Device for near-infrared real-time measurement of crystallinity of polylactic acid suction pipe

Abstract

The utility model relates to the technical field of devices for near-infrared real-time measurement of crystallinity of polylactic acid suction pipes, in particular to a device for near-infrared real-time measurement of crystallinity of polylactic acid suction pipes. The device comprises a production line and a detection box, the production line is driven by a stepping motor and penetrates through the detection box, and the bottom of the production line is supported by a rack; window shades are arranged on the two sides of the detection box, a near-infrared parallel light source, a near-infrared camera, a mass spectrometer and a positioning table are arranged in the detection box, a controller and a buzzer are arranged on the top of the detection box, and a display screen and operation keys are arranged on the side face of the detection box; the infrared and near-infrared parallel light source, the near-infrared camera, the mass spectrometer, the positioning table, the display screen and the operation keys are electrically connected with the controller; and the controller is in two-way communication with the Ali cloud Internet of Things platform. According to the near-infrared real-time detection device for the crystallinity of the polylactic acid suction pipe, the near-infrared real-time detection device for the crystallinity of the polylactic acid suction pipe is manufactured by using a near-infrared spectrum and near-infrared image analysis technology to detect the crystallinity of the polylactic acid, the operation steps are simple, and the detection sensitivity is high.

Description

Technical Field

[0001] This utility model relates to the technical field of devices for real-time near-infrared measurement of the crystallinity of polylactic acid straws, and in particular to a device for real-time near-infrared measurement of the crystallinity of polylactic acid straws. Background Technology

[0002] Near-infrared (NIR) spectroscopy is a novel detection technique capable of rapidly and accurately performing non-destructive testing on the physical, mechanical, and chemical properties of organic samples, including powders, liquids, and solids. It has been widely and rapidly applied in various fields, enabling field testing, online monitoring, and product quality control. In materials science, NIR is extensively used to determine the chemical composition, density, and strength of materials; however, research on determining the crystallinity of materials is relatively limited.

[0003] Crystallinity is an important material property indicator for polylactic acid (PLA) products, especially in the manufacture of heat-resistant products such as cups and straws. Crystallinity directly affects the quality of PLA and its derivatives. Traditional PLA crystallinity measurements are not only complex and time-consuming, but also require the use of chemicals to separate the sample material, making large-scale measurements impractical. Utility Model Content

[0004] To overcome the shortcomings of existing methods, this invention provides a near-infrared real-time device for measuring the crystallinity of polylactic acid straws.

[0005] The technical solution adopted by this utility model to solve its technical problem is: a device for real-time near-infrared determination of the crystallinity of polylactic acid pipettes, characterized in that it includes a production line and a detection box; the production line is driven by a stepper motor, runs through the interior of the detection box, and is supported at the bottom by a frame; the detection box is equipped with light-shielding curtains on both sides, and includes a near-infrared parallel light source, a near-infrared camera, a mass spectrometer, and a positioning stage inside, with a controller and a buzzer on the top, and a display screen and operation buttons on the side; the near-infrared parallel light source, near-infrared camera, mass spectrometer, positioning stage, display screen, and operation buttons are electrically connected to the controller; the controller communicates bidirectionally with the Alibaba Cloud IoT platform.

[0006] According to another embodiment of the present invention, the positioning platform is further comprising: a mass sensor is provided in the middle of the production line; a condenser lens is provided at the bottom of the condenser lens; the bottom of the condenser lens is connected to a light collecting tube via a light collecting component; the bottom of the light collecting tube is connected to a mass spectrometer via an optical fiber; and the mass sensor is electrically connected to a controller.

[0007] According to another embodiment of the present invention, the condenser lens is larger than the positioning stage.

[0008] According to another embodiment of the present invention, the detection box is further provided with a near-infrared camera at the top center and several sets of near-infrared parallel light sources at the top and around the perimeter; the near-infrared camera is connected to the controller via a Raspberry Pi, and the near-infrared parallel light sources are arranged parallel to each other at the top, with the sides at a 90-degree angle to the top near-infrared parallel light sources, and are electrically connected to the controller.

[0009] According to another embodiment of the present invention, the Raspberry Pi further includes acquiring near-infrared camera image data and performing data analysis, and communicating bidirectionally with the controller based on TCP protocol Socket technology.

[0010] According to another embodiment of the present invention, the controller further includes, characterized in that, an STM32 main control board, a WIFI module, a data acquisition module, an output module, an alarm module, and a power supply module; the power supply module supplies power to the STM32 main control board; the STM32 main control board is connected to operation buttons, a near-infrared camera, a mass sensor, and a mass spectrometer through the data acquisition module; it is connected to a stepper motor, a near-infrared parallel light source, and a display screen through the output module; it is connected to a buzzer through the alarm module; and it communicates bidirectionally with the Alibaba Cloud IoT platform through the WIFI module.

[0011] According to another embodiment of the present invention, the Alibaba Cloud IoT platform communicates bidirectionally with the business server, the business server stores data in the database, and communicates bidirectionally with the APP.

[0012] The beneficial effects of this invention are that it improves the accuracy of measurement by using near-infrared imaging and spectral technology, and the operation is simple, fast, and easy to promote. Attached Figure Description

[0013] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0014] Figure 1 This is a schematic diagram of the structure of this utility model;

[0015] Figure 2 yes Figure 1 Sectional view of AA;

[0016] Figure 3 This is a schematic diagram of the structure at the top of the testing box;

[0017] Figure 4 This is a structural diagram of the positioning platform;

[0018] Figure 5 This is a schematic diagram of the controller's structure;

[0019] Figure 6 This is a flowchart of the process of this utility model.

[0020] In the diagram: 1. Production line; 2. Testing box; 3. Stepper motor; 4. Frame; 5. Blackout curtain; 6. Infrared parallel light source; 7. Near-infrared camera; 8. Mass spectrometer; 9. Positioning stage; 10. Controller; 11. Buzzer; 12. Display screen; 13. Operation buttons; 14. Mass sensor; 15. Condenser lens; 16. Light collector; 17. Light collector tube. Detailed Implementation

[0021] like Figure 1 This is a schematic diagram of the structure of this utility model, a device for real-time near-infrared determination of the crystallinity of polylactic acid pipettes, characterized by comprising a production line 1 and a detection chamber 2; the production line 1 is driven by a stepper motor 3, runs through the interior of the detection chamber 2, and is supported at the bottom by a frame 4; the detection chamber 2 is provided with light-shielding curtains 5 on both sides, and includes a near-infrared parallel light source 6, a near-infrared camera 7, a mass spectrometer 8, and a positioning stage 9 inside, with a controller 10 and a buzzer 11 on the top, and a display screen 12 and operation buttons 13 on the side; the near-infrared parallel light source 6, the near-infrared camera 7, the mass spectrometer 8, the positioning stage 9, the display screen 12, and the operation buttons 13 are electrically connected to the controller 10; the controller 10 communicates bidirectionally with the Alibaba Cloud IoT platform.

[0022] According to another embodiment of the present invention, the positioning stage 9 is disposed in the middle of the production line 1, a mass sensor 14 is disposed in the middle, a condenser lens 15 is disposed at the bottom, and the bottom of the condenser lens 15 is connected to a light collecting tube 17 through a light collecting component 16; the bottom end of the light collecting tube 17 is connected to a mass spectrometer 8 through an optical fiber; the mass sensor 14 is electrically connected to a controller 10.

[0023] According to another embodiment of the present invention, the condenser lens 15 is larger than the positioning stage 9.

[0024] Specifically, the near-infrared light source 6 emits near-infrared light, which illuminates the polylactic acid pipette to be tested on the positioning stage 9. The reflected light from the test item is focused by the condenser lens 6 and collected by the funnel-shaped light collector 7. The light signal is transmitted to the mass spectrometer 8 through the optical fiber via the light collector tube 17. The mass spectrometer 8 analyzes the collected signal and transmits the analysis results to the controller 10.

[0025] According to another embodiment of the present invention, the detection box 2 is further provided with a near-infrared camera 7 at the top center and a number of near-infrared parallel light sources 6 at the top and around the perimeter; the near-infrared camera 7 is connected to the controller 10 via a Raspberry Pi, the near-infrared parallel light sources 6 are arranged parallel to the top, the sides are at a 90-degree angle to the top near-infrared parallel light sources 6, and are electrically connected to the controller 10.

[0026] According to another embodiment of the present invention, the Raspberry Pi further includes acquiring image data from the near-infrared camera 7 and performing data analysis, and communicating bidirectionally with the controller 10 based on TCP protocol Socket technology.

[0027] Specifically, the Raspberry Pi captures images from the near-infrared camera 7, which are then processed by the software platform. The image is transformed from the RGB color space to the Lab color space through a visual control system. The polylactic acid (PLA) straw region is segmented by establishing a Gaussian mixture model. The segmented image containing only the PLA straw region is then converted into grayscale. Wavelet transform is used to reduce speckle noise interference. The DBSCAN clustering algorithm is used to find pixels containing only the PLA straw region. The crystallinity center value is calculated and used as the input to the piecewise regression model. The predicted crystallinity value is then output to the controller 10.

[0028] According to another embodiment of the present invention, the controller 10 further includes an STM32 main control board, a WIFI module, a data acquisition module, an output module, an alarm module, and a power supply module. The power supply module supplies power to the STM32 main control board. The STM32 main control board is connected to operation buttons 13, a near-infrared camera 7, a mass sensor 14, and a mass spectrometer 8 through the data acquisition module. It is connected to a stepper motor 3, a near-infrared parallel light source 6, and a display screen 12 through the output module. It is connected to a buzzer 11 through the alarm module. It communicates bidirectionally with the Alibaba Cloud IoT platform through the WIFI module.

[0029] According to another embodiment of the present invention, the Alibaba Cloud IoT platform communicates bidirectionally with the business server, the business server stores data in the database, and communicates bidirectionally with the APP.

[0030] Specifically, the Alibaba Cloud IoT Platform is an integrated platform that combines functions such as device management, secure data communication, and message subscription. It supports connecting to a massive number of devices and collecting device data for cloud upload. It provides cloud APIs, allowing the server to send commands to the device for remote control and output information to the APP. This makes it easy to view recent overall testing data and individual historical data, and to understand the crystallinity of the polylactic acid straws produced, facilitating adjustments.

[0031] In the specific operation process, the straw to be tested is placed on the production line 1. The stepper motor 3 is driven by the controller 10 to enter the testing box 2. Data is collected by the infrared parallel light source 6 in conjunction with the near-infrared camera 7 and the condenser lens 15. When the quality sensor 14 detects a change in quality, the real-time collected data is output to the controller 10 for data analysis. The results are transmitted to the display screen 12 in real time and stored in the cloud through the Alibaba Cloud IoT platform. The data is then received through the APP.

[0032] The above description is illustrative only and not restrictive of this utility model. Those skilled in the art will understand that many modifications, variations or equivalents can be made without departing from the spirit and scope defined by the appended claims, and all such modifications, variations or equivalents will fall within the protection scope of this utility model.

Claims

1. A device for real-time near-infrared determination of the crystallinity of polylactic acid pipettes, comprising a production line (1) and a detection box (2); the production line (1) is driven by a stepper motor (3), runs through the interior of the detection box (2), and is supported at the bottom by a frame (4); the detection box (2) is provided with light-shielding curtains (5) on both sides, and includes a near-infrared parallel light source (6), a near-infrared camera (7), a mass spectrometer (8), and a positioning stage (9) inside, a controller (10) and a buzzer (11) on the top, and a display screen (12) and operation buttons (13) on the side; the near-infrared parallel light source (6), the near-infrared camera (7), the mass spectrometer (8), the positioning stage (9), the display screen (12), and the operation buttons (13) are electrically connected to the controller (10); the controller (10) communicates bidirectionally with the Alibaba Cloud IoT platform; characterized in that, The detection box (2) is equipped with a near-infrared camera (7) at the top center and several sets of near-infrared parallel light sources (6) at the top and around the perimeter. The positioning stage (9) is set in the middle of the production line (1), with a mass sensor (14) in the middle and a condenser lens (15) at the bottom. The bottom of the condenser lens (15) is connected to a light collecting tube (17) through a light collecting component (16), and the bottom of the light collecting tube (17) is connected to a mass spectrometer (8) through an optical fiber. The near-infrared parallel light source (6) illuminates the sample on the positioning stage (9), and the reflected light is collected by the condenser lens (15) and transmitted to the mass spectrometer (8). The near-infrared camera (7) is connected to the controller (10) through a Raspberry Pi.

2. The device for real-time near-infrared determination of polylactic acid pipette crystallinity according to claim 1, characterized in that, The condenser (15) is larger than the positioning stage (9).

3. The device for real-time near-infrared determination of polylactic acid pipette crystallinity according to claim 1, characterized in that, The near-infrared parallel light source (6) is set parallel to the top, and the side is at a 90-degree angle to the top near-infrared parallel light source (6).

4. The device for real-time near-infrared determination of polylactic acid pipette crystallinity according to claim 1, characterized in that, The Raspberry Pi collects image data from the near-infrared camera (7) and performs data analysis, and communicates bidirectionally with the controller (10) based on the TCP protocol Socket technology.

5. The device for real-time near-infrared determination of polylactic acid pipette crystallinity according to claim 1, characterized in that, The controller (10) includes an STM32 main control board, a WIFI module, a data acquisition module, an output module, an alarm module, and a power supply module. The power supply module supplies power to the STM32 main control board. The STM32 main control board is connected to the operation button (13), near-infrared camera (7), mass sensor (14), and mass spectrometer (8) through the data acquisition module. It is connected to the stepper motor (3), near-infrared parallel light source (6), and display screen (12) through the output module. It is connected to the buzzer (11) through the alarm module. It communicates bidirectionally with the Alibaba Cloud IoT platform through the WIFI module.

6. The device for real-time near-infrared determination of polylactic acid pipette crystallinity according to claim 5, characterized in that, The Alibaba Cloud IoT platform communicates bidirectionally with the business server, which stores data in the database and communicates bidirectionally with the APP.

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