adapt to the shape change in the region, ensure that the laser scanning can be performed along the optimal direction, and thus more accurately capture the detailed information of the region. This also helps to improve the quality of the scanning data, reduce noise and deviation in the data, and make the obtained data more truly reflect the actual situation of the beam shape fluctuation region. High-quality data is crucial for subsequent three-dimensional reconstruction, structural analysis, and other work, and can improve the reliability and accuracy of the analysis results. Under the condition of the first beam shape tendency category, the reference normal vector is determined according to the normal vectors in the beam shape fluctuation region to adjust the laser incidence direction of the laser scanning on the beam shape fluctuation region. Furthermore, the laser detection mode is adjusted adaptively according to the shape tendency of the key region of the construction beam during the construction beam laser detection process, and the detection efficiency and detection accuracy of the construction beam laser detection are improved.

[0092] Specifically, it can be understood that when the laser incidence direction is parallel to the normal vector of the beam shape fluctuation region, the laser beam is perpendicular to the surface of the region, which can ensure that the distance from the emission point to the beam surface is most accurately measured during laser propagation, because the path of laser propagation is the shortest when the incidence is perpendicular, and there is no distance measurement deviation caused by the inclination of the incidence angle, thereby improving the accuracy of distance measurement of each point of the beam shape fluctuation region, which helps to accurately obtain the geometric shape and size information of the beam, and the vertically incident laser can reduce data noise and interference caused by reflection, refraction and scattering, etc. When the laser is parallel to the normal vector of the beam surface, the direction of the reflected light is relatively stable and easy to predict, which facilitates the sensor to accurately receive the reflected light signal, thereby improving the signal-to-noise ratio and stability of the data. High-quality data is crucial for accurately analyzing the shape, structure and potential defects of the beam, which can reduce the error and uncertainty of subsequent data analysis, and further, the laser detection mode is adaptively adjusted during the construction beam laser detection process, improving the detection efficiency and detection accuracy of the construction beam laser detection.

[0093] Specifically, the laser detection adjustment module is used to adjust the scanning path, wherein,

[0094] The scanning path is a path for scanning the feature sub-regions according to the order of the angle values.

[0095] The angle is the angle between the normal vector of the feature region of the construction beam and the horizontal direction calculated by the laser detection adjustment module.

[0096] Specifically, the feature sub-regions are sorted according to the order of the angle values, the scanning path is a forward order of the feature sub-regions or a reverse order of the feature sub-regions, the forward order of the feature sub-regions is sorted according to the order of the angle values from small to large, and the reverse order of the feature sub-regions is sorted according to the order of the angle values from large to small.

[0097] Specifically, the laser detection adjustment module is used to adjust the laser incidence direction for laser scanning of the feature sub-regions, and the laser incidence direction is parallel to the normal vector of the feature sub-regions.

[0098] Specifically, under the condition of the second beam frame morphology tendency category, the scanning path and the laser incidence direction of the laser scanning are adjusted according to the normal vectors in the characteristic region of the construction beam frame, and it can be understood that the surface curvature of the second beam frame morphology tendency category, that is, the characteristic region of the construction beam frame, changes obviously, and the vector directions of the normal vectors of different characteristic sub-regions are relatively inconsistent. When the laser incidence direction is parallel to the vector direction of the normal vector, the reflection efficiency of the laser energy is the highest, the reflected signal is the strongest and the most stable. In order to accurately obtain the laser detection value of the region with obvious surface curvature change, the laser incidence direction needs to be adjusted according to the normal vector of each characteristic sub-region. However, frequent and large changes in the laser incidence direction will introduce noise, causing fluctuations or errors in the obtained data. Adjusting the scanning path of the laser scanning according to the normal vectors can effectively avoid frequent and large changes in the laser incidence direction, reduce such noise interference, improve the accuracy and reliability of the data, and make the measured beam frame surface characteristics more truly reflect its actual morphology, providing a more comprehensive and accurate data basis for subsequent beam frame morphology analysis and defect detection. Under the condition of the second beam frame morphology tendency category, the scanning path and the laser incidence direction of the laser scanning are adjusted according to the normal vectors in the characteristic region of the construction beam frame, and then, in the laser detection process of the construction beam frame, the laser detection mode is adaptively adjusted according to the morphology tendency of the key region of the construction beam frame, and the detection efficiency and detection accuracy of the laser detection of the construction beam frame are improved.

[0099] So far, the technical solutions of the present application have been described in combination with the preferred embodiments shown in the drawings, but those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to related technical features without departing from the principles of the present application, and the technical solutions after such changes or replacements will fall within the protection scope of the present application.

[0100] The above description is only the preferred embodiments of the present application and is not intended to limit the present application. Those skilled in the art can make various changes and modifications to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A construction beam inspection system based on laser detection, characterized in that, include: The feature recognition module is used to perform laser scanning on each preset collection point of the beam frame to be tested to obtain point cloud data; The feature preprocessing module, which is connected to the feature recognition module, is used to divide the construction beam frame to be tested into several detection areas, obtain beam frame morphology factors based on the point cloud data of the detection areas to determine beam frame morphology fluctuation parameters, and filter construction beam frame feature areas based on the beam frame morphology fluctuation parameters. The feature preprocessing module is used to determine the beam frame shape fluctuation parameters. The feature preprocessing module determines several beam surface widths within the detection area based on point cloud data, determines the maximum and minimum beam surface widths within the detection area as the first beam frame shape factor and the second beam frame shape factor, respectively, calculates the difference between the first beam frame shape factor and the second beam frame shape factor, and determines the difference as the beam frame shape fluctuation parameters. The feature analysis module is connected to the feature recognition module and the feature preprocessing module respectively. It is used to determine the curvature characterization coefficient of the feature sub-regions based on the normal vectors of several feature sub-regions and the laser axis within the feature area of ​​the construction beam frame, so as to determine the beam frame shape tendency category. The laser detection and adjustment module is connected to the feature recognition module, the feature preprocessing module, and the feature analysis module, respectively. It is used to select the laser detection and adjustment method according to the beam shape tendency category, which is to determine the reference normal vector based on several normal vectors in the beam shape fluctuation area, so as to adjust the laser incident direction for laser scanning of the beam shape fluctuation area. Alternatively, adjust the scanning path and laser incident direction of the laser scan; The beam frame shape fluctuation region is determined based on the beam frame shape factor of the characteristic region of the construction beam frame.

2. The laser-based construction beam inspection system according to claim 1, characterized in that, The feature preprocessing module is used to filter feature regions of the construction beam frame, wherein... If the beam shape fluctuation parameters in the detection area meet the characteristic area determination conditions, the feature preprocessing module will filter the detection area as a construction beam characteristic area. The condition for determining the characteristic region is that the beam shape fluctuation parameter exceeds the preset beam shape fluctuation reference value.

3. The laser-based construction beam inspection system according to claim 2, characterized in that, The feature analysis module is used to determine the radian characterization coefficient of the feature sub-region. in, The feature analysis module divides the feature region of the construction beam frame into several feature sub-regions, and determines the normal vector and laser axis of each feature sub-region based on point cloud data. Calculate the angle between the direction of the normal vector and the direction of the laser axis, and determine the angle as the radian characterization coefficient of the feature sub-region.

4. The laser-based construction beam inspection system according to claim 3, characterized in that, The feature analysis module is used to determine the beam frame morphology tendency category, wherein, If several arc characterization coefficients within the characteristic area of ​​the construction beam frame meet the first beam frame shape tendency determination conditions, the feature analysis module will determine the characteristic area of ​​the construction beam frame as the first beam frame shape tendency category. If several arc characterization coefficients within the characteristic area of ​​the construction beam frame do not meet the first beam frame shape tendency determination conditions, the feature analysis module will determine the characteristic area of ​​the construction beam frame as the second beam frame shape tendency category. The first beam frame shape tendency determination condition is that the variance of the curvature characterization coefficient does not exceed a preset variance threshold.

5. The laser-based construction beam inspection system according to claim 4, characterized in that, The laser detection and adjustment module is used to select the laser detection and adjustment method according to the beam frame shape and orientation category. If the beam shape tendency category is the first beam shape tendency category, the laser detection and adjustment module selects the laser detection and adjustment method as determining the reference normal vector based on several normal vectors in the beam shape fluctuation area, so as to adjust the laser incident direction for laser scanning of the beam shape fluctuation area. If the beam shape tendency category is the second beam shape tendency category, then the laser detection adjustment module selects the laser detection adjustment method as adjusting the scanning path and laser incident direction of the laser scan according to several normal vectors in the characteristic area of ​​the construction beam.

6. The laser-based construction beam inspection system according to claim 5, characterized in that, The beam frame morphology fluctuation area is the area enclosed by the line segment of the first beam frame morphology factor, the line segment of the second beam frame morphology factor, and the edge contour in the length direction of the construction beam frame to be measured within the characteristic area of ​​the construction beam frame; The reference normal vector is the vector obtained by adding several normal vectors within the fluctuating region of the beam frame shape.

7. The laser-based construction beam inspection system according to claim 6, characterized in that, The laser detection and adjustment module is used to adjust the laser incident direction for laser scanning of the beam frame shape fluctuation area. The laser incident direction is parallel to the reference normal vector of the beam frame shape fluctuation area.

8. The construction beam inspection system based on laser detection according to claim 7, characterized in that, The laser detection and adjustment module is used to adjust the scanning path, wherein... The scanning path is a path that scans the feature sub-regions containing the included angle in order of sorting by the size of the included angle value; The included angle is the angle between the normal vector within the characteristic area of ​​the construction beam frame calculated by the laser detection and adjustment module and the horizontal plane direction.

9. The laser-based construction beam inspection system according to claim 8, characterized in that, The laser detection adjustment module is used to adjust the laser incident direction for laser scanning of the feature sub-region, wherein the laser incident direction is parallel to the normal vector of the feature sub-region.

Images