Hawthorn kernel removal positioning detection system and method

Abstract

The invention relates to the technical field of agricultural product processing, in particular to a hawthorn kernel removal positioning detection system and method, and the system comprises a visual detection module, a controller, a calculation module and a kernel removal device. Hawthorn images are collected and preprocessed through a dual-trigger mechanism; the calculation module stores a standard image database established based on more than or equal to 10 manual inspection samples, compares images through a feature matching algorithm, and determines the deviation number and angle of the positioning module; the controller realizes hierarchical control according to a preset threshold value, triggers the pause or full stop of the previous process, and controls the positioning module to correct the angle; the coring device adopts a sharp-corner hollow tubular cutter, and the position and depth are dynamically adjusted according to the fruit diameter size detected visually so as to adapt to the size difference of the haws. According to the method, through the steps of image acquisition, comparative analysis, threshold judgment and cutter adaptation, real-time monitoring and adjustment of hawthorn positioning deviation and accurate control of the kernel removing process are achieved, and the processing quality and efficiency are effectively improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of agricultural product processing, and particularly relates to a hawthorn kernel removal positioning detection system and method. BACKGROUND

[0002] Hawthorn is a kind of fruit rich in nutrients and is widely used in the field of food processing. In the processing of hawthorn, kernel removal is a crucial link, which directly affects the quality and processing efficiency of subsequent products. In order to improve the automation level of hawthorn processing, various hawthorn processing equipment has been developed in the related technical field.

[0003] The existing Chinese invention patent with the patent number CN117064068A and the name of hawthorn processing equipment. The existing hawthorn processing equipment mainly includes a rack, a rotating mechanism, a clamping mechanism, a kernel removal mechanism and a flat head mechanism. Its working process is as follows: the hawthorn is placed on the support frame, clamped and fixed by the mechanical clamping jaw, and the rotating frame body is driven to rotate by the power assembly. The fixed hawthorn is sequentially conveyed to the kernel removal station and the head removal station. In the kernel removal station, the kernel removal mechanism on the rotating frame completes the kernel removal operation. Then, the rotating frame conveys the kernel-removed hawthorn to the head removal station. At this time, the support frame is separated from the hawthorn, and only the mechanical clamping jaw clamps. In the process of the hawthorn passing through the head removal station with the rotating frame body, the two blades remove the heads of the hawthorn at both ends. The equipment realizes the integration of kernel removal and flat head processing, and improves the processing efficiency to a certain extent. However, the existing technology still has the following significant defects in actual application: 1. Insufficient kernel positioning accuracy: Since the kernels in hawthorn usually have a multi-particle distribution, the positioning accuracy of the existing equipment is poor, which easily leads to incomplete kernel removal, with some kernels remaining in the fruit, affecting product quality; 2. Positioning deviation causing fruit damage: If the deviation angle or amplitude is too large during the positioning of hawthorn, it is easy to cause the fruit to crack during kernel removal, reducing the yield; 3. Unable to adapt to the differences in hawthorn shape: There are natural differences in the size of individual hawthorn. The kernel removal mechanism of the existing equipment lacks targeted adjustment, which easily leads to excessive removal of fruit flesh due to size mismatch, causing waste of raw materials.

[0004] Therefore, the present application is proposed. SUMMARY

[0005] In order to solve the above technical problems existing in the prior art, the present application provides a hawthorn kernel removal positioning detection system and method. The visual detection module is compared with the standard image and combined with a real-time correction mechanism to ensure accurate kernel removal position and reduce residual kernels. An infrared horizontal angle measuring instrument is used to calibrate the camera and set double threshold triggers for hierarchical control to avoid cracking caused by deviation. The visual detection measures the fruit diameter and controls the sharp hollow tube-shaped cutter to move to the center line and dynamically adjusts the descent depth to reduce fruit flesh loss.

[0006] To achieve the above object, the technical scheme of the present application is as follows: In a first aspect, a hawthorn kernel positioning and detection system comprises a visual detection module, a controller, a computing module, and a kernel removal device. The visual detection module is in communication with the computing module and the controller, and the controller is electrically connected to the kernel removal device. The visual detection module is used to collect image data of hawthorn, the computing module stores a standard image database, and can compare the image data with the standard image to determine the amount of deviation and the angle of deviation of the positioning module of the kernel removal device. The controller is used to receive the deviation information and control the operating state of the kernel removal device according to a preset first threshold value and a second threshold value, wherein the first threshold value indicates the maximum amount of deviation and the angle of deviation of the positioning module within a preset first period, and the second threshold value indicates the maximum amount of deviation and the angle of deviation of the positioning module within a preset second period.

[0007] Further, the visual detection module comprises an industrial computer, an industrial camera, a compensation light source, a communication line, and a signal controller; the industrial computer is connected to the industrial camera through the communication line, and the signal controller is used to trigger image collection.

[0008] Further, the signal controller comprises a miniature roller rocker arm type limit switch and a mirror surface induction feedback type photoelectric switch. The limit switch is suitable for a frequency of 50-60 Hz, a rated voltage of 220-380 V, and a rated current of 0-100 A. The current specification of the photoelectric switch is 300 mA, the rated voltage is DC 6V-36V, the distance measurement is 2M±10%, the output mode is NPNNO, the level signal is low, and the response time is ≤2ms.

[0009] Further, the standard images in the standard image database are derived from hawthorn samples that are artificially inspected and measured during a trial production stage, the number of samples N≥10, and the standard images contain color, shape, standard positioning angle position, and fruit diameter size information of hawthorn.

[0010] Further, the positioning module is a circular turntable or an elliptical turntable; and further comprising an infrared horizontal angle measuring instrument for calibrating the industrial camera of the visual detection module to ensure that its installation position is not skewed.

[0011] Further, the kernel removal device comprises a sharp corner hollow tube-shaped cutter, the included angle of the sharp corner of the cutter is 60°, and the visual detection module can measure the fruit diameter size of hawthorn and compare it with the standard image database to control the cutter to move to the center line of the fruit.

[0012] Further, when the angle deviation of the positioning module meets the first threshold, the controller is a PLC controller, which can receive an instruction from an industrial computer and output a correction instruction to control the positioning module to rotate 3°-5°.

[0013] Further, the first threshold is that the number of defective products is greater than 3 and the angle deviation is 3°-5° within a preset first period of 60 seconds; and the second threshold is that the number of defective products is greater than 5 and the angle deviation is 5°-8° within a preset second period of 100 seconds.

[0014] Still further, when the first threshold is met, the controller controls the front process of the de-nucleating device to pause; and when the second threshold is met, the controller controls the de-nucleating device to stop all work.

[0015] In a second aspect, a method for positioning and detecting hawthorn de-nucleation includes the following steps: S1, collecting image data of hawthorn through a visual detection module; S2, comparing the image data with a standard image database stored in a calculation module to determine the number of deviations and the angle deviation of the positioning module of the de-nucleating device; S3, if the deviations of the positioning module meet the first threshold, a controller controls the front process of the de-nucleating device to pause; S4, if the deviations meet the second threshold after the front process is paused, the controller controls the de-nucleating device to stop running; The first threshold indicates the maximum number of deviations and the angle within a preset first period, and the second threshold indicates the maximum number of deviations and the angle within a preset second period.

[0016] Further, in the step S1, the triggering mechanism of image collection is that a miniature roller rocker arm type limit switch and a mirror surface inductive feedback type photoelectric switch are triggered, the photoelectric switch emits infrared light, and a light shielding inductive effect is realized by cooperating with a light reflecting plate.

[0017] Further, the establishment step of the standard image database includes: Taking photos of hawthorn samples checked by N≥10 artificial inspectors in a trial production stage, collecting color, shape, standard positioning angle position, and fruit diameter size, and storing the closest images into the database.

[0018] Further, in the step S2, an infrared horizontal angle measuring instrument is used to calibrate an industrial camera of the visual detection module, and the number of deviations and the angle deviation are determined based on the collected data of the calibrated camera.

[0019] Further, it further includes a cutter adapting step of measuring the fruit diameter size of hawthorn through the visual detection module and controlling a sharp hollow tube shaped cutter to move to the center line of the fruit.

[0020] Further, in the step S3, the first threshold is that the number of defective products within 60S > 3 and the angle of deviation is 3-5°, at this time, the correction instruction is output by the PLC controller, and the positioning module is controlled to rotate 3-5°.

[0021] Compared with the prior art, the above-mentioned hawthorn core positioning detection system and method provided by the application, the system comprises a visual detection module, a controller, a calculation module and a core removal device. Hawthorn images are collected and preprocessed through a double triggering mechanism; the calculation module stores a standard image database established based on 10 manual inspection samples, and determines the number and angle of deviation of the positioning module through image comparison by a feature matching algorithm; the controller realizes hierarchical control according to a preset threshold, triggers the pause or stop of the previous process, and controls the correction angle of the positioning module; the core removal device adopts a sharp hollow tube-shaped cutter, and dynamically adjusts the position and depth according to the fruit diameter size detected by the visual detection, and adapts to the size difference of hawthorn. Through the steps of image collection, comparison analysis, threshold judgment and cutter adaptation, the method realizes real-time monitoring and adjustment of hawthorn positioning deviation, precise control of the core removal process, and effectively improves the processing quality and efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The structure diagram of the hawthorn core positioning detection system provided by the embodiment of the application is shown. DETAILED DESCRIPTION

[0023] The technical solutions of the application will be clearly described below with reference to the drawings, and obviously, the described embodiments are not all the embodiments of the application, and all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0024] It should be noted that, unless otherwise specified, the relative arrangement of components and steps, numerical expressions described in these embodiments should not be understood as limiting the scope of the application.

[0025] The following description of exemplary embodiments is merely illustrative in nature and is in no way intended to limit the application or its application or use in any way. Here, the technologies, methods and devices known to those skilled in the related art may not be discussed in detail, but in the case of applying these technologies, methods and devices, these technologies, methods and devices should be regarded as part of the present specification.

[0026] Embodiment one Reference Figure 1 , Figure 1A structure diagram of a hawthorn core positioning detection system is provided, which specifically comprises a visual detection module, a PLC controller, a calculation module and a core removal device, stable data interaction links are established between the modules through communication lines (such as Ethernet or RS485 bus) to ensure the real-time and accuracy of instruction transmission and information feedback, and the specific functions and cooperation mechanisms of the modules are as follows: M1, visual detection module: used for hawthorn image acquisition, preprocessing and basic data extraction; its hardware is composed of rock valley brand industrial computer, hikvision industrial camera, compensation light source, communication line and signal controller (including Honeywell miniature roller rocker arm type limit switch and mirror surface induction feedback type photoelectric switch).

[0027] Among them, the industrial computer as the module control core, through the communication line and the industrial camera connection to coordinate the rhythm of image acquisition, compensation light source is used to eliminate the environmental light interference to ensure the image definition, signal controller through the double trigger mechanism realizes the accurate synchronization of image acquisition, when the hawthorn moves to the detection station along the conveying line, first trigger the limit switch with adaptive frequency 50-60Hz, rated voltage 220-380V, the system enters the detection state, then the hawthorn blocks the current 300mA, rated voltage DC6V-36V, range 2M±10% of the photoelectric switch infrared light, its NPNNO output mode immediately sends low level signal, trigger the industrial camera to complete the shooting within ≤2ms, ensure to capture the real-time state of hawthorn.

[0028] The collected image is transmitted to the industrial computer through the communication line, and the built-in visual processing program is used for pretreatment (such as noise reduction, graying, edge enhancement), the basic features of hawthorn such as contour and positioning angle are extracted, and standardized data is provided for subsequent comparison.

[0029] M2, controller: used for receiving deviation information, controlling the running state of the core removal device according to threshold value logic, realizing accurate linkage; the controller adopts PLC controller, first receives and analyzes information, receives the deviation information (including deviation number, angle) and threshold value judgment result sent by the calculation module, and converts these information into executable control instructions after analysis.

[0030] In terms of hierarchical control logic: when the deviation meets the first threshold (the number of defective products within 60S > 3 and the deviation angle is 3°-5°, such as the maximum capacity of the turntable is M≥4, and the positioning reference angle is 90°±3°-5°), the PLC controller immediately sends a pause instruction to the "previous process equipment" (such as the loading conveying line), only the positioning module and the visual detection module continue to run, and at the same time, according to the adjustment instruction of the calculation module, the motor of the positioning module (circular or oval-shaped turntable) is driven to rotate forward or reverse by 3°-5°, thereby completing the angle correction; when the deviation meets the second threshold (the number of defective products within 100S > 5 and the deviation angle is 5°-8°, such as the maximum capacity of the turntable is M≥6, and the positioning reference angle is 90°±5°-8°), the PLC controller issues a "full stop instruction" to the device, and all processes such as loading, positioning, kernel removal, and detection are stopped synchronously to avoid the production of a large number of defective products, and an alarm device can be triggered to prompt manual intervention.

[0031] Among them, defective products refer to fruits that do not meet the standard parameters of large cotton ball hawthorn. For example: within 60 seconds, if there are 4 hawthorns, their color deviates from the standard range of orange-red (such as green or dark brown), or the longitudinal diameter and transverse diameter deviation exceeds ±0.5CM, and there is a fruit core residual length exceeding 0.3CM, these hawthorns will be judged as defective products.

[0032] In addition, the PLC controller is also responsible for tool control linkage. After receiving the fruit diameter size data transmitted by the visual detection module, the PLC controller calculates the descent depth of the tool (hollow pipe with sharp corners, sharp corner angle 60°), controls the servo motor to drive the tool to move to the center line of the fruit, and realizes adaptive kernel removal action for different sizes of hawthorn.

[0033] M3, calculation module: used for storing standard image database and executing image comparison algorithm; the stored standard image database is derived from a plurality of hawthorn samples preliminarily checked and measured by manual during the trial production stage, specifically, a plurality of hawthorns with a number N≥10 are selected, the color, shape, standard positioning angle position, fruit diameter size and other data information of each sample are collected, and then the closest image to the ideal state is selected from the collected images, which is set and saved as a reference template for subsequent image comparison.

[0034] After receiving the preprocessed image transmitted by the visual detection module, the calculation module compares through a feature matching algorithm, in which the core feature is the standard positioning angle position, that is, by comparing the positioning angle of the hawthorn in the measured image with the standard positioning angle in the standard image, the number of hawthorns deviating from the standard positioning (the number of hawthorns deviating from the standard positioning per unit time) and the angle deviation (the difference between the measured positioning angle and the standard positioning angle) of the positioning module are calculated, and a quantitative deviation report containing these data is generated.

[0035] The calculation module determines whether the preset threshold has been reached based on the data in the offset report: the first threshold is that the number of offsets within 60 seconds is greater than 3 and the offset angle is between 3° and 5° (for example, when the maximum capacity of the turntable is M≥4, the positioning reference angle is 90°±3°-5°). The second threshold is defined as the number of offsets exceeding 5 within 100 seconds and the offset angle being between 5° and 8° (for example, when the maximum capacity of the turntable is M≥6, the positioning reference angle is 90°±5°-8°). The above judgment results and related offset data are then sent to the PLC controller in real time, providing an accurate basis for the controller to execute corresponding control actions.

[0036] M4, Pitting Device: Composed of a positioning module and an adaptive tool, it directly determines the processing quality. The positioning module uses a circular or elliptical turntable with positioning grooves on the edge that fit the shape of the hawthorn, ensuring stable placement of the hawthorn during processing. Its angle adjustment is driven by a motor through a PLC controller, allowing for 3°-5° forward and reverse fine-tuning according to instructions, returning the positioning angle to the standard positioning angle (reference 90°±3°-5°).

[0037] The adaptive cutter adopts a hollow tubular structure with a pointed corner angle of 60°. It is driven by a servo motor to move vertically. The movement trajectory of the cutter is collinear with the optical axis of the industrial camera to ensure precise alignment with the center line of the fruit. Its descent depth is dynamically adjusted according to the fruit diameter measured by the vision inspection module and determined by comparing it with the fruit diameter information stored in the standard database, thereby reducing fruit pulp loss while accurately removing the pit.

[0038] Example 2 This invention proposes a hawthorn pitting positioning detection method. This method, through image acquisition, comparative analysis, threshold judgment, and tool adaptation steps, achieves real-time monitoring and adjustment of hawthorn positioning deviation and precise control of the pitting process, effectively improving processing quality and efficiency. Specific steps may include: S1. Image data of hawthorn is acquired through the visual inspection module. When the hawthorn is conveyed to the inspection station by the conveyor line, the Honeywell miniature roller rocker arm limit switch (adaptive frequency 50-60Hz, rated voltage 220-380V) is triggered. The system synchronously preheats and compensates the light source to ensure stable image acquisition brightness. The hawthorn continues to move to the industrial camera's shooting area, blocking the infrared light from the Honeywell mirror-sensor photoelectric switch (the probe is a PMMA lens with a reflector). The switch outputs a low-level signal (response time ≤ 2ms), triggering the Hikvision industrial camera to complete the capture within 2ms. The acquired image data is preprocessed (noise reduction, grayscale conversion) by the Iwatani industrial control computer and then transmitted to the computing module via a communication line.

[0039] S2, compare the image data with the standard image database stored in the calculation module to determine the number of deviations and the angle deviation of the positioning module of the kernel removing device; the calculation module calls the standard image database (derived from N>=10 hawthorn sample images screened by artificial in the trial production stage, containing color, shape, standard positioning angle 90 degrees, fruit diameter size, etc. Information); Extract the positioning angle, fruit diameter size, etc. Features of the hawthorn to be detected, compare the measured positioning angle with the standard angle 90 degrees (such as 87 degrees measured, 3 degrees deviated), and ensure the accuracy of the data through the infrared horizontal angle measuring instrument calibrated industrial camera, count the number of deviations and angles within 60S, and generate a quantitative report containing the number of deviations and angle deviations.

[0040] S3, if the deviation of the positioning module meets the first threshold, the controller controls the front process of the kernel removing device to pause; if the number of deviations is >3 and the angle is 3-5 degrees (the capacity of the circular turntable is >=4) within 60S, the PLC controller immediately pauses the feeding process, and only the positioning module and the detection module are kept running; At the same time, receive the instruction of industrial computer, drive the positioning module (circular turntable) motor to rotate forward or reverse 3-5 degrees, until the positioning angle returns to 90 degrees+ / -3-5 degrees, and resume feeding after correction; S4, if the deviation meets the second threshold after the front process is paused, the controller controls the kernel removing device to stop running; if the number of deviations is still >5 and the angle is 5-8 degrees (corresponding to the positioning reference angle 90 degrees+ / -5-8 degrees) within 100S after the front process is paused, the PLC controller sends a kernel removing device stop command to stop all processes such as feeding, positioning, kernel removing, and detection, and triggers an alarm to prompt manual maintenance.

[0041] After the image comparison in step S2 is completed, the calculation module sends an instruction to the PLC controller before the kernel removing action; the PLC controller controls the servo motor to drive the sharp hollow pipe-shaped cutter (included angle 60 degrees) to move to the center line of the fruit, and the lowering depth is dynamically adjusted according to the fruit diameter size and the comparison result of the standard database, to ensure accurate kernel removal and reduce fruit flesh loss.

[0042] In summary, the present application has the following advantages: 1. By comparing the visual detection module with the standard image, taking the positioning angle as the core feature, combining the real-time correction mechanism, ensuring the accuracy of the kernel removal position and reducing the residual kernel; 2. Calibrate the camera through the infrared horizontal angle measuring instrument, set double thresholds, trigger hierarchical control to avoid cracking caused by deviation; 3. Measure the fruit diameter through visual detection, control the sharp hollow pipe-shaped cutter to move to the center line, dynamically adjust the lowering depth, and reduce the loss of fruit flesh.

[0043] The above detailed description merely illustrates the technical solutions of the present application and is not limiting, and although the present application has been described in detail with reference to the examples, it should be understood by those skilled in the art that the technical solutions of the present application can be modified or equivalently replaced without departing from the scope of the technical solutions of the present application, and all should be covered in the scope of the claims of the present application.

Claims

1. A hawthorn pitting and localization detection system, characterized in that, include: Visual inspection module, controller, computing module, and kernel removal device; The visual detection module is communicatively connected to the computing module and the controller, and the controller is electrically connected to the kernel removal device. The visual detection module is used to collect image data of hawthorn, and the calculation module stores a standard image database and can compare the image data with the standard image to determine the number and angle of the offset of the positioning module of the core removal device. The controller is used to receive the offset information and control the operating state of the core removal device according to a preset first threshold and a second threshold. The first threshold indicates the maximum number of offsets and the offset angle of the positioning module within a preset first period, and the second threshold indicates the maximum number of offsets and the offset angle of the positioning module within a preset second period.

2. The hawthorn pitting and positioning detection system according to claim 1, characterized in that, The vision inspection module includes an industrial computer, an industrial camera, a compensation light source, a communication line, and a signal controller; the industrial computer and the industrial camera are connected via the communication line, and the signal controller is used to trigger image acquisition.

3. The hawthorn pitting and positioning detection system according to claim 2, characterized in that, The signal controller includes a miniature roller rocker arm limit switch and a mirror-sensing feedback photoelectric switch. The limit switch is suitable for frequencies of 50-60Hz, rated voltages of 220-380V, and rated currents of 0-100A. The photoelectric switch has a current rating of 300mA, a rated voltage of DC6V-36V, a ranging range of 2M±10%, an output mode of NPNNO, a low-level signal, and a response time of ≤2ms.

4. The hawthorn pitting and positioning detection system according to claim 1, characterized in that, The standard images in the standard image database are derived from hawthorn samples that have been manually inspected and measured during the trial production stage. The number of samples N≥10. The standard images include information on the color, shape, standard positioning angle, and fruit diameter of the hawthorn.

5. The hawthorn pitting and positioning detection system according to claim 1, characterized in that, The positioning module is a circular turntable or a near-elliptical turntable; it also includes an infrared horizontal angle measuring instrument for calibrating the industrial camera of the vision inspection module to ensure that its installation position is not skewed.

6. The hawthorn pitting and positioning detection system according to claim 1, characterized in that, The pitting device includes a hollow tubular blade with a pointed angle of 60°; the visual detection module can measure the diameter of the hawthorn fruit and compare it with a standard image database, and control the blade to move to the center line of the fruit.

7. The hawthorn pitting and positioning detection system according to claim 1, characterized in that, When the angular deviation of the positioning module meets the first threshold, the controller is a PLC controller that can receive instructions from the industrial control computer and output correction instructions to control the positioning module to rotate 3°-5°.

8. The hawthorn pitting and positioning detection system according to claim 1, characterized in that, The first threshold is: within a preset first cycle of 60 seconds, the number of defective products is greater than 3 and the deviation angle is 3°-5°; the second threshold is: within a preset second cycle of 100 seconds, the number of defective products is greater than 5 and the deviation angle is 5°-8°.

9. The hawthorn pitting and positioning detection system according to claim 8, characterized in that, When the first threshold is met, the controller controls the preprocessing of the core removal device to pause; when the second threshold is met, the controller controls the core removal device to stop all operations.

10. A method for detecting the location of pitted hawthorn berries, characterized in that, Includes the following steps: S1. Collect image data of hawthorn through the visual inspection module; S2. Compare the image data with the standard image database stored in the calculation module to determine the number and angle of the offset of the positioning module of the kernel removal device; S3. If the offset of the positioning module meets the first threshold, the controller controls the previous process of the core removal device to pause. S4. If the offset meets the second threshold after the previous process is paused, the controller controls the core removal device to stop running. Wherein, the first threshold indicates the maximum number and angle of deviation within a preset first period, and the second threshold indicates the maximum number and angle of deviation within a preset second period.

11. The method for detecting the pitting and localization of hawthorn according to claim 10, characterized in that, In step S1, the image acquisition triggering mechanism is as follows: triggered by a miniature roller rocker arm limit switch and a mirror-sensing feedback photoelectric switch. The photoelectric switch emits infrared light, which works with a reflector to achieve light-blocking sensing.

12. The method for detecting the pitting and localization of hawthorn according to claim 10, characterized in that, The steps for establishing the standard image database include: Take photos of hawthorn samples that have been manually inspected by N≥10 people during the trial production stage, and collect information on color, shape, standard positioning angle and fruit diameter. Select the closest images and store them in the database.

13. The method for detecting the pitting and localization of hawthorn according to claim 10, characterized in that, In step S2, the industrial camera of the vision inspection module is calibrated using an infrared horizontal angle measuring instrument, and the number and angle of deviation are determined based on the data collected by the calibrated camera.

14. The method for detecting the pitting and localization of hawthorn according to claim 10, characterized in that, It also includes a blade adaptation step: measuring the diameter of the hawthorn fruit through a vision detection module and controlling the sharp-angled hollow tubular blade to move to the center line of the fruit.

15. The method for detecting the pitting and localization of hawthorn according to claim 10, characterized in that, In step S3, the first threshold is when the number of defective products is greater than 3 within 60 seconds and the offset angle is 3°-5°. At this time, the PLC controller outputs a correction command to control the positioning module to rotate 3°-5°.

Images