Lonicera caerulea active ingredient spectrum quantitative analysis system based on deep learning

Abstract

The utility model relates to the technical field of spectral quantitative analysis, in particular to a spectral quantitative analysis system for active ingredients of lonicera caerulea based on deep learning, which comprises a base, a detection shell is mounted at the upper end of the base, a lifting mechanism is jointly mounted in the base and the detection shell, a supporting plate piece is mounted on the lifting mechanism, and the supporting plate piece is mounted on the detection shell. A mounting box is arranged on one side of the detection shell in a penetrating manner, a linkage mechanism is mounted in the mounting box, an extension rod piece and a mounting frame are arranged on the linkage mechanism, and the extension rod piece is connected with the supporting plate piece. According to the system, shooting and hyperspectral image acquisition operation in a closed environment can be realized, the influence of an external environment on image acquisition can be fully avoided, meanwhile, circulating acquisition operation can be realized, and the acquisition efficiency and quality are improved.

Description

Technical Field

[0001] This invention relates to the field of spectroscopic quantitative analysis technology, and in particular to a spectroscopic quantitative analysis system for active ingredients in honeysuckle fruit based on deep learning. Background Technology

[0002] Honeysuckle berries have a bitter taste and cooling properties. They can clear heat and purge fire, reduce swelling and abscesses, and treat carbuncles, appendicitis, erysipelas, and other heat-toxin sores. The fruit contains anthocyanins, carotene, and other chemical components; it has the effects of lowering blood pressure, improving myocardial ischemia, enhancing children's vision, and preventing skin aging.

[0003] The main active ingredients in honeysuckle berries include anthocyanins, vitamin P, vitamin C, vitamin B1, B2, potassium, iron, zinc, calcium, and polyphenols such as phenolic acids and flavonoids. These components give honeysuckle berries a variety of health benefits.

[0004] Currently, the main methods for determining the content of active ingredients in plants and traditional Chinese medicinal materials include gas chromatography (GC), ultraviolet spectrophotometry (UV), high-performance liquid chromatography (HPLC), gas chromatography-mass spectrometry (GC-MS), and nuclear magnetic resonance (NMR). Although these methods are technically mature and highly accurate, they involve complex pretreatment, cumbersome procedures, and long processing times, failing to achieve the goal of rapid detection of active ingredients in plants and traditional Chinese medicinal materials. Therefore, improvements are needed. Utility Model Content

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a deep learning-based spectral quantitative analysis system for active ingredients in honeysuckle fruit.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A deep learning-based spectroscopic quantitative analysis system for active ingredients in honeysuckle fruit includes a base, a detection housing mounted on the upper end of the base, a lifting mechanism mounted together in the base and the detection housing, a support plate mounted on the lifting mechanism, a mounting box extending through one side of the detection housing, a linkage mechanism mounted in the mounting box, an extension rod and a mounting frame mounted on the linkage mechanism, and the extension rod and the support plate being connected.

[0008] A camera assembly and a hyperspectral imaging assembly are mounted on one side of the mounting bracket, and a flipping mechanism is connected to the other side of the mounting bracket. A sealing cover is provided on the flipping mechanism, and the sealing cover is hinged to the upper side of the detection housing.

[0009] The pallet component is equipped with a circulation mechanism, and the circulation mechanism is equipped with multiple carrying trays.

[0010] Compared with existing technologies, this system can perform shooting and hyperspectral image acquisition in a closed environment, which can fully avoid the influence of the external environment on image acquisition. At the same time, it can realize cyclic acquisition, improving the efficiency and quality of acquisition.

[0011] Preferably, the circulation mechanism includes a linkage belt assembly mounted on the pallet, and a circulation motor assembly is mounted on one side of the lower end of the pallet, the output shaft of the circulation motor assembly being connected to the linkage belt assembly;

[0012] Multiple bushings are installed at equal intervals on the linkage belt assembly. A vertical shaft is rotatably sleeved inside each bushing. A bearing tray is installed at the upper end of the vertical shaft, and a sliding member is installed at the lower end of the vertical shaft. The sliding member is slidably installed on the support plate.

[0013] Furthermore, the circulating motor assembly drives the linkage belt assembly to circulate. In actual operation, the linkage belt assembly consists of a belt component and multiple pulley components. Teeth can be set on the belt and pulleys for meshing to ensure linkage effect. At the same time, multiple pulley components can be evenly distributed on the edge of the pallet component so that the linkage belt assembly can move stably in circulation.

[0014] Preferably, the lifting mechanism includes two lead screws that pass through the detection housing and the base. The lower ends of the two lead screws are located inside the base. The lower ends of the two lead screws are fixed with synchronous pulleys. A synchronous belt is sleeved on the two synchronous pulleys. A drive motor assembly is installed inside the base. The drive motor assembly is connected to the lower end of one of the lead screws.

[0015] The lead screw is threaded to one end of the detection housing and a lead screw nut is connected to it. Both lead screw nuts are installed through the support plate.

[0016] Furthermore, the drive motor assembly enables one of the lead screw components to rotate, while the synchronous pulley and synchronous belt work together to achieve synchronous rotation of the two lead screw components. The rotation of the lead screw components enables the lead screw nut component to drive the support plate component to rise and fall stably.

[0017] Preferably, the linkage mechanism includes an elastic telescopic component installed at the bottom of the mounting box, an extension rod fixed to the upper end of the elastic telescopic component, one end of the extension rod extending to the lower end of the support plate, and a swing rod rotatably connecting the extension rod and the mounting frame.

[0018] Furthermore, by raising and lowering the pallet component, the extension rod can be driven to compress and extend, so that the swing rod can pull the mounting frame to move into the detection housing, and the camera component and hyperspectral imaging component can be moved into the detection housing, so that the camera component and hyperspectral imaging component can sample images of the honeysuckle berries placed on the carrying tray.

[0019] Preferably, the flipping mechanism includes a pusher fixed to one side of the mounting bracket, one end of the pusher penetrating the detection housing and extending to one side of the detection housing, and the end of the pusher located outside the detection housing is rotatably connected to a diagonal rod, the upper end of the diagonal rod being rotatably connected to a connector, and the connector being fixed to one side of the sealing cover.

[0020] Furthermore, the movement of the mounting bracket can drive the pusher to move, and the movement of the pusher can cause the inclined rod to rotate the sealing cover. That is, after the pallet is lowered into place, the sealing cover and the detection housing are closed to avoid external influences.

[0021] Preferably, a control component is installed on one side of the detection housing.

[0022] Furthermore, the control components can manipulate the operation of corresponding automated parts and process and analyze the collected data.

[0023] The beneficial effects of this utility model are:

[0024] 1. The control component can be programmed to control the operation of automated parts, receive and transmit collected data, process and analyze the data, and analyze the active ingredients of honeysuckle fruit.

[0025] 2. It can perform shooting and hyperspectral image acquisition in a closed environment, which can fully avoid the influence of the external environment on image acquisition. At the same time, it can realize cyclic acquisition operation, improving the efficiency and quality of acquisition.

[0026] 3. The circulating motor assembly drives the linkage belt assembly to circulate. In actual operation, the linkage belt assembly consists of a belt component and multiple pulley components. Teeth can be set on the belt and pulleys for meshing to ensure linkage effect. At the same time, multiple pulley components can be evenly distributed on the edge of the pallet component so that the linkage belt assembly can move stably in circulation.

[0027] 4. The drive motor assembly enables one of the lead screw components to rotate. Simultaneously, the synchronous pulley and synchronous belt work together to achieve synchronous rotation of the two lead screw components. Furthermore, the rotation of the lead screw components enables the lead screw nut component to drive the support plate component to rise and fall stably.

[0028] 5. The movement of the mounting bracket can drive the pusher to move, and the movement of the pusher can cause the inclined rod to rotate the sealing cover. That is, after the pallet is lowered into place, the sealing cover and the detection housing are closed to avoid external influences. Attached Figure Description

[0029] Figure 1This is a structural diagram of the deep learning-based spectroscopic quantitative analysis system for active ingredients in honeysuckle fruit proposed in this invention.

[0030] Figure 2 The diagram shows the internal structure of the shell in the deep learning-based spectroscopic quantitative analysis system for active ingredients in honeysuckle fruit proposed in this invention.

[0031] Figure 3 Appendix to this utility model Figure 2 Enlarged view of point A;

[0032] In the diagram: 1. Base, 2. Pushing component, 3. Detection housing, 4. Control component, 5. Connecting component, 6. Sealing cover, 7. Diagonal rod, 8. Mounting box, 9. Lead screw and nut component, 10. Lead screw component, 11. Synchronous belt, 12. Drive motor assembly, 13. Elastic telescopic assembly, 14. Synchronous pulley, 15. Extension rod, 16. Swing rod component, 17. Mounting bracket, 18. Camera assembly, 19. Hyperspectral imaging assembly, 20. Bearing tray, 21. Vertical shaft, 22. Bushing, 23. Sliding component, 24. Linkage belt assembly, 25. Support plate component, 26. Circulating motor assembly. Detailed Implementation

[0033] The technical solutions of the present utility model will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present utility model. Obviously, the described embodiments are only some embodiments of the present utility model, and not all embodiments.

[0034] Reference Figure 1-3 The deep learning-based spectroscopic quantitative analysis system for active ingredients in honeysuckle fruit includes a base 1, a detection housing 3 mounted on the upper end of the base 1, and a control component 4 mounted on one side of the detection housing 3. The control component 4 can control the operation of corresponding automated components and process and analyze the collected data.

[0035] Reference Figure 1-3 A lifting mechanism is installed in both the base 1 and the detection housing 3. A support plate 25 is installed on the lifting mechanism. A mounting box 8 is provided through one side of the detection housing 3. A linkage mechanism is installed in the mounting box 8. An extension rod 15 and a mounting frame 17 are provided on the linkage mechanism. The extension rod 15 and the support plate 25 are connected. By controlling the operation of the lifting mechanism and the linkage mechanism, the position of the extension rod 15 and the mounting frame 17 can be controlled. The camera assembly 18 and the hyperspectral imaging assembly 19 can be used to photograph the honeysuckle fruit.

[0036] Reference Figure 1-3A camera assembly 18 and a hyperspectral imaging assembly 19 are mounted on one side of the mounting bracket 17. A flipping mechanism is connected to one side of the mounting bracket 17. A sealing cover 6 is provided on the flipping mechanism. The sealing cover 6 is hinged to the upper side of the detection housing 3. The flipping mechanism can make the sealing cover 6 and the detection housing 3 come into contact and seal, which can ensure the stability of the sampling environment.

[0037] Reference Figure 1-3 The pallet 25 is provided with a circulation mechanism, and the circulation mechanism is provided with multiple carrying trays 20; the circulation mechanism includes a linkage belt assembly 24 installed on the pallet 25, and a circulation motor assembly 26 is installed on one side of the lower end of the pallet 25, and the output shaft of the circulation motor assembly 26 is connected to the linkage belt assembly 24.

[0038] Multiple bushings 22 are evenly spaced on the linkage belt assembly 24. A vertical shaft 21 is rotatably connected inside the bushing 22. A bearing tray 20 is installed at the upper end of the vertical shaft 21, and a sliding member 23 is installed at the lower end of the vertical shaft 21. The sliding member 23 is slidably installed on the support plate 25. The linkage belt assembly 24 can be driven to circulate through the action of the circulating motor assembly 26. In actual operation, the linkage belt assembly 24 is composed of a belt component and multiple pulley components. Teeth can be set on the belt and pulleys for meshing to ensure linkage effect. At the same time, multiple pulley components can be evenly distributed on the edge of the support plate 25 so that the linkage belt assembly 24 can move stably in circulation.

[0039] Reference Figure 1-3 The lifting mechanism includes two lead screws 10 that pass through the detection housing 3 and the base 1. The lower ends of both lead screws 10 are located inside the base 1, and a synchronous pulley 14 is fixed to the lower end of each lead screw 10. A synchronous belt 11 is fitted onto both synchronous pulleys 14. A drive motor assembly 12 is installed inside the base 1 and is connected to the lower end of one of the lead screws 10. A lead screw nut 9 is threaded onto one end of the lead screw 10 located inside the detection housing 3. Both lead screw nuts 9 are passed through the support plate 25. The drive motor assembly 12 enables one of the lead screws 10 to rotate. Simultaneously, the synchronous pulleys 14 and the synchronous belt 11 work together to achieve synchronous rotation of the two lead screws 10. The rotation of the lead screws 10 enables the lead screw nuts 9 to drive the support plate 25 to rise and fall stably.

[0040] Reference Figure 1-3The linkage mechanism includes an elastic telescopic component 13 installed at the bottom of the mounting box 8. An extension rod 15 is fixed to the upper end of the elastic telescopic component 13. One end of the extension rod 15 extends to the lower end of the tray 25. A swing rod 16 is rotatably connected between the extension rod 15 and the mounting frame 17. By raising and lowering the tray 25, the extension rod 15 can be squeezed, so that the swing rod 16 can pull the mounting frame 17 to move into the detection housing 3, and the camera assembly 18 and the hyperspectral imaging assembly 19 can be moved into the detection housing 3, so that the camera assembly 18 and the hyperspectral imaging assembly 19 can sample the images of the honeysuckle berries placed on the carrying tray 20.

[0041] Reference Figure 1-3 The flipping mechanism includes a pusher 2 fixed to one side of the mounting bracket 17. One end of the pusher 2 passes through the detection housing 3 and extends to one side of the detection housing 3. The end of the pusher 2 located outside the detection housing 3 is rotatably connected to a diagonal rod 7. The upper end of the diagonal rod 7 is rotatably connected to a connector 5, which is fixed to one side of the sealing cover 6. The movement of the mounting bracket 17 can drive the pusher 2 to move. The movement of the pusher 2 can cause the diagonal rod 7 to flip the sealing cover 6. That is, after the support plate 25 is lowered into place, the sealing cover 6 and the detection housing 3 are closed to avoid external influence.

[0042] In this invention, the operator can place the honeysuckle berries in the support tray 20. When the tray 25 descends, the tray 25 can press the extension rod 15, causing the swing rod 16 to pull the mounting frame 17 to move the camera assembly 18 and the hyperspectral image assembly 19 out. This facilitates the sampling of the honeysuckle berries that move sequentially from its lower end. The shooting situation of the camera assembly 18 and the hyperspectral image assembly 19 is controlled to ensure that the specifications of the captured images are the same. This ensures that the honeysuckle berries are in the same position in the image. The condition of the honeysuckle berry skin can be determined by the image captured by the camera assembly 18, and the sampling range within the image can be further clarified. This also clarifies the image acquired by the hyperspectral image assembly 19, allowing for the selection of the analysis range.

[0043] The collected data is transmitted and effectively processed by control component 4. The YOLOv5 model algorithm improves the processing effect on small objects. After selecting the appropriate sampling range, it can be divided into an S×S grid. Each grid is responsible for predicting whether the center point falls in the area. The analysis of active ingredients is achieved through comparison of multiple data.

[0044] The above description is only a preferred embodiment of the present utility model, but the protection scope of the present utility model is not limited thereto. Any equivalent substitutions or changes made by those skilled in the art within the technical scope disclosed in the present utility model, based on the technical solution and the inventive concept of the present utility model, should be included within the protection scope of the present utility model.

Claims

1. A deep learning-based spectroscopic quantitative analysis system for active ingredients in honeysuckle fruit, comprising a base (1), characterized in that: The upper end of the base (1) is equipped with a detection housing (3). A lifting mechanism is installed in both the base (1) and the detection housing (3). A support plate (25) is installed on the lifting mechanism. An installation box (8) is provided through one side of the detection housing (3). A linkage mechanism is installed in the installation box (8). An extension rod (15) and a mounting bracket (17) are provided on the linkage mechanism. The extension rod (15) and the support plate (25) are connected. A camera assembly (18) and a hyperspectral imaging assembly (19) are mounted on one side of the mounting bracket (17). A flipping mechanism is connected to one side of the mounting bracket (17). A sealing cover (6) is provided on the flipping mechanism. The sealing cover (6) is hinged to the upper side of the detection housing (3). The pallet component (25) is provided with a circulation mechanism, and the circulation mechanism is provided with multiple carrying trays (20).

2. The deep learning-based spectroscopic quantitative analysis system for active ingredients in honeysuckle berries according to claim 1, characterized in that: The circulation mechanism includes a linkage belt assembly (24) mounted on a pallet (25), and a circulation motor assembly (26) is mounted on one side of the lower end of the pallet (25). The output shaft of the circulation motor assembly (26) is connected to the linkage belt assembly (24). Multiple bushings (22) are installed at equal intervals on the linkage belt assembly (24). A vertical shaft (21) is rotatably sleeved inside the bushing (22). A bearing tray (20) is installed at the upper end of the vertical shaft (21). A sliding member (23) is installed at the lower end of the vertical shaft (21). The sliding member (23) is slidably installed on the pallet member (25).

3. The deep learning-based spectroscopic quantitative analysis system for active ingredients in honeysuckle berries according to claim 1, characterized in that: The lifting mechanism includes two lead screws (10) that pass through the detection housing (3) and the base (1). The lower ends of the two lead screws (10) are located inside the base (1). The lower ends of the two lead screws (10) are fixed with synchronous pulleys (14). The two synchronous pulleys (14) are fitted with a synchronous belt (11). A drive motor assembly (12) is installed inside the base (1). The drive motor assembly (12) is connected to the lower end of one of the lead screws (10). The lead screw component (10) is located inside the detection housing (3) with a lead screw nut component (9) threaded on one end. Both lead screw nut components (9) are installed through the support plate component (25).

4. The deep learning-based spectroscopic quantitative analysis system for active ingredients in honeysuckle berries according to claim 1, characterized in that: The linkage mechanism includes an elastic telescopic component (13) installed at the bottom of the mounting box (8). An extension rod (15) is fixed at the upper end of the elastic telescopic component (13). One end of the extension rod (15) extends to the lower end of the support plate (25). A swing rod (16) is rotatably connected between the extension rod (15) and the mounting frame (17).

5. The deep learning-based spectroscopic quantitative analysis system for active ingredients in honeysuckle berries according to claim 1, characterized in that: The flipping mechanism includes a pusher (2) fixed to one side of the mounting bracket (17). One end of the pusher (2) passes through the detection housing (3) and extends to one side of the detection housing (3). The pusher (2) located outside the detection housing (3) is rotatably connected to a diagonal rod (7). The upper end of the diagonal rod (7) is rotatably connected to a connector (5). The connector (5) is fixed to one side of the sealing cover (6).

6. The deep learning-based spectroscopic quantitative analysis system for active ingredients in honeysuckle berries according to claim 1, characterized in that: A control component (4) is installed on one side of the detection housing (3).

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