CN210497309U - Capsule defect detection system based on machine vision - Google Patents
Capsule defect detection system based on machine vision Download PDFInfo
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- CN210497309U CN210497309U CN201921105488.9U CN201921105488U CN210497309U CN 210497309 U CN210497309 U CN 210497309U CN 201921105488 U CN201921105488 U CN 201921105488U CN 210497309 U CN210497309 U CN 210497309U
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Abstract
The utility model relates to a capsule defect detecting system based on machine vision, the system includes machine vision optical device, conveyer, sensing trigger device, PC-based image processing platform, removing device and feeding and discharging hardware control module, wherein, feeding and discharging hardware control includes vibration of vibration tank in the system, rotation of sequencing wheel, start and stop of conveyer belt and material state monitoring alarm, etc.; the conveying and triggering device realizes ordered conveying of the capsules and relative fixation of the positions in the conveying process, and meets the requirement of 360-degree shooting by virtue of friction rolling of the capsules and the bottom plate; the machine vision optical device consists of a light source, an industrial camera and a lens, acquires a capsule image according to a trigger signal, converts the capsule image into a digital image and transmits the digital image to a PC (personal computer) for processing; this intelligent capsule detection device can make accurate the discernment to the capsule defect, has improved defect detection efficiency, has practiced thrift labour cost, can satisfy the enterprise's demand basically, has extensive marketing prospect.
Description
Technical Field
The utility model relates to a detecting system, concretely relates to capsule defect detecting system based on machine vision belongs to capsule defect detection field.
Background
The capsule is a finished product which is sold to a pharmaceutical enterprise by a capsule shell manufacturer and filled with the medicament by the pharmaceutical enterprise, so the quality of the hollow capsule directly influences the quality of the finished capsule product. In the production of the hollow capsule, various hollow capsule defects such as size length defect, spots, end concavity, plum blossom head, insertion and splitting, shrivelled shell and the like are easily generated due to the restriction of a production process, and the filling of the medicament is seriously and directly influenced, so that the capsule loses the function of a container or the medicament amount is too low, and the defect detection of the hollow capsule becomes an indispensable production process for capsule manufacturing.
At present, the traditional manual lamp inspection method is mainly used for domestic capsule inspection, namely whether the capsule is qualified or not is judged by observing the appearance and the surface gloss of the capsule through naked eyes under a strong light irradiation table. Therefore, in order to improve the accuracy and the production efficiency of capsule quality detection and reduce the enterprise management cost, an intelligent capsule detection system based on machine vision is adopted.
At present, the foreign capsule detector has a mature product and relatively stable performance, but the high price makes ordinary small and medium-sized enterprises to be prosperous, and the domestic capsule detector also has some detection systems, such as a great constant technology full-automatic capsule detector, but the detection efficiency and the system stability can not be comparable with those of the foreign product, so that the development of a set of high-efficiency and stable-performance intelligent capsule detection system is imperative.
SUMMERY OF THE UTILITY MODEL
The utility model provides a capsule defect detection device based on machine vision, aiming at the problems existing in the prior art, and the device can solve the problems of slow picking speed, easy generation of visual fatigue, low detection accuracy rate, high enterprise management cost and the like of the traditional manual light inspection method; the intelligent detection of the capsule defects can be realized, the accuracy and the production efficiency of capsule quality detection are improved, the artificial risk is reduced, and the production cost and the management difficulty of enterprises are also reduced.
In order to achieve the above object, the technical solution of the present invention is as follows, a capsule defect detecting system based on machine vision, the system mainly contains machine vision optics (image acquisition) device, transmission and sensing trigger device, image processing platform based on PC, rejecting device and feeding and discharging hardware control module.
Furthermore, the conveying device mainly comprises a hopper, a material state monitoring sensor connected with the hopper, a vibration groove, a sequencing wheel, a conveying chain, a plurality of capsule grooves connected with the chain, a bottom plate and a direct current motor, wherein the vibration groove is arranged below the hopper, and the sequencing wheel is arranged between the vibration groove and the conveying chain; the sensing trigger device is characterized in that a special fluted disc is additionally arranged on a rotating shaft of the direct current motor, and opposite photoelectric sensors are arranged on two sides of the fluted disc. The conveying chain is formed by splicing chain plates, and each chain plate is provided with two capsule grooves slightly larger than capsules for relatively fixing the positions of the capsules in the conveying process; the direct current motor is used for driving the sequencing wheel and the conveying chain to simultaneously operate and keeping the linear speeds of the sequencing wheel and the conveying chain consistent, so that capsules on the sequencing wheel can accurately fall into the capsule grooves; and the friction force exists between the bottom plate and the capsules, so that the capsules are conveyed forwards in a rolling mode under the pushing of the capsule grooves, the ordered conveying of the capsules and the relative fixing of the positions in the conveying process are realized, and the requirement of 360-degree complete shooting is met.
Furthermore, the sensing trigger device is formed by adding a special fluted disc on a rotating shaft of the direct current motor, so that when the transmission chain moves to the position of one capsule groove, the fluted disc correspondingly rotates by the angle of one tooth, and the two sides of the fluted disc are provided with opposite photoelectric sensors to generate pulse signals to trigger the industrial camera to synchronously acquire the pulse signals.
Preferably, the opposite-emitting photoelectric sensor adopts an ohm dragon EE-SX670 groove type photoelectric sensor to generate an external trigger pulse, so that the acquisition frequency of the camera and the transmission speed of the capsule are mutually synchronous.
Further, the machine vision optical device is composed of a light source, an industrial camera and a lens. Under the external pulse trigger mode, the conveying chain moves one capsule groove every time to promote synchronous acquisition of 3 industrial cameras, wherein 2 end face images of the capsule are shot by the first camera, 4 cylindrical surface images of the capsule are shot by the second camera and the third camera respectively, and the images are transmitted to an image processing platform based on a PC to detect the size abnormality and the cylindrical surface defects of the capsule.
Preferably, the industrial camera adopts 3 CrevisMV-BV40G cameras; the camera lens selects an M0814-MP2 camera lens of a Computer company with a focal length of 8mm according to parameters such as the pixel size, the resolution, the working distance of the camera lens, the size of a shooting capsule and the like of the CrevisMV-BV40G camera; the light source, the camera II and the camera III adopt independent long-strip-shaped infrared LED backlight sources, a layer of diffusion plate is additionally arranged on the light source, so that the brightness of 4 capsules to be detected in the field of view of the camera keeps consistent, and because the camera I detects the defects of the end parts of the capsules, under the condition that the shooting mode of the camera is not changed, the two end surfaces of the capsules are respectively provided with a parallel infrared LED light source for front irradiation, and whether the end parts have defects or not is detected by observing reflected light.
Furthermore, the PC-based image processing platform mainly comprises modules for user management, image processing, historical data query, camera control, parameter configuration and the like, and is convenient for an operator to control hardware and query a system background database.
Preferably, the image processing platform selects Microsoft Visual Studio 2010 as a development environment, C # as a development subject language and SQL Server as a development database, and combines the development environment, the development subject language and the development database, and the image algorithm development is carried out on the C # encapsulated Opencv (EmguCV image processing library) under NET; the interaction between the PC and the external hardware control module is completed by a serial port I/O protocol, so that the PC controls the vibration of a vibration groove in a system, the rotation of a sequencing wheel, the starting and stopping of a conveyor belt, the alarm of material state monitoring and the like, and the system adopts a MoxaCP-102E type serial port card for communication.
Further, the rejecting device comprises an air pump, an air solenoid valve, a nozzle, a defective box and the like. After the acquired capsule images are analyzed and processed by the PC-based image processing module, the positions of defective capsules are marked, the number of intervals between a defective capsule groove and a defective capsule groove of a removing device is calculated, when the defective capsules reach the position above a removing spray valve, an upper computer sends a command through a serial port, a lower computer receives the command and controls to open a solenoid valve to spray the defective capsules into a defective box by using compressed gas, so that the defective capsules are removed, and the system selects a 6A-ACA-JDAA-1BA type solenoid valve of an MAC company.
Compared with the prior art, the utility model has the advantages of as follows: the technical scheme is suitable for the field of capsule defect detection, 2 end faces and 4 cylindrical images of capsules sequentially transmitted on a transmission chain are shot by a machine vision optical device in an external pulse triggering mode, the images are transmitted to a PC-based image processing platform in a digital image mode, whether the capsules have defects is judged after analysis and processing, if the capsules have the defects, a specific instruction is sent to a serial port by a PC to control a rejecting device to act, the capsules are blown into a defective box, the capsules are separated from qualified capsules which finally fall into a finished box, the intelligent detection of the capsule defects is realized, the accuracy and the production efficiency of capsule quality detection are improved, and the production cost and the management difficulty caused by the traditional manual lamp inspection method of a capsule shell manufacturer are reduced.
Drawings
Fig. 1 is a schematic view of a capsule defect detection device based on machine vision according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating the operation of the capsule defect detecting apparatus shown in fig. 1.
The specific implementation mode is as follows:
for the purpose of enhancing the understanding of the present invention, the following detailed description is made with reference to the accompanying drawings.
Example 1: referring to fig. 1, please refer to fig. 1, the embodiment of the present invention: a capsule defect detection system based on machine vision comprises a transmission and sensing trigger device, a machine vision optical (image acquisition) device, an image processing platform based on PC, an eliminating device, a feeding and discharging hardware control module and the like; the conveying device mainly comprises a hopper 11, a material state monitoring sensor 12 connected with the hopper 11, a vibration groove 13, a sequencing wheel 14, a conveying chain 15, a plurality of capsule grooves 16 connected with the chain, a bottom plate and a direct current motor; the sensing trigger device is formed by adding a special fluted disc on a rotating shaft of the direct current motor and arranging opposite photoelectric sensors 115 on two sides of the fluted disc.
The machine vision optical (image acquisition) device mainly comprises a light source 17, 3 industrial cameras 18 and a lens, wherein irradiation light vertical to the end face is additionally required for detecting the capsule end face of the camera 1, so that interference on light rays of the cameras 2 and 3 is avoided, the middle part of the capsule end face is separated by a baffle 19, and meanwhile, the whole set of machine vision optical device is placed in a closed shading box 110 so as to ensure that subsequent image acquisition is not interfered by external light rays; the PC-based image processing platform mainly comprises an industrial control upper computer 113, an extended image acquisition card, a serial port card and a display 114, realizes the acquisition and processing of images and the detection of capsule defects, sends an eliminating instruction to a serial port if the capsules have defects, controls an eliminating device 111 to open an electromagnetic valve to blow the defective capsules into a defective tank 112, and separates the defective capsules from the qualified capsules which finally fall into a finished product box 118, thereby realizing the intelligent detection of the capsule defects; wherein, the correlation type photoelectric sensor 115 adopts an ohm dragon EE-SX670 groove type photoelectric sensor; the industrial camera 18 adopts 3 CrevisMV-BV40G type cameras; the lens is an M0814-MP2 lens of a Computer company with the focal length of 8 mm; the gas electromagnetic valve is a 6A-ACA-JDAA-1BA type electromagnetic valve of MAC company.
Referring to the working flow chart of the capsule defect detecting device shown in fig. 2, firstly, the blanking 21 is performed by pouring capsules into the hopper 11 and entering the trough and arranging the capsules in order through a special structure; because the material groove is blocked due to mutual extrusion when a plurality of capsules are available, the vibrator is added in the material shaking 22 process, and the capsules are prevented from being blocked and silted through the vibration of the vibration groove 13, so that the capsules can smoothly enter the hole grooves of the sequencing wheel 14, and the material discharging 23 process is realized; the sequencing wheel 14 rotates anticlockwise, and the direct current motor drives the sequencing wheel and the conveying chain to simultaneously operate, so that the linear speed of the sequencing wheel and the conveying chain is kept consistent, and when the capsules rotate to the bottom, the capsules can automatically and accurately fall into the capsule grooves 16 of the conveying chain 15.
The conveying chain 15 is formed by splicing chain plates, each chain plate is provided with two capsule grooves 16 slightly larger than capsules, the capsule grooves are used for relatively fixing the positions of the capsules in the conveying process, and the capsules are pushed by the capsule grooves to be conveyed forwards in a rolling mode in the conveying 24 process due to the friction force between the bottom plate and the capsules; in order to facilitate the positioning of the area where the capsule is located in the image, the camera acquires the capsule once when the capsule rolls one groove, namely the position of the capsule groove in the image acquired by the camera each time is relatively fixed, the following technology is adopted: a special fluted disc is additionally arranged on a rotating shaft of a direct current motor, so that when a transmission chain 15 moves to the position of a capsule groove 16, the fluted disc correspondingly rotates by the angle of one tooth, ohmic dragon EE-SX670 groove type opposite emission type photoelectric sensors 115 are arranged on two sides of the fluted disc, the fluted disc is arranged in a sensor groove, the optical signal of the sensor is vertical to the fluted disc, when the optical signal transmitted by a transmitter is shielded by the fluted disc, the chain 15 is transmitted in the capsule, and when the capsule reaches a preset position, the optical signal of the transmitter is just induced by a receiver through the gap between the teeth on the fluted disc and the intertooth teeth to generate an external trigger pulse, and 3 CrevisMV-BV40G type cameras are triggered to simultaneously carry out the image acquisition 25 process.
The camera 1 is responsible for shooting 2 end face images of the capsule, a special illumination mode is adopted for end detection under the condition that the shooting mode of the camera is not changed, an infrared LED light source is respectively arranged at two ends of the capsule and is vertical to the front face of the end face for irradiation, and whether defects exist in the end part is detected by observing reflected light; the cameras 2 and 3 are respectively responsible for shooting 4 cylindrical images of the capsule to ensure that the cylindrical surface of the capsule can be completely unfolded in a camera view field by 360 degrees, and the light sources of the cameras 2 and 3 adopt a strip-shaped infrared LED backlight embedded in a bottom plate and are additionally provided with a layer of diffusion plate, so that the brightness of 4 capsule images to be detected in the camera view field is kept consistent; according to the parameters of the CrevisMV-BV40G camera, such as pixel size, resolution, lens working distance, capsule shooting size and the like, the lenses of the 3 cameras are M0814-MP2 lenses of Computer company with the focal length of 8 mm.
In addition, the rolling of the capsule depends only on the friction force between the capsule and the bottom plate, and the friction force between the capsule and the capsule groove can counteract the friction force between the capsule and the bottom plate, so that the capsule can not roll in the conveying process, and the cameras 2 and 3 can not shoot a complete cylindrical image of the capsule. The system thus optimizes the shape of the capsule slot 16: two pointed bulges are respectively added at the left side and the right side of the groove, so that the original surface contact of the capsule and the frames at the left side and the right side of the groove is changed into point contact, and the friction force is greatly reduced; the upper side and the lower side of the groove are respectively provided with the square groove, when the capsule is contacted with the upper side and the lower side of the groove, because the end part of the capsule is a hemispherical surface, the two sharp corners of the capsule and the groove are also in point contact, so that the friction force is reduced, and the slight point connection enables the image of the capsule and the frame of the groove to be easily separated in the subsequent image processing, thereby reducing the complexity of the image processing.
The image processing platform based on the PC mainly comprises an industrial personal computer 26, an extended image acquisition card, a serial port card 29 and a display 28, wherein the industrial personal computer 26 selects Microsoft Visual Studio 2010 as a development environment, C # as a development subject language and SQL Server as a development database and combines the development environment, the C # encapsulated Opencv (EmguCV) image processing library under NET is used for developing an image algorithm, and the image processing platform mainly comprises: modules for user login and management, image processing, historical data query, detection scheme management, camera control, parameter configuration and the like; the interaction between the industrial personal computer 26 and an external hardware control module is completed by the communication of the serial port 29, a MoxaCP-102E serial port card is selected in the system, and through the serial port 29, the industrial personal computer 26 controls the vibration of the vibration groove 13 in the system, the rotation of the sequencing wheel 14, the starting and stopping of the conveying chain 15, the material state monitoring of the material sensor 211, the starting of the alarm device 212 for alarming when the hopper 11 is empty, the starting of the removing device 210 for action if the capsule detects a defect and the like.
In the detection scheme management interface, each specification type of capsule corresponds to a series of detection parameters and camera parameters, for convenience of management, the detection parameters and the camera parameters corresponding to one capsule are classified into one detection scheme, the detection scheme management interface is responsible for creating and deleting the detection scheme of the system and modifying the parameters in the scheme, and a user inputs the parameters which are debugged in the parameter test interface and are related to image processing and defect judgment into a self-defined scheme.
Returning to the main interface, selecting the previously defined detection scheme and clicking 'start' to start detection; the program calls an image processing algorithm in real time to process and judge the defects of the capsule image acquired by the camera, the processing result is displayed on a main interface, if the capsule has defects, the position of the defective capsule is marked, the number of intervals between the defective capsule groove and a removing device groove is calculated, when the defective capsule reaches the position above a removing spray valve, the industrial personal computer 26 sends a removing instruction to a serial port 29, a gas electromagnetic valve is opened, and the defective capsule is sprayed into a defective box 112 by compressed gas, and the system selects a JD6A-ACA-AA-1 BA type electromagnetic valve of the MAC company; in the detection process, the material sensor 211 monitors the material state in the hopper 11 at regular time, if the hopper 11 is empty, the program sends an instruction to the alarm device 212 to start the alarm, the user is informed to feed materials, and if the detection of the whole batch is finished, the user clicks an end button of the main interface to stop the detection.
The embodiment of the utility model provides a pair of capsule defect detection device based on machine vision, shoot 2 terminal surfaces of capsule and 4 cylinder images of conveying in order on the conveying chain through machine vision optical device under outer pulse trigger mode, capsule image is through the image processing platform analysis and the processing back based on PC, judge whether there is the defect in the capsule, if there is the defect then the PC sends specific command control removing devices action to the serial ports, the intelligent detection of capsule defect has been realized, not only the rate of accuracy and the production efficiency that capsule quality detected have been improved, reduce artifical risk, the manufacturing cost and the management degree of difficulty of enterprise have still been reduced.
It should be noted that the above-mentioned embodiments are not intended to limit the scope of the present invention, and all equivalent changes and substitutions made on the basis of the above-mentioned technical solutions are within the scope of the present invention as defined in the claims.
Claims (5)
1. A capsule defect detection system based on machine vision is characterized by comprising a machine vision optical image acquisition device, a transmission device, a sensing trigger device, an image processing platform based on a PC (personal computer), an eliminating device and a feeding and discharging hardware control module;
the conveying device mainly comprises a hopper, a material state monitoring sensor connected with the hopper, a vibration groove, a sequencing wheel, a conveying chain, a capsule groove connected with the chain, a bottom plate and a direct current motor, wherein the vibration groove is arranged below the hopper, and the sequencing wheel is arranged between the vibration groove and the conveying chain; the sensing trigger device is characterized in that a fluted disc is additionally arranged on a rotating shaft of the direct current motor, and opposite photoelectric sensors are arranged on two sides of the fluted disc;
the conveying chain is formed by splicing chain plates, and each chain plate is provided with two capsule grooves with the size larger than that of a capsule and used for relatively fixing the position of the capsule in the conveying process; the direct current motor is used for driving the sequencing wheel and the conveying chain to simultaneously operate and keeping the linear speeds of the sequencing wheel and the conveying chain consistent, so that capsules on the sequencing wheel can accurately fall into the capsule grooves; the friction force exists between the bottom plate and the capsules, the capsules are pushed by the capsule grooves to be conveyed forwards in a rolling mode, the ordered delivery of the capsules and the relative fixation of the positions in the delivery process are realized, and the requirement of 360 degrees is metoThe need for a complete shot.
2. The system of claim 1, wherein the machine vision based capsule defect inspection device is mainly composed of a light source, 3 industrial cameras and a lens, wherein the first camera and the second camera are separated by a baffle, and the whole machine vision based capsule defect inspection device is arranged in a light shielding box.
3. The machine vision-based capsule defect detection system of claim 2, wherein the industrial camera adopts 3 CrevisMV-BV40G cameras, and in the external pulse trigger mode, the conveying chain moves one groove each time to enable the 3 cameras to synchronously acquire images, wherein the first camera acquires two end images of the capsule, and the second camera and the third camera respectively acquire 4 cylindrical surfaces of the capsule for detecting the abnormal size and cylindrical surface defects of the capsule; the PC-based image processing platform mainly comprises an industrial control upper computer, an extended image acquisition card, a serial port card and a display, realizes the acquisition and processing of images and the detection of capsule defects, sends a rejection instruction to a serial port if the capsules have defects, controls a rejection device to open an electromagnetic valve to blow the defective capsules into a defective tank so as to separate the defective capsules from qualified capsules which finally fall into a finished product box, and further realizes the intelligent detection of the capsule defects; wherein, the correlation type photoelectric sensor 115 adopts an ohm dragon EE-SX670 groove type photoelectric sensor; the industrial camera adopts 3 CrevisMV-BV40G type cameras.
4. The system of claim 3, wherein the correlation type photoelectric sensor adopts an ohm dragon EE-SX670 groove type photoelectric sensor to generate an external trigger pulse, so as to ensure that the acquisition frequency of the camera and the conveying speed of the capsule are mutually synchronous.
5. The system of claim 4, wherein the rejecting device comprises an air pump, an air solenoid valve, a nozzle and a defective capsule, the PC-based image processing module analyzes and processes the acquired capsule image, marks the position of the defective capsule and calculates the number of intervals between the defective capsule slot and the rejecting device slot, when the defective capsule reaches the position above the rejecting spray valve, the upper computer sends a command through a serial port, and the lower computer receives the command and controls to open the solenoid valve to spray the defective capsule into the defective capsule by using compressed air, so that the defective capsule is rejected.
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| CN111845076A (en) * | 2020-09-18 | 2020-10-30 | 季华实验室 | Substrate and method for judging pixel printing defects |
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| CN112837311A (en) * | 2021-03-02 | 2021-05-25 | 苏州零样本智能科技有限公司 | Polyethylene particle defect detection and identification system and method based on deep learning |
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| CN114062262A (en) * | 2021-09-24 | 2022-02-18 | 贵州大学 | Annular light source-oriented multi-view capsule defect detection device |
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| CN113589756B (en) * | 2021-10-08 | 2021-12-14 | 华兴源创(成都)科技有限公司 | Displacement sensing signal triggering device, equipment, detection system and related method |
| CN113589756A (en) * | 2021-10-08 | 2021-11-02 | 华兴源创(成都)科技有限公司 | Displacement sensing signal triggering device, equipment, detection system and related method |
| CN114887906A (en) * | 2022-05-06 | 2022-08-12 | 浙江庆元县和顺自动化科技有限公司 | Sorting all-in-one machine based on visual acquisition image |
| CN115144406A (en) * | 2022-09-07 | 2022-10-04 | 广州珐玛珈智能设备股份有限公司 | Omnibearing online industrial visual detection and screening device and method |
| CN115144406B (en) * | 2022-09-07 | 2022-11-11 | 广州珐玛珈智能设备股份有限公司 | Omnibearing online industrial visual detection and screening device and method |
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