CN106773991B - Embedded deviation rectifying system based on CMOS sensor and deviation rectifying method thereof - Google Patents
Embedded deviation rectifying system based on CMOS sensor and deviation rectifying method thereof Download PDFInfo
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- CN106773991B CN106773991B CN201611270904.1A CN201611270904A CN106773991B CN 106773991 B CN106773991 B CN 106773991B CN 201611270904 A CN201611270904 A CN 201611270904A CN 106773991 B CN106773991 B CN 106773991B
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0423—Input/output
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24215—Scada supervisory control and data acquisition
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention discloses an embedded type deviation rectifying system based on a CMOS sensor and a deviation rectifying method thereof, wherein the embedded type deviation rectifying system based on the CMOS sensor comprises a deviation rectifying instrument and a control box; the correcting instrument comprises a bracket, an annular light source module, a shell, an STM32 main operation controller, a first Bluetooth module, a WiFi module, a CMOS image sensor, a state display and key control module and a TFT liquid crystal display module, wherein the annular light source module is fixed at the bottom of the bracket, the shell is fixed at the upper part of the bracket and positioned above the annular light source module, the STM32 main operation controller, the first Bluetooth module and the WiFi module are arranged in the shell, the CMOS image sensor is arranged at the lower end face of the shell, and the state display and key control module and the TFT liquid crystal display module are arranged at the upper end face of the shell; and a motor driving module and a second Bluetooth module electrically connected with the motor driving module are arranged in the control box. The invention can detect the edge of the strip before correcting the deviation, effectively prevent the phenomenon of error correction, improve the accuracy and reliability of correcting the deviation and adapt to the comprehensive requirements of actual strip production.
Description
Technical Field
The invention relates to an embedded correction system based on a CMOS sensor and a correction method thereof.
Background
At present, a visible light sensor, namely a photoelectric sensor, is mainly used in the domestic deviation correction control system, and although research on an infrared sensor and a CCD sensor is carried out, the infrared sensor and the CCD sensor are not applied to practice. The visible light sensor outputs a switching signal of offset, which can only indicate whether the visible light sensor is offset or not and the offset direction, so that the control has the problems of vibration and low precision; meanwhile, the sensor has larger light receiving interference ratio and poor anti-interference capability, so that the application range is always narrower; finally, considering that certain defects are unavoidable at the edges of the actual industrial strip, if deviation correction is carried out on the strip at the defect positions of the edges, the deviation correction is quite suitable, and even the strip is broken. In summary, the existing visible light sensor cannot meet the comprehensive requirements of actual strip production.
Disclosure of Invention
The invention aims to provide an embedded deviation rectifying system based on a CMOS sensor and a deviation rectifying method thereof, which can identify the edge defect of a strip in real time and accurately seek trace and rectify.
The technical scheme for realizing the aim of the invention is as follows: an embedded deviation rectifying system based on a CMOS sensor comprises a deviation rectifying instrument and a control box; the correcting instrument comprises a bracket, an annular light source module, a shell, an STM32 main operation controller, a first Bluetooth module, a WiFi module, a CMOS image sensor, a state display and key control module and a TFT liquid crystal display module, wherein the annular light source module is fixed at the bottom of the bracket, the shell is fixed at the upper part of the bracket and positioned above the annular light source module, the STM32 main operation controller, the first Bluetooth module and the WiFi module are arranged in the shell, the CMOS image sensor is arranged at the lower end face of the shell, and the state display and key control module and the TFT liquid crystal display module are arranged at the upper end face of the shell; the annular light source module, the first Bluetooth module, the WiFi module, the CMOS image sensor, the state display and key control module and the TFT liquid crystal display module are electrically connected with the STM32 main operation controller; a motor driving module and a second Bluetooth module electrically connected with the motor driving module are arranged in the control box; the motor driving module is electrically connected with a driving motor of the corrected equipment; and communication is realized between the STM32 main operation controller of the deviation rectifying instrument and the motor driving module of the control box through the first Bluetooth module and the second Bluetooth module.
The annular light source module of the deviation rectifying instrument is positioned at the position of 10 cm to 15cm below the lens of the CMOS image sensor.
STM32 main operation controller of deviation rectifying instrument adopts STM32F4 series chip.
The CMOS image sensor of the deviation rectifying instrument adopts OV series cameras.
The deviation rectifying method of the embedded deviation rectifying system based on the CMOS sensor comprises the following steps:
(1) firstly, powering up and initializing an STM32 main operation controller and a CMOS image sensor, then capturing a field synchronous signal, a row synchronous signal and an image synchronous signal of the CMOS image sensor by the STM32 main operation controller, and effectively acquiring an edge image of a target strip according to a signal time sequence;
(2) the STM32 main operation controller stores the acquired information into an SRAM memory of the STM32 main operation controller in a two-dimensional array mode, and displays the acquired information on the TFT liquid crystal display module in real time;
(3) the STM32 main operation controller reads the WiFi instruction and key detection in real time and judges whether the system enters a manual adjustment state or not; if the system enters a manual adjustment state, the STM32 main operation controller uploads the acquired image information to a user mobile phone through a WiFi module, and detects whether light source debugging and motor driving control are performed in real time; otherwise, if the system enters a non-manual regulation state, the STM32 main operation controller carries out real-time image processing on the collected image information, then judges whether the strip has edge defects, if so, the image collection is returned, if not, the error relative to the center of the visual field of the CMOS image sensor is calculated according to the edge centroid position of the strip, fuzzy PID control is adopted on the error, finally, a control result is sent to a motor driving module through a first Bluetooth module, and closed-loop driving is carried out on the driving motor of the rectifying equipment, so that the edge centroid position of the strip is always kept at the center of the visual field of the CMOS image sensor, and the accurate rectifying on the position of the target material is realized.
The flow of the STM32 main operation controller in the step (1) for effectively collecting the edge image of the target strip through the CMOS image sensor is as follows: after the CMOS image sensor is initialized, row counting zero clearing and column counting zero clearing are sequentially carried out; then the STM32 main operation controller detects whether the field synchronization of the CMOS image sensor reaches a falling edge or not; detecting whether the line counter reaches 480 after the field synchronization reaches the falling edge, if so, ending the acquisition of one frame of image, otherwise, detecting whether the line synchronization of the CMOS image sensor reaches the rising edge; after the line synchronization reaches the rising edge, detecting whether the image synchronization of the CMOS image sensor reaches the falling edge; when the image synchronization reaches the falling edge, a pixel value is acquired, and a column counter is increased by 1; then, whether the column counter reaches 640 is detected, if not, whether the image synchronization of the CMOS image sensor reaches the falling edge is detected, if so, the row counter is increased by 1, and if so, whether the row counter reaches 480 is detected.
In the step (3), when the system enters a non-manual regulation state, the flow of real-time image processing of the collected image information by the STM32 main operation controller is as follows: preprocessing an image, extracting an image edge, and fitting the image edge; and then identifying the image edge, judging the image edge as a defect of the strip edge if the image edge is a curve, and positioning the target edge if the image edge is a straight line to obtain an edge error.
By adopting the technical scheme, the invention has the following beneficial effects: (1) The invention not only can capture the direction of the strip edge deviation in real time, but also can acquire the deviation measurement (pixel unit), and simultaneously can detect the defects of the strip edge before correcting, and only correct the detected defect-free strip edge part, thereby effectively preventing the phenomenon of error correction, improving the accuracy and reliability of correction, and being capable of adapting to the comprehensive requirements of actual strip production.
(2) According to the invention, the annular light source module is arranged right below the CMOS image sensor lens, and the light source can be modulated through the keys, so that on one hand, the precision and accuracy of extracting the strip edge image are improved, and on the other hand, the anti-interference capability of the system to external light in actual strip production is improved.
(3) According to the rectification apparatus, the STM32 main operation controller and the motor driving module of the control box are communicated through the first Bluetooth module and the second Bluetooth module, so that the installation of the two modules is not limited by an industrial environment.
(4) The WiFi module is arranged, so that a user can directly acquire the running state of the system and manually adjust the system through the mobile phone APP, and the system operation is more intelligent and more convenient.
Drawings
In order that the invention may be more readily understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings, in which
Fig. 1 is a functional block diagram of the present invention.
Fig. 2 is a schematic structural diagram of the deviation rectifying device of the present invention.
Fig. 3 is a top view of fig. 2.
Fig. 4 is a flow chart of the deviation rectifying method of the present invention.
FIG. 5 is a flow chart of the effective acquisition of an edge image of a target strip by the STM32 main operation controller of the present invention through the CMOS image sensor.
FIG. 6 is a flowchart of real-time image processing of the acquired image information by the STM32 main operation controller when the invention enters a non-manual adjustment state.
The reference numerals in the drawings are:
the device comprises a deviation rectifying instrument 1, a bracket 1-1, an annular light source module 1-2, a shell 1-3, an STM32 main operation controller 1-4, a first Bluetooth module 1-5, a WiFi module 1-6, a CMOS image sensor 1-7, a state display and key control module 1-8 and a TFT liquid crystal display module 1-9;
control box 2, motor drive module 2-1, second bluetooth module 2-2.
Detailed Description
Example 1
Referring to fig. 1 to 3, the embedded rectification system based on the CMOS sensor of the present embodiment includes a rectification apparatus 1 and a control box 2.
The correction instrument 1 comprises a support 1-1, an annular light source module 1-2 fixed at the bottom of the support 1-1, a shell 1-3 fixed at the upper part of the support 1-1 and positioned above the annular light source module 1-2, an STM32 main operation controller 1-4, a first Bluetooth module 1-5 and a WiFi module 1-6 which are arranged in the shell 1-3, a CMOS image sensor 1-7 which is arranged at the lower end face of the shell 1-3, a state display and key control module 1-8 and a TFT liquid crystal display module 1-9 which are arranged at the upper end face of the shell 1-3. The ring-shaped light source module 1-2, the first Bluetooth module 1-5, the WiFi module 1-6, the CMOS image sensor 1-7, the state display and key control module 1-8 and the TFT liquid crystal display module 1-9 are electrically connected with the STM32 main operation controller 1-4. The annular light source module 1-2 is positioned at a position of 10-15cm right below the lens of the CMOS image sensor 1-7. STM32 main operation controller 1-4 adopts STM32F4 series chip. The CMOS image sensors 1 to 7 employ OV-series cameras.
The control box 2 is internally provided with a motor driving module 2-1 and a second Bluetooth module 2-2 electrically connected with the motor driving module 2-1. The motor driving module 2-1 is electrically connected with a driving motor of the rectifying device. The STM32 main operation controller 1-4 of the deviation rectifying instrument 1 and the motor driving module 2-1 of the control box 2 are communicated through the first Bluetooth module 1-5 and the second Bluetooth module 2-2.
Referring to fig. 4, the rectification method of the embedded rectification system based on the CMOS sensor of the present embodiment includes the following steps:
(1) firstly, the STM32 main operation controller 1-4 and the CMOS image sensor 1-7 are electrified and initialized, then the STM32 main operation controller 1-4 captures a field synchronous signal, a line synchronous signal and an image synchronous signal of the CMOS image sensor 1-7, and the effective acquisition of the edge image of the target strip is realized according to the signal time sequence.
(2) The STM32 main operation controller 1-4 stores the acquired information into the SRAM memory of the STM32 main operation controller in a two-dimensional array mode, and displays the acquired information on the TFT liquid crystal display module 1-9 in real time.
(3) The STM32 main operation controller 1-4 reads the WiFi instruction and key detection in real time and judges whether the system enters a manual adjustment state or not; if the system enters a manual adjustment state, the STM32 main operation controller 1-4 uploads the acquired image information to a user mobile phone through the WiFi module 1-6, and detects whether light source debugging and motor driving control are performed in real time; otherwise, if the system enters a non-manual regulation state, the STM32 main operation controller 1-4 carries out real-time image processing on the collected image information, then judges whether the strip has edge defects, if so, the strip returns to image collection, if not, the error relative to the center of the visual field of the CMOS image sensor 1-7 is calculated according to the edge centroid position of the strip, fuzzy PID control is adopted on the error, finally, a control result is sent to the motor driving module 2-2 through the first Bluetooth module 1-5, and closed-loop driving is carried out on the driving motor of the rectifying equipment, so that the edge centroid position of the strip is always kept at the center of the visual field of the CMOS image sensor 1-7, and accurate rectifying on the position of the target material is realized.
Referring to fig. 5, in step (1), the flow of effective collection of the edge image of the target strip by the STM32 main operation controller 1-4 through the CMOS image sensor 1-7 is as follows: after the CMOS image sensor 1-7 is initialized, row counting zero clearing and column counting zero clearing are sequentially carried out; then the STM32 main operation controller 1-4 detects whether the field synchronization of the CMOS image sensor 1-7 reaches the falling edge; after the field synchronization reaches the falling edge, detecting whether the line counter reaches 480, if so, ending the acquisition of one frame of image, otherwise, detecting whether the line synchronization of the CMOS image sensor 1-7 reaches the rising edge; after the line synchronization reaches the rising edge, detecting whether the image synchronization of the CMOS image sensor 1-7 reaches the falling edge; when the image synchronization reaches the falling edge, a pixel value is acquired, and a column counter is increased by 1; then, whether the column counter reaches 640 is detected, if not, whether the image synchronization of the CMOS image sensor 1-7 reaches the falling edge is detected, if so, the row counter is increased by 1, and if so, whether the row counter reaches 480 is detected.
Referring to fig. 6, in the step (3), when the system enters the non-manual adjustment state, the STM32 main operation controller 1-4 performs real-time image processing on the collected image information, where the process is as follows: preprocessing an image, extracting an image edge, and fitting the image edge; and then identifying the image edge, judging the image edge as a defect of the strip edge if the image edge is a curve, and positioning the target edge if the image edge is a straight line to obtain an edge error.
While the foregoing is directed to embodiments of the present invention, other and further details of the invention may be had by the present invention, it should be understood that the foregoing description is merely illustrative of the present invention and that no limitations are intended to the scope of the invention, except insofar as modifications, equivalents, improvements or modifications are within the spirit and principles of the invention.
Claims (5)
1. A deviation rectifying method of an embedded deviation rectifying system based on a CMOS sensor comprises a deviation rectifying instrument (1) and a control box (2); the correcting instrument (1) comprises a bracket (1-1), an annular light source module (1-2) fixed at the bottom of the bracket (1-1), a shell (1-3) fixed at the upper part of the bracket (1-1) and positioned above the annular light source module (1-2), an STM32 main operation controller (1-4), a first Bluetooth module (1-5) and a WiFi module (1-6) which are arranged in the shell (1-3), a CMOS image sensor (1-7) arranged at the lower end face of the shell (1-3), a state display and key control module (1-8) and a TFT liquid crystal display module (1-9) which are arranged at the upper end face of the shell (1-3); the ring-shaped light source module (1-2), the first Bluetooth module (1-5), the WiFi module (1-6), the CMOS image sensor (1-7), the state display and key control module (1-8) and the TFT liquid crystal display module (1-9) are electrically connected with the STM32 main operation controller (1-4); a motor driving module (2-1) and a second Bluetooth module (2-2) which is electrically connected with the motor driving module (2-1) are arranged in the control box (2); the motor driving module (2-1) is electrically connected with a driving motor of the corrected equipment; the STM32 main operation controller (1-4) of the deviation rectifying instrument (1) is communicated with the motor driving module (2-1) of the control box (2) through the first Bluetooth module (1-5) and the second Bluetooth module (2-2); the annular light source module (1-2) of the deviation rectifying instrument (1) is positioned at a position of 10-15cm below the lens of the CMOS image sensor (1-7);
the method is characterized in that: the deviation rectifying method comprises the following steps:
(1) firstly, powering up and initializing an STM32 main operation controller (1-4) and a CMOS image sensor (1-7), and then capturing a field synchronous signal, a row synchronous signal and a image synchronous signal of the CMOS image sensor (1-7) by the STM32 main operation controller (1-4), so as to realize effective acquisition of an edge image of a target strip according to a signal time sequence;
(2) the STM32 main operation controller (1-4) stores the acquired information into an SRAM memory of the STM32 main operation controller in a two-dimensional array form, and displays the acquired information on the TFT liquid crystal display module (1-9) in real time;
(3) the STM32 main operation controller (1-4) reads WiFi instructions and key detection in real time, and judges whether the system enters a manual adjustment state or not; if the system enters a manual adjustment state, the STM32 main operation controller (1-4) uploads the acquired image information to a user mobile phone through the WiFi module (1-6) and detects whether light source debugging and motor driving control are performed in real time; otherwise, if the system enters a non-manual regulation state, the STM32 main operation controller (1-4) carries out real-time image processing on the collected image information, then judges whether the strip has edge defects, if yes, the image collection is returned, if no, the error relative to the center of the visual field of the CMOS image sensor (1-7) is calculated according to the edge centroid position of the strip, fuzzy PID control is adopted on the error, finally, a control result is sent to the motor driving module (2-1) through the first Bluetooth module (1-5), and closed-loop driving is carried out on the driving motor of the rectifying equipment, so that the edge centroid position of the strip is always kept at the center of the visual field of the CMOS image sensor (1-7) to realize accurate rectifying on the position of the target material.
2. The method for rectifying a deviation of a CMOS sensor-based embedded deviation rectifying system according to claim 1, characterized in that: STM32 main operation controller (1-4) of rectifying instrument (1) adopts STM32F4 series chip.
3. The method for rectifying a deviation of a CMOS sensor-based embedded deviation rectifying system according to claim 1, characterized in that: CMOS image sensors (1-7) of the deviation rectifying instrument (1) adopt OV series cameras.
4. The method for rectifying a deviation of a CMOS sensor-based embedded deviation rectifying system according to claim 1, characterized in that: the STM32 main operation controller (1-4) in the step (1) effectively collects the edge image of the target strip through the CMOS image sensor (1-7) as follows: after the CMOS image sensor (1-7) is initialized, row counting zero clearing and column counting zero clearing are sequentially carried out; then, an STM32 main operation controller (1-4) detects whether the field synchronization of the CMOS image sensor (1-7) reaches a falling edge or not;
detecting whether the line counter reaches 480 after the field synchronization reaches the falling edge, if so, ending the acquisition of one frame of image, otherwise, detecting whether the line synchronization of the CMOS image sensor (1-7) reaches the rising edge; after the line synchronization reaches the rising edge, detecting whether the image synchronization of the CMOS image sensor (1-7) reaches the falling edge; when the image synchronization reaches the falling edge, a pixel value is acquired, and a column counter is increased by 1; then, whether the column counter reaches 640 is detected, if not, whether the image synchronization of the CMOS image sensor (1-7) reaches the falling edge is detected, if so, the row counter is increased by 1, and if so, whether the row counter reaches 480 is detected.
5. The method for rectifying a deviation of a CMOS sensor-based embedded deviation rectifying system according to claim 1, characterized in that: in the step (3), when the system enters a non-manual regulation state, the STM32 main operation controller (1-4) carries out real-time image processing on the acquired image information, and the flow is as follows: preprocessing an image, extracting an image edge, and fitting the image edge; and then identifying the image edge, judging the image edge as a defect of the strip edge if the image edge is a curve, and positioning the target edge if the image edge is a straight line to obtain an edge error.
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| CN109942036A (en) * | 2019-03-22 | 2019-06-28 | 桑尼环保（江苏）有限公司 | Adaptive waste water control device |
| CN112637451A (en) * | 2020-12-09 | 2021-04-09 | 武汉茂格科技有限公司 | Based on AI image recognition sensor probe mends limit control system |
| CN112506106A (en) * | 2020-12-14 | 2021-03-16 | 重庆市新众誉科技有限公司 | Deviation correcting controller based on TOUCHGFX |
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