In recent years, to improve the consumer experience and create convenient conditions for consumers usage, many liquid product manufacturers prefer the packaging machinery equipped with an advanced visual recognition system in the filling and capping of handle bottles to ensure the opening direction consistency of the product cap and the bottle handle. After purchasing the corresponding products, consumers do not need to manually align the position of the cap and the bottle body to easily open it, which further improves the consumer experience and stimulates consumer behavior, and also brings more market opportunities for the products with accurate positioning of the cap and the bottle body.
After discovering the positioning problem of the bottle cap and bottle body, Newamstar increased the research and development of the machine vision system and developed a filling and sealing integrated device equipped with visual recognition capping technology. Multiple visual inspection units are set up in the filler. Under visual inspection and data calculation, the servo control is used for precise positioning on the bottle and cap conveyor system, which solves the problem of precise positioning between the cap and the bottle body during capping, and achieved good application in well-known enterprises such as Wilmar, Hengshun and so on.
The vision system uses a CCD camera to convert the detected target information into an image signal and send it to a dedicated image processing system. The image processing system performs various operations to extract the characteristics of the target, such as area, quantity, position, and length, and then outputs the results according to the preset allowability and other conditions, including size, angle, quantity, presence/absence, etc., to achieve automatic recognition features. A typical industrial machine vision system includes light source, lens, camera, image acquisition unit, image processing unit, data transmission mechanism and motion control mechanism.
Newamstar visual recognition system is mainly composed of image acquisition and conversion system, image recognition and processing system, adaptive bottle cap positioning and catching mechanism, bottle body positioning mechanism, servo angle correction capping mechanism.
First: Image Acquisition and Conversion System
The image acquisition and conversion system consist of lighting source, a CCD or CMOS camera and lens, a camera mounting bracket, and an image acquisition and transmission system.
1.Lighting Source
The design of the lighting source needs to consider the external lighting conditions, the state of the detected object (bottle, material, cap) and the background of the detected object. External lighting conditions mainly consider the light color temperature and light intensity; the state of the detected object needs to consider its color, degree of reflection, appearance shape size and MARK point status; the detected object mainly considers the background color, background depth of field and background reflection degree.
2.Camera and Lens
The camera and lens need to be selected according to the specific conditions. The shooting focal length, shooting lighting conditions, background conditions and motion state of the subject should be taken into consideration.
It is necessary to select the lens corresponding to the focal length according to the distance of the subject from the lens; the illumination change and state of the subject directly affects the choice of the lens aperture size, and also affects the corresponding shooting parameters, such as metering method, exposure time, photosensitive ISO settings, flash parameter settings, etc.; the depth of field of the subject background affects the choice of aperture and shooting distance during shooting; the background conditions of the subject also affect the setting of the camera’s shooting parameters; the movement state of the subject directly determines the camera exposure time and its interval time.
3.Camera Mounting Bracket
It is necessary to ensure that there is no relative displacement between the camera and related parts of the device when the equipment is operating, to ensure the stability and clarity of the imaging.
4.Image Acquisition and Transmission System
It is necessary to consider the interval speed of the shooting data file generation, the file size, the single operation time of the entire system captured by the image acquisition and transmission, and the processing capacity of the image recognition processing system.
Image acquisition and transmission needs to ensure that the generated files do not appear to have longer shooting intervals due to data accumulation. This requires that the generated files must be input to image processing at high speed, processed at high speed, and output to the motion control terminal at high speed. The result is that the collected image file data does not accumulate, and the single operation time that takes up the entire system reaches a minimum.
The result of the entire image acquisition and conversion system is to convert images with clear contrast, clear pictures, and obvious MARK points into data at high speed and transmit them to the image recognition and processing system.
Second: Image Recognition and Processing System
The image recognition and processing system is mainly composed of four modules: data input, image processing, image recognition and data output.
Data input: It is necessary to ensure the smoothness of high-speed data transmission. Generally, it will be equipped with storage chips, data transmission chips, and main control modules for high-speed data transmission.
Image processing: To facilitate image recognition, the brightness, contrast, color, and other attributes of the captured image are adjusted to obtain an image with brighter contrast, clearer picture, and more obvious MARK point.
Image recognition: Identify the required image features, such as shape, size, angle, color, surface roughness, etc., and parameterize the recognition results and output them to the motion control mechanism.
Data output: basically, consistent with the requirements of data input, its purpose is to transmit the recognition results to the motion control mechanism.
Third: Self-Adaptive Bottle Cap Positioning and Catching Mechanism
In the traditional capping equipment, the capping head catches the cap, moves up and down following the cam curve, and presses the cap against the bottle mouth. However, visual recognition positioning requires that the cap remain relatively stationary with the capping head after being inspected. This requires that after the cap is photographed by the camera, the relative rotation with the capping head must be controlled within a certain range.
For this purpose, the filling-tech division designed cap positioning star wheels and mechanical active catcher to ensure that the caps in the capping star wheel and the station groove on the star wheel remain relatively stationary; When the cap is handed over, the relative rotation angle with the capping head is guaranteed to be within a certain range; the cap remains relatively stationary with the capping head after being grabbed.
The bottle cap positioning star wheel is equipped with a catching positioning mechanism. When the bottle cap enters the star wheel from the falling cap guide rail, it will be clamped and positioned, so that the cap and the station groove remain relatively stationary, until the handover of the cap and cap removal mechanism is completed.
The main functions of the active catcher are self-adaptive cap removal, following clamping positioning and active cap removal. When the active catcher contacts the bottle cap, the bottle cap starts to follow the movement of the active catcher so that the bottle cap and the catcher remain relatively still. When the active catcher is lowered under the control of the capping cam, the bottle cap and the catcher are always kept relatively still, and when the bottle cap is lowered to a certain position, the bottle cap will be clamped and locked completely.
Fourth: Bottle Positioning Mechanism
In the traditional capping equipment, bottle conveyor does not need to consider the self-rotation of the bottle. However, visual recognition positioning requires that the bottle body needs to maintain relative rotation and stillness with the capping machine after being monitored. This requires that after the bottle is photographed by the camera, the relative rotation with the capping machine must be controlled within a certain range.
In response to this problem, the filling-tech division designed a bottle body catcher for positioning at the position of the capper. The catcher catches the bottle body passively after the bottle body is handed over to the capper to keep it relatively stationary with the capper in it. The purpose is to position the bottle body and create conditions for the subsequent servo angle correction capping.
Fifth: Servo Angle Correction Capping Mechanism
In the traditional capping equipment, the lifting assembly does not need to consider the rotation of the capper head. However, the visual positioning system needs to correct the bottle cap with an incorrect angular position to the correct position. This requires a high-precision servo motion actuator for the lifting of the capping.
The filling-tech division added a set of servo motion actuators composed of servo motors and transmission gears to the lifting of the capping. This mechanism is the final motion control actuator in the visual positioning system, which is used to execute the correction parameters given by the visual recognition system. Its main function is to receive motion control information, and rotate the capping mold to make the cap and the bottle body at the correct angular position, and then lift the assembly and then press the cap correctly to the bottle mouth under the control of the capping cam.
The Newamstar visual recognition positioning capping technology has been verified by actual production with a capacity of 6,000 BPH. The operating efficiency of the entire system can reach 100%, and the recognition and operating accuracy of the entire system can reach 99.99%. While ensuring industrial production efficiency, it has greatly improved the production accuracy and provides an effective way for the intelligentialize of industrial production, which not only promotes the maturity and progress of machine vision technology in the food industry, but also creates more possibilities for its own sustainable development.
