A device and method for detecting internal defects in walnuts based on infrared thermal imaging technology

Abstract

This invention discloses a walnut internal defect detection device based on infrared thermal imaging technology, comprising a conveyor belt assembly driven by a drive component mounted on a support of the conveyor belt assembly. A hopper is located at one end of the support, with a discharge port at its lower end, corresponding to the upper side of one end of the conveyor belt. A support leg is fixed to the lower side of the hopper. This invention relates to the technical field of walnut internal defect detection equipment, specifically to a walnut internal defect detection device and method based on infrared thermal imaging technology. Utilizing the different thermal conductivity characteristics of different substances within the walnut, the device employs continuous heating with a halogen lamp, uses an infrared thermal imager for non-destructive testing of the walnut's interior, and then uses an air-jet matrix for rejection. This provides a high-efficiency, low-cost method for internal defect detection in the walnut production and processing industry.

Description

Technical Field

[0001] This invention relates to the field of equipment for detecting internal defects in walnuts, and more specifically, to a device and method for detecting internal defects in walnuts based on infrared thermal imaging technology. Background Technology

[0002] Walnuts, as a nutritious and highly sought-after nut, are favored in the market, and their quality directly impacts consumer experience and economic benefits. However, during growth, harvesting, storage, and transportation, walnuts are prone to internal defects such as empty shells, shriveled kernels, mold, and insect damage. These defects are difficult to accurately identify with the naked eye, posing a significant challenge to quality screening by production and processing enterprises. Traditional testing methods rely heavily on manual screening, which is not only inefficient and labor-intensive but also highly subjective, with inconsistent testing standards, leading to missed or false detections and failing to meet the demands of modern large-scale production. Therefore, developing an efficient, accurate, and automated technology for detecting internal defects in walnuts is crucial for improving walnut product quality, reducing production costs, and ensuring food safety. Existing non-destructive testing technologies, such as X-ray inspection, can identify internal defects, but the equipment is expensive and poses radiation safety risks; near-infrared spectroscopy is easily affected by sample surface conditions and environmental factors, and its detection accuracy needs further improvement. Infrared thermal imaging technology, as an emerging non-destructive testing method, has the advantages of being non-contact, fast, intuitive, and radiation-free. It reflects the internal structural information of an object by detecting the temperature distribution differences on the surface of the object, providing a new and feasible approach for detecting internal defects in walnuts. Summary of the Invention

[0003] The technical problem to be solved by this invention is to provide a device and method for detecting internal defects in walnuts based on infrared thermal imaging technology. By utilizing the different thermal conductivity characteristics of different substances inside the walnut, and using a halogen lamp for continuous heating, an infrared thermal imager is used to perform non-destructive testing on the inside of the walnut, and defects are removed by an air jet matrix. This provides a high-efficiency and low-cost method for detecting internal defects in the walnut production and processing industry.

[0004] A walnut internal defect detection device based on infrared thermal imaging technology includes a conveyor belt assembly. The conveyor belt assembly is driven by a drive component, which is mounted on a support of the conveyor belt assembly. A hopper is provided at one end of the support of the conveyor belt assembly, and the lower end of the hopper is a discharge port. The discharge port corresponds to the upper side of one end of the conveyor belt of the conveyor belt assembly. A support leg is fixed to the lower side of the hopper. A heating and insulation module is provided on the upper side of the support of the conveyor belt assembly. A toothed baffle is provided between the heating and insulation module and the discharge port. The toothed baffle is fixed on the support of the conveyor belt assembly. A blowing assembly is also fixed on the support of the conveyor belt assembly. The blowing assembly is located at the discharge end of the heating and insulation module. A first collection box and a second collection box are provided at the other end of the conveyor belt assembly. The first collection box is located on both sides of the other end of the conveyor belt assembly and corresponds to the blowing assembly respectively. The second collection box is located at the end of the other end of the conveyor belt assembly. It also includes a controller, a jet generator, an encoder, and a host computer equipped with a detection algorithm. The controller transmits data with the heating and insulation module and is electrically connected to the jet generator. The air outlet of the jet generator is connected to the purging assembly through a pipeline. The host computer is electrically connected to the drive unit and controller of the conveyor belt assembly. The detection algorithm built into the host computer is used to complete walnut positioning and matching, temperature data processing, defect category judgment, and calculation of air jet rejection parameters. The encoder is electrically connected to the host computer and the conveyor belt assembly, respectively, and is used to collect the displacement pulse signal of the conveyor belt and transmit it to the host computer.

[0005] Furthermore, the heating and insulation module includes a heating and insulation box and a thermal imaging processing module. The heating and insulation box has openings on the lower sides of both ends. The opening near the hopper is the inlet, and the opening away from the hopper is the outlet. A heat source, which is a halogen lamp, is fixedly installed on the upper inner side of the heating and insulation box. Both sides of the heating and insulation box corresponding to both ends of the conveyor belt assembly are heat insulation and light-blocking plate structures. The thermal imaging processing module includes a first sensor, a second sensor, a first thermal imager, and a second thermal imager. The first sensor and the first thermal imager are sequentially fixed on the upper side of the heating and insulation box and correspond to the inlet. The second sensor and the second thermal imager are fixed on the upper side of the heating and insulation box and correspond to the outlet. The first sensor and the second sensor are symmetrically arranged, and the first thermal imager and the second thermal imager are symmetrically arranged. The first sensor, the second sensor, the first thermal imager, and the second thermal imager all transmit data with the controller. The first sensor is electrically connected to the first thermal imager, and the second sensor is electrically connected to the second thermal imager.

[0006] Furthermore, the purging assembly includes a fixed frame, main jet heads, support columns, and auxiliary jet heads. The fixed frame is fixed to the support of the conveyor belt assembly. A group of main jet heads arranged in a matrix is ​​fixedly mounted on the lower side of the fixed frame. Several support columns are evenly fixed on both sides of the support of the conveyor belt assembly, located below the fixed frame. Auxiliary jet heads are fixedly mounted on the side of the support columns facing the conveyor belt, and the auxiliary jet heads are inclined. Both the main jet heads and auxiliary jet heads are connected to the air outlet of the jet generator through pipelines. The adjacent spacing of the main jet heads is 30mm, and the vertical distance from the surface of the conveyor belt is 70mm. The adjacent spacing of the auxiliary jet heads is 30mm, and the vertical distance from their fixed base plates to the surface of the conveyor belt is 100mm.

[0007] Furthermore, it also includes a discharge buffer belt, which is fixed to the other end of the conveyor belt assembly and is positioned at an angle to the second collection box to buffer the impact force of qualified walnuts falling.

[0008] Furthermore, the detection algorithm built into the host computer includes a positioning and matching sub-algorithm. This sub-algorithm uniquely matches the initial positioning information of the walnuts collected by the first sensor with the final positioning information collected by the second sensor, based on the conveyor belt speed, the installation distance between the first sensor, the second sensor, the first thermal imager, and the second thermal imager. It also uniquely matches the initial temperature information collected by the first thermal imager with the final temperature information collected by the second thermal imager, ensuring that the initial and final temperatures of each walnut correspond one-to-one with its own position information. After the matching is completed, the information of defective walnuts is automatically deleted to release memory space.

[0009] Furthermore, the detection algorithm built into the host computer also includes a temperature data analysis sub-algorithm. The temperature data analysis sub-algorithm first calculates the temperature change ΔT for each walnut, where ΔT = final temperature T1 - initial temperature T0. Then, based on the walnut's mass range, it compares the temperature change ΔT with a preset temperature threshold range. Simultaneously, it combines a binary search method to quickly determine the walnut defect category, classifying the walnuts into four categories: normal, average, slightly defective, and severely defective.

[0010] Furthermore, the detection algorithm built into the host computer also includes a sub-algorithm for calculating air jet rejection parameters. This sub-algorithm includes a position trigger calculation module and a jet parameter adaptive module: The position trigger calculation module converts the final positioning information of the defective walnut into an encoder pulse count value. By calculating the number of pulses corresponding to the fixed transmission distance from the detection point to the spray valve position, it calculates the precise trigger position for the defective walnut to reach the blowing component. The jet parameter adaptive module dynamically calculates the spray angle θ based on the lateral coordinates of the defective walnut, the fixed coordinates of the nozzle, and the vertical height from the nozzle to the conveyor belt. Simultaneously, it adaptively adjusts the air jet intensity of the main / auxiliary jet heads and the number of nozzles opened, taking into account the conveyor belt running speed and signal transmission delay time.

[0011] A method for detecting internal defects in walnuts using the aforementioned device includes the following steps: S1. Material pretreatment: The walnuts are initially screened by appearance, and defective walnuts with broken shells, incomplete green skin removal, and exposed kernels are removed. The screened walnuts are placed into the silo, and the silo conveys the walnuts at a uniform speed to the conveyor belt of the conveyor belt assembly through the discharge port. S2. Material arrangement: Walnuts move along the conveyor belt at a speed of 24m / h. After passing the spike-tooth baffle, they are separated into a single row by the baffle bars and move forward in sequence to avoid stacking and congestion. S3. Initial data acquisition: When the walnut moves to the inlet of the heating and heat preservation module, the first sensor is triggered. The first sensor controls the first thermal imager to acquire the initial temperature T0 and unique initial positioning information of each walnut. The information is transmitted to the host computer via the controller, and the positioning matching sub-algorithm of the host computer completes the storage and marking of the initial information. S4. Thermal excitation heating: The walnuts enter the heating and insulation box with the conveyor belt and are continuously heated for 120 seconds by two halogen lamps. The sandwich structure of the heating and insulation box maintains a stable internal temperature and realizes heat conduction from the surface of the walnut to the inside. S5. Final state data acquisition: After heating, the walnuts are moved to the outlet of the heating and heat preservation module, triggering the second sensor. The second sensor controls the second thermal imager to acquire the final temperature T1 and unique final positioning information of each walnut. The information is transmitted to the host computer via the controller. S6. Defect Judgment: The host computer first uses a positioning matching sub-algorithm, combined with the conveyor belt speed and the distance between the two sensors, to uniquely match the initial / final positioning and initial / final temperature of each walnut. After the matching is completed, the information of walnuts without defect prediction is automatically deleted. Then, the temperature data analysis sub-algorithm calculates the temperature change ΔT = T1 - T0. Based on the walnut's quality range, the preset temperature threshold range is called. Combined with the binary search method, the defect category of the walnut is quickly determined. Walnuts with temperature changes falling into the normal or general range are edible, while those falling into the mild or severe defect range are inedible. S7. Defect Removal: If the host computer determines that the defective walnut is defective, the position trigger calculation module is triggered by the air jet removal parameter calculation sub-algorithm to convert the final positioning of the defective walnut into an encoder pulse signal, and calculate the precise position and trigger time of the defective walnut reaching the blowing component. Then, through the blowing parameter adaptive module, the spray angle θ is dynamically calculated according to the lateral coordinate of the defective walnut, and the air jet intensity and the opening parameters of 2-3 matching nozzles are adaptively adjusted. The host computer sends a command to the controller, and the controller controls the jet to work. The main / auxiliary jet head sprays out instantaneous airflow to push the defective walnut to the first collection box on both sides of the conveyor belt. S8. Collection of qualified products: Edible qualified walnuts continue to move along the conveyor belt, and after being buffered by the discharge buffer belt, they fall into the second collection box, completing the fully automatic detection and sorting of internal defects of the walnuts.

[0012] Furthermore, in step S6, the mass range of the walnuts is divided into two categories: [6.2, 8.0] g and [10.0, 14.85] g. The preset temperature threshold range is as follows: 1) When the mass is [6.2, 8.0] g, the ΔT for normal walnuts is [22.57, 31.57) ℃, the ΔT for average walnuts is [23.98, 30.11) ℃, the ΔT for slightly defective walnuts is [11.25, 18.75) ℃, and the ΔT for severely defective walnuts is [13.38, 19.71) ℃; 2) When the mass is [10.0, 14.85] g, the ΔT for normal walnuts is [12.47, 17.44] ℃, the ΔT for average walnuts is [13.25, 16.64] ℃, the ΔT for slightly defective walnuts is [6.22, 10.36] ℃, and the ΔT for severely defective walnuts is [7.39, 10.89] ℃.

[0013] Furthermore, in step S7, the calculation of the spray angle θ is based on the lateral coordinate X_{walnut} of the defective walnut, the fixed lateral coordinate X_{nozzle} of the nozzle, and the vertical height H_{nozzle} from the nozzle to the conveyor belt; the pulse count calculation of the position trigger calculation module includes compensation for the delay time during data processing and signal transmission to ensure that the nozzle is accurately triggered when the defective walnut arrives directly below.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: By utilizing the different thermal conductivity characteristics of different substances inside walnuts, and employing a method of continuous heating with a halogen lamp, an infrared thermal imager is used to perform non-destructive testing on the inside of walnuts, and defects are removed using an air jet matrix. This provides a high-efficiency and low-cost method for detecting internal defects in the walnut production and processing industry. By utilizing the differences in thermophysical parameters caused by variations in the internal structure, composition density, and defect state of walnuts, the internal heat conduction process will be affected when the walnut is subjected to external thermal stimulation. Specifically, internal defects such as cracks, cavities, or mold can hinder or alter normal heat flow. By analyzing the average temperature of each walnut, the internal defects can be identified and located non-destructively. By using active thermal excitation and non-contact temperature measurement with an infrared thermal imager, it is possible to accurately capture abnormal heat flow fields caused by defects such as internal cavities, decay, or incomplete kernel development in walnuts, and quantify them as characteristic temperature differences that characterize the integrity of the internal structure. This method fundamentally overcomes the inherent limitations of traditional methods, which rely on external physical characteristics, suffer from low operational efficiency, pose radiation safety risks, or have insufficient resolution of minute internal defects. Furthermore, this method possesses the high-speed response capability to cover multiple samples across the entire field of view in a single detection. Combined with the real-time positioning and air-jet rejection structure integrated in this invention, it can be seamlessly integrated into modern production lines, ultimately achieving fully automated, high-precision, and high-efficiency identification and sorting of walnuts with internal defects. This has irreplaceable industrial application value in improving product quality and production efficiency. The entire process requires no destructive treatment of the samples, preserving the commercial value and morphological integrity of the walnuts. At the same time, the technology has the ability to respond quickly and scan large areas. Combined with image processing algorithms, it can achieve automated, high-precision identification and grading of large batches of walnuts, greatly improving the efficiency and reliability of quality control in industrial production processes. Attached Figure Description

[0015] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without creative effort. In the drawings: Figure 1 The three-dimensional representation of the present invention Figure 1 ; Figure 2 This is a side view of the present invention; Figure 3 The three-dimensional representation of the present invention Figure 2 ; Figure 4 This is a flowchart of the infrared thermal imaging process of the present invention; Figure 5 This is a flowchart of the purging assembly of the present invention; Figure 6 This is a flowchart of the present invention; In the diagram: 1. Hopper; 101. Discharge port; 2. Support leg; 3. Toothed baffle; 4. Conveyor belt assembly; 5. Heating and insulation box; 6. First collection box; 7. Second collection box; 8. Discharge buffer belt; 9. Blowing assembly; 91. Main jet nozzle; 92. Bracket; 93. Support column; 94. Secondary jet nozzle; 10. Heat source; 11. First sensor; 111. Second sensor; 12. Drive unit; 13. First thermal imager; 131. Second thermal imager. Detailed Implementation

[0016] The following detailed description of a specific embodiment of the present invention is provided in conjunction with the accompanying drawings. However, it should be understood that the scope of protection of the present invention is not limited to the specific embodiment.

[0017] In the description of this invention, it should be understood that the terms "center," "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 invention 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, they should not be construed as limitations on this invention.

[0018] The terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art will understand the specific meaning of these terms in this invention based on the specific circumstances.

[0019] The following description of exemplary embodiments refers to the accompanying drawings. The same reference numerals in different figures denote the same or similar elements. The following detailed description does not limit the invention. Rather, the scope of the invention is defined by the appended claims. For simplicity, the following embodiments describe the terminology and structure of the system; however, the embodiments described below are not limited to this system but can be applied to any other applicable system.

[0020] Thread self-locking refers to the fact that a threaded connection will not automatically loosen when the static load and operating temperature change little. The self-locking condition is that the thread helix angle is less than the equivalent friction angle of the helical pair. All threaded connections in this application meet the self-locking condition.

[0021] Movable and rotating connections include hinge connections, bearing connections, pin connections, etc. The terms mentioned above all refer to two components that cannot move relative to each other at the connection point, but can rotate relative to each other. The above explanation, combined with the accompanying drawings, can unambiguously identify the structure. The above explanation is from mechanical design manuals and Baidu Encyclopedia, and is common knowledge familiar to those skilled in the art.

[0022] Set screws are used for fixing, mostly in shaft holes. They hold the shaft in place, preventing it from moving back and forth. They also have many other names: set screws, nut screws, and locking screws. Their main function is positioning. Set screws operate on the same tightening principle as screws and are mostly used between shafts and sleeves to prevent positional changes during use. They can prevent relative movement between the shaft and sleeve. In some cases, set screws facilitate disassembly, for example, when two parts fit tightly together and can be separated using set screws.

[0023] Linear guides mainly consist of sliders and guide rails. Linear guides, also known as linear guides, linear rails, slide rails, linear guides, or linear slide rails, are used in linear reciprocating motion applications and can withstand a certain amount of torque. They can achieve high-precision linear motion under high loads. The function of linear guides is to support and guide moving parts to perform reciprocating linear motion in a given direction.

[0024] Example: Figure 1-6 This invention discloses a walnut internal defect detection device based on infrared thermal imaging technology, including a conveyor belt assembly 4. The conveyor belt assembly 4 is driven by a drive component 12, which is mounted on a support 92 of the conveyor belt assembly 4. A hopper 1 is provided at one end of the support 92 of the conveyor belt assembly 4, and the lower end of the hopper 1 is a discharge port 101, which corresponds to the upper side of one end of the conveyor belt of the conveyor belt assembly 4. A support leg 2 is fixed to the lower side of the hopper 1. A heating and heat preservation module is provided on the upper side of the support 92 of the conveyor belt assembly 4. A toothed baffle 3 is provided between the heating and heat preservation module and the discharge port 101, and the toothed baffle 3 is fixed on the support 92 of the conveyor belt assembly 4. The support 92 of the conveyor belt assembly 4 is also fixed with a blowing assembly 9. The blowing assembly 9 is located at the discharge end of the heating and heat preservation module. The other end of the conveyor belt assembly 4 is provided with a first collection box 6 and a second collection box 7. The first collection box 6 is located on both sides of the other end of the conveyor belt assembly 4 and corresponds to the blowing assembly 9 respectively. The second collection box 7 is located at the end of the other end of the conveyor belt assembly 4. It also includes a controller, a jet generator, an encoder, and a host computer equipped with a detection algorithm. The controller transmits data with the heating and insulation module and is electrically connected to the jet generator. The air outlet of the jet generator is connected to the purging assembly 9 through a pipeline. The host computer is electrically connected to the drive unit 12 of the conveyor belt assembly 4 and the controller. The detection algorithm built into the host computer is used to complete walnut positioning and matching, temperature data processing, defect category judgment, and calculation of air jet rejection parameters. The encoder is electrically connected to the host computer and the conveyor belt assembly 4, respectively, and is used to collect the displacement pulse signal of the conveyor belt and transmit it to the host computer. The toothed baffle 3 is arranged across the conveyor belt. The toothed baffle 3 includes a crossbeam and several baffles welded thereon. The baffles divide the crossbeam of the toothed baffle 3 into multiple channels for individual walnuts to pass through along the transverse region. The width of the discharge port 101 of the hopper 1 is smaller than the width of the conveyor belt. The width of the conveyor belt is 0.7m, the width of the discharge port 101 is 0.5m, and the height is 0.1m. The running speed of the conveyor belt is 24m / h.

[0025] The heating and heat preservation module includes a heating and heat preservation box 5 and a thermal imaging processing module. The heating and heat preservation box 5 has openings on the lower sides of both ends. The opening closer to the hopper 1 is the inlet, and the opening farther away from the hopper 1 is the outlet. A heat source 10 is fixedly installed on the upper inner side of the heating and heat preservation box 5. The heat source 10 is a halogen lamp. The two sides of the heating and heat preservation box 5 corresponding to both ends of the conveyor belt assembly 4 are heat insulation and light blocking plate structures. The thermal imaging processing module includes a first sensor, a second sensor, a first thermal imager, and a second thermal imager. The first sensor and the first thermal imager are sequentially fixed on the upper side of the heating and insulation box and correspond to the inlet. The second sensor and the second thermal imager are fixed on the upper side of the heating and insulation box and correspond to the outlet. The first sensor and the second sensor are symmetrically arranged, and the first thermal imager and the second thermal imager are symmetrically arranged. The first sensor, the second sensor, the first thermal imager, and the second thermal imager all transmit data with the controller. The first sensor is electrically connected to the first thermal imager, and the second sensor is electrically connected to the second thermal imager.

[0026] The heating and insulation box 5 has a sandwich structure, consisting of layers of insulation cotton, cardboard, and more insulation cotton stacked in sequence. The front and rear sides of the heating and insulation box 5 are seamlessly attached to the conveyor belt. Two halogen lamps are symmetrically installed on the top of the heating and insulation box 5 to provide continuous heat stimulation for the walnuts.

[0027] The purging assembly 9 includes a fixed frame, main jet heads 91, support columns 93, and auxiliary jet heads 94. The fixed frame is fixed on the bracket 92 of the conveyor belt assembly 4. A group of main jet heads 91 are evenly arranged in a matrix on the lower side of the fixed frame. Several support columns 93 are evenly fixed on both sides of the bracket 92 of the conveyor belt assembly 4. The support columns 93 are located below the fixed frame. Auxiliary jet heads 94 are fixed on the side of the support columns 93 facing the conveyor belt. The auxiliary jet heads 94 are inclined. The main jet heads 91 and auxiliary jet heads 94 are connected to the air outlet of the jet engine through pipelines. The main jet head 91 has an adjacent spacing of 30mm and a vertical distance of 70mm from the conveyor belt surface. It has a total of 10 horizontal × 4 vertical nozzles, with the jet holes of the nozzles set vertically downward. The airflow coverage area of ​​the main jet head 91 has an overlap area of ​​10-15%. The auxiliary jet head 94 has an adjacent spacing of 30mm, a fixed base plate with a vertical distance of 100mm from the conveyor belt surface, and an angle of 40-50 degrees between the auxiliary jet head 94 and the support column 93. The auxiliary jet head 94 is set obliquely downward.

[0028] It also includes a discharge buffer belt 8, which is fixed to the other end of the conveyor belt assembly 4, and the discharge buffer belt 8 corresponds to the second collection box 7 and is inclined to buffer the impact force of qualified walnuts falling.

[0029] The detection algorithm built into the host computer includes a positioning and matching sub-algorithm. The positioning and matching sub-algorithm uniquely matches the initial positioning information of the walnut collected by the first sensor 11 with the final positioning information collected by the second sensor 111 based on the conveyor belt speed, the installation distance between the first sensor 11, the second sensor 111, the first thermal imager 13, and the second thermal imager 131. It also uniquely matches the initial temperature information collected by the first thermal imager 13 with the final temperature information collected by the second thermal imager 131, so that the initial temperature and final temperature of each walnut correspond one-to-one with its own position information. After the matching is completed, the information of defective walnuts is automatically deleted to release memory space.

[0030] Both the first thermal imager 13 and the second thermal imager 131 employ infrared imaging for detection. The detection principle is as follows: Utilizing the differences in thermophysical parameters caused by variations in the internal structure, density, and defect state of the walnut, the internal heat conduction process is affected when the walnut is subjected to external thermal stimulation. Specifically, internal defects such as cracks, cavities, or mold can hinder or alter normal heat flow. By analyzing the average temperature of each walnut, non-destructive identification and location of internal defects can be achieved. According to the Stefan-Boltzmann law, the infrared energy radiated by an object's surface is closely related to its temperature; the emissivity per unit area of ​​an object can be expressed as:

[0031] in, The total radiance of the object. The emissivity of the object. The Stefan-Boltzmann constant (values) ), It is the thermodynamic temperature.

[0032] For biomaterials like walnuts, their surface radiation characteristics can be approximated as gray bodies. The emissivity is affected by the surface condition and internal structure. The difference in emissivity between normal tissue and defective areas provides a physical basis for temperature field analysis.

[0033] In active infrared detection, when a walnut is subjected to external thermal excitation (such as a halogen lamp array), heat is conducted from the surface to the interior. According to Fourier's law of thermal conduction, the heat flux density... With temperature difference The relationship between them is:

[0034] in, The thermal conductivity of the material is denoted by . Defects such as cracks, cavities, or mold inside the walnut can alter the local thermal resistance, hindering or delaying the normal propagation of heat flow, resulting in a temperature difference between the defective and normal areas during heat diffusion.

[0035] The formula for calculating specific heat capacity is:

[0036] in The amount of heat absorbed, For specific heat capacity, The weight and size of the walnuts For the efficiency of halogen lamps, This is the total heating time. The thermal efficiency of a halogen lamp.

[0037] As shown in the formula above, under the same heating conditions, each walnut absorbs the same amount of heat. With a constant mass, the specific heat capacity is inversely proportional to the temperature increase. Therefore, by comparing the heating temperatures of walnuts, we can determine their specific heat capacity and thus the state of the kernel inside.

[0038] The built-in detection algorithm of the host computer also includes a temperature data analysis sub-algorithm. This sub-algorithm first calculates the temperature change ΔT for each walnut, where ΔT = final temperature T1 - initial temperature T0. Then, based on the walnut's quality range, it compares the temperature change ΔT with a preset temperature threshold range. Simultaneously, it uses a binary search method to quickly determine the walnut defect category, classifying walnuts into four types: normal, average, slightly defective, and severely defective. The temperature data analysis sub-algorithm includes criteria for walnut quality such as: freshness, bitter taste (not fresh), shriveled, blackened (burnt, charred), altered taste, moldy, mildewed, greenish, spoiled, infested with insects, and completely shriveled and brittle.

[0039] Preparation before heating: Since the size and weight of the walnut itself will affect the size and speed of the temperature change, the walnut to be tested is first weighed and then moved onto the conveyor belt in preparation for heating.

[0040] Each walnut has a slightly different initial temperature, so its initial temperature T before heating must be measured and recorded. After heating, its final temperature T1 is measured and recorded after 120 seconds. The difference between the two, ΔT (temperature change ΔT = final temperature T1 - initial temperature T), is the temperature rise response of the walnut after thermal excitation.

[0041] According to the formula Q=cm△T, when the degree of thermal excitation is the same, if we take walnuts of roughly the same mass, in order to compare the different specific heat capacities of walnuts, we need to compare their temperature change △T, and c is inversely proportional to △T.

[0042] Walnut quality classification: Due to the diverse quality categories of walnuts, they are classified into four categories: ① The first category is "normal": fresh, good-tasting walnuts; ②The second category is "general": It is still edible, but the taste is slightly bitter, or it is slightly shriveled or blackened; ③ The third category is "mild defects": inedible, charred black, or even partially blackened or shriveled; ④ The fourth category is "severe defects": the kernel is severely dehydrated and completely carbonized due to hair growth, insect infestation, mold, deterioration, and shriveling.

[0043] After obtaining the data, analysis was performed: After each walnut data measurement, the walnuts were opened and categorized into the four categories ①②③④ mentioned above through observation and tasting. Then, the A value for each walnut was calculated, and the A values ​​of walnuts in the same category were analyzed for statistical regularity. The analysis revealed: When the weight of a "normal" walnut is [6.2, 8.0] g, its temperature change is [22.57, 31.57) ℃; When the mass of a "typical" walnut variety is [6.2, 8.0] g, its temperature change is [23.98, 30.11) ℃; When the weight of walnuts with "slight defects" is [6.2, 8.0] g, the temperature change is [11.25, 18.75) ℃; When the weight of a walnut with "severe defects" is [6.2, 8.0] g, its temperature change is [13.38, 19.71) ℃.

[0044] Because the quality of walnuts decreases significantly when they spoil and rot, and the weight of bad walnuts is usually less than 10g, when the weight of the walnut being tested is ≥10g: (taking the weight range of [10.0, 14.85]g as an example) The "normal" temperature variation for walnuts is [12.47, 17.44]℃; The typical temperature variation for walnuts is [13.25, 16.64]℃; The temperature change of walnuts with "mild defects" is [6.22, 10.36]℃; The temperature variation of "severely defective" walnuts is [7.39, 10.89]℃.

[0045] Data analysis shows that as the quality of walnuts improves, the upper and lower limits of the temperature change range will gradually increase, and the number of bad walnuts will gradually decrease.

[0046] By calculating the temperature changes of the four types of walnuts, non-destructive testing can be performed based on the temperature change range corresponding to the mass of the walnut being tested. Specifically, when the temperature change of the walnut measured using infrared thermal imaging is in the "normal" and "moderate" range, it is considered an edible walnut; when the temperature change is in the "severe defect" and "slight defect" range, it is considered an inedible walnut.

[0047] The built-in detection algorithm of the host computer also includes a sub-algorithm for calculating air jet rejection parameters. This sub-algorithm comprises a position trigger calculation module and a jet parameter adaptive module: The position trigger calculation module converts the final positioning information of the defective walnut into encoder pulse count values. It calculates the precise trigger position of the defective walnut reaching the blowing component by counting the pulses corresponding to the fixed transmission distance from the detection point to the spray valve position. The jet parameter adaptive module dynamically calculates the spray angle θ based on the lateral coordinates of the defective walnut, the fixed coordinates of the nozzle, and the vertical height from the nozzle to the conveyor belt. Simultaneously, it adaptively adjusts the air jet intensity of the main / auxiliary jet heads and the number of nozzles opened, taking into account the conveyor belt speed and signal transmission delay time. Once the walnut completes infrared thermal imaging detection and is identified as a defective product, the host computer immediately initiates the position tracking mechanism. At the instant the infrared thermal imager captures the image of the defective walnut, the system outputs the final position of the walnut, converting it into an encoder pulse count value. This value uniquely corresponds to the initial position of the defective walnut on the longitudinal axis of the conveyor belt.

[0048] Position tracking employs a real-time closed-loop control mode, with the system continuously reading the current pulse value from the encoder. The location that triggers culling is calculated using the following formula:

[0049] in The fixed transmission distance from the detection point to the valve position has been converted into the number of encoder pulses. The system executes in a high-speed cycle. Real-time judgment, The encoder collects real-time position information of the walnuts to ensure that a rejection signal is triggered immediately when a defective walnut reaches directly below the spray valve.

[0050] The calculation of air jet parameters includes two key elements: injection angle and air jet intensity. Injection angle Dynamically adjust based on the lateral position of the walnuts on the conveyor belt:

[0051] in Let be the horizontal coordinate of the defective walnut. For the fixed lateral coordinate of the jet valve, This is the vertical height from the nozzle outlet to the conveyor belt.

[0052] A method for detecting internal defects in walnuts using the aforementioned device includes the following steps: S1. Material pretreatment: The walnuts are initially screened by appearance, and defective walnuts with broken shells, incomplete green skin removal, and exposed kernels are removed. The screened walnuts are placed into the silo 1, and the silo 1 conveys the walnuts at a uniform speed to the conveyor belt of the conveyor belt assembly 4 through the discharge port 101. S2, Material Arrangement: Walnuts move along the conveyor belt at a speed of 24m / h. After passing the spike-tooth baffle 3, they are separated into a single row by the baffle bar and move forward in sequence to avoid stacking and congestion. S3. Initial data acquisition: When the walnut moves to the inlet of the heating and heat preservation module, the first sensor 11 is triggered. The first sensor 11 controls the first thermal imager to acquire the initial temperature T0 and unique initial positioning information of each walnut. The information is transmitted to the host computer via the controller, and the positioning matching sub-algorithm of the host computer completes the storage and marking of the initial information. S4. Thermal excitation heating: The walnuts enter the heating and insulation box 5 along the conveyor belt and are continuously heated for 120 seconds by two halogen lamps. The sandwich structure of the heating and insulation box 5 maintains a stable internal temperature and realizes heat conduction from the surface of the walnuts to the inside. S5. Final state data acquisition: After heating, the walnuts are moved to the outlet of the heating and heat preservation module, triggering the second sensor 111. The second sensor 111 controls the second thermal imager to collect the final temperature T1 and unique final positioning information of each walnut. The information is transmitted to the host computer via the controller. S6. Defect Judgment: The host computer first uses a positioning matching sub-algorithm, combined with the conveyor belt speed, the distance between the two sensors, and the distance between the two thermal imagers, to uniquely match the initial / final positioning and initial / final temperature of each walnut. After the matching is completed, the information of walnuts without defect prediction is automatically deleted. Then, the temperature data analysis sub-algorithm calculates the temperature change ΔT = T1 - T0. Based on the walnut's quality range, the preset temperature threshold range is called, and the binary search method is used to quickly determine the walnut defect category. Walnuts with temperature changes falling into the normal or general range are edible, while those falling into the mild or severe defect range are inedible defective walnuts. S7. Defect Removal: If the host computer determines that the defective walnut is defective, the position trigger calculation module is triggered by the air jet removal parameter calculation sub-algorithm to convert the final positioning of the defective walnut into an encoder pulse signal, and calculate the precise position and trigger time of the defective walnut reaching the blowing component. Then, through the blowing parameter adaptive module, the spray angle θ is dynamically calculated according to the lateral coordinate of the defective walnut, and the air jet intensity and the opening parameters of 2-3 matching nozzles are adaptively adjusted. The host computer sends a command to the controller, and the controller controls the jet to work. The main / auxiliary jet head sprays out instantaneous airflow to push the defective walnut to the first collection box on both sides of the conveyor belt. S8. Collection of qualified products: Edible qualified walnuts continue to move along the conveyor belt, and after being buffered by the discharge buffer belt, they fall into the second collection box, completing the fully automatic detection and sorting of internal defects of the walnuts.

[0053] In step S6, the weight range of the walnuts is divided into two categories: [6.2, 8.0] g and [10.0, 14.85] g. The preset temperature threshold range is as follows: 1) When the weight is [6.2, 8.0] g, the ΔT for normal walnuts is [22.57, 31.57) ℃, the ΔT for average walnuts is [23.98, 30.11) ℃, the ΔT for slightly defective walnuts is [11.25, 18.75) ℃, and the ΔT for severely defective walnuts is [13.38, 19.71) ℃; 2) When the mass is [10.0, 14.85] g, the ΔT for normal walnuts is [12.47, 17.44] ℃, the ΔT for average walnuts is [13.25, 16.64] ℃, the ΔT for slightly defective walnuts is [6.22, 10.36] ℃, and the ΔT for severely defective walnuts is [7.39, 10.89] ℃.

[0054] In step S7, the spray angle θ is calculated based on the lateral coordinate X_{walnut} of the defective walnut, the fixed lateral coordinate X_{nozzle} of the nozzle, and the vertical height H_{nozzle} from the nozzle to the conveyor belt; the pulse count calculation of the position trigger calculation module includes compensation for the delay time during data processing and signal transmission to ensure that the nozzle is accurately triggered when the defective walnut arrives directly below.

[0055] It is worth mentioning that the halogen lamp can be replaced with thermal excitation equipment such as a constant temperature chamber and a heating plate, and the air jet removal method of the purging component can be replaced with a mechanical removal method using a push rod and a deflector. Moreover, after the replacement, it is still compatible with the detection algorithm built into the host computer, and only the parameters of the jet parameter calculation module of the algorithm need to be adjusted.

[0056] The method of using this invention is as follows: The operators first perform a preliminary visual screening of the walnuts, removing those with damaged shells, incomplete removal of the green husk, or exposed kernels. The screened walnuts are then placed into hopper 1, which, through outlet 101, uniformly transports the walnuts onto the conveyor belt of conveyor belt assembly 4. The walnuts move at a speed of 24 m / h along the conveyor belt, passing through toothed baffles 3 and being separated into single rows to prevent stacking and congestion. When the walnuts reach the inlet of the heating and insulation module, the first sensor 11 is triggered. The first sensor 11 controls the first thermal imager 13 to collect the initial temperature T0 and unique initial positioning information of each walnut. This information is transmitted to the host computer via the controller, where the positioning and matching sub-algorithm stores and labels the initial information. Subsequently, the walnuts enter the heating and insulation box 5 via a conveyor belt. They are continuously heated for 120 seconds by two halogen lamps. The sandwich structure of the heating and insulation box 5 maintains a stable internal temperature, facilitating heat conduction from the walnut surface to the interior. After heating, the walnuts move to the outlet of the heating and insulation module, triggering the second sensor 111. The second sensor 111 controls the second thermal imager 131 to collect the final temperature T1 and unique final positioning information of each walnut. This information is transmitted to the host computer via the controller. The host computer first uses a positioning matching sub-algorithm, combined with the conveyor belt speed and the distance between the two sensors, to uniquely match the initial / final positioning and initial / final temperature of each walnut. After matching, the information of walnuts without defect prediction is automatically deleted. Next, the temperature data analysis sub-algorithm calculates the temperature change ΔT = T1 - T0. Based on the walnut's quality range, a preset temperature threshold range is called, and a binary search method is used to quickly determine the walnut defect category. Walnuts with temperature changes falling within the normal or general range are edible, while those falling within the slightly defective or severely defective range are inedible. If the host computer determines that a walnut is defective, the position trigger calculation module, through the air-jet rejection parameter calculation sub-algorithm, converts the final positioning of the defective walnut into an encoder pulse signal, calculating the precise position and trigger time of the defective walnut reaching the blowing component. Then, through the blowing parameter adaptive module, the spray angle θ is dynamically calculated based on the lateral coordinate of the defective walnut (based on the lateral coordinate X of the defective walnut, the fixed lateral coordinate X of the nozzle, and the vertical height H of the nozzle from the conveyor belt), adaptively adjusting the air jet intensity and the opening parameters of 2-3 matching nozzles. The host computer sends a command to the controller, which controls the jet generator to operate. The main / auxiliary jet heads spray instantaneous airflow, pushing the defective walnut to the first collection box on both sides of the conveyor belt. Edible, qualified walnuts continue to move with the conveyor belt, are buffered by the discharge buffer belt, and fall into the second collection box, thus completing the fully automatic detection and sorting of internal defects in the walnuts.

[0057] Throughout this specification, the terms "an embodiment" or "an embodiment" mean that a specific feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment of the disclosed subject matter. Therefore, the phrases "in one embodiment" or "in an embodiment" appearing throughout this specification do not necessarily refer to the same embodiment. Furthermore, any suitable manner may be adopted to incorporate a specific feature, structure, or characteristic in one or more embodiments. It should be understood that this specification is not intended to limit the invention. Rather, exemplary embodiments are intended to cover alternatives, modifications, and equivalents that are included within the spirit and scope of the invention as defined by the appended claims. Furthermore, numerous specific details are set forth in the detailed description of exemplary embodiments to provide a comprehensive understanding of the claimed invention. However, those skilled in the art will understand that various embodiments may also be practiced without these specific details.

[0058] Although features and elements of these exemplary embodiments have been described in particular combination in the embodiments, each feature and element may be used alone without the other features and elements of the embodiments, or in combination with or without the other features and elements disclosed herein.

[0059] This written description uses examples, including the best mode, to disclose the invention and enables any person skilled in the art to practice the invention, including making and utilizing any apparatus or system and performing any combined methods. The patentable scope of the invention is defined by the claims and may include other examples as would be apparent to those skilled in the art. Such other examples are considered to be included within the scope of the claims if they have structural elements that are not different from the verbal language of the claims, or if they include structural elements equivalent to those described in the verbal language of the claims.

Claims

1. A walnut internal defect detection device based on infrared thermal imaging technology, comprising a conveyor belt assembly, wherein the conveyor belt assembly is driven by a drive component, the drive component being mounted on a support of the conveyor belt assembly, characterized in that, The support of the conveyor belt assembly is provided with a hopper at one end, and the lower end of the hopper is a discharge port. The discharge port corresponds to the upper side of the conveyor belt at one end of the conveyor belt assembly, and a support leg is fixed to the lower side of the hopper. A heating and heat preservation module is provided on the upper side of the support of the conveyor belt assembly, and a toothed baffle is provided between the heating and heat preservation module and the discharge port. The toothed baffle is fixed on the support of the conveyor belt assembly. The support of the conveyor belt assembly is also fixed with a purging assembly. The purging assembly is located at the discharge end of the heating and heat preservation module. The other end of the conveyor belt assembly is provided with a first collection box and a second collection box. The first collection box is located on both sides of the other end of the conveyor belt assembly and corresponds to the purging assembly respectively. The second collection box is located at the end of the other end of the conveyor belt assembly. It also includes a controller, a jet generator, an encoder, and a host computer equipped with a detection algorithm. The controller transmits data with the heating and insulation module and is electrically connected to the jet generator. The air outlet of the jet generator is connected to the purging assembly through a pipeline. The host computer is electrically connected to the drive unit and controller of the conveyor belt assembly. The detection algorithm built into the host computer is used to complete walnut positioning and matching, temperature data processing, defect category judgment, and calculation of air jet rejection parameters. The encoder is electrically connected to the host computer and the conveyor belt assembly, respectively, and is used to collect the displacement pulse signal of the conveyor belt and transmit it to the host computer.

2. The walnut internal defect detection device based on infrared thermal imaging technology according to claim 1, characterized in that, The heating and insulation module includes a heating and insulation box and a thermal imaging processing module. The heating and insulation box has openings on its lower sides at both ends; the opening closer to the hopper is the inlet, and the opening further away is the outlet. A heat source, a halogen lamp, is fixedly installed on the upper inner side of the heating and insulation box. Both sides of the heating and insulation box corresponding to the two ends of the conveyor belt assembly have heat-insulating and light-blocking plate structures. The thermal imaging processing module includes a first sensor, a second sensor, a first thermal imager, and a second thermal imager. The first sensor and the first thermal imager are sequentially fixed on the upper side of the heating and insulation box and correspond to the inlet. The second sensor and the second thermal imager are fixed on the upper side of the heating and insulation box and correspond to the outlet. The first sensor and the second thermal imager are symmetrically arranged. All three sensors transmit data to the controller. The first sensor is electrically connected to the first thermal imager, and the second sensor is electrically connected to the second thermal imager.

3. The walnut internal defect detection device based on infrared thermal imaging technology according to claim 1, characterized in that, The purging assembly includes a fixed frame, main jet heads, support columns, and auxiliary jet heads. The fixed frame is fixed to the support of the conveyor belt assembly. A group of main jet heads arranged in a matrix is ​​fixedly mounted on the lower side of the fixed frame. Several support columns are evenly fixed on both sides of the support of the conveyor belt assembly, located below the fixed frame. Auxiliary jet heads are fixedly mounted on the side of the support columns facing the conveyor belt, and the auxiliary jet heads are inclined. Both the main jet heads and auxiliary jet heads are connected to the air outlet of the jet generator through pipelines. The adjacent spacing of the main jet heads is 30mm, and the vertical distance from the surface of the conveyor belt is 70mm. The adjacent spacing of the auxiliary jet heads is 30mm, and the vertical distance from their fixed base plates to the surface of the conveyor belt is 100mm.

4. The walnut internal defect detection device based on infrared thermal imaging technology according to claim 1, characterized in that, It also includes a discharge buffer belt, which is fixed to the other end of the conveyor belt assembly and is inclined to correspond to the second collection box to buffer the impact force of qualified walnuts falling.

5. The walnut internal defect detection device based on infrared thermal imaging technology according to claim 1, characterized in that, The detection algorithm built into the host computer includes a positioning and matching sub-algorithm. The positioning and matching sub-algorithm uniquely matches the initial positioning information of the walnut collected by the first sensor with the final positioning information collected by the second sensor, based on the conveyor belt speed, the first sensor, the second sensor, the installation distance between the first thermal imager and the second thermal imager, and uniquely matches the initial temperature information collected by the first thermal imager 13 and the final temperature information collected by the second thermal imager 131. This ensures that the initial temperature and final temperature of each walnut correspond one-to-one with its own position information. After the matching is completed, the information of defective walnuts is automatically deleted to release memory space.

6. The walnut internal defect detection device based on infrared thermal imaging technology according to claim 7, characterized in that, The built-in detection algorithm of the host computer also includes a temperature data analysis sub-algorithm. The temperature data analysis sub-algorithm first calculates the temperature change ΔT for each walnut, where ΔT = final temperature T1 - initial temperature T0. Then, based on the walnut's mass range, it compares the temperature change ΔT with a preset temperature threshold range. Simultaneously, it combines a binary search method to quickly determine the walnut defect category, classifying the walnuts into four categories: normal, average, slightly defective, and severely defective.

7. The walnut internal defect detection device based on infrared thermal imaging technology according to claim 6, characterized in that, The built-in detection algorithm of the host computer also includes a sub-algorithm for calculating air jet rejection parameters. This sub-algorithm includes a position trigger calculation module and a jet parameter adaptive module: The position trigger calculation module converts the final positioning information of the defective walnut into encoder pulse count values. By calculating the number of pulses corresponding to the fixed transmission distance from the detection point to the spray valve position, it calculates the precise trigger position for the defective walnut to reach the blowing component. The jet parameter adaptive module dynamically calculates the spray angle θ based on the lateral coordinates of the defective walnut, the fixed coordinates of the nozzle, and the vertical height from the nozzle to the conveyor belt. Simultaneously, it adaptively adjusts the air jet intensity of the main / auxiliary jet heads and the number of nozzles opened, taking into account the conveyor belt running speed and signal transmission delay time.

8. A method for detecting internal defects in walnuts using the apparatus as described in any one of claims 1-7, characterized in that, Includes the following steps: S1. Material pretreatment: The walnuts are initially screened by appearance, and defective walnuts with broken shells, incomplete green skin removal, and exposed kernels are removed. The screened walnuts are placed into the silo, and the silo conveys the walnuts at a uniform speed to the conveyor belt of the conveyor belt assembly through the discharge port. S2. Material arrangement: Walnuts move along the conveyor belt at a speed of 24m / h. After passing the spike-tooth baffle, they are separated into a single row by the baffle bars and move forward in sequence to avoid stacking and congestion. S3. Initial data acquisition: When the walnut moves to the inlet of the heating and heat preservation module, the first sensor is triggered. The first sensor controls the first thermal imager to acquire the initial temperature T0 and unique initial positioning information of each walnut. The information is transmitted to the host computer via the controller, and the positioning matching sub-algorithm of the host computer completes the storage and marking of the initial information. S4. Thermal excitation heating: The walnuts enter the heating and insulation box with the conveyor belt and are continuously heated for 120 seconds by two halogen lamps. The sandwich structure of the heating and insulation box maintains a stable internal temperature and realizes heat conduction from the surface of the walnut to the inside. S5. Final state data acquisition: After heating, the walnuts are moved to the outlet of the heating and heat preservation module, triggering the second sensor. The second sensor controls the second thermal imager to acquire the final temperature T1 and unique final positioning information of each walnut. The information is transmitted to the host computer via the controller. S6. Defect Judgment: The host computer first uses the positioning matching sub-algorithm, combined with the conveyor belt speed and the distance between the two sensors, to uniquely match the initial / final positioning and initial / final temperature of each walnut. After the matching is completed, the information of walnuts without defect prediction is automatically deleted. Then, the temperature change ΔT = T1 - T0 is calculated by the temperature data analysis sub-algorithm. Based on the quality range of the walnuts, the preset temperature threshold range is called. Combined with the binary search method, the defect category of the walnuts is quickly determined. Walnuts with temperature changes falling into the normal or general range are edible, while those falling into the mild or severe defect range are inedible. S7. Defect Removal: If the host computer determines that the defective walnut is defective, the position trigger calculation module is triggered by the air jet removal parameter calculation sub-algorithm to convert the final positioning of the defective walnut into an encoder pulse signal, and calculate the precise position and trigger time of the defective walnut reaching the blowing component. Then, through the blowing parameter adaptive module, the spray angle θ is dynamically calculated according to the lateral coordinate of the defective walnut, and the air jet intensity and the opening parameters of 2-3 matching nozzles are adaptively adjusted. The host computer sends a command to the controller, and the controller controls the jet to work. The main / auxiliary jet head sprays out instantaneous airflow to push the defective walnut to the first collection box on both sides of the conveyor belt. S8. Collection of qualified products: Edible qualified walnuts continue to move along the conveyor belt, and after being buffered by the discharge buffer belt, they fall into the second collection box, completing the fully automatic detection and sorting of internal defects of the walnuts.

9. The detection method according to claim 8, characterized in that, In step S6, the weight range of the walnuts is divided into two categories: [6.2, 8.0] g and [10.0, 14.85] g. The preset temperature threshold range is as follows: 1) When the weight is [6.2, 8.0] g, the ΔT for normal walnuts is [22.57, 31.57) ℃, the ΔT for average walnuts is [23.98, 30.11) ℃, the ΔT for slightly defective walnuts is [11.25, 18.75) ℃, and the ΔT for severely defective walnuts is [13.38, 19.71) ℃; 2) When the mass is [10.0, 14.85] g, the ΔT for normal walnuts is [12.47, 17.44] ℃, the ΔT for average walnuts is [13.25, 16.64] ℃, the ΔT for slightly defective walnuts is [6.22, 10.36] ℃, and the ΔT for severely defective walnuts is [7.39, 10.89] ℃.

10. The detection method according to claim 9, characterized in that, In step S7, the spray angle θ is calculated based on the lateral coordinate X of the defective walnut, the fixed lateral coordinate X of the nozzle, and the vertical height H of the nozzle from the conveyor belt. The pulse count calculation of the position trigger calculation module includes compensation for the delay time during data processing and signal transmission to ensure that the nozzle is accurately triggered when the defective walnut arrives directly below.

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