CN108380509B - Machine vision-based LED lamp panel sorting and detecting system - Google Patents
Machine vision-based LED lamp panel sorting and detecting system Download PDFInfo
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- CN108380509B CN108380509B CN201711295826.5A CN201711295826A CN108380509B CN 108380509 B CN108380509 B CN 108380509B CN 201711295826 A CN201711295826 A CN 201711295826A CN 108380509 B CN108380509 B CN 108380509B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/34—Sorting according to other particular properties
- B07C5/344—Sorting according to other particular properties according to electric or electromagnetic properties
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
- B07C5/36—Sorting apparatus characterised by the means used for distribution
- B07C5/361—Processing or control devices therefor, e.g. escort memory
- B07C5/362—Separating or distributor mechanisms
Abstract
The invention discloses a machine vision-based LED lamp panel sorting and detecting system and a machine vision-based LED lamp panel sorting and detecting method, wherein the system comprises a camera identification station, a mechanical arm grabbing station, an electrical parameter measuring station and a product sorting station, the camera identification station comprises a camera frame and a camera, the mechanical arm grabbing station comprises a transverse sliding table, a sliding piece, a vertical sliding table, a rotating motor, a vacuum chuck and a longitudinal sliding table, the product sorting station comprises a rotating cylinder, a baffle and a sliding chute, and the method comprises the following steps: image recognition; positioning the manipulator; testing the quality of the electric energy; and (4) sorting the products. The LED lamp panel sorting and detecting system and method based on machine vision are completely mechanized, the working efficiency is higher than that of traditional manual detection, the phenomenon that inferior-quality products are mixed in finished products is avoided, the safety of workers is guaranteed through complete automatic processing, detection data of the products are processed and stored in a unified mode, checking and recording are facilitated, sorting can be carried out according to different LED lamp panel shapes, and subsequent boxing and packaging are greatly facilitated.
Description
Technical Field
The invention relates to the technical field of sorting and detecting of LED lamp panels, in particular to a sorting and detecting system and method of an LED lamp panel based on machine vision.
Background
The current industrial production line gradually moves to automatic production, and the detection technology of products still uses a manual detection method more than ever. Obviously, the speed of manual detection is absolutely inferior to the production speed of an automatic production line, so that the product can only be sampled and checked, and the quality of the product cannot be effectively guaranteed. When mechanical operation is performed for a long time, workers are easy to suffer mental fatigue, and defective products are mixed in finished products. Meanwhile, the household power supply with the voltage of 220V is usually used for testing, and if the use mode of a testing instrument is improper, an accident will occur, so that the household power supply belongs to one of dangerous stations in a production line. To sum up, the disadvantages/shortcomings of the prior art:
1. the manual detection speed is slow;
2. has certain dangerousness;
3. statistical difficulties in the data;
4. a situation may arise in which inferior products are mixed into the finished product.
Disclosure of Invention
The invention aims to provide a machine vision-based LED lamp panel sorting and detecting system and a machine vision-based LED lamp panel sorting and detecting method, which have higher working efficiency than the traditional manual detection, do not cause the phenomenon that inferior-quality products are mixed in finished products, have complete automatic treatment, keep workers away from danger, ensure the safety of the workers, uniformly process and store detection data of the products, and are convenient to check and record so as to solve the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: LED lamp panel letter sorting and detecting system based on machine vision, snatch station, electrical parameter measurement station and product letter sorting station including camera discernment station, arm, camera discernment station includes camera frame and camera, and camera frame movable mounting is on equipment support, camera shelf location camera, a side-mounting conveyer belt of camera frame, place the LED lamp panel on the conveyer belt, the arm snatchs the station and includes horizontal slip table, saddle, vertical slip table, rotating electrical machines, vacuum chuck and vertical slip table, and vertical slip table is installed on equipment support, and the block has horizontal slip table on the vertical slip table, and vertical slip table slides on horizontal slip table through fixed connection's saddle, install the rotating electrical machines on the vertical slip table, vacuum chuck is installed to the bottom of rotating electrical machines, electrical parameter measurement station includes the LED testboard, the side at the conveyer belt is installed to the LED testboard, product letter sorting station includes revolving cylinder, baffle and spout, and the revolving cylinder is installed in the side of conveyer belt, and the baffle is installed on the top of revolving cylinder, the side at another conveyer belt is installed to the spout.
Preferably, the camera is electrically connected with the PC terminal.
Preferably, the mechanical arm grabbing station is controlled by a PLC.
Another technical problem to be solved by the present invention is to provide a system and a method for sorting and detecting LED lamp panels based on machine vision, comprising the following steps:
firstly, identifying an image;
secondly, positioning the manipulator;
thirdly, testing the quality of the electric energy;
and fourthly, sorting the products.
Preferably, the step one image recognition comprises the following steps:
firstly, calibrating;
secondly, distinguishing the LED lamp panels, taking a picture with two LED lamp panels, extracting shape information of the two LED lamp panels by using labview, and distinguishing different lamp panels by using the shape of the two LED lamp panels;
step three, extracting the position information of the LED lamp panel;
fourthly, setting a modbus host by using an opc of labview, wherein the communication format is consistent with the setting in the PLC;
and fifthly, connecting the PC and the PLC through a 485 communication line, and binding the required variables to realize communication.
Preferably, the positioning of the second manipulator comprises the following steps:
the method comprises the steps of firstly, performing origin point regression, wherein when a servo motor is powered on and started up each time, the origin point regression needs to be performed once to ensure that the current value of a pulse at the origin point is reset, and the PLC performs the origin point regression by using a ZRN instruction;
secondly, positioning a manipulator, wherein in order to enable the manipulator to accurately and quickly reach a positioning point, a linear interpolation instruction PPMA of an absolute coordinate is used;
preferably, the step three power quality test comprises the following steps:
the method comprises the following steps that firstly, the PLC communicates with the power quality module, and the communication protocol of the power quality module is a Modbus RTU communication protocol, so that the PLC can read data of a slave computer by using a MODRD instruction. The communication format is consistent with the PC communication;
and step two, floating point number conversion, wherein the read data are double-precision floating point numbers, each register only stores 8 bits of data, four registers of D1073, D1074, D1075 and D1076 are respectively occupied, D1037 is a high bit, D1076 is a low bit, and the register data need to be recombined into 16 bits because the PLC instruction INT is a 16-bit instruction, so that the floating point number conversion can be carried out.
Preferably, the step four product sorting comprises the following steps:
step one, after the LED lamp panel test is completed, the LED lamp panel enters a product sorting station:
secondly, when the LED lamp panel is tested to be qualified, the rotary cylinder does not act, and the LED lamp panel enters a qualified area; when the LED lamp panel is unqualified in test, the rotary air cylinder controls the baffle to act, and finally the LED lamp panel enters the unqualified area through the sliding groove.
Preferably, the calibration in step one comprises the following steps:
firstly, loading a collected calibration template image, wherein the calibration template is horizontally placed on a working plane in the image;
and secondly, performing threshold segmentation on the image by adjusting parameters to enable black dots to be displayed from the background. If the calibration template does not completely cover the view field, the range of the calibration template needs to be manually marked, and the measurement precision can be ensured only in the area covered by the template. Finally, defining the size range and the roundness range of the identified points to prevent fine noise points in the image from being identified as calibration dots by mistake;
inputting related information of the calibration template, the distance between the centers of two adjacent circle points in the X direction, and the distance between the centers of two adjacent circle points in the Y direction and the unit of the distance;
fourthly, the system learns the template, a calculation method needs to be manually selected, the three distortion coefficients and the tangential distortion are considered at the same time, the calibration precision is improved, the calculation speed is reduced, and the system needs to be selected according to actual requirements;
fifthly, setting a coordinate system for the calibration image so as to obtain accurate coordinate values of the points in subsequent measurement;
sixthly, storing the calibrated result as a png format file, and calling the png format file during measurement;
and seventhly, testing the calibration precision, shooting a picture in which the ruler is placed, loading the calibrated file, and measuring the precision by using a visual assistant, wherein the precision reaches 0.01mm.
Compared with the prior art, the invention has the beneficial effects that: according to the LED lamp panel sorting and detecting system and method based on machine vision, two LED lamp panels of different models are recognized by a camera recognition station, collected image information is sent to a PC (personal computer) end, information obtained by analyzing and processing the appearance shapes of the LED lamp panels through LabVIEW is sent to a PLC (programmable logic controller), the information is sent to the PLC to drive a vacuum chuck on a manipulator to sort the two LED lamp panels and place the LED lamp panels into corresponding electrical parameter measuring stations, after detection is completed, the LED lamp panels are grabbed and returned to a conveying belt to be conveyed to a product sorting station, and when the quality of electric energy of the LED lamp panels is qualified, the LED lamp panels continue to move forwards on the conveying belt to enter a qualified area. When the electric energy quality of LED lamp panel is unqualified, revolving cylinder control baffle, make unqualified lamp plate get into the spout, get into unqualified district, each station interrelating cooperation, complete mechanization work, work efficiency is higher than traditional artifical the detection, the phenomenon that the substandard product thoughtlessly enters the finished product can not appear, complete automated processing, let the workman keep away from danger, guarantee workman's safety, the detection data of product is unified to be handled at the computer and deposits, conveniently look over and the record, and can sort according to the LED lamp panel shape of difference, and the locating position after the letter sorting is fixed, subsequent vanning packing has been made things convenient for greatly.
Drawings
FIG. 1 is a schematic view of the overall structure of the present invention;
FIG. 2 is a schematic structural diagram of a camera recognition station of the present invention;
FIG. 3 is a schematic view of a robot arm gripping station of the present invention;
FIG. 4 is a schematic diagram of an electrical parameter measurement station of the present invention;
FIG. 5 is a schematic diagram of a product sorting station of the present invention;
FIG. 6 is a state diagram of loading a captured calibration template image;
FIG. 7 is a state diagram of the test calibration accuracy;
fig. 8 is a schematic diagram of extracting position information of the LED lamp panel;
FIG. 9 is a schematic diagram of an origin regression routine;
fig. 10 is a schematic diagram of a routine for using a linear interpolation command PPMA of absolute coordinates;
FIG. 11 is a schematic diagram of a use routine of a PLC using a MODRD instruction;
FIG. 12 is a schematic diagram of a routine for using a PLC instruction INT that is a 16-bit instruction;
in the figure: the camera recognition station is 1, the camera frame is 11, the camera is 12, the mechanical arm grabbing station is 2, the transverse sliding table is 21, the sliding table is 22, the sliding table is 23 vertical, the rotating motor is 24, the vacuum chuck is 25, the sliding table is 26 longitudinal, the electrical parameter measuring station is 3, the LED test table is 31, the product sorting station is 4, the rotating cylinder is 41, the baffle is 42, the sliding chute is 43, the conveying belt is 5, the equipment support is 6, and the LED lamp panel is 7.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, the system for sorting and detecting LED lamp panels based on machine vision includes a camera recognition station 1, a mechanical arm grabbing station 2, an electrical parameter measuring station 3 and a product sorting station 4, the camera recognition station 1 includes a camera frame 11 and a camera 12, the camera frame 11 is movably mounted on an equipment support 6, the camera frame 11 is mounted with the camera 12, the camera 12 is electrically connected with a PC terminal, used for analyzing the data of the LED lamp panel 7, a conveyor belt 5 is arranged on one side of a camera frame 11, the LED lamp panel 7 is placed on the conveyor belt 5, the LED lamp panel 7 is randomly placed on the conveyor belt 5, a camera 12 identifies the shape of the LED lamp panel 7, the position information on the conveyor belt 5 and the deflection angle of the relative electrical parameter measuring station 3, and sends the identified information to a PLC, so as to facilitate the subsequent station processing, the mechanical arm grabbing station 2 comprises a transverse sliding table 21, a sliding piece 22, a vertical sliding table 23, a rotating motor 24, a vacuum sucker 25 and a longitudinal sliding table 26, the mechanical arm grabbing station 2 is controlled by a PLC, the longitudinal sliding table 26 is installed on the equipment support 6, the transverse sliding table 21 is clamped on the longitudinal sliding table 26, the longitudinal sliding table 26 slides on the transverse sliding table 21 through the sliding piece 22 which is fixedly connected, the rotating motor 24 is installed on the vertical sliding table 23, the vacuum sucker 25 is installed at the bottom end of the rotating motor 24, after obtaining the information of the coordinate and the deflection angle recognized by the camera 12, the PLC controls the mechanical arm to grab the LED lamp panel 7, the electric parameter measuring station 3 comprises an LED test bench 31, the LED test bench 31 is arranged on the side surface of the conveyor belt 5, after the shape information of the camera 12 is obtained, the PLC controls the LED lamp panel 7 to reach the corresponding test bench, and the rotating motor 24 on the Z axis rotates and aligns, so that the LED lamp panel 7 is connected to a power supply of the test bench. And then measuring electrical parameters and judging whether the lamp panel is qualified or not. And finally, the LED lamp panel 7 is sent back to the conveyor belt 5, the working efficiency is higher than that of traditional manual detection, the phenomenon that inferior-quality products are mixed into finished products cannot occur, detection data of the products are processed and stored in a unified mode and are convenient to check and record, the product sorting station 4 comprises a rotary cylinder 41, a baffle 42 and a sliding groove 43, the rotary cylinder 41 is installed on the side face of the conveyor belt 5, the baffle 42 is installed at the top end of the rotary cylinder 41, the sliding groove 43 is installed on the other side face of the conveyor belt 5, and the LED lamp panel 7 enters the product sorting station 4 after the test is completed. When the LED lamp panel 7 is tested to be qualified, the rotary cylinder 41 does not act, and the LED lamp panel 7 enters a qualified area; when the LED lamp panel 7 is unqualified in test, the rotating cylinder 41 controls the baffle 42 to act, and finally the LED lamp panel 7 enters an unqualified area through the sliding groove 43, so that the worker is kept away from danger, the safety of the worker is guaranteed, the LED lamp panel 7 can be sorted according to different shapes, the placing position after sorting is fixed, and the subsequent packing is greatly facilitated.
The LED lamp panel sorting and detecting system and method based on machine vision comprises the following steps:
the method comprises the following steps of firstly, image recognition, wherein the image recognition comprises the following steps:
(1) Calibrating, wherein calibrating comprises;
1) Loading the collected calibration template image, wherein the calibration template should be horizontally placed on the working plane in the image, as shown in fig. 6:
2) The image is thresholded by adjusting parameters so that the black dots appear from the background. If the calibration template does not completely cover the view field, the range of the calibration template needs to be manually marked, and the measurement precision can be ensured only in the area covered by the template. Finally, defining the size range and the roundness range of the identified points to prevent fine noise points in the image from being identified as calibration dots by mistake;
3) Inputting related information of a calibration template, a distance between two circle points adjacent to each other in the X direction, and a distance between two circle points adjacent to each other in the Y direction and a distance unit;
4) The system learns the template, needs to manually select a calculation method, considers three distortion coefficients and tangential distortion simultaneously to improve the calibration precision, reduces the calculation speed and needs to select according to actual requirements;
5) Setting a coordinate system for the calibration image so as to obtain accurate coordinate values of the points in subsequent measurement;
6) Storing the calibrated result as a png format file, and calling the png format file during measurement;
7) And finally, testing the calibration precision, shooting a picture in which the ruler is placed, loading the calibrated file, and performing precision measurement by using a visual assistant until the precision reaches 0.01mm, as shown in FIG. 7:
(2) Distinguishing the LED lamp panels, taking a picture with two LED lamp panels, extracting shape information of the two LED lamp panels by using labview, and distinguishing different lamp panels by using the shape of the LAbview;
(3) Extracting the position information of the LED lamp panel, as shown in the following figure 8:
(4) Carrying out modbus host setting by using the opc of labview, wherein the communication format is consistent with the setting in the PLC;
(5) The PC and the PLC are connected through a 485 communication line, and required variables are bound, so that communication can be carried out between the PC and the PLC.
Secondly, positioning the manipulator, wherein the positioning of the manipulator comprises;
(1) The origin returns, when letting servo motor power-on start at every turn, all need carry out the origin and return once, ensures that the pulse current value of origin resets, and PLC uses the ZRN instruction to carry out the origin and returns, and the origin returns the routine and sees figure 9:
(2) In order to enable the manipulator to accurately and quickly reach a positioning point, a linear interpolation command PPMA of absolute coordinates is used, and a using routine of the command is shown in fig. 10:
and thirdly, testing the power quality, wherein the testing of the power quality comprises the following steps:
(1) The PLC communicates with the power quality module, and the communication protocol of the power quality module is a Modbus RTU communication protocol, so that the PLC can read data of the slave machine by using a MODRD instruction. The communication format is consistent with the PC communication, and the instruction use routine is shown in FIG. 11:
(2) Floating point number conversion, because the data that reads are double precision floating point number, each register has only stored 8 bits of data, occupies four registers D1073, D1074, D1075, D1076 respectively, and D1037 is the high order, and D1076 is the low order, and because PLC instruction INT is 16 bit instructions again, so need to make up 16 bits with register data reconfiguration, just can carry out floating point number conversion, the routine is seen in fig. 12:
fourthly, sorting the products, wherein the sorting of the products comprises:
(1) The LED lamp panel 7 enters a product sorting station after the test is completed:
(2) When the LED lamp panel 7 is tested to be qualified, the rotary cylinder 41 does not act, and the LED lamp panel 7 enters a qualified area; when the LED lamp panel 7 fails in the test, the rotary air cylinder 41 controls the baffle plate 42 to act, and finally the LED lamp panel 7 enters the failure area through the sliding groove 43.
The working process is as follows: two types of LED lamp panels 7 with different models are placed on a small conveyor belt, a camera 12 sends collected image information to a PC (personal computer) end on a camera identification station 1, the appearance shapes of the LED lamp panels 7 are analyzed and processed through LabVIEW, position information (including coordinates, angles and the like) of the LED lamp panels 7 with different models is obtained, and the identified information is sent to a PLC (programmable logic controller). In the mechanical arm grabbing station 2, the PLC drives the vacuum chuck 25 on the mechanical arm to sort the two LED lamp panels 7 and place the two LED lamp panels into the corresponding electrical parameter measuring stations 3. And testing important indexes such as power factors, frequency and the like of the LED lamp panel 7 by using the electric energy quality testing module, and sending data to the touch screen. After the detection is finished, the LED lamp panel 7 is grabbed and returned to the conveying belt 5, and along with the movement of the conveying belt 5, the LED lamp panel 7 enters the product sorting station 4. When the power quality of the LED lamp panel 7 is qualified, the LED lamp panel 7 continues to move forwards on the conveyor belt 5 and enters a qualified area. When the electric energy quality of the LED lamp panel 7 is unqualified, the rotary air cylinder 41 controls the baffle 42 to enable the unqualified lamp panel to enter the chute 43 and enter the unqualified area, and the test and sorting of the LED lamp panel 7 are completed.
In summary, according to the system and the method for sorting and detecting the LED lamp panels based on the machine vision, the camera recognition station 1 is adopted to recognize two types of LED lamp panels 7 with different models and send collected image information to the PC end, information obtained by analyzing and processing the appearance shapes of the LED lamp panels 7 by LabVIEW is sent to the PLC, the information is sent to the PLC to drive the vacuum chuck 25 on the manipulator to sort the two types of LED lamp panels 7 and place the LED lamp panels 7 in the corresponding electrical parameter measuring station 3, after the detection is finished, the LED lamp panels 7 are grabbed and sent back to the conveyor belt 5 to be conveyed to the product sorting station 4, and when the quality of the electric energy of the LED lamp panels 7 is qualified, the LED lamp panels 7 continue to move forward on the conveyor belt 5 and enter a qualified area. When the electric energy quality of LED lamp panel 7 is unqualified, revolving cylinder 41 controls baffle 42, make unqualified lamp plate get into spout 43, get into the unqualified district, each station interrelating cooperation, complete mechanization work, work efficiency is higher than traditional manual detection, the phenomenon that the substandard product thoughtlessly advances in the finished product can not appear, complete automated processing, let the workman keep away from danger, guarantee workman's safety, the detection data of product is unified to be handled at the computer and is deposited, conveniently look over and the record, and can sort according to the 7 shapes of different LED lamp panels, and the locating place after the letter sorting is fixed, subsequent vanning packing has been made things convenient for greatly.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered as the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.
Claims (1)
1. A method for sorting and detecting LED lamp panels based on machine vision is characterized by being applied to an LED lamp panel sorting and detecting system based on machine vision, the system comprises a camera identification station (1), a mechanical arm grabbing station (2), an electrical parameter measuring station (3) and a product sorting station (4), the camera identification station (1) comprises a camera frame (11) and a camera (12), the camera frame (11) is movably installed on an equipment support (6), the camera frame (11) is provided with the camera (12), a side installation conveying belt (5) of the camera frame (11), an LED lamp panel (7) is placed on the conveying belt (5), the mechanical arm grabbing station (2) comprises a transverse sliding table (21), a sliding piece (22), a vertical sliding table (23), a rotating motor (24), a vacuum sucker (25) and a longitudinal sliding table (26), the longitudinal sliding table (26) is installed on the equipment support (6), the transverse sliding table (21) is clamped on the longitudinal sliding table (26), the longitudinal sliding table (26) is fixedly connected with the sliding piece (22) on the transverse sliding table (21), the sliding table (24) comprises the rotating motor (24), and the sliding table (24) is provided with the vacuum parameter measuring motor (31), the LED testing table (31) is arranged on the side face of the conveying belt (5), the product sorting station (4) comprises a rotary cylinder (41), a baffle plate (42) and a sliding chute (43), the rotary cylinder (41) is arranged on the side face of the conveying belt (5), the baffle plate (42) is arranged at the top end of the rotary cylinder (41), and the sliding chute (43) is arranged on the other side face of the conveying belt (5); the camera (12) is electrically connected with the PC end; the mechanical arm grabbing station (2) is controlled by a PLC;
the method comprises the following steps:
s1, image recognition, which comprises the steps of calibrating, extracting shape information of an LED lamp panel and distinguishing the LED lamp panel;
s2, positioning a manipulator;
s3, testing the quality of the electric energy;
s4, sorting products;
s1 comprises the following steps:
s11, calibrating;
s12, distinguishing the LED lamp panels, taking a picture of the two LED lamp panels, extracting shape information of the two LED lamp panels by using labview, and distinguishing different lamp panels by using the shapes of the two LED lamp panels;
s13, extracting position information of the LED lamp panel;
s14, setting a modbus host by using the opc of labview, wherein the communication format is consistent with the setting in the PLC;
s15, connecting the PC end with the PLC through a 485 communication line, and binding required variables to enable communication to be carried out;
s2 comprises the following steps:
s21, performing origin point regression, wherein when the servo motor is powered on and started up each time, the origin point regression needs to be performed once to ensure that the current value of the pulse at the origin point is reset, and the PLC performs the origin point regression by using a ZRN instruction;
s22, positioning the manipulator, wherein in order to enable the manipulator to accurately and quickly reach a positioning point, a linear interpolation instruction PPMA of absolute coordinates is used;
s3 comprises the following steps:
s31, the PLC communicates with the power quality module, and a communication protocol of the power quality module is a Modbus RTU communication protocol, so that the PLC can read data of a slave machine by using a MODRD instruction; the communication format is consistent with the communication of the PC terminal;
s32, floating point number conversion, wherein the read data are double-precision floating point numbers, each register only stores 8 bits of data and occupies four registers of D1073, D1074, D1075 and D1076 respectively, D1037 is a high bit and D1076 is a low bit, and the PLC instruction INT is a 16-bit instruction, so that the register data are required to be recombined into 16 bits, and the floating point number conversion can be carried out;
s4 comprises the following steps:
s41, after the LED lamp panel (7) is tested, the LED lamp panel enters a product sorting station:
s42, when the LED lamp panel (7) is tested to be qualified, the rotary air cylinder (41) does not act, and the LED lamp panel (7) enters a qualified area; when the LED lamp panel (7) is unqualified in test, the rotating cylinder (41) controls the baffle (42) to act, and finally the LED lamp panel (7) enters an unqualified area through the sliding groove (43);
s11 comprises the following steps:
s111, loading a collected calibration template image, wherein the calibration template is horizontally placed on a working plane in the image;
s112, carrying out threshold segmentation on the image by adjusting parameters to enable black dots to be displayed from the background; if the calibration template does not completely cover the view field, the range of the calibration template needs to be manually marked, and the measurement precision can be ensured only in the area covered by the template; finally, defining the size range and the roundness range of the identified points to prevent fine noise points in the image from being identified as calibration dots by mistake;
s113, inputting related information of the calibration template, the distance between the centers of two adjacent circle points in the X direction, and the distance between the centers of two adjacent circle points in the Y direction and the unit of the distance;
s114, the system learns the template, a calculation method needs to be manually selected, the calibration precision is improved by considering three distortion coefficients and tangential distortion, the calculation speed is reduced, and the method needs to be selected according to actual requirements;
s115, setting a coordinate system for the calibration image so as to obtain an accurate coordinate value of a point in subsequent measurement;
s116, storing the calibrated result as a png format file, and calling during measurement;
and S117, finally testing the calibration precision, shooting a picture in which the ruler is placed, loading the calibrated file, and measuring the precision by using a visual assistant, wherein the precision reaches 0.01mm.
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