Multispectral imaging device for detecting stored grain pests

Abstract

The utility model provides a multispectral imaging device for detecting stored grain pests, which comprises a sealed box body as well as a sample table, a light source and a bracket which are arranged in the box body, and is characterized in that the bracket is a T-shaped bracket, the tail end of the transverse part of the T-shaped bracket is connected with an imaging sensor, the bottom of the imaging sensor is connected with a lens facing the sample table, and the lens is connected with the light source. A plurality of optical filters switched through optical filter wheels are arranged below the lens, and a sample protection cover is arranged between the lens and the sample table. The grain pest detection device realizes rapid, lossless and high-precision detection of pests in grains, reduces grain storage loss, is simple in overall structure and wide in detection range, can improve the detection efficiency of the pests in the grains, overcomes the defects of low efficiency, poor accuracy, unfriendliness to the environment and the like of a traditional detection method, and is suitable for popularization and application. And an efficient and environment-friendly solution is provided for storage, processing and quality control of grains.

Description

Technical Field

[0001] This utility model relates to the field of agricultural detection technology, specifically a multispectral imaging device for detecting pests in stored grain. Background Technology

[0002] Grains are highly susceptible to pest infestation during storage, which not only leads to weight loss and reduced quality but can also cause mold growth and the production of harmful substances such as aflatoxin, posing a threat to human health. Therefore, timely and accurate detection of pests and their species in grains is crucial for ensuring food security and minimizing economic losses.

[0003] Traditional methods for detecting grain pests mainly include visual inspection and chemical reagent testing. However, visual inspection is inefficient and cannot meet the needs of large-scale grain testing; its accuracy relies heavily on the experience and subjective judgment of the inspectors, making it prone to misjudgment or missed detection. While chemical reagent testing methods improve accuracy to some extent, the use of chemical reagents may contaminate rice, affecting its quality and safety; moreover, the testing process is complex, costly, and environmentally unfriendly, failing to meet the requirements of modern green agriculture and environmental protection.

[0004] With the development of technology, spectral imaging technology has been used in agricultural product detection. However, dedicated devices for grain pests still have the following problems: limited light source configuration, with existing equipment mostly using fixed-band light sources, failing to cover the spectral characteristics of pests at different life stages; severe environmental interference, lack of standardized imaging environments, and low signal-to-noise ratio due to external light interference. Multispectral imaging, by simultaneously acquiring spectral information at multiple wavelengths, can more comprehensively reflect the physical and chemical properties of the target object. In grain pest detection, multispectral imaging technology holds promise for overcoming the shortcomings of traditional methods, achieving rapid, accurate, and non-destructive pest detection. Therefore, developing a rapid, accurate, and environmentally friendly grain pest detection device is of great significance. Utility Model Content

[0005] To address the problems of existing technologies, this invention provides a multispectral imaging device for detecting pests in stored grain. Utilizing advanced multispectral imaging technology, it achieves rapid, non-destructive, and high-precision detection of pests in grain, reducing storage losses. The device has a simple overall structure, is easy to assemble, and has a wide detection range. It improves the detection efficiency of pests in grain, overcoming the shortcomings of traditional detection methods such as low efficiency, poor accuracy, and environmental unfriendliness. This provides an efficient and environmentally friendly solution for grain storage, processing, and quality control.

[0006] This utility model includes a sealed box and a sample stage, a light source, and a support set inside the box. The support is a T-shaped support. An imaging sensor is connected to the end of the horizontal part of the T-shaped support. A lens facing the sample stage is connected to the bottom of the imaging sensor. Several filters that can be switched by a filter wheel are set below the lens. A sample protective cover is set between the lens and the sample stage.

[0007] In a further improvement, the filter wheel has a circular structure, with a central shaft connected to the center of the filter wheel. Several circular holes are distributed on the circumference of the filter wheel, and different filters are placed in each hole. The different filters are rotated to the bottom of the lens through the central shaft of the filter wheel.

[0008] In a further improvement, the inner wall of the box is coated with a light-absorbing material, and a door is opened on the side wall.

[0009] In a further improvement, the light source is a plurality of LEDs with different wavelengths.

[0010] In a further improvement, the imaging sensor is connected to a data processing module outside the housing.

[0011] In a further improvement, the sample protective cover is a cuboid without a bottom surface. The top of the cuboid is made of colorless transparent glass, and the sides are coated with a black coating. The light source is located at the top edge of the cuboid.

[0012] As a further improvement, the sample stage surface is coated with a black anti-reflective coating.

[0013] The beneficial effects of this utility model are as follows:

[0014] 1. It can image grains and their pests using light of multiple wavelengths, capturing the unique spectral responses of different substances. This multi-dimensional spectral information enables the device to more accurately distinguish the types of pests in grains, with an identification accuracy far exceeding that of traditional manual visual inspection or single-wavelength detection methods.

[0015] 2. Employing optical imaging technology, this method eliminates the need for physical contact or chemical treatment of grain samples, enabling non-destructive testing. This not only avoids potential damage to grain quality but also meets the requirements of food safety and green agriculture. Compared to traditional chemical reagent testing methods, this device requires no chemical reagents, avoiding environmental pollution and representing a truly environmentally friendly testing technology.

[0016] 3. The device has a simple structure, is easy to operate, and has a wide range of applications. It is not only suitable for detecting pests in grains, but can also be applied to the detection of pests in other grains (such as wheat, corn, soybeans, etc.) or agricultural products by adjusting the wavelength of the light source and imaging parameters.

[0017] 4. The device can visually display the detection results as images, clearly showing the location, quantity, and type of pests in the grain. Simultaneously, the device can store and export the detected data, facilitating subsequent analysis and traceability. This data visualization and traceability provide strong support for grain storage management and help establish a comprehensive grain quality monitoring system.

[0018] 5. By rapidly and accurately detecting pests in grains, this device can help reduce grain losses caused by pest infestations, improve grain storage quality, and enhance economic benefits. Furthermore, this device reduces the use of chemical reagents, lowers environmental pollution, meets the requirements of sustainable development, and has significant social benefits. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this utility model, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this utility model. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the overall structure of the present invention (unit: mm).

[0021] Figure 2 This is a side view of the structure of this utility model (unit: mm).

[0022] Figure 3 This is a top view of the structure of this utility model (unit: mm).

[0023] In the diagram, 1. Box body, 2. Box door, 3. Robotic arm up / down adjustment knob, 4. Robotic arm forward / backward adjustment knob, 5. Up / down tension adjustment knob, 6. Forward / backward tension adjustment knob, 7. Support, 8. Filter wheel central shaft, 9. Imaging sensor, 10. Lens, 11. Filter wheel, 12. Sample protective cover, 13. Sample stage. Detailed Implementation

[0024] The technical solutions of the present utility model will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present utility model, and not all embodiments. Based on the embodiments of the present utility model, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present utility model.

[0025] The structure of this utility model is as follows: Figure 1-3As shown, the main body consists of a housing 1, an imaging sensor 9, a lens 10, and a sample stage 13. The housing is generally rectangular, with a door 2 on one side and a sample stage 13 on the bottom inside for holding samples. Inside the housing is a T-shaped bracket 7, which is an important structure connecting the various parts of the device. In this embodiment, the position of the lens 10 can be adjusted. To adjust the lens 10, first loosen the screws by rotating the up / down adjustment knob 5 and the back / forward adjustment knob 6, then rotate the up / down adjustment knob 3 and the back / forward adjustment knob 4 to move the lens position for adjustment and to achieve focus. The imaging sensor 9 is fixed to the horizontal end of the bracket 7. The imaging sensor can transmit images to the data processing module of the computer in real time, which is convenient for staff to observe and record in real time. The bottom of the imaging sensor is connected to the lens 10. The filter on the lens 10 can be switched by the filter wheel 11 to observe real-time images at different wavelengths. The filter wheel 11 is circular with six small holes around its circumference, which can hold filters of different wavelengths. The center of the filter wheel is fixedly connected to its central axis 8, and the filter wheel can rotate around the center to switch filters. There is a sample protective cover 12 between the filter wheel 11 and the sample stage 13. The protective cover is a bottomless cuboid with a colorless transparent glass top and LED lights installed on the top edges. The sides of the cuboid are coated with a black anti-reflective coating. The protective cover restricts the sample placement range and focuses the light. The sample stage 13 is also coated with a black anti-reflective coating. In this embodiment, the coating material is epoxy resin from Shenzhen Kuang-Chi Nanomaterials, which is resistant to damp heat cycling, has a coating thickness of 15-25μm, and the coating optical performance requirements are an average reflectance of <2% in the 400-2500nm wavelength band.

[0026] In this embodiment, the box is 450mm long and wide, and 650mm high. The inner wall of the box is coated with a light-absorbing material to isolate external light interference. The sample protective cover is 160mm long and 230mm wide. The data processing module is used to analyze the multispectral images and identify pests and their species in the grain. The data processing module includes an image processing unit and a pest identification unit. The image processing unit is used to preprocess the multispectral images, and the pest identification unit is used to identify pests and their species in the grain.

[0027] The method for detecting pests and their species in grain using the multispectral device described in this invention includes the following steps:

[0028] A: First, turn on the power, place the prepared sample on the sample stage, connect the imaging sensor to the computer, and observe the clarity of the image on the display screen.

[0029] B: Then, while observing the image, rotate the movement knob until the image is clear, close the chamber door, observe the sample on the display screen and record it;

[0030] C: Then rotate the filter wheel, observe the images under filters of different wavelengths, and record the observation results at different wavelengths;

[0031] D: Combining the wavelengths selected in the above steps with the dedicated software equipped in the device, after the image is denoised and enhanced, it is input into the model to generate pest species and coordinate information;

[0032] E: The results are displayed on the screen, clearly showing the pests and their species in the grain.

[0033] The working principle of this utility model is as follows:

[0034] This invention comprises a sealed enclosure. A multispectral imaging device emits light sources of various wavelengths to illuminate grain samples. Pests and grains reflect or absorb this light, forming reflected light signals with unique spectral characteristics. An imaging module receives these reflected light signals and generates multispectral images, where images at different wavelengths reflect the spectral differences between grains and pests. A data processing module analyzes these multispectral images, utilizing the differences in spectral characteristics between pests and grains at specific wavelengths. Through image recognition algorithms and machine learning models, it quickly and accurately identifies pests in the grain. After image correction and feature fusion, the morphological features of the pests are extracted, and their species are determined using a classification model, thus achieving high-precision detection and classification of pests in grains.

[0035] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, for the device embodiments, the above descriptions are merely preferred embodiments of this utility model. Since they are fundamentally similar to the method embodiments, the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments. The above descriptions are merely specific embodiments of this utility model, but the protection scope of this utility model is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this utility model, without departing from the principle of this utility model, should be included within the protection scope of this utility model. Therefore, the protection scope of this utility model should be determined by the scope of the claims.

Claims

1. A multispectral imaging device for detecting stored grain pests, characterized in that: The device includes a sealed enclosure and a sample stage, a light source, and a support disposed within the enclosure. The support is a T-shaped support, with an imaging sensor connected to the end of the horizontal portion of the T-shaped support. A lens facing the sample stage is connected to the bottom of the imaging sensor. Several filters, switchable via a filter wheel, are disposed below the lens. A sample protective cover is disposed between the lens and the sample stage.

2. The multispectral imaging device for detecting stored grain pests according to claim 1, characterized in that: The filter wheel has a circular structure, with a central shaft connected to the center of the filter wheel. Several circular holes are distributed on the circumference of the filter wheel, and different filters are placed in each hole. The different filters are rotated to the bottom of the lens through the central shaft of the filter wheel.

3. The multispectral imaging device for detecting stored grain pests according to claim 1, characterized in that: The inner wall of the box is coated with light-absorbing material, and the side wall has a door.

4. A multispectral imaging device for detecting stored grain pests according to claim 1, characterized in that: The light source consists of multiple LEDs with different wavelengths.

5. A multispectral imaging device for detecting stored grain pests according to claim 1, characterized in that: The imaging sensor is connected to the data processing module outside the housing.

6. A multispectral imaging device for detecting stored grain pests according to claim 1, characterized in that: The sample protective cover is a cuboid without a bottom surface. The top of the cuboid is made of colorless transparent glass, and the sides are coated with a black coating. The light source is located at the top edge of the cuboid.

7. A multispectral imaging device for detecting stored grain pests according to claim 1, characterized in that: The sample stage surface is coated with a black anti-reflective coating.

Images