Integrated automatic imaging and identification analysis device for two insects and plankton in water

Abstract

The utility model relates to an integrated automatic imaging and identification analysis device for two insects and plankton in water. The integrated automatic imaging and identification analysis device comprises a camera, a fluorescent light source, an electric objective table, a driving mechanism, an objective lens, an electric objective table and a backlight source. The objective lens comprises a two-insect objective lens and a plankton objective lens (switchable), or only the two-insect objective lens is used for switching detection. The two-worm objective lens is 40 times, the floating objective lens is 20 times, or the camera is integrated with the 20 times objective lens. The driving mechanism is diversified and comprises a motor, a guide rail, a synchronous belt, a proximity sensor and a synchronous belt pressing block. The device solves the problems that traditional detection is low in efficiency, poor in accuracy and insufficient in equipment adaptability, automatic imaging and recognition analysis of the two insects and the plankton are achieved, the water resource pollution source monitoring efficiency and quality are improved, and technical support is provided for water ecological environment protection and treatment.

Description

Technical Field

[0001] This application relates to a detection system, specifically an integrated automatic imaging and identification analysis device for two insects and plankton in water. Background Technology

[0002] In the process of monitoring water pollution sources, with the gradual development of detection technologies and the continuous updating of standards, the level of microbial detection is constantly evolving. Traditional total coliform microbial detection has long been used as a basic detection method, while the newly revised GB / T5750-2023 "Standard Examination Methods for Drinking Water" introduces the filter membrane concentration density gradient separation fluorescent antibody method for "two parasites" (Cryptospora and Giardia lamblia), further expanding the dimensions of microbial detection for water pollution and highlighting the increased emphasis on monitoring microscopic pathogenic organisms.

[0003] From a macro-ecological perspective, eutrophication of water bodies is becoming increasingly severe, with frequent algal blooms in China, seriously disrupting the aquatic ecological balance. Algae and phytoplankton, as key components of aquatic ecosystems, are diverse, abundant, and reproduce rapidly. Their excessive proliferation not only severely disrupts aquatic biodiversity, but also the algal toxins produced by the death of some algae can endanger human health through the food chain. Therefore, accurate classification and counting of algae in water are of great significance for the management and prevention of aquatic ecological problems, providing crucial data for maintaining aquatic ecological stability and protecting human health.

[0004] Currently, the detection of phytoplankton (algae) and other zooplankton is mainly based on HJ1215-2021 "Determination of Phytoplankton in Water Quality: Filter Membrane-Microscopic Counting Method" and HJ1216-2021 "Determination of Phytoplankton in Water Quality: 0.1ml Counting Frame-Microscopic Counting Method". These two standards are based on direct microscopic examination, which requires dilution or concentration of collected samples, staining and slide preparation, followed by morphological identification and counting by testing personnel using a microscope.

[0005] However, this traditional testing method has significant drawbacks. On the one hand, the testing efficiency is extremely low, relying entirely on manual microscopic observation, identification, and counting. Testing a single sample often takes 2-3 hours, which severely hinders testing efficiency and timeliness when dealing with a large number of samples, making it difficult to meet the needs of rapid water quality monitoring. On the other hand, the testing accuracy is poor. Due to the strong subjectivity of human judgment, the complexity of planktonic species, and the large differences in judgment among personnel with different levels of skill and expertise, the accuracy and consistency of the test results are poor, affecting the assessment and treatment decisions for water pollution.

[0006] Furthermore, the detection equipment has poor adaptability. The size difference between the two types of parasites and planktonic organisms is significant, requiring frequent and substantial adjustments to microscope parameters such as focal length and magnification during microscopic examination. The two types of parasites are tiny and require high-magnification imaging systems, while planktonic organisms are larger, and using the same imaging configuration will result in incomplete imaging, increasing the target search and scanning time.

[0007] Given the numerous shortcomings of existing detection technologies, there is an urgent need for an innovative integrated automated imaging and identification analysis device for aquatic parasites, spirilla, and planktonic organisms. For example, by rationally configuring components such as a camera, fluorescent light source, electroporative stage, drive mechanism, objective lens, motorized stage, and backlight, efficient and accurate detection of these parasites and planktonic organisms can be achieved. This would improve detection efficiency, accuracy, and equipment adaptability, meeting the growing demand for water pollution source monitoring and providing solid technical support for aquatic ecological environment protection and governance. Utility Model Content

[0008] The purpose of this application is to address the aforementioned problems in the prior art by providing an integrated automatic imaging and identification analysis device for two types of insects and plankton in water.

[0009] To achieve the above-mentioned application objectives, this application adopts the following technical solution: an integrated automatic imaging and identification analysis device for two aquatic insects and plankton includes a camera, a fluorescent light source located below the camera, an electrozooscopic stage located below the fluorescent light source, a first drive mechanism for driving the electrozooscopic stage, the fluorescent light source and the camera to move along the Z-axis, an objective lens located below the electrozooscopic stage, an electric stage located below the objective lens, a second drive mechanism for driving the electric stage to move horizontally along the X and Y axes, and a backlight source located below the electric stage.

[0010] The objectives include a two-insect objective for detecting two types of insects and a planktonic objective for detecting plankton. The objectives can be switched by rotating or moving horizontally.

[0011] Furthermore, the two insect objectives are 40x objectives, and the floating objective is a 20x objective; or, the camera integrates a 20x objective.

[0012] Furthermore, when the electroscope stage is moved along the Z-axis, the first drive mechanism includes a Z-axis motor.

[0013] Furthermore, when driving the electric stage to move horizontally, the second drive mechanism includes an X-axis motor and / or a Y-axis motor.

[0014] Furthermore, it also includes a DIC component and a third drive mechanism for driving the DIC component to move horizontally, corresponding to DIC imaging when the DIC component moves below the camera, and exiting DIC imaging when the DIC component moves out of the camera's field of view.

[0015] Furthermore, the third drive mechanism includes a drive motor, a guide rail, and a timing belt. The DIC assembly is connected to the timing belt, and the drive motor drives the DIC assembly to move back and forth along the length of the guide rail through the timing belt and the timing belt pulley set on the guide rail.

[0016] Furthermore, the third drive mechanism also includes a proximity sensor for detecting the extreme positions of the DIC component.

[0017] Furthermore, the DIC component is connected to the timing belt via a timing belt pressure block.

[0018] Furthermore, the timing belt pressure block is connected to the DIC assembly via a fixing plate.

[0019] Compared with the prior art, the present invention has the following significant advantages:

[0020] 1. Significantly improved detection efficiency: It changes the inefficient method of manual microscopic observation, identification and counting in the past. Through the integrated automatic imaging and identification analysis device, the sample can be detected quickly, eliminating the need for 2-3 hours of manual testing for a single sample. This greatly shortens the detection time and can process a large number of test samples in a short time, meeting the needs of rapid water resource monitoring and improving the overall detection efficiency.

[0021] 2. Significantly improved detection accuracy: This overcomes the problem of large discrepancies in test results caused by subjective judgment differences among different testers. The device's automated imaging and precise identification analysis functions can perform detection based on pre-set programs and parameters, reducing the interference of human factors in the determination of plankton species. This makes the test results more accurate, reliable, and stable, providing a solid data foundation for the precise management of the aquatic ecological environment.

[0022] 3. Enhanced Equipment Adaptability: Addressing the significant size differences between the two organisms (parasites and plankton) and the varying imaging light source requirements, this device utilizes different magnification objectives (e.g., 40x for parasites, 20x for plankton, or a 20x objective integrated with the camera). Combined with flexible switching of the electro-microscope stage and precise control of its position or motorized stage via the drive mechanism, along with targeted fluorescent and backlight sources, the device effectively adapts to the detection requirements of both parasites and plankton on the same instrument. This avoids the inconvenience and errors caused by frequent equipment changes or microscope parameter adjustments, enabling efficient detection of multiple target organisms, optimizing the detection process, and improving the overall performance and adaptability of the equipment. This provides an effective solution for comprehensive monitoring of water pollution sources. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of a preferred embodiment of the present application;

[0024] Figure 2 This is a schematic diagram of another preferred embodiment of the present application;

[0025] Figure 3 yes Figure 2 A schematic diagram of the third drive mechanism in the diagram;

[0026] Figure 4 This is a schematic diagram illustrating the application of a preferred embodiment of this application in a system;

[0027] Figure 5 This is a flowchart of a preferred embodiment of this application.

[0028] In the diagram, 1. Cloud server; 2. Host computer; 3. Integrated automatic imaging and identification analysis device for aquatic insects and plankton; 4. Two-insect objective lens; 5. Plankton objective lens; 6. Plankton classification information database; 7. Sample slide; 8. Third drive mechanism; 9. DIC component; 21. Display module; 31. Housing; 32. Camera; 33. Fluorescent light source; 34. Electroacoustic stage; 35. Objective lens; 36. Electroacoustic stage; 37. Backlight; 81. Drive motor; 82. Guide rail; 83. Synchronous belt; 84. Proximity sensor; 85. Synchronous belt pressure block; 86. Fixing plate; 87. Synchronous belt pulley assembly. Detailed Implementation

[0029] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0030] Those skilled in the art should understand that, in the disclosure of this application, the terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the above terms should not be construed as limitations on this application.

[0031] Example 1

[0032] like Figure 1As shown, this integrated automatic imaging and identification analysis device 3 for aquatic insects and plankton includes a housing 31, a camera 32 (which can be a CCD camera or a CMOS camera, without limitation) housed within the housing 31, a fluorescence light source 33 located below the camera 32, an electrophysiological stage 34 located below the fluorescence light source 33, an objective lens 35 located below the electrophysiological stage 34, a motorized stage 36 located below the objective lens 35, and a backlight 37 located below the motorized stage 36. The motorized stage 36 is used to place the sample 7 and can move along the XY axes (or the XYZ axes). Multiple objective lenses 35 with varying magnifications are available. The electrophysiological stage 34 can be rotated to switch between objective lenses 35, or it can be moved horizontally to switch between objective lenses, without limitation. The electrophysiological stage 34, fluorescence light source 33, and camera 32 move simultaneously as a whole, driven by a Z-axis motor to move up and down along the Z-axis.

[0033] The motorized stage 36 is driven by X-axis and Y-axis motors. The driving principle of the motorized stage 36 is consistent with that of existing electron microscope stages, utilizing X-axis and Y-axis motors in combination with a lead screw drive, similar to existing XY two-axis linear modules. Its principle and structure will not be elaborated further here. If it is a three-axis (XYZ) system, an additional Z-axis motor is added for driving.

[0034] Among them, the motorized stage 36 is used to place the sample 7; the objective lens 35 includes a two-insect objective lens 4 (40x objective lens) for detecting two insects and a planktonic objective lens 5 (20x objective lens) for detecting plankton, and the objective lens 35 can be switched by rotating or moving horizontally;

[0035] Preferably, since plankton includes algae and zooplankton, and most zooplankton are examined under a microscope like algae, this embodiment mainly focuses on detecting algae. If other zooplankton need to be detected, different magnification objectives can be used, but a 20x objective is usually chosen. If two insects are being detected, a 40x objective is usually chosen. The specific detection and identification methods are based on existing algorithms, and this application does not make any improvements.

[0036] Example 2

[0037] Based on the same concept, such as Figure 2 and Figure 3 As shown, this embodiment provides a third drive mechanism 8 and a DIC component 9. In this embodiment, the DIC component 9 uses the third drive mechanism 8 to drive horizontal movement to achieve the switching of DIC mode.

[0038] DIC stands for Differential Interference Contrast, a microscope invented by Francis Smith around 1947 and improved by Georges Nomarski in 1952, remaining in use today. It can be used for imaging transparent samples such as cells, producing images with strong three-dimensional depth. In imaging transparent samples, compared to phase contrast and oblique illumination techniques, DIC is suitable for slightly thicker samples, offering stronger three-dimensionality, a higher numerical aperture, and richer detail. Specific details are prior art and will not be elaborated here. The DIC component 9 is also prior art, and its structure and principle will not be described further. The key technical point of this invention lies in the addition of a third driving mechanism 8 to drive the DIC component 9.

[0039] In this embodiment, when the DIC component 9 moves horizontally, the third drive mechanism 8 includes an X-axis motor and / or a Y-axis motor. Preferably, the third drive mechanism 8 includes a drive motor 81, a guide rail 82, and a synchronous belt 83. The DIC component 9 is connected to the synchronous belt 83 via a synchronous belt pressure block 85, which is connected to the DIC component 9 via a fixing plate 86. The drive motor 81 drives the DIC component 9 to move back and forth along the length of the guide rail 82 via the synchronous belt 83 and the synchronous belt pulley set 87 on the guide rail 82. That is, linear motion output is achieved by using the rotational motion of the motor through belt drive.

[0040] Preferably, the third drive mechanism 8 further includes a proximity sensor 84, which is used to detect the extreme positions of the DIC component 9. The proximity sensor 84 can also be a limit switch or a photoelectric sensor commonly used in automation. The specific method of implementing the limit is also existing technology and will not be elaborated here.

[0041] When the DIC component 9 moves below the camera 32, it detects two insects and enters the DIC imaging mode. When the DIC component 9 moves out of the camera 32, it detects plankton and exits the DIC imaging mode. That is, in this embodiment, the camera 32 can detect plankton using its own hardware in its original state. When the DIC component 9 moves below the camera 32, it can detect two insects by switching the objective lens 35 on the electro-observatory stage 34. The specific detection and identification method is an application of existing technology algorithms, and this application has not made any improvements.

[0042] The electric stage 36 can move along the XY axes (or the XYZ axes), which is consistent with the scheme in Embodiment 1, and will not be described again here.

[0043] In this embodiment, the electric stage 36 can move horizontally along the XY axis, and the electric stage 34, camera 32, fluorescent light source 33, and DIC assembly 9 can move vertically along the Z axis.

[0044] Example 3

[0045] Based on the same concept, for ease of understanding, such as Figure 4 and Figure 5 As shown, based on Example 1, this example provides an application scheme for integrating the integrated automatic imaging and identification analysis device 3 for aquatic insects and plankton into the system, specifically including:

[0046] Cloud server 1 is connected to host computer 2;

[0047] In this embodiment, the cloud server 1 is a product of the prior art, and its main function is to store the data uploaded by the host computer 2 and to act as a data relay. Then, it notifies the testing personnel of the message through the message notification interface via mini-program, mobile terminal, SMS and other means, without the need for personnel monitoring.

[0048] The host computer 2 is equipped with a display module 21, which is used to display the recognition results;

[0049] In this embodiment, the host computer 2 can be a computer or a tablet device. It can perform human-computer interaction and display detection results through the display module 21, and communicate with the two insect objective lens 4, the planktonic objective lens 5, and the integrated automatic imaging and identification analysis device for two insects and planktonic organisms in water 3. The communication method can be wireless communication or wired communication, and the communication protocol is not limited here.

[0050] The integrated automatic imaging and identification analysis device 3 for aquatic insects and plankton is connected to the host computer 2 for scanning sample 7.

[0051] In this embodiment, the integrated automatic imaging and identification analysis device 3 for two insects and plankton in water can install the existing analysis and identification algorithm for detecting two insects on the storage device of the host computer 2. Based on the user's selection, the host computer 2 can call the analysis and identification algorithm for detecting two insects in the storage device to perform identification, and also carries the parameters of the integrated automatic imaging and identification analysis device 3 for detecting two insects in water.

[0052] Among them, such as Figure 3 As shown, the detection process for the two insects includes:

[0053] The integrated automatic imaging and identification analysis device 3 for aquatic insects and plankton receives instructions from the host computer 2. The electric objective stage 34 switches to the two-insect objective, the fluorescence light source 33 is turned on, the backlight 37 is turned off, and the electric stage 36 moves upward in the Z-axis direction to the appropriate focal length driven by the motor. The user places the sample in the corresponding position of the electric stage 36, and the two insect targets in the sample 7 are clearly imaged. The electric stage 36 begins to move under the drive of the X-axis and Y-axis motors. The camera 32 scans the target area of ​​the sample and finally transmits the image back to the host computer 2 for automatic identification and analysis.

[0054] In this embodiment, existing analysis and identification algorithms for plankton can be installed on the storage device of the host computer 2. Based on the user's selection, the host computer 2 can call the plankton analysis and identification algorithm in the storage device for identification. It also carries the parameters of the integrated automatic imaging and identification analysis device 3 for plankton, including aquatic insects and plankton.

[0055] Among them, such as Figure 3 As shown, the plankton detection process is as follows:

[0056] The integrated automatic imaging and identification analysis device 3 for aquatic insects and plankton receives instructions from the host computer 2. The electric stage 34 switches to the plankton objective 5, the fluorescence light source 33 is turned off, the backlight 37 is turned on, and the electric stage 36 moves downward in the Z-axis direction to the appropriate focal length driven by the motor. The user places the sample in the corresponding position of the electric stage 36, and the plankton target in the sample 7 is clearly imaged. The electric stage 36 begins to move under the drive of the XY axis motor, and the camera 32 scans the target area of ​​the sample. Finally, the image is transmitted back to the host computer 2 for automatic identification and analysis.

[0057] Preferably, the system also includes a plankton classification information database 6, which stores a large number of plankton species. This database helps the plankton objective lens 5 to perform data comparison and then provides analysis and identification results based on the comparison, thereby improving identification efficiency and accuracy. The method of comparison is existing technology and will not be elaborated here.

[0058] The parts not described in detail in this application are prior art, so they are not described in detail in this application. The algorithms mentioned in this application are all utilizations of prior art and do not improve the methods of computer programs.

[0059] It is understood that the term "a" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element can be one, while in another embodiment, the number of the element can be multiple, and the term "a" should not be understood as a limitation on the number.

[0060] Although this document uses a significant amount of technical terminology, the possibility of using other terms is not excluded. These terms are used merely to facilitate the description and explanation of the nature of this application; interpreting them as any additional limitation would be contrary to the spirit of this application.

[0061] This application is not limited to the above-described preferred embodiments. Anyone can derive other products in various forms under the guidance of this application. However, regardless of any changes made to their shape or structure, any technical solution that is the same as or similar to that of this application falls within the protection scope of this application.

Claims

1. An integrated automatic imaging and identification analysis device for two aquatic insects and plankton, characterized in that, It includes a camera, a fluorescent light source located below the camera, an electro-animal stage located below the fluorescent light source, a first drive mechanism for driving the electro-animal stage, the fluorescent light source and the camera to move along the Z-axis, an objective lens located below the electro-animal stage, an electric stage located below the objective lens, a second drive mechanism for driving the electric stage to move horizontally along the X and Y axes, and a backlight located below the electric stage. The objective lens includes a dual-insect objective lens for detecting two insects and a planktonic objective lens for detecting plankton. The objective lens can be switched by rotating or moving horizontally.

2. The integrated automatic imaging and identification analysis device for two aquatic insects and plankton as described in claim 1, characterized in that, The two insect objectives are 40x objectives, and the floating objective is a 20x objective.

3. The integrated automatic imaging and identification analysis device for two aquatic insects and plankton as described in claim 1, characterized in that, The first drive mechanism includes a Z-axis motor.

4. The integrated automatic imaging and identification analysis device for two aquatic insects and plankton according to claim 1, characterized in that, When driving the electric stage to move horizontally, the second drive mechanism includes an X-axis motor and / or a Y-axis motor.

5. The integrated automatic imaging and identification analysis device for aquatic insects and plankton according to any one of claims 1-4, characterized in that, It also includes a DIC component and a third drive mechanism for driving the DIC component to move horizontally. When the DIC component moves to below the camera, it corresponds to DIC imaging, and when the DIC component moves out of the camera's field of view, it exits DIC imaging.

6. The integrated automatic imaging and identification analysis device for two aquatic insects and plankton according to claim 5, characterized in that, The third drive mechanism includes a drive motor, a guide rail, and a timing belt. The DIC component is connected to the timing belt, and the drive motor drives the DIC component to move back and forth along the length of the guide rail through the timing belt and the timing belt pulley set on the guide rail.

7. The integrated automatic imaging and identification analysis device for two aquatic insects and plankton according to claim 6, characterized in that, The third drive mechanism also includes a proximity sensor for detecting the extreme positions of the DIC component.

8. The integrated automatic imaging and identification analysis device for two aquatic insects and plankton according to claim 6, characterized in that, The DIC component is connected to the timing belt via a timing belt pressure block.

9. The integrated automatic imaging and identification analysis device for two aquatic insects and plankton according to claim 8, characterized in that, The synchronous belt pressure block is connected to the DIC assembly via a fixing plate.

Images