CN112595231A - Two-dimensional follow-up system dynamic monitoring device and method based on intelligent image recognition - Google Patents
Two-dimensional follow-up system dynamic monitoring device and method based on intelligent image recognition Download PDFInfo
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Abstract
The invention discloses a dynamic monitoring device and method of a two-dimensional follow-up system based on intelligent image recognition, wherein a moving target simulation system comprises a laser and a two-dimensional moving mechanism, and the effect of simulating a target is achieved by irradiating light spots formed on a fixed white board by the laser; the laser is fixed on the two-dimensional motion mechanism, and the motion change of the pitching yawing angle of the two-dimensional motion mechanism is controlled by a control computer instruction to realize the effect of simulating a target motion track; a measurement camera of the optical measurement system images a fixed white board containing laser spots, collects a simulation target image and transmits the simulation target image to a control computer for target position calculation, identification and analysis; the measuring camera is fixed on the camera mounting platform, the camera mounting platform has a fine adjustment function for the direction of the sight of the measuring camera, and the control computer realizes the resolving function of the target angle and the direction through image recognition of laser. The invention can evaluate the motion control quality of the two-dimensional follow-up unit.
Description
Technical Field
The invention relates to the technical field of dynamic monitoring devices, in particular to a dynamic monitoring device and method based on an intelligent image recognition two-dimensional follow-up system.
Background
The dynamic monitoring device is mainly composed of data acquisition equipment and data processing equipment, acquires data through the data acquisition equipment, processes the data through the data processing equipment, and then dynamically monitors the data, so that the use requirements can be basically met; however, the current dynamic monitoring device is still relatively simple in structure, and there are still some disadvantages to be improved. Therefore, the invention designs a dynamic monitoring device and method of a two-dimensional follow-up system based on intelligent image recognition.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a dynamic monitoring device and a dynamic monitoring method based on an intelligent image recognition two-dimensional follow-up system, which can finish the measurement of the tracking and aiming precision of a device to be tested (a stable platform) and send the obtained aiming error data and images to virtual instrument equipment. And further, the motion control quality of the two-dimensional follow-up unit is evaluated in detail.
In order to achieve the purpose, the invention is realized by the following technical scheme: a dynamic monitoring device of a two-dimensional follow-up system based on intelligent image recognition comprises a moving target simulation system and an optical measurement system, wherein the moving target simulation system comprises a laser and a two-dimensional movement mechanism, and the effect of simulating a target is achieved by irradiating light spots formed on a fixed white board by the laser; the laser is fixed on the two-dimensional motion mechanism, and the motion change of the pitching and yawing angles of the two-dimensional motion mechanism is controlled by a control computer instruction to realize the effect of simulating a target motion track; the optical measurement system comprises a measurement camera, a camera mounting platform and a laser, wherein the measurement camera images a fixed white board containing laser spots, collects simulated target images and transmits the simulated target images to a control computer for target position calculation, identification and analysis; the measuring camera is fixed on the camera mounting platform, the camera mounting platform has a fine adjustment function for the direction of the sight of the measuring camera, and the control computer realizes the resolving function of the target angle and the direction through image recognition of laser.
The laser is a focus-adjustable laser, the change of the size of the light spot can be realized by adjusting the focal length, and the requirement of the system on the size of the light spot can be met. Meanwhile, the input voltage of 220VAC can be realized through the matched external power supply controller, and the power of the light spot can be controlled.
The white board is used for carrying out laser spot projection, and the distance from the two-dimensional movement mechanism is about 10m-20 m. The whiteboard include steel structure frame and advertisement cloth, the advertisement cloth nail is on steel structure frame, 3 sections totally of steel construction base, can reach 0.9 meters at most, can be according to indoor highly down regulation, the regulatory region 0.3 meters at every turn.
The control computer receives the instruction of the virtual instrument equipment, controls the moving target simulation part, receives the image collected by the optical measurement part, processes the image to obtain the angle measurement information of the target and transmits the angle measurement information to the virtual instrument equipment.
The camera mounting platform adopts a three-dimensional angular displacement combined platform.
The optical measurement system also comprises a detection chessboard, the size of the chessboard is larger than 1.4 multiplied by 1.4 meters, and the chessboard with the size of 2 multiplied by 2 meters is provided for reserving the allowance.
The laser is fixedly connected with the device to be measured through a laser fixing support.
The dynamic monitoring method comprises the following procedures:
1. the moving target simulation part simulates the moving track of a target by controlling the movement of a light spot irradiated by a laser on a fixed white board, the control computer controls the rotation of the two-dimensional moving mechanism according to the radius and the circle speed set by a user, and the laser irradiates on a test white board to draw a circle. The frequency laser can also be set to scan the white board vertically and horizontally to realize the simulation of the moving target.
2. The optical measurement system judges the angular speed of the equipment to be measured, the direction from the original point and the deviation of the pitch angle according to the position of a laser point, which is arranged on the equipment to be measured, of the laser point on the chessboard board.
The step 2 specifically comprises the following steps: parameter setting of an industrial camera → image preprocessing → image calibration → image recognition and target detection → target position calculation.
The invention has the beneficial effects that: the laser position measuring device mainly comprises a dynamic target simulation system, a target identification and analysis system and a moving light spot projection curtain. The device is used for simulating and measuring dynamic parameters of pitching and azimuth motions of the two-dimensional follow-up unit, so that the motion control quality of the two-dimensional follow-up unit is evaluated in detail.
The dynamic target simulation system consists of a two-dimensional follow-up unit and a laser projection unit, wherein the laser projection unit synthesizes the pitching and azimuth movements of the two-dimensional follow-up unit into a composite movement of a light spot and projects the composite movement onto a curtain.
The AI image recognition and track calculation system consists of an AI image recognition unit and a track calculation unit. The AI image recognition unit adopts a high-definition industrial camera to acquire images of the moving light spots on the curtain, and adopts an AI image automatic recognition algorithm to process, analyze and understand the dynamic light spots so as to recognize indexes such as the moving track, the conveying speed, the moving acceleration and the like of the laser light spots.
And the track resolving unit performs track resolving and fitting on the output result of the AI image recognition unit. The motion control quality of the two-dimensional follow-up unit can be evaluated through comparison between the actual motion track of the light spot and a theoretical curve and graphical curve fitting.
Drawings
The invention is described in detail below with reference to the drawings and the detailed description;
FIG. 1 is a schematic diagram of the system of the present invention;
FIG. 2 is a diagram of a moving object simulation system of the present invention;
FIG. 3 is a schematic view of an optical measurement system of the present invention;
fig. 4 is a schematic view of a whiteboard configuration of the present invention;
FIG. 5 is a schematic structural view of the checkerboard of the present invention;
FIG. 6 is a schematic diagram of industrial camera parameter setting according to the present invention;
FIG. 7 is a schematic diagram of corner-to-rectangle conversion; FIG. 7(a) is a schematic diagram of the central projective transformation of the present invention; FIG. 7(b) is a schematic view of an arbitrary quadrilateral according to the present invention; FIG. 7(c) is a schematic view of a rectangle of the present invention;
FIG. 8 is a general flow chart of the software of the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to be clearly understood, the invention is further described by combining the specific embodiments.
Referring to fig. 1 to 8, the following technical solutions are adopted in the present embodiment: a two-dimensional servo system dynamic monitoring device based on intelligent image recognition comprises a moving target simulation system and an optical measurement system, wherein the moving target simulation system comprises a laser 1 and a two-dimensional movement mechanism 2, and the effect of simulating a target is achieved by irradiating light spots formed on a fixed white board by the laser; the laser 1 is fixed on the two-dimensional motion mechanism 2, and the motion change of the pitching yawing angle of the two-dimensional motion mechanism 2 is controlled through the instruction of the control computer 3 to realize the effect of simulating the target motion track; the optical measurement system comprises a measurement camera 6, a camera mounting platform 7 and a laser, wherein the measurement camera 6 images a fixed white board containing laser spots, collects a simulated target image and transmits the simulated target image to a control computer for target position calculation, identification and analysis; the measuring camera 6 is fixed on the camera mounting platform 7, the camera mounting platform has a fine adjustment function for the direction of the sight of the measuring camera, and the control computer realizes the resolving function of the target angle and the direction through image recognition of laser.
The laser 1 is a focus-adjustable laser, the change of the size of the light spot can be realized by adjusting the focal length, and the requirement of the system on the size of the light spot can be met. Meanwhile, the input voltage of 220VAC can be realized through the matched external power supply controller, and the power of the light spot can be controlled.
The white board 5 is used for laser spot projection, and the distance from the two-dimensional movement mechanism is about 10m-20 m. The white board comprises a steel structure frame 5-1 and advertisement cloth 5-2, the advertisement cloth is nailed on the steel structure frame, the steel structure base is totally 3 sections, the maximum height can reach 0.9 meter, the white board can be downwards adjusted according to the indoor height, and the adjustment range is 0.3 meter each time.
The control computer 3 receives the instruction of the virtual instrument device 4 (the control computer 3 is connected with the PXI virtual instrument device through the RS 422), controls the moving target simulation part, receives the image collected by the optical measurement part, processes the image to obtain the angle measurement information of the target and transmits the angle measurement information to the virtual instrument device.
The camera mounting platform 7 adopts a three-dimensional angular displacement combined platform.
The optical measurement system also comprises a detection chessboard plate 8, wherein the size of the chessboard plate 8 is larger than 1.4 multiplied by 1.4 meters, and a chessboard plate of 2 multiplied by 2 meters is provided for reserving allowance.
The laser is fixedly connected with the device to be measured through a laser fixing support.
The dynamic monitoring method comprises the following procedures:
1. the moving target simulation part simulates the moving track of a target by controlling the movement of a light spot irradiated by a laser on a fixed white board, the control computer controls the rotation of the two-dimensional moving mechanism according to the radius and the circle speed set by a user, and the laser irradiates on a test white board to draw a circle. The frequency laser can also be set to scan the white board vertically and horizontally to realize the simulation of the moving target.
2. The optical measurement system judges the angular speed of the equipment to be measured, the direction from the original point and the deviation of the pitch angle according to the position of a laser point, which is arranged on the equipment to be measured, of the laser point on the chessboard board.
The step 2 specifically comprises the following steps:
1. setting parameters of the industrial camera: default setting of camera parameters is required before image acquisition, and basic processing is required to be carried out on the image after the image is acquired for subsequent processing.
2. Image preprocessing: the method mainly comprises two steps of digital filtering and chessboard recognition;
after setting the industrial camera through default values or parameters obtained through operation recording, obtaining a high-quality image to meet the requirement of subsequent data processing, wherein the digital filtering adopts Gaussian filtering, and the chessboard identification process comprises the following steps: the whole chessboard positioning process is a cyclic process, namely, firstly, the histogram of the read chessboard image is equalized, then, adaptive binarization is carried out, and then, the image after binarization is expanded. For the robustness of positioning, the size of the kernel adopted by the adaptive binarization and the expansion cannot be unique, so that the chessboard image is processed by continuously and circularly using different parameters, and the size of the kernel adopted by the expansion is gradually increased.
The following steps are required for each cycle.
(1) And drawing a white rectangular frame (which is convenient for contour extraction) on the periphery of the binarized image, then carrying out contour extraction on the expanded binary image, separating each black square, and obtaining the contour of each square after contour extraction, wherein a plurality of interference contours exist. And performing polygon fitting on the contour, excluding contours which are not rectangular, and using other properties of the rectangle to exclude some interference contours.
(2) And searching adjacent grids of each grid, recording the number of the adjacent grids, and storing the adjacent grids and the information of the adjacent grids in a corresponding structural body. After the binary image is expanded, the adjacent squares are separated, the original connected parts have a common point, and the separation is changed into two points. After finding the adjacent squares, the original common points are calculated, and the common points are used for replacing the separated points after expansion.
(3) Classifying all 'squares' (including misjudged squares), wherein the classification principle is that all squares in the class are adjacent;
(4) and judging whether the square grids in each class are the required square grids of the chessboard according to the known number of the angular points, and sequencing the square grids of the chessboard, namely the row and the column of the square grid. In the process, the total missing squares of each type of square can be added, and the redundant squares in each type of square can be deleted.
(5) And confirming whether the positions and the number of the squares are correct or not according to the number of the squares (calculated by the angular points of the chessboard) of the known chessboard, and determining the position of a rough strong angular point (the connecting position of two squares). The checkerboard squares are checked again for correct extraction.
(6) And if all the squares in one step are not qualified, entering a new cycle. If the circulation is over and no square lattice meeting the requirement is found, the chessboard positioning fails and the function is quitted.
And finally, determining the accurate position of the strong corner according to the position of the strong corner in the previous step. The position of the entire board is thus identified.
3. Image calibration: the chessboard calibration board is adopted to solve the problem of image distortion, and images generated by the industrial camera can be in one-to-one correspondence with actual physical points on the whiteboard through the angular point identification of the chessboard patterns. Knowing such a correspondence, the conversion of pixel coordinates to checkerboard coordinates can be achieved. Distortion in the image is corrected.
4. Image recognition and target detection: after image preprocessing and chessboard calibration, brightness information detection can be carried out in the area of the chessboard board, and the position of the target area is calculated through the brightness information.
The specific process of target extraction: obtaining an image matrix A (i, j) from the image data, wherein the value range of the i, j is a chessboard detection area, traversing the A (i, j) according to a set threshold, and for a pixel point a exceeding the thresholdi，jRecording the horizontal and vertical coordinates of the pixel point and accumulating the horizontal and vertical coordinates to the horizontal coordinate recording variable xcountRecording the variable y on the ordinatecountAnd recording the pixel data into a variable PixcountAnd adding 1. AAfter the traversal of the image is completed, the image is formed by xcount/Pixcount，ycount/PixcountAnd respectively obtaining the coordinates of the center position of the target. The algorithm flow is shown in FIG. 6
5. And (3) resolving the target position: the method comprises two steps, namely solving the original point in the first step and solving the real-time point in the second step.
The origin calculation is that the air-floating rotary table transmits origin coordinate light spots to a chessboard after rotating to the center position of the air-floating rotary table, and the position on the chessboard coordinate is calculated by preprocessing, image calibration, cursor identification and the like.
And (3) a coordinate resolving process:
(1) according to the corner point positions of the rectangles in the image calibration, knowing which rectangular space of the center of the target on the chessboard;
(2) according to the distortion information of the coordinates of the four angular points, the position of the point on the chessboard board can be calculated;
the calculation method is as follows:
assuming that point E is a luminous source, an arbitrary quadrilateral q00 q01q11 q10 may be projected on one plane as r00 r01 r11 r 10. As shown in fig. 7 (b). q00 is projected as r00, q01 is projected as r01, q11 is projected as r11, and q10 is projected as r 10. With knowledge of linear algebra, it is very simple to map the coordinates of Q in an arbitrary quadrangle to the coordinates of a mapping point r in a rectangle, and to map the arbitrary quadrangle Q00Q 01Q 11Q 10 in fig. 7(b) to the arbitrary quadrangle Q00Q 01Q 11Q 10 in fig. 7(a), as long as the coordinates of the respective vertices in fig. 7 are known; the rectangle R00R 01R 11R 10 in FIG. 7(c) is mapped to the rectangle R00R 01R 11R 10 in FIG. 7(a), and then the point of the pixel in the rectangular space can be obtained through calculation according to the mapping relation of R to q.
Obtaining the physical coordinates (origin ) of the actual chessboard board by the point of the pixel in the rectangular space through the proportion transformation.
In the experiment of real-time optical measurement, the real-time physical coordinate of the cursor is obtained by the method, the physical coordinate of the origin is subtracted in the X and Y directions to obtain the relative coordinates (object X, object) of each test point, and considering that the chessboard board is placed at the position of 10 meters of the starting platform, the pitching and azimuth angles of the air floating platform can be obtained by the following formula
Since the frequency of the camera is 25HZ, the real-time angular velocity can be obtained by comparing the difference between the two pitch angles and the azimuth angle by 40ms for each frame interval and dividing by 40 ms.
According to the test mode, the software is divided into two parts, wherein the first part is a target simulation part and receives a control command sent by a case, and the control command comprises the following steps:
the control mode is that the circle or the transverse direction and the longitudinal direction are scanned;
controlling parameters, radius size and scanning frequency;
the control computer analyzes the control command and sends data to the two-dimensional cloud platform control cloud platform through the RS 422.
The overall design of the optical measurement system is divided into three modules, including a camera control module, a data processing and serial port communication module. The camera control module is mainly used for setting working parameters and working modes of the camera; the data processing processes the obtained image data to obtain the required information serial port communication module which is mainly responsible for the data exchange function of the system. The specific flow is shown in fig. 8.
The software development of this embodiment implements many general algorithms in image processing and computer vision. The algorithms greatly simplify the algorithm difficulty of image preprocessing, origin calibration and target calibration, reduce the number of BUGs and greatly improve the operation efficiency of the algorithms. The processing speed of real-time data is increased.
The foregoing shows and describes the basic principles and principal features of the invention, together with the advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are given by way of illustration of the principles of the present invention, and that various changes and modifications may be made without departing from the spirit and scope of the invention as defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. A dynamic monitoring device of a two-dimensional follow-up system based on intelligent image recognition is characterized by comprising a moving target simulation system and an optical measurement system, wherein the moving target simulation system comprises a laser and a two-dimensional movement mechanism, and the effect of simulating a target is achieved by irradiating light spots formed on a fixed white board by the laser; the laser is fixed on the two-dimensional motion mechanism, and the motion change of the pitching yawing angle of the two-dimensional motion mechanism is controlled by a control computer instruction to realize the effect of simulating a target motion track; the optical measurement system comprises a measurement camera, a camera mounting platform and a laser, wherein the measurement camera images a fixed white board containing laser spots, collects simulated target images and transmits the simulated target images to the control computer for target position calculation, identification and analysis; the measuring camera is fixed on the camera mounting platform, the camera mounting platform has a fine adjustment function for the direction of the sight of the measuring camera, and the control computer realizes the resolving function of the target angle and the direction through image recognition of laser.
2. The device for dynamically monitoring the two-dimensional servo system based on intelligent image recognition according to claim 1, wherein the laser is a tunable laser, and an external power controller is matched with the laser to realize an input voltage of 220VAC and control the power of a light spot.
3. The device and the method for dynamically monitoring the two-dimensional follow-up system based on the intelligent image recognition are characterized in that the white board is used for carrying out laser spot projection, and the distance from the white board to the two-dimensional motion mechanism is about 10m-20 m; the whiteboard include steel structure frame and advertisement cloth, the advertisement cloth nail is on steel structure frame, 3 sections totally of steel construction base, can reach 0.9 meters at most, can be according to indoor highly down regulation, the regulatory region 0.3 meters at every turn.
4. The device for dynamically monitoring the two-dimensional follow-up system based on the intelligent image recognition as recited in claim 1, wherein the control computer receives an instruction of a virtual instrument device, controls a moving target simulation part, receives an image collected by the optical measurement part, processes the image to obtain angle measurement information of a target, and transmits the angle measurement information to the virtual instrument device.
5. The device for dynamically monitoring the two-dimensional follow-up system based on the intelligent image recognition as claimed in claim 1, wherein the camera mounting platform adopts a three-dimensional angular displacement combined platform.
6. The device for monitoring the dynamic of a two-dimensional servo system based on intelligent image recognition as claimed in claim 1, wherein the optical measurement system further comprises a chessboard plate, the size of the chessboard plate is larger than 1.4 x 1.4 m, and a chessboard plate of 2 x 2 m is provided for the purpose of remaining margin.
7. The two-dimensional follow-up system dynamic monitoring device based on intelligent image recognition as claimed in claim 1, wherein the laser is fixedly connected with the device to be measured through a laser fixing support.
8. A dynamic monitoring method of a two-dimensional follow-up system based on intelligent image recognition is characterized by comprising the following procedures: (1) the moving target simulation part simulates the moving track of a target by controlling the movement of light spots irradiated by the laser on the fixed white board, the control computer controls the rotation of the two-dimensional moving mechanism according to the radius and the circle speed set by a user, and the simulation of the moving target is realized by irradiating the laser on the test white board to draw a circle or setting the frequency and vertically scanning the white board by the laser up and down;
(2) and the optical measurement system judges the angular speed of the tested equipment, the direction from the original point and the offset of the pitch angle according to the position of the laser point of the checkerboard where the laser installed on the tested equipment is shot.
9. The method for dynamically monitoring the two-dimensional follow-up system based on the intelligent image recognition as claimed in claim 8, wherein the step (2) specifically comprises the following steps: parameter setting of an industrial camera → image preprocessing → image calibration → image recognition and target detection → target position calculation.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010054519A1 (en) * | 2008-11-14 | 2010-05-20 | 中国科学院沈阳自动化研究所 | A device and method for measuring 6 dimension posture of moving object |
| CN102377932A (en) * | 2011-11-03 | 2012-03-14 | 深圳市贝斯得电子有限公司 | Video camera with focus-variable laser illuminator |
| CN103090883A (en) * | 2013-01-15 | 2013-05-08 | 中国电子科技集团公司第二十七研究所 | Device and method for calibrating dynamic tracking precision of photoelectric tracking system |
| CN103363902A (en) * | 2013-07-16 | 2013-10-23 | 清华大学 | Dust environment moving object pose detection device and method based on infrared lasers |
| CN103592756A (en) * | 2013-11-26 | 2014-02-19 | 中国人民解放军国防科学技术大学 | Aperture-sharing light beam two-dimensional positioning tracking method and device |
| US20140376768A1 (en) * | 2013-06-19 | 2014-12-25 | The Boeing Company | Systems and Methods for Tracking Location of Movable Target Object |
| CN204785358U (en) * | 2015-07-06 | 2015-11-18 | 天津大学 | Two dimension angle displacement adapter |
| US20160170024A1 (en) * | 2014-12-12 | 2016-06-16 | Leica Geosystems Ag | Laser tracker |
| CN108921901A (en) * | 2018-05-04 | 2018-11-30 | 北京航空航天大学 | A kind of big visual field camera calibration method based on accurate two-axis platcform and laser tracker |
| CN110246115A (en) * | 2019-04-23 | 2019-09-17 | 西安理工大学 | A kind of detection method of far-field laser light spot image |
| CN110319792A (en) * | 2019-07-23 | 2019-10-11 | 四川大学 | A kind of rail linearity degree detection system and method |
| CN111337908A (en) * | 2020-03-30 | 2020-06-26 | 苏州华兴源创科技股份有限公司 | Laser radar detection system and detection method thereof |
-
2020
- 2020-12-10 CN CN202011436278.5A patent/CN112595231A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010054519A1 (en) * | 2008-11-14 | 2010-05-20 | 中国科学院沈阳自动化研究所 | A device and method for measuring 6 dimension posture of moving object |
| CN102377932A (en) * | 2011-11-03 | 2012-03-14 | 深圳市贝斯得电子有限公司 | Video camera with focus-variable laser illuminator |
| CN103090883A (en) * | 2013-01-15 | 2013-05-08 | 中国电子科技集团公司第二十七研究所 | Device and method for calibrating dynamic tracking precision of photoelectric tracking system |
| US20140376768A1 (en) * | 2013-06-19 | 2014-12-25 | The Boeing Company | Systems and Methods for Tracking Location of Movable Target Object |
| CN103363902A (en) * | 2013-07-16 | 2013-10-23 | 清华大学 | Dust environment moving object pose detection device and method based on infrared lasers |
| CN103592756A (en) * | 2013-11-26 | 2014-02-19 | 中国人民解放军国防科学技术大学 | Aperture-sharing light beam two-dimensional positioning tracking method and device |
| US20160170024A1 (en) * | 2014-12-12 | 2016-06-16 | Leica Geosystems Ag | Laser tracker |
| CN204785358U (en) * | 2015-07-06 | 2015-11-18 | 天津大学 | Two dimension angle displacement adapter |
| CN108921901A (en) * | 2018-05-04 | 2018-11-30 | 北京航空航天大学 | A kind of big visual field camera calibration method based on accurate two-axis platcform and laser tracker |
| CN110246115A (en) * | 2019-04-23 | 2019-09-17 | 西安理工大学 | A kind of detection method of far-field laser light spot image |
| CN110319792A (en) * | 2019-07-23 | 2019-10-11 | 四川大学 | A kind of rail linearity degree detection system and method |
| CN111337908A (en) * | 2020-03-30 | 2020-06-26 | 苏州华兴源创科技股份有限公司 | Laser radar detection system and detection method thereof |
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