Unmanned aerial vehicle building wall surface detection system and method based on dynamic coordinate identification

Abstract

The invention discloses an unmanned aerial vehicle building wall surface detection system and method based on dynamic coordinate recognition, and relates to the technical field of building detection, the system comprises a ground control station, an unmanned aerial vehicle body, a coordinate recognition mechanism, a coordinate positioning mechanism and a detection mechanism, the detection mechanism is arranged at the top of the unmanned aerial vehicle body, and the coordinate positioning mechanism is arranged at the bottom of the unmanned aerial vehicle body; the coordinate recognition mechanism comprises a workbench, height-adjustable supporting legs, a first tilt angle sensor and a photoelectric sensor, the unmanned aerial vehicle body is provided with a second tilt angle sensor and a controller, and the control system and the controller are each provided with a timing module. The control system comprehensively compares time information of the two timing modules, wall surface information and height information collected by the detection mechanism and coordinate information recognized by the coordinate recognition mechanism, screening of wall surface detection information is achieved, and a perpendicularity curve and a flatness graph of the wall surface are drawn according to qualified data obtained after screening.

Description

Technical Field

[0001] The present invention relates to the technical field of building detection, and in particular to a drone building wall detection system and method based on dynamic coordinate recognition. Background Art

[0002] The existing invention patent CN117470127B discloses a drone building wall detection system and method based on dynamic coordinate recognition, which relates to the field of building detection technology, including a ground control station, a coordinate positioning mechanism, and a drone body. The belly of the drone body is provided with a coordinate correction auxiliary mechanism used in conjunction with the coordinate positioning mechanism. The back of the drone body is provided with a fixing plate in the longitudinal direction, and a plurality of first laser ranging sensors are arranged in a matrix at the front end of the fixing plate. The first laser ranging sensor is electrically connected to the controller of the drone body through a wire. The drone body is connected to the ground control station signal through a wireless signal transceiver. The ground control station is used to control the flight and landing of the drone, and draw the verticality curve and wall flatness graph of the wall according to the data signal transmitted by the drone body. The invention realizes the drone wall deformation detection of high-rise buildings by correcting the drone's aerial coordinates. The detection results are accurate and reliable, providing a reference for engineering practice.

[0003] This invention solves the problem that when drones measure building walls from the air, their own position is unstable, which leads to low measurement accuracy. However, the following problems still exist: 1. Although this patent can solve the problem of unstable position by coordinate correction, it cannot really solve the trouble caused by airflow and vibration. In practical applications, the difficulty of this patent lies in the need to accurately locate an object flying in the air flow within a set coordinate system. It is understandable that as the drone's altitude increases, the factors affecting the airflow will become more and more obvious. In some narrow gaps between buildings, a relatively fast airflow will be generated due to the narrow tube wind gathering effect. In severe windy weather, the airflow will also be very fast. As the airflow speeds up and the wind force increases, it is difficult for the drone body to find its own accurate measurement position through coordinate correction; 2. Paragraph 0013 of the document records the method of coordinate correction - "When correcting the coordinate position of the drone body, firstly project the measurement light of the third laser ranging sensor onto the third positioning point, so that the drone body hovers at the indicated point. The height is determined; then, the measuring light of the four second laser ranging sensors is located at the specified angle position stored in the database at the height of point A by adjusting the extension and contraction amount of the electric cylinder; the drone body is rotated horizontally by a small amplitude, so that the measuring light of the four second laser ranging sensors is projected on the corresponding first marking point or the second marking point respectively; when the detection data of the four second laser ranging sensors is consistent with the corresponding data in the database, it means that the coordinate position and posture of the drone are corrected, and at the same time, several first laser ranging sensors complete the wall distance data collection. "It can be seen that the coordinate correction of the invention is not only difficult to operate, but also the operation steps are cumbersome, which will reduce the detection efficiency of the drone for the wall and affect the progress of the project.

[0004] In view of the problems that the invention is difficult to correct coordinates under the influence of airflow, and the detection operation is cumbersome and inefficient, it is necessary to improve the existing technology. Summary of the invention

[0005] The present invention provides a drone building wall detection system and method based on dynamic coordinate recognition, with the purpose of solving the problems described in the background technology parts 1 and 2. The present invention changes the idea of ​​accurately correcting the drone coordinates and making the drone stationary at the set coordinate position before performing wall verticality and flatness detection, realizes dynamic coordinate recognition of the detection mechanism in the dynamic adjustment of the drone, completes the collection of wall detection data in the process of identifying the coordinates, thereby greatly reducing the difficulty of coordinate positioning of the detection mechanism, and can be applied to detection environments with large airflow, overcome the influence of its own vibration factors, and improve detection efficiency.

[0006] To achieve the above object, the technical solution of the present invention is: A drone building wall detection system based on dynamic coordinate recognition comprises a ground control station, a drone body, a coordinate recognition mechanism, a coordinate positioning mechanism, and a detection mechanism. The detection mechanism is provided on the top of the drone body, and the coordinate positioning mechanism is provided on the bottom. The coordinate recognition mechanism comprises a workbench, and an adjustable height support leg is provided at the bottom of the workbench. A first inclination sensor is installed at the bottom of the workbench, and a plurality of photoelectric sensors for receiving laser signals are arranged in a matrix at the top of the workbench. The area of ​​the matrix is ​​larger than the displacement range caused by the wind force or the self-vibration of the drone body when it is hovering under a set wind force. The coordinate positioning mechanism is used in conjunction with the coordinate recognition mechanism. The photoelectric sensor, the first inclination sensor, and the adjustable height support leg are respectively connected to the ground control station through wires. The control system of the station is electrically connected, the UAV body is provided with a second inclination sensor and a controller, the second inclination sensor, the detection mechanism, and the coordinate positioning mechanism are respectively connected to the controller signal through wires, the controller is electrically connected to the airborne power supply of the UAV body, the controller is configured to control the flight posture of the UAV body, the controller is connected to the control system signal through a wireless signal transceiver, the control system and the controller are both provided with a timing module, the control system performs a comprehensive comparison of the time information of the two timing modules, the wall distance information and height information collected by the detection mechanism, and the coordinate information identified by the coordinate identification mechanism, so as to realize the screening of the wall detection information, and draw the verticality curve and flatness graph of the wall according to the qualified data obtained after the screening.

[0007] Preferably, the workbench is a cubic structure, a plurality of mounting holes are arranged in a matrix on the top of the workbench, the photoelectric sensors are embedded in the mounting holes, and the adjustable height supporting legs are 4 electric cylinders arranged in a rectangular shape.

[0008] Preferably, the coordinate positioning mechanism includes a first regular octagonal prism-shaped mounting tube vertically arranged on the belly of the drone body, and each side of the bottom end of the first regular octagonal prism-shaped mounting tube is evenly arranged with a plurality of first laser ranging sensors. The measuring light of the first laser ranging sensor is emitted vertically downward, and the installation positions of the first laser ranging sensors on each side are consistent.

[0009] Preferably, the first laser ranging sensors on the same side include odd-numbered first laser ranging sensors and even-numbered first laser ranging sensors, and the distance A of the measurement light of adjacent odd-numbered first laser ranging sensors is consistent with the distance B of the measurement light of adjacent even-numbered first laser ranging sensors. In the matrix, the distance between the photoelectric sensor and the adjacent photoelectric sensors in the front-to-back direction and / or the left-to-right direction is distance C, and the distance C is equal to distance A and distance B.

[0010] Preferably, there are five first laser ranging sensors on the same side, and each photoelectric sensor is provided with a number in the control system, and the number corresponds to the position information of the photoelectric sensor in the matrix.

[0011] Preferably, the detection mechanism includes a second regular octagonal prism-shaped mounting tube, and a plurality of second laser ranging sensors are arranged in a matrix at the same position on the upper part of each side surface of the second regular octagonal prism-shaped mounting tube, each second laser ranging sensor is provided with a number, and has a fixed position in the second laser ranging sensor matrix; the second regular octagonal prism-shaped mounting tube and the first regular octagonal prism-shaped mounting tube are mirror-set with respect to the drone body, the bottom of the second regular octagonal prism-shaped mounting tube is connected to the top of the drone body, and the reverse extension line of the measuring light of the first laser ranging sensor is coplanar with the starting point of the measuring light of the second laser ranging sensors arranged in the corresponding matrix above.

[0012] A method for using a drone building wall detection system based on dynamic coordinate recognition comprises the following steps: Step 1: Arrange a seat recognition mechanism on the ground in front of the wall to be detected, adjust the workbench to a horizontal level through the adjustable support legs, and adjust the direction of the workbench so that the rows of the photoelectric sensor matrix are parallel to the wall. At this time, the columns of the photoelectric sensor matrix are perpendicular to the wall. Step 2, the ground control station controls the drone body to rise vertically upward in stages above the workbench. At the beginning of the rise, the controller and the control system simultaneously start the timing module through the wireless signal transceiver; the drone body hovers after each rise of a set distance according to the preset program. When hovering, the controller controls the drone body to maintain a horizontal posture through the information of the second tilt sensor, and continues to detect the distance information of the wall through the second laser ranging sensor; at the same time, the first laser ranging sensor emits a measuring light to the surface of the workbench; when the drone body is hovering, the control system receives the signal of the photoelectric sensor, when at least two adjacent photoelectric sensors in the same row receive the signal, the control system records the number of the photoelectric sensor that receives the signal and the time D of receiving the signal, when the drone body sends the collected wall distance information to the control system, the control system compares and identifies the wall distance information corresponding to the time D as qualified data; in this way, the drone body continues to rise and hovers intermittently to achieve wall detection of one workstation; Step 3: The staff moves the workbench to different positions and repeats steps 1 and 2 to detect the verticality and flatness of the entire wall. The control system draws the verticality curve and flatness graph of the wall based on the selected qualified data.

[0013] Preferably, in step 2, when the control system finds that the screened qualified data is insufficient, the drone body is moved autonomously within the range of the photoelectric sensor matrix through the wireless signal transceiver. During the movement, the drone body maintains a horizontal posture, and the first laser ranging sensor and the second laser ranging sensor continue to emit measurement light. When the amount of data collected reaches a preset standard, the drone body continues to rise and hover in stages. The autonomous movement of the drone body is as follows: the drone body swings back and forth to the left and right at a set angle, and moves back and forth, left and right, to complete the wall detection data collection without exceeding the range of the photoelectric sensor matrix, and the set angle does not exceed 45 degrees.

[0014] Preferably, in step 2, the row position of the laser ranging sensor in one row of the matrix is ​​set as the reference position. When the drone body is hovering, if the position of the row where the photoelectric sensor that receives the measuring light corresponding to the collected qualified data is not the reference position, the control system calculates the distance E between the row and the reference position, adds or subtracts the distance E from the detected qualified data to obtain the corrected qualified data, and the verticality curve and flatness graph of the wall are drawn based on the corrected qualified data.

[0015] Preferably, in step 2, when at least two adjacent photoelectric sensors in the same row detect a signal, a side of the second regular octagonal prism-shaped mounting tube that is opposite to the photoelectric sensors in the row above and below is a detection surface facing the wall, and two adjacent surfaces of the detection surface facing the wall are 45-degree angle detection surfaces. The measuring light emitted by the second laser ranging sensor on the 45-degree angle detection surface measures the distance to the wall at a horizontal 45-degree oblique angle. According to the cosine theorem of a right triangle, the control system calculates the vertical distance from the starting point of the measuring light of the second laser ranging sensor on the 45-degree angle detection surface to the projection point of the measuring light, and obtains corrected qualified data through distance correction with respect to the reference position.

[0016] The present invention provides a drone building wall detection system and method based on dynamic coordinate recognition, which has the following beneficial effects: when the present invention is in use, it is not necessary to deliberately position the drone body in a set coordinate system before collecting wall data. It only needs to intermittently hover during the ascent process, and when the amount of collected data is insufficient, it can naturally collect the required amount of wall detection data by walking in a set posture within the range of the photoelectric sensor matrix. According to the height information of the drone, the position information of the starting point of the measurement light, and the distance information between the starting point of the measurement light and the wall, the verticality curve and flatness diagram of the wall can be drawn. Based on the above principles, the present invention overcomes the influence of airflow factors and the vibration factors of the drone itself on the measurement results. The airflow factors and vibration factors become the driving force for collecting data, which greatly reduces the difficulty of detection. Therefore, the present invention can be applied to various airflow environments for wall quality detection, which can effectively improve the detection efficiency and ensure the accuracy of the detection results. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a schematic diagram of the structure of the present invention when performing wall detection.

[0018] Figure 2 It is a schematic diagram of the top structure of the workbench of the present invention.

[0019] Figure 3 It is a front view structural schematic diagram of the drone body of the present invention.

[0020] Figure 4 The figure is a schematic diagram of the top view of the UAV body of the present invention.

[0021] Figure 5 The figure is a schematic diagram of the structure of the drone body of the present invention when viewed from above (the landing gear is omitted).

[0022] Figure 6 This is a schematic diagram of the principle of data correction in the present invention.

[0023] Figure 7 It is a schematic diagram of the principle of data correction for the 45-degree angle detection surface of the present invention.

[0024] 1. Wall; 2. UAV body detection unit; 201. UAV body; 202. Protruding arm; 203. Second regular octagonal prism-shaped mounting tube; 2031. Detection surface facing the wall; 20311. Measuring light of the detection surface facing the wall; 2032. 45-degree angle detection surface; 2033. Second starting point; 2034. First starting point; 20321. Hypotenuse; 20322. Parallel side of the detection surface facing the wall; 20323. 45-degree internal angle; 20324. Right-angle side; 204. Second laser ranging sensor; 2 05. First regular octagonal prism-shaped mounting tube; 206. Landing gear; 207. First laser ranging sensor; 2071. Odd-numbered first laser ranging sensor; 2072. Even-numbered first laser ranging sensor; 3. Coordinate recognition mechanism; 301. First tilt sensor; 302. Adjustable height support leg; 303. Workbench; 304. Photoelectric sensor; 4. Measuring light; 5. Distance E; 6. Row position indication arrow; 7. Reference position indication arrow; 8. 45-degree oblique column; 9. Triggered photoelectric sensor.

[0025] It should be noted that the above figures are all schematic diagrams, and the size ratios between the various structures of the present invention should not be understood based on the proportional relationships drawn in the figures. The actual size ratios are set according to needs. DETAILED DESCRIPTION

[0026] The following describes in detail the implementation mode of the present invention in a step-by-step manner. The description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0027] In the description of the present invention, it should be noted that the directions or positional relationships indicated by terms such as “upper”, “lower”, “left”, “right”, “top”, “bottom”, “inside” and “outside” are based on the directions or positional relationships shown in the accompanying drawings, and are only for the purpose of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, and a specific direction structure and operation, and therefore cannot be understood as a limitation on the present invention.

[0028] Embodiment 1: The present invention provides a drone building wall detection system based on dynamic coordinate recognition, such as Figure 1-7 As shown, it includes a ground control station, a drone body 2, a coordinate identification mechanism 3, a coordinate positioning mechanism, and a detection mechanism. The top of the drone body 2 is provided with a detection mechanism, and the bottom is provided with a coordinate positioning mechanism. The coordinate identification mechanism includes a workbench 303, and the bottom of the workbench 303 is provided with an adjustable height support leg 302. The bottom of the workbench 303 is installed with a first tilt sensor 301, and the top of the workbench 303 is arranged in a matrix with a plurality of photoelectric sensors 304 for receiving laser signals. The area of ​​the matrix is ​​larger than the displacement range caused by the wind force or the vibration of the drone body when it is hovering under the set wind force. The coordinate positioning mechanism is used in conjunction with the coordinate identification mechanism. The photoelectric sensor 304, the first tilt sensor 301, and the adjustable height support leg 302 are electrically connected to the control system of the ground control station through wires respectively. The drone body is provided with a second tilt sensor and a controller (not shown in the figure). The second inclination sensor, the detection mechanism, and the coordinate positioning mechanism are respectively connected to the controller signal through wires, the controller is electrically connected to the airborne power supply of the drone body, the controller is configured to control the flight posture of the drone body, and other related structures of the drone body are solved by existing solutions; the controller is connected to the control system signal through a wireless signal transceiver, and the control system and the controller are both provided with a timing module. The control system performs a comprehensive comparison of the time information of the two timing modules, the wall distance information and height information collected by the detection mechanism, and the coordinate information recognized by the coordinate recognition mechanism to realize the screening of the wall detection information, and draws the verticality curve and flatness graph of the wall according to the qualified data obtained after the screening. It should be noted that it is a prior art to detect the distance information of the wall by a laser ranging sensor and then draw the verticality curve and flatness graph of the wall. The present invention explains the innovative points of the relevant drawing method.

[0029] Embodiment 2, as Figure 1 , 2 As shown, the workbench 303 is a cubic structure, and a plurality of mounting holes are arranged in a matrix on the top of the workbench 303. The photoelectric sensors are embedded in the mounting holes, and the adjustable height support legs 302 are four electric cylinders arranged in a rectangular shape.

[0030] Embodiment 3, as Figure 3-5 As shown, the coordinate positioning mechanism includes a first regular octagonal prism-shaped mounting tube 205 vertically arranged on the belly of the drone body 2, and each side of the bottom end of the first regular octagonal prism-shaped mounting tube 205 is evenly arranged with a plurality of first laser ranging sensors 207. The measuring light of the first laser ranging sensor 207 is emitted vertically downward, and the first laser ranging sensors 207 on each side are installed in the same position.

[0031] Embodiment 4, as Figure 5 As shown, the first laser ranging sensors 207 on the same side include odd-numbered first laser ranging sensors 2071 and even-numbered first laser ranging sensors 2072, and the distance A of the measurement light of adjacent odd-numbered first laser ranging sensors 2071 is consistent with the distance B of the measurement light of adjacent even-numbered first laser ranging sensors 2072. In the matrix, the distance between the photoelectric sensor 304 and the photoelectric sensors 304 adjacent in the front-to-back direction and / or the left-to-right direction is distance C, and the distance C is equal to the distance A and the distance B. In this embodiment, when the measuring light (laser line) emitted by 2 or more odd-numbered first laser ranging sensors 2071 or 2 or more even-numbered first laser ranging sensors 2072 triggers the photoelectric sensors in the same row, since distance C is equal to distance A and distance B, the measuring light of the first laser ranging sensor that does not trigger the photoelectric sensor is projected onto the workbench surface (the workbench surface where the photoelectric sensor gap is located), thereby realizing the measurement of the height of the drone. When the drone is hovering, each hovering height corresponds to a number of qualified data, and the relevant verticality curve and flatness graph are drawn based on this. It can be understood that the matrix is ​​densely covered with photoelectric sensors. When the drone body is displaced due to wind or its own vibration factors, the photoelectric sensors in other rows will be triggered, and the qualified data needs to be corrected at this time.

[0032] Embodiment 5, as Figure 5 As shown, there are five first laser ranging sensors 207 on the same side, such as Figure 1 , 2 As shown, each photoelectric sensor 304 is provided with a number in the control system, and the number corresponds to the position information of the photoelectric sensor 304 in the matrix. That is, the measured qualified data can be deduced from the corrected qualified data relative to the reference position according to the row spacing between the row and the reference position.

[0033] Embodiment 6, as Figure 3-5 As shown, the detection mechanism includes a second regular octagonal prism-shaped mounting tube 203, and a plurality of second laser ranging sensors 204 for detecting the distance to the wall are arranged in a matrix at the same position on the upper part of each side of the second regular octagonal prism-shaped mounting tube 203, and each second laser ranging sensor is provided with a number and has a fixed position in the second laser ranging sensor matrix; the second regular octagonal prism-shaped mounting tube 203 and the first regular octagonal prism-shaped mounting tube 205 are mirror-set with respect to the drone body, the bottom of the second regular octagonal prism-shaped mounting tube is connected to the top of the drone body, and the reverse extension line of the measuring light 4 of the first laser ranging sensor 207 is coplanar with the starting point of the measuring light of the second laser ranging sensors 204 arranged in the corresponding matrix above. That is to say, the starting point of the measuring light of the second laser ranging sensor 204 arranged in the matrix is ​​located in the facade where the measuring light 4 of the first laser ranging sensor 207 is located. When the measuring light 4 of the first laser ranging sensor 207 triggers at least two adjacent photoelectric sensors in a row, the connecting line of the photoelectric sensors in this row is located in the facade (the connecting line can be used as the center line of the row as needed. Since it is impossible for the measuring light and the center point of the photoelectric sensor to be 100% aligned, a set error is allowed), which represents the wall distance measured by the second laser ranging sensor facing the wall, that is, the distance between the row and the wall. Here, the foundation is laid for correcting qualified data according to the row spacing.

[0034] Example 7: Based on the above examples, this example discloses a method for using a drone building wall detection system based on dynamic coordinate recognition, such as Figure 1 As shown, the following steps are included: Step 1: Arrange the seat recognition mechanism 3 on the ground in front of the wall 1 to be detected, adjust the workbench 303 to a horizontal position through the adjustable support legs 302, and adjust the direction of the workbench 303 so that the rows of the matrix of the photoelectric sensor 304 are parallel to the wall 1. At this time, the columns of the matrix of the photoelectric sensor 304 are perpendicular to the wall 1; Step 2, the ground control station controls the drone body 2 to rise vertically upward in stages above the workbench 303. At the beginning of the rise, the controller and the control system simultaneously start the timing module through the wireless signal transceiver; the drone body 2 hovers after each rise of a set distance according to the preset program. When hovering, the controller controls the drone body 2 to maintain a horizontal posture through the information of the second inclination sensor, and continuously detects the distance information of the wall 1 through the second laser ranging sensor 204 (the continuous at this time refers to collecting data at very small intervals, such as collecting once at an interval of 1 second, or continuous collection can be performed according to the parameters of the sensor itself, the same below); at the same time, the first laser ranging sensor 207 is used to emit measurement light to the surface of the workbench 303; the control When the drone body 2 is hovering, the control system receives the signal of the photoelectric sensor 304. When at least two adjacent photoelectric sensors 304 in the same row receive the signal, the control system records the number of the photoelectric sensor 304 that receives the signal and the time D of receiving the signal. After the drone body 2 sends the collected wall distance information to the control system, the control system compares and identifies the wall distance information corresponding to the time D as qualified data. In this way, the drone body continues to rise and hover intermittently to achieve wall detection of one workstation. It should be noted that in order to avoid unnecessary interference of the photoelectric sensor signals (i.e., the front and rear sides facing each other trigger the two rows of photoelectric sensors at the same time or only the side far from the wall triggers the same row of photoelectric sensors), when in use, Figure 7 As shown, except for the first laser distance measuring sensors corresponding to the wall detection surface 2031 and the 45-degree angle detection surfaces 2032 on the adjacent two sides, the other first laser distance measuring sensors are turned off; Step 3: The staff moves the workbench 303 to different positions and repeats steps 1 and 2 to detect the verticality and flatness of the entire wall. The control system draws the verticality curve and flatness graph of the wall according to the selected qualified data.

[0035] Embodiment 8, as Figure 6 , 7As shown, in the step 2, when the control system finds that the screened qualified data is insufficient, the wireless signal transceiver makes the drone body 2 move autonomously within the range of the photoelectric sensor matrix. During the movement, the drone body maintains a horizontal posture, and the first laser ranging sensor 207 and the second laser ranging sensor 204 continue to emit measurement light 4. When the amount of data collected reaches the preset standard, the drone body continues to rise and hover in stages. In this embodiment, the drone body moves autonomously in the following manner: the drone body swings back and forth at a set angle to the left and right, and moves back and forth, left and right, and completes the wall detection data collection without exceeding the range of the photoelectric sensor matrix. The set angle does not exceed 45 degrees, and this action can be completed by the preset program of the drone body. In the process of implementing the autonomous movement action, the drone coordinates do not need to be deliberately positioned to realize the collection of wall data. Similarly, the autonomous movement of this embodiment also simulates the principle that the drone body realizes wall data collection due to swinging and displacement under the conditions of wind and self-vibration.

[0036] Embodiment 9, as Figure 6-7 As shown, in step 2, the row position of the photoelectric sensor 304 in one row of the matrix is ​​set as the reference position (see Figure 6 The reference position indicating arrow 7) indicates that when the drone body is hovering, if the position of the row where the photoelectric sensor 304 receiving the measuring light 4 corresponds to the collected qualified data is not the reference position, the control system calculates the distance E5 between the row and the reference position, adds or subtracts the distance E5 from the detected qualified data to obtain the corrected qualified data, and the verticality curve and flatness graph of the wall are drawn based on the corrected qualified data. The corrected position is equivalent to correcting the position of the starting point of the measuring light, so that the starting points of the measuring light in the same vertical plane parallel to the photoelectric sensor matrix column are all located in the same vertical line, which is equivalent to simulating the situation where the drone body rises along the vertical line without deviation.

[0037] Embodiment 10, as Figure 6 , 7 As shown, in the step 2, when at least two adjacent photoelectric sensors 304 in the same row detect a signal, a side of the second regular octagonal prism-shaped mounting tube 203 that is opposite to the photoelectric sensors 304 in the row is a detection surface 2031 facing the wall, and two adjacent surfaces of the detection surface 2031 facing the wall are 45-degree angle detection surfaces 2032 (the interior angle of the regular octagonal prism is 135 degrees, so the acute angle between the 45-degree angle detection surface 2032 and the detection surface 2031 facing the wall is 45 degrees), and the measurement light emitted by the second laser ranging sensor 204 on the 45-degree angle detection surface 2032 measures the distance to the wall 1 at a horizontal 45-degree oblique angle, as shown in FIG. Figure 7As shown, according to the cosine theorem of a right triangle, the control system calculates the vertical distance from the starting point of the measuring light of the second laser ranging sensor on the 45-degree angle detection surface 2032 to the projection point of the measuring light (i.e., the length of the right-angle side 20324), and obtains the corrected qualified data after the distance correction with the reference position. Figure 7 As shown, the starting point of the measuring light of the second laser ranging sensor on the 45-degree angle detection surface 2032 is the first starting point 2034. The projection point of the measuring light from the first starting point 2034 to the wall constitutes the hypotenuse 20321 of the right triangle. The hypotenuse and the parallel side 20322 facing the wall detection surface form another right-angled side of the right triangle. According to the law of cosines, the length of the right-angled side 20324 can be calculated. According to the known distance between the first starting point of the measuring light of the second laser ranging sensor and the second starting point 2033 of the measuring light of the wall detection surface, combined with the method of Example 9, the qualified data detected by the 45-degree angle detection surface 2032 is corrected to obtain the corrected qualified data. When drawing a verticality curve or a flatness diagram, it is necessary to base it on the height data of the drone, the wall distance detected based on the reference position (corrected wall distance), and the position data of the second photoelectric sensor on the row where the reference position is located. Figure 6 As shown, the position data of the second photoelectric sensor on the row where the reference position is located is calculated and obtained in the following manner: suppose there are 3 triggered photoelectric sensors 9 in the row, since the triggered photoelectric sensor 9 has a relative positional relationship with the corresponding first photoelectric sensor above, and since the position of each second laser distance measuring sensor facing the wall detection surface 2031 is fixed, the relative position of each second laser distance measuring sensor and the row where the triggered photoelectric sensor 9 is located can be calculated, and the height data of each second laser distance measuring sensor can be combined, and the corrected position of the second laser distance measuring sensor can be obtained after correction after comparison with the reference position, that is, the vertical surface where the starting point of the measuring light is located in the row where the reference position is located. Similarly, the position of the second laser distance measuring sensor on the 45-degree angle detection surface and the position of the right-angled vertex of the above-mentioned right-angled triangle can be calculated, and the position of the vertex is used as the corrected starting point position of the measuring light. Among the wall distance information collected at each hovering position, the wall distance information corresponding to the starting points of several measuring light rays connected in series in the Z-axis direction constitutes the basis for drawing the wall verticality line, and several verticality lines are summarized to form a wall flatness map.

[0038] Embodiment 11: This embodiment provides another method for drawing a wall verticality curve and a flatness diagram. This method is obviously simpler than the previous method and does not require correction of the wall distance data according to the reference position. The details are as follows: The photoelectric sensor matrix is ​​understood as a grid structure, and the rows and columns of the grid structure are the center lines of the photoelectric sensor rows and columns respectively (that is, they are also the lines connecting the centers of the sensing ends of the photoelectric sensors in the same row or column), and the intersection of the rows and columns has fixed coordinates in the grid structure. When determining the starting point coordinates of the measuring light in the qualified data measured by the second laser ranging sensor, the grid structure is vertically raised to make the starting point of the measuring light located in the horizontal plane where the grid is located, and the coordinate value of the starting point of the measuring light is calculated in the grid area. The starting point coordinates of the measuring light at each hovering height are classified according to the coordinate value of the starting point, and the starting point coordinates of the measuring light at each hovering height located on the same facade are set as the same group of data. The facade is parallel to the columns of the photoelectric sensor matrix, and the projection points of the same group of measuring light on the wall are connected to form an actual verticality curve diagram of the wall. According to these graphics, the relevant verticality curves and wall flatness diagrams are drawn.

[0039] Embodiment 11: This embodiment provides a simpler method for dynamically identifying the coordinates of the drone body, specifically: The first regular octagonal prism-shaped mounting tube and the second regular octagonal prism-shaped mounting tube are respectively fixed with a fixing seat at one end close to the drone body, a fixing shaft is connected between the center points of the two fixing seats, the fixing shaft passes through the belly and the top of the drone body and is rotatably connected to the drone body, a stepper motor for driving the fixing shaft to swing back and forth is arranged in the drone body, a driven gear is arranged on the rotating shaft, a driving gear is arranged on the output shaft of the stepper motor, the driving gear and the driven gear are meshed and connected, the stepper electrical appliance drives the first regular octagonal prism-shaped mounting tube and the second regular octagonal prism-shaped mounting tube to swing left and right around the fixing shaft during the forward, backward, left and right movement of the drone body, and the amplitude of the left or right swing does not exceed 45 degrees, so that during the movement of the drone body, the coordinates of the drone body are instantly identified through the cooperation of the first laser ranging sensor and the photoelectric sensor matrix, and then the coordinates of the starting point of the light measured by each second photoelectric sensor during coordinate identification are also determined, and the wall distance data measured during coordinate identification is regarded as qualified data. In this embodiment, the controller can control the forward, backward, left and right movement of the drone body, and at the same time control the first regular octagonal prism-shaped mounting tube and the second regular octagonal prism-shaped mounting tube to swing left and right around a fixed axis during the forward, backward, left and right movement of the drone body, thereby realizing rapid identification of the coordinates of the drone body (i.e., when at least two photoelectric sensors in the same row are triggered, the coordinates of the starting point of the measurement light are identified). This embodiment further reduces the difficulty of dynamic coordinate identification of the drone body and significantly improves measurement efficiency.

[0040] As described above, when the present invention is in use, it is not necessary to deliberately position the drone body within the set coordinate system before collecting wall data. It only needs to intermittently hover during the ascent process, and when the amount of collected data is insufficient, it can naturally collect the required amount of wall detection data by walking in a set posture within the range of the photoelectric sensor matrix. According to the height information of the drone, the position information of the starting point of the measurement light, and the distance information between the starting point of the measurement light and the wall, the verticality curve and flatness diagram of the wall can be drawn. Based on the above principles, the present invention overcomes the influence of airflow factors and the vibration factors of the drone itself on the measurement results. The airflow factors and vibration factors become the driving force for collecting data, which greatly reduces the difficulty of detection. Therefore, the present invention can be applied to various airflow environments for wall quality detection, which can effectively improve the detection efficiency and ensure the accuracy of the detection results.

Claims

1. A drone building wall detection system based on dynamic coordinate recognition, characterized by: It includes a ground control station, a drone body, a coordinate recognition mechanism, a coordinate positioning mechanism, and a detection mechanism; The top of the drone body is provided with a detection mechanism, the bottom is provided with a coordinate positioning mechanism, the coordinate identification mechanism includes a workbench, the bottom of the workbench is provided with an adjustable height support leg, the bottom of the workbench is installed with a first tilt sensor, and the top of the workbench is arranged in a matrix with a plurality of photoelectric sensors for receiving laser signals; The area of ​​the matrix is ​​larger than the displacement range of the drone body caused by wind force or self-vibration when hovering under set wind force, the coordinate positioning mechanism is used in conjunction with the coordinate identification mechanism, and the photoelectric sensor, the first tilt sensor, and the adjustable height support leg are electrically connected to the control system of the ground control station through wires; The drone body is provided with a second tilt sensor and a controller. The second tilt sensor, the detection mechanism, and the coordinate positioning mechanism are respectively connected to the controller signal through wires. The controller is electrically connected to the airborne power supply of the drone body. The controller is configured to control the flight attitude of the drone body. The controller is connected to the control system signal through a wireless signal transceiver. The control system and controller are both provided with a timing module. The control system screens the wall detection information by performing a comprehensive comparison of the time information of the two timing modules, the wall distance information and height information collected by the detection mechanism, and the coordinate information identified by the coordinate identification mechanism, and draws the verticality curve and flatness graph of the wall according to the qualified data obtained after the screening.

2. The UAV building wall detection system based on dynamic coordinate recognition as claimed in claim 1, characterized in that: The workbench is a cubic structure, and a plurality of mounting holes are arranged in a matrix on the top of the workbench. The photoelectric sensors are embedded in the mounting holes, and the height-adjustable supporting legs are four electric cylinders arranged in a rectangular shape.

3. The UAV building wall detection system based on dynamic coordinate recognition as claimed in claim 2, characterized in that: The coordinate positioning mechanism comprises a first regular octagonal prism-shaped mounting cylinder vertically arranged on the belly of the drone body; A plurality of first laser distance measuring sensors are evenly arranged on each side of the bottom end of the first regular octagonal prism-shaped installation tube, and the measuring light of the first laser distance measuring sensors is emitted vertically downward, and the installation positions of the first laser distance measuring sensors on each side are consistent.

4. A drone building wall detection system based on dynamic coordinate recognition as claimed in claim 3, characterized in that: the first laser ranging sensors on the same side include odd-numbered first laser ranging sensors and even-numbered first laser ranging sensors, and the distance A of the measurement light of adjacent odd-numbered first laser ranging sensors is consistent with the distance B of the measurement light of adjacent even-numbered first laser ranging sensors; In the matrix, the distance between a photoelectric sensor and the photoelectric sensors adjacent in the front-to-back direction and / or the left-to-right direction is distance C, and distance C is equal to distance A and distance B.

5. A drone building wall detection system based on dynamic coordinate recognition as described in claim 4, characterized in that: there are 5 first laser ranging sensors on the same side, and each photoelectric sensor is numbered in the control system, and the number corresponds to the position information of the photoelectric sensor in the matrix.

6. The UAV building wall detection system based on dynamic coordinate recognition as claimed in claim 5, characterized in that: The detection mechanism comprises a second regular octagonal prism-shaped mounting cylinder, and a plurality of second laser ranging sensors are arranged in a matrix at the same position on the upper part of each side surface of the second regular octagonal prism-shaped mounting cylinder, and each second laser ranging sensor is provided with a number and has a fixed position in the second laser ranging sensor matrix; The second regular octagonal prism mounting tube and the first regular octagonal prism mounting tube are mirror-imaged with respect to the drone body, the bottom of the second regular octagonal prism mounting tube is connected to the top of the drone body, and the reverse extension line of the measuring light of the first laser ranging sensor is coplanar with the starting point of the measuring light of the second laser ranging sensor arranged in a corresponding matrix above.

7. The UAV building wall detection system based on dynamic coordinate recognition as claimed in claim 6, characterized in that: The first regular octagonal prism-shaped mounting tube and the second regular octagonal prism-shaped mounting tube are respectively fixed with a fixing seat at one end close to the drone body; A fixed shaft is connected between the center points of the two fixing seats, and the fixed shaft passes through the belly and top of the drone body and is rotatably connected to the drone body; A stepper motor is provided in the drone body to drive the fixed shaft to swing back and forth, a driven gear is provided on the rotating shaft, a driving gear is provided on the output shaft of the stepper motor, and the driving gear and the driven gear are meshed and connected; The stepper motor drives the first regular octagonal prism-shaped mounting tube and the second regular octagonal prism-shaped mounting tube to swing left and right during the forward, backward, left and right movement of the drone body, and the swing range to the left or right does not exceed 45 degrees; During the movement of the drone body, the coordinates of the drone body are instantly identified through the cooperation of the first laser ranging sensor and the photoelectric sensor matrix, and then the coordinates of the starting points of the light measured by each second photoelectric sensor during coordinate identification are determined, and the wall distance data measured during coordinate identification is regarded as qualified data.

8. The method for using the drone building wall detection system based on dynamic coordinate recognition as claimed in claim 7, characterized in that: The steps include: Step 1: Arrange a seat recognition mechanism on the ground in front of the wall to be detected, adjust the workbench to a horizontal level through the adjustable support legs, and adjust the direction of the workbench so that the rows of the photoelectric sensor matrix are parallel to the wall. At this time, the columns of the photoelectric sensor matrix are perpendicular to the wall. Step 2: The ground control station controls the drone body to rise vertically upward in stages above the workbench. At the beginning of the rise, the controller and the control system simultaneously start the timing module through the wireless signal transceiver. The drone body hovers after each rise of a set distance according to a preset program. When hovering, the controller controls the drone body to maintain a horizontal posture through the information of the second inclination sensor, and continuously detects the distance information of the wall through the second laser ranging sensor. At the same time, the first laser ranging sensor emits a measuring light to the surface of the workbench. When the drone body is hovering, the control system receives the signal from the photoelectric sensor. When at least two adjacent photoelectric sensors in the same row receive the signal, the control system records the number of the photoelectric sensor that receives the signal and the time D of receiving the signal. When the drone body sends the collected wall distance information to the control system, the control system compares and identifies the wall distance information corresponding to the time D as qualified data. In this way, the drone body continuously rises and intermittently hovers to achieve wall detection of one workstation. Step 3: The staff moves the workbench to different positions and repeats steps 1 and 2 to detect the verticality and flatness of the entire wall. The control system draws the verticality curve and flatness graph of the wall according to the selected qualified data; In the step 2, when the control system finds that the screened qualified data is insufficient, the drone body is moved autonomously within the range of the photoelectric sensor matrix through the wireless signal transceiver. During the movement, the drone body maintains a horizontal posture, and the first laser ranging sensor and the second laser ranging sensor continue to emit measurement light. When the amount of data collected reaches a preset standard, the drone body continues to rise and hover in stages. The autonomous movement of the drone body is as follows: a. The drone body swings back and forth to the left and right at a set angle, and moves forward and backward and left and right to complete the wall detection data collection without exceeding the range of the photoelectric sensor matrix, and the set angle does not exceed 45 degrees; b. The controller controls the UAV body to move forward, backward, left and right, and at the same time controls the first regular octagonal prism-shaped mounting tube and the second regular octagonal prism-shaped mounting tube to swing left and right around the fixed axis during the UAV body's forward, backward, left and right movement.

9. The method for using the drone building wall detection system based on dynamic coordinate recognition as claimed in claim 8, characterized in that: In the step 2, the row position of the laser ranging sensor in one row of the matrix is ​​set as the reference position. When the drone body is hovering, if the position of the row of the photoelectric sensor receiving the measuring light corresponding to the collected qualified data is not the reference position, the control system calculates the distance E between the row and the reference position, adds or subtracts the distance E from the detected qualified data to obtain the corrected qualified data, and the verticality curve and flatness graph of the wall are drawn based on the corrected qualified data; In the step 2, when at least two adjacent photoelectric sensors in the same row detect a signal, a side of the second regular octagonal prism-shaped mounting tube that is opposite to the photoelectric sensors in the row above and below is a detection surface facing the wall, and two adjacent surfaces of the detection surface facing the wall are 45-degree angle detection surfaces. The measuring light emitted by the second laser ranging sensor on the 45-degree angle detection surface measures the distance to the wall from a horizontal 45-degree oblique angle. According to the cosine theorem of a right triangle, the control system calculates the vertical distance from the starting point of the measuring light of the second laser ranging sensor on the 45-degree angle detection surface to the projection point of the measuring light, and obtains the corrected qualified data after distance correction with respect to the reference position.

10. The method for using the drone building wall detection system based on dynamic coordinate recognition as claimed in claim 8, characterized in that: In the step 2, the photoelectric sensor matrix is ​​understood as a grid structure, the rows and columns of the grid structure are the center lines of the photoelectric sensor rows and columns, and are also the lines connecting the centers of the sensing ends of the photoelectric sensors in the same row or column; The intersection of the rows and columns has fixed coordinates in the grid structure. When determining the coordinates of the starting point of the measuring light in the qualified data measured by the second laser ranging sensor, the grid structure is vertically raised until the starting point of the measuring light is located in the horizontal plane where the grid is located; Calculate the coordinate value of the starting point of the measuring light in the grid area, classify the starting point coordinates of the measuring light at each hovering height according to the coordinate value of the starting point, and set the starting point coordinates of the measuring light at each hovering height located on the same vertical plane as the same set of data, and the vertical plane is parallel to the columns of the photoelectric sensor matrix; In the step 3, the projection points of the same set of measuring light rays on the wall are connected to form a verticality curve diagram of the wall, and a wall flatness diagram is drawn based on a plurality of verticality curves.

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