Soil particle size distribution detection walking stick based on microscopic image and analysis method

Abstract

The invention discloses a soil particle size distribution detection walking stick based on microscopic images and an analysis method, and belongs to the technical field of soil research, the soil particle size distribution detection walking stick comprises a main body, the main body is cylindrical, the length of the main body can be adjusted, a handle is arranged at the top end of the main body, a control assembly is arranged on the handle, and a data transmission interface is arranged on the back face of the handle. The bottom of the main body is provided with a detection assembly, and the main body is internally provided with a central control assembly. According to the soil particle size distribution detection walking stick based on the microscopic image and the analysis method, the microscopic imaging technology, the image analysis algorithm and the intelligent data processing system are integrated in the portable equipment, the collected soil microscopic image is processed in real time, soil particle size distribution data are rapidly calculated and displayed in real time, and the detection accuracy of the soil particle size distribution is improved. The method can adapt to soil environments of different types and different scenes, and can quickly and accurately detect the soil granularity.

Description

Technical Field

[0001] The present invention relates to the technical field of soil research, and in particular to a soil particle size distribution detection cane and analysis method based on microscopic imaging. Background Art

[0002] In agriculture, soil particle size distribution significantly influences soil fertility, water retention, and air permeability. Accurately understanding soil particle size distribution helps farmers apply fertilizers, irrigate appropriately, and select appropriate crop varieties. For example, sandy soils have larger particles, offer good air permeability but poor water retention, making them suitable for growing drought-tolerant crops. Clayey soils, with their finer particles, retain water but poor air permeability, are more suitable for growing aquatic crops.

[0003] In the fields of geological exploration and soil research, researchers need to quickly obtain soil particle size data at different locations in the field to assist in geological structure analysis, soil type classification, and ecological environment assessment.

[0004] Traditional soil particle size analysis methods include sieving, hydrometers, and laser detection, but these methods are cumbersome and time-consuming. For example, sieving requires preparing multiple sieves of varying apertures and performing the sieving process manually or mechanically. This process is susceptible to human interference and has limited accuracy for fine-grained soils. The hydrometer method requires the preparation of specific solutions and complex sedimentation tests, which require a high level of laboratory environment and operator skill, and the analysis process can take hours or even days to complete. While laser particle size analysis has improved detection efficiency to a certain extent, it also has numerous drawbacks. Its equipment is bulky and expensive, making it difficult to carry for field testing. Furthermore, this method requires extremely high sample dispersion; poor dispersion can seriously affect the accuracy of the test results. Furthermore, laser particle size analysis is susceptible to environmental factors such as temperature and humidity during the detection process, resulting in poor data stability. These traditional methods are extremely inconvenient to carry large amounts of equipment and reagents for field testing, making them incapable of rapidly acquiring soil particle size distribution information. Summary of the Invention

[0005] The purpose of the present invention is to provide a soil particle size distribution detection stick and analysis method based on microscopic imaging, which integrates microscopic imaging technology, image analysis algorithm and intelligent data processing system into a portable device, performs real-time processing on the collected soil microscopic images, quickly calculates the soil particle size distribution data and displays it in real time, can adapt to soil environments of different types and scenarios, and quickly and accurately detect soil particle size.

[0006] To achieve the above-mentioned objectives, the present invention provides a soil particle size distribution detection walking stick based on microscopic imaging, comprising a main body, the main body being cylindrical, the main body being adjustable in length, a handle being provided at the top of the main body, a control component being provided on the handle, a data transmission interface being provided on the back of the handle, a detection component being installed at the bottom of the main body, and a central control component being provided inside the main body.

[0007] Preferably, the control component includes operating buttons and a display screen.

[0008] Preferably, the detection component includes a camera, a fill light, a protective cover and a protective cover control switch, the camera is configured with no less than one magnifying lens, and the fill light is controlled by a fill light driver chip.

[0009] Preferably, the central control component includes a main control chip, which exchanges signals with the memory card, receives electrical signal inputs from the operation button, the time management chip and the charge and discharge management module, controls the display screen to display information, and controls the operation of the camera and the fill light driver chip; the lithium battery provides power for the display screen, the time management chip, the charge and discharge management module, the fill light driver chip and the positioning module.

[0010] The present invention also provides a soil particle size distribution analysis method based on microscopic imaging, comprising the following steps:

[0011] S1, image preprocessing;

[0012] S2, particle identification and segmentation;

[0013] S3, particle size measurement and statistics;

[0014] S4, the results show;

[0015] S5. Data storage.

[0016] Preferably, in S1, the image preprocessing includes the following steps:

[0017] S11, noise reduction, using Gaussian filtering to remove noise points in the image;

[0018] S12. Enhance contrast by using the histogram equalization method to redistribute the grayscale values of the image and enhance the contrast between soil particles and the background.

[0019] Preferably, in S2, particle identification and segmentation includes the following steps:

[0020] S21. Use the Canny edge detection algorithm to identify the edges of soil particles;

[0021] S22, calculate gradient magnitude and direction, refine edges by non-maximum suppression, detect edges by double thresholds, and connect edges to obtain boundaries to soil particles;

[0022] S23. Through morphological processing, the shape of particles is optimized, existing voids are filled, and adhered particles are separated to achieve precise segmentation of soil particles.

[0023] Preferably, in S3, the particle size measurement and statistics are specifically as follows:

[0024] S31. Calculate the area of the soil particle contour by image area calculation, denoted as A;

[0025] S32. Calculate the equivalent diameter of the soil using the formula:

[0026] S33. Count the particle sizes, classify them into corresponding particle size intervals, and calculate the percentage of the number of particles in each interval to the total number of particles.

[0027] Preferably, in S4, the result display is specifically to transmit the statistically obtained soil particle size distribution data to the display screen of the detection cane.

[0028] Preferably, in S5, the collected image data is transferred to an SD card and the latitude and longitude, horizontal altitude and time are recorded, and the results of S1-S4 are stored in a separate file in the form of a data table.

[0029] Therefore, the present invention adopts the above-mentioned soil particle size distribution detection stick and analysis method based on microscopic imaging, which has the following advantages:

[0030] (1) Integrated design: The microscopic imaging technology, image analysis algorithm and intelligent data processing system are integrated into a cane-shaped portable device, avoiding the limitations of traditional detection equipment such as bulky size and separate components. This allows users to perform soil particle size testing anytime and anywhere without having to carry a large amount of professional equipment and tools, greatly improving the convenience and flexibility of testing.

[0031] (2) Real-time analysis and visualization: Using image analysis and recognition algorithms, the soil microscopic images collected by the detection stick are processed in real time, and the soil particle size distribution data is quickly calculated and displayed intuitively on the handle display. Compared with traditional methods that require samples to be taken back to the laboratory for complex analysis, the detection stick can immediately provide test results on site, providing users with timely decision-making basis.

[0032] (3) Multi-scenario adaptability: With its replaceable detection probes and flexible operation mode, the detection stick can adapt to different types of soil environments. Whether it is sandy soil in arid areas or clay soil in humid areas, it can accurately collect samples and perform analysis. At the same time, its portability makes it suitable for a variety of scenarios such as agricultural fields, geological exploration sites, and soil research field surveys.

[0033] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a structural schematic diagram of an embodiment of a soil particle size distribution detection stick and analysis method based on microscopic imaging of the present invention;

[0035] Figure 2 Schematic diagram of a circuit module of an embodiment of a soil particle size distribution detection cane and analysis method based on microscopic imaging according to the present invention;

[0036] Figure 3 This is a soil collection image of an embodiment of a soil particle size distribution detection cane and analysis method based on microscopic imaging of the present invention;

[0037] Figure 4 This is an equivalent particle distribution area extraction result of an embodiment of a soil particle size distribution detection cane and analysis method based on microscopic imaging of the present invention.

[0038] Reference numerals

[0039] 1. Protective cover control switch; 2. Main body; 3. Data transmission interface; 4. Display screen; 5. Operation button; 6. Handle; 7. Camera; 8. Fill light; 9. Detection component; 10. Protective cover. DETAILED DESCRIPTION

[0040] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0041] Unless otherwise defined, the technical or scientific terms used in the present invention shall have the usual meanings understood by persons of ordinary skill in the field to which the present invention belongs. The words "first", "second" and similar terms used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Words such as "include" or "comprise" mean that the elements or objects preceding the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connect" or "connected" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0042] Example 1

[0043] The present invention provides a soil particle size distribution detection stick based on microscopic imaging, the structure of which is as follows: Figure 1 As shown, the main body 2 is cylindrical and made of a high-strength and lightweight material, preferably carbon fiber, coated aluminum alloy, or coated titanium alloy. It can withstand external impact and pressure, reduce operator labor intensity, and ensure longevity in complex environments. The main body 2 is adjustable in length to accommodate users of different heights.

[0044] A handle 6 is provided at the top of the main body 2, and the surface of the handle 6 can be covered with a non-slip, wear-resistant rubber material to increase the stability and comfort of holding. A control component is provided on the handle 6, and the control component includes an operation button 5 and a display screen 4. The display screen 4 is used to display the number, soil particle size analysis results, operation menu and equipment status information in real time, such as power level, data transmission status, etc. The operation button 5 includes a power button, a detection start button, a data storage button, and a data correction button to facilitate the user to perform various operations. In addition, the handle 6 can also be connected to a protective rope, which can be put on the user's wrist to prevent the detection cane from accidentally falling out of the hand, and at the same time it is convenient to hang and store when not in use or charging. A data transmission interface 3 is provided on the back of the handle 6. The data transmission interface 3 is protected by a waterproof cover and a USB interface, which can charge the main body, transfer data, and establish a wireless connection with smart mobile devices such as mobile phones and tablets to facilitate the adjustment of data acquisition parameters.

[0045] Mounted at the bottom of the main body 2 is a detection assembly 9 comprising a camera 7, fill lights 8, a protective cover 10, and a cover control switch 1. Camera 7 is equipped with at least one magnifying lens, providing microscopic imaging capabilities. Its magnification, focal length, ISO, and lens equivalent parameters are adjustable. The adjustment range is specifically set as follows: magnification 1x to 250x, focal length 4mm to 50mm, ISO 10 to 2500, and lens equivalent 0.1 to 0.5. These settings can be tailored to the target object and the environment, with the optimal adjustment criteria being to clearly capture the finest morphology, size, and texture characteristics of soil particles. Fill lights 8, controlled by a fill light driver chip, provide light during image acquisition. Fill lights 8 are evenly distributed around the lens, providing uniform, soft, and sufficient illumination for the soil sample. Protective cover 10 comprises a cover, a cover control switch 1, and a rubber portion at the bottom that contacts the ground. The cover protects camera 7 from impurities such as ground dust and effectively blocks dust when not collecting data. The cover is controlled by a protective cover control switch 1. When the bottom of the detection cane contacts the ground and is subjected to a certain amount of pressure, the cover opens, allowing soil sample image acquisition. When the cane is lifted from the ground and the pressure is removed, the cover returns to its initial state, activated by a return spring or other elastic element, causing the cover to automatically close. The rubber portion not only increases friction between the cane and the ground, ensuring it remains stable and prevents slippage during data acquisition, but also cushions impact forces from the ground, preventing damage to the internal circuitry from the bottom contacting moist soil.

[0046] The main body 2 is provided with a central control component, a detection component 9 and a control component. The circuit structure of each functional module inside the central control component, the detection component 9 and the control component is as follows: Figure 2 The central control component includes a main control chip, which can be loaded with soil data processing algorithms. The main control chip exchanges electrical signals with the memory card and receives electrical inputs from the operation buttons, time management chip, and charge and discharge management module. The main control chip controls the display screen, camera 7, and fill light driver chip. A lithium battery provides power for the display screen 4, time management chip, charge and discharge management module, fill light driver chip, and positioning module.

[0047] The main control chip performs image acquisition, reading, recording, storage, and computation. It coordinates the orderly operation of the various components of the inspection cane through interrupt and output modes. It receives and processes camera data, location information, and time information, and performs preliminary processing, storage, and output for display. The positioning module acquires longitude, latitude, and altitude data in real time and transmits it to the main control chip. This provides a spatial basis for subsequent analysis of the relationship between soil particle size distribution and geographic location in different regions, revealing the inherent connection between geological structure and soil formation. The charge and discharge management module prevents overcharging and over-discharging, effectively extending battery life. Furthermore, through communication with the main control chip, it provides real-time feedback on the battery charge level, which is displayed to the user on the display screen, allowing users to keep track of the device's power status and plan inspections accordingly.

[0048] When using the inspection cane, the detection component 9 receives the start signal, decodes and verifies it, and upon verification, activates the camera 7, entering a ready-to-use state. Once the camera 7 begins operating, it quickly captures microscopic images of soil particles and converts them into analog electrical signals. The built-in image sensor samples and quantizes the analog signals, converting them into digital signals. To facilitate transmission and subsequent processing, the camera 7 encodes the digital image signals.

[0049] The present invention also provides a soil particle size distribution analysis method based on microscopic imaging, comprising the following steps:

[0050] S1, image preprocessing;

[0051] S11. Noise reduction. The collected microscopic images may be affected by environmental noise, equipment noise, etc. Gaussian filtering is used to remove noise points in the image to make the image smoother, which is convenient for subsequent particle identification and measurement.

[0052] S12. Enhance contrast. Use the histogram equalization method to redistribute the grayscale values of the image, enhance the contrast between soil particles and the background, make the grayscale distribution of the image more uniform, thereby improving the clarity and recognizability of the image and showing the outline of the soil particles more clearly.

[0053] S2, particle identification and segmentation;

[0054] S21. Use the Canny edge detection algorithm to identify the edges of soil particles;

[0055] S22, calculate gradient magnitude and direction, refine edges by non-maximum suppression, detect edges by double thresholds, and connect edges to obtain boundaries to soil particles;

[0056] S23. Through morphological processing, the shape of particles is optimized, existing voids are filled, and adhered particles are separated to achieve precise segmentation of soil particles.

[0057] S3, particle size measurement and statistics;

[0058] S31. Calculate the area of the soil particle contour by image area calculation, and record it as A.

[0059] S32. Calculate the equivalent diameter of the soil using the formula: The irregularly shaped soil particles are converted into the diameter of round particles with the same area in order to perform unified particle size statistics.

[0060] S33. Count the particle sizes, classify them into corresponding size intervals, and calculate the percentage of particles in each interval relative to the total number of particles. For example, classify the particle sizes into <0.01mm, 0.01-1mm, and >1mm. Traverse the equivalent diameter data to determine the size interval to which each particle belongs. Then, cumulatively count the number of particles in each interval and calculate the number or percentage of soil particles in each interval.

[0061] S4. Result display: The statistically obtained soil particle size distribution data is transmitted to the display screen of the detection cane. The data on the display screen is only represented by intuitive cumulative bar graphs and numerical values, so that users can understand the distribution of soil particle size at a glance, providing a strong basis for soil analysis and related decision-making.

[0062] S5, data storage: transfer the collected image data to the SD card and record the latitude and longitude, horizontal altitude and time. Store the results of S1-S4 in a separate file in the form of a data table. Each record will be added to the table.

[0063] Figure 3 is a soil image collected using the detection cane of the present invention, Figure 4 is with Figure 3 The corresponding equivalent particle distribution area extraction results.

[0064] The detection cane provided by the present invention is suitable for the following tasks:

[0065] Soil fertility assessment: Use a testing stick to detect soil particle size distribution and understand soil texture (sandy, loam, clay). Due to their different water and fertilizer retention abilities, you can accurately and rationally apply fertilizers and irrigation accordingly to improve crop yield and quality.

[0066] Crop planting planning: Different crops have different soil requirements. For example, peanuts and watermelons are suited to sandy soil, while rice prefers clay soil. The detection cane helps select crops based on soil characteristics, enabling precise planting and improving land utilization.

[0067] Soil erosion monitoring: In ecologically fragile areas, such as mountainous areas and along rivers, soil particle size distribution is regularly monitored using a monitoring stick. Soil erosion can cause changes in particle size distribution. Long-term monitoring can identify signs of erosion, assess its extent, and support prevention and control efforts.

[0068] Land pollution assessment: Soil around industrially polluted areas and landfills is susceptible to contamination, which can affect soil particle aggregation and particle size distribution. By combining this with other indicators, particle size distribution can be used to assess contamination status, determine the extent of contamination, and provide a basis for remediation.

[0069] Therefore, the present invention adopts the above-mentioned soil particle size distribution detection stick and analysis method based on microscopic imaging, integrates microscopic imaging technology, image analysis algorithm and intelligent data processing system into a portable device, processes the collected soil microscopic images in real time, quickly calculates the soil particle size distribution data and displays it in real time, can adapt to soil environments of different types and scenarios, and quickly and accurately detect soil particle size.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A soil particle size distribution detection cane based on microscopic imaging, characterized by: It includes a main body, which is cylindrical and has an adjustable length. A handle is provided on the top of the main body, a control component is provided on the handle, a data transmission interface is provided on the back of the handle, a detection component is installed at the bottom of the main body, and a central control component is provided inside the main body.

2. The soil particle size distribution detection cane based on microscopic imaging according to claim 1, characterized in that: The control component includes an operating button and a display screen.

3. The soil particle size distribution detection cane based on microscopic imaging according to claim 2, characterized in that: The detection component includes a camera, a fill light, a protective cover and a protective cover control switch. The camera is equipped with at least one magnifying lens, and the fill light is controlled by a fill light driving chip.

4. The soil particle size distribution detection cane based on microscopic imaging according to claim 3, characterized in that: The central control component includes a main control chip, which interacts with the memory card through signals. The main control chip receives electrical signal inputs from the operation button, the time management chip, and the charge and discharge management module. The main control chip controls the display information on the display screen and controls the operation of the camera and the fill light driver chip. The lithium battery provides power for the display screen, the time management chip, the charge and discharge management module, the fill light driver chip, and the positioning module.

5. A soil particle size distribution analysis method based on microscopic imaging, characterized in that: The following steps are involved: S1, image preprocessing; S2, particle identification and segmentation; S3, particle size measurement and statistics; S4, the results show; S5. Data storage.

6. The soil particle size distribution analysis method based on microscopic imaging according to claim 5, characterized in that: In S1, image preprocessing includes the following steps: S11, noise reduction, using Gaussian filtering to remove noise points in the image; S12. Enhance contrast by using the histogram equalization method to redistribute the grayscale values of the image and enhance the contrast between soil particles and the background.

7. The soil particle size distribution analysis method based on microscopic imaging according to claim 5, characterized in that: In S2, particle identification and segmentation include the following steps: S21. Use the Canny edge detection algorithm to identify the edges of soil particles; S22, calculate gradient magnitude and direction, refine edges by non-maximum suppression, detect edges by double thresholds, and connect edges to obtain boundaries to soil particles; S23. Through morphological processing, the shape of particles is optimized, existing voids are filled, and adhered particles are separated to achieve precise segmentation of soil particles.

8. The soil particle size distribution analysis method based on microscopic imaging according to claim 5, characterized in that: In S3, particle size measurement and statistics are as follows: S31. Calculate the area of the soil particle contour by image area calculation, denoted as A; S32. Calculate the equivalent diameter of the soil using the formula: S33. Count the particle sizes, classify them into corresponding particle size intervals, and calculate the percentage of the number of particles in each interval to the total number of particles.

9. The soil particle size distribution analysis method based on microscopic imaging according to claim 5, characterized in that: In S4, the result display is specifically to transmit the statistically obtained soil particle size distribution data to the display screen of the detection cane.

10. The soil particle size distribution analysis method based on microscopic imaging according to claim 5, characterized in that: In S5, the collected image data is transferred to the SD card and the latitude and longitude, horizontal altitude and time are recorded. The results of S1-S4 are stored in a separate file in the form of a data table.

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