Feeding speed control method and device of feeder special for green coconut

Abstract

The invention provides a feeding speed control method and device of a feeder special for coconut green, and relates to the technical field of automatic control. The average mass and the average diameter of coconut green to be conveyed are measured, and the reference feeding speed is determined; before conveying, the mass, the water content and the image of each coconut green are collected in real time, and the diameter and the surface roughness of the coconut green are obtained based on the coconut green images; adjusting buffer values are set, when the deviation between the real-time mass and the diameter and the average value exceeds the adjusting buffer values, the reference feeding speed is adjusted for the first time to generate a first feeding speed, and then the first feeding speed is adjusted for the second time according to the water content, the surface roughness, the water content threshold value and the reference surface roughness to generate a second feeding speed; and the final feeding speed is generated, and accurate feeding speed control is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of automatic control, and in particular to a feeding speed control method and device of a special feeding machine for young coconut. Background Art

[0002] With the advancement of agricultural modernization, the automated processing and transportation of young coconuts has become an important link in improving production efficiency and product quality. In the process of transporting young coconuts, accurate control of the feeding speed is crucial. Traditional feeding equipment often fails to take into account the differences between different young coconuts, resulting in unstable feeding speed, too slow or too fast feeding speed, which leads to damage and quality degradation of young coconuts during transportation. In addition, the existing technology is insufficient in real-time monitoring and dynamic control of speed, making it difficult to effectively respond to the transportation needs of young coconuts of different specifications, increasing the loss cost. Therefore, there is an urgent need for a device that can dynamically adjust the feeding speed according to actual data to improve the safety and efficiency of young coconut transportation.

[0003] The existing automatic feeding system for young coconut faces many technical defects, mainly reflected in the lack of adaptability to the changes in the characteristics of young coconut, the unreasonable speed control method, and the reliance on a single parameter to set the feeding speed, which cannot effectively cope with the diversity of young coconut in terms of volume and roughness. This single-dimensional control method makes it difficult to fine-tune the feeding speed, which may lead to problems such as product damage, low circulation efficiency, and waste of resources.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The object of the present invention is to provide a feeding speed control method and device of a special feeder for young coconut, so as to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: A feeding speed control method for a special feeder for young coconut, the specific steps comprising: Step 1: Determine the average mass of a batch of young coconuts to be conveyed into the feeder, and randomly select 10% of the total number of young coconuts in this batch to measure their diameters, generate the average diameter of the young coconut samples, and use it to replace the average diameter of this batch of young coconuts. Determine the base feeding speed based on the average mass and average diameter of the young coconuts; Step 2: Before entering the conveyor belt, each young coconut passes through an electronic weighing sensor, an optical sensor, and an infrared spectrometer to collect the quality and moisture content of the young coconut, as well as the image of the young coconut in real time; Step 3: Grayscale the green coconut image to generate a first recognition image, extract edge pixels of the first recognition image based on the Canny algorithm, measure the distance between the two farthest edge pixels as the diameter of the green coconut, generate an LBP histogram based on the local binary pattern, and generate the surface roughness of the green coconut based on the variance of the LBP histogram; Step 4: Setting an adjustment buffer value. When the mass and diameter of a single young coconut collected in real time do not exceed the adjustment buffer value relative to the average mass and average diameter of the young coconut, the first feeding speed is kept equal to the reference feeding speed. When the adjustment buffer value is exceeded, a first adjustment amplitude is generated to adjust the reference feeding speed, and the first feeding speed is calculated. Step 5: Perform maximum-minimum normalization on the moisture content and surface roughness of the young coconut, set a moisture content threshold and a reference surface roughness, and generate a second adjustment range based on the normalized moisture content and surface roughness and the moisture content threshold and the reference surface roughness to adjust the first feeding speed and generate a final feeding speed.

[0007] Furthermore, the principles for generating the average mass and average diameter of young coconut are: The average mass is calculated based on the formula: ; in, Indicates the average quality of this batch of young coconuts to be transported, Indicates the total mass of this batch of young coconuts to be transported. Indicates the number of young coconuts to be delivered in this batch; The formula for generating the average diameter of young coconut is: ; in, Indicates the average diameter of young coconut. Indicates the index of the coconut sample. represents the number of young coconut samples, Indicates The diameter of the coconut samples.

[0008] Furthermore, the principle of extracting edge pixels of the first recognition image based on the Canny algorithm is: For each pixel in the first recognition image, the matrix consisting of the pixel and its neighboring pixels is convolved with the horizontal template and vertical template of the Prewitt operator to generate the grayscale difference of the pixel in the horizontal and vertical directions. The formula is: ; ; ; ; in, Represents the horizontal template of the Prewitt operator, Represents the vertical template of the Prewitt operator, Represents the horizontal difference of the pixel. Represents the vertical difference of the pixel. Represents the coordinates of the pixel; The gradient amplitude of each pixel is generated based on the grayscale difference in the horizontal and vertical directions. The formula is: ; in, The coordinates are The gradient amplitude of the pixel point, Represents the horizontal difference of the pixel. Indicates the vertical difference of the pixel; The edge threshold is preset. When the gradient amplitude of a pixel point is higher than the edge threshold, the pixel point is retained as an edge pixel point, otherwise the pixel point is discarded.

[0009] Furthermore, the principle on which the surface roughness of young coconut is generated is: Take each pixel in the first recognition image as the center and compare its grayscale value with that of the surrounding neighboring pixels. When the grayscale value of the neighboring pixel is greater than or equal to the central pixel, it is marked as 1, otherwise it is marked as 0. Starting from the neighboring pixel at the upper left corner of the central pixel, all marks are arranged into a binary number in a clockwise direction, and the binary number is converted into decimal as the LBP value of the central pixel. The LBP values ​​of all pixels in the first recognition image are counted to generate an LBP histogram reflecting the probability of occurrence of different LBP values. The variance of the LBP histogram is calculated based on the formula: ; ; ; in, represents the index of the LBP value, and , Indicates The probability of an LBP value appearing, Indicates The number of times the LBP value appears, represents the mean of the LBP histogram, Represents the variance of the LBP histogram; ; in, Indicates the surface roughness of young coconut.

[0010] Furthermore, the principle for generating the first adjustment range is: Set the adjustment buffer value to 10% of the average weight and average diameter of the young coconut. and At this time, there is no need to adjust the base feeding speed; in, Indicates the real-time quality of a single young coconut. Indicates the diameter of a single coconut collected in real time; Otherwise, the first adjustment amplitude is generated to adjust the reference feeding speed, and the formula is as follows: ; ; ; in, Indicates the quality adjustment range, represents the quality influence coefficient, Indicates the diameter adjustment range. represents the diameter influence coefficient, Indicates the first adjustment range; The formula for calculating the first feeding speed is: ; in, Indicates the first feeding speed, Indicates the base feed speed.

[0011] Furthermore, the principle for generating the second adjustment range is: ; in, Indicates the second adjustment range, represents the normalized water content, represents the water content threshold, The weight coefficient representing the water content, represents the normalized surface roughness, Indicates the reference surface roughness, represents the weight coefficient of surface roughness, ,and ; The formula used to generate the final feed rate is: ; in, Indicates the final feeding speed.

[0012] The present invention also provides a feeding speed control device for a special feeder for young coconuts, and the device is used to implement the feeding speed control method for the special feeder for young coconuts, which specifically includes: The pre-processing module is used to determine the average mass of a batch of young coconuts to be conveyed into the feeder, and randomly select 10% of the total number of young coconuts in the batch to measure the diameter, generate the average diameter of the young coconut samples, and use it to replace the average diameter of the batch of young coconuts. The reference feeding speed is determined based on the average mass and average diameter of the young coconuts; The data acquisition module is used to collect the quality and moisture content of the coconut and the image of the coconut in real time before each coconut enters the conveyor belt through an electronic weighing sensor, an optical sensor and an infrared spectrometer; A data processing module is used to grayscale the green coconut image to generate a first recognition image, extract edge pixels of the first recognition image based on a canny algorithm, measure the distance between the two farthest edge pixels as the diameter of the green coconut, generate an LBP histogram based on a local binary pattern, and generate the surface roughness of the green coconut based on the variance of the LBP histogram; The first control module is used to set an adjustment buffer value. When the mass and diameter of a single coconut collected in real time relative to the average mass and average diameter of the coconut do not exceed the adjustment buffer value, the first feeding speed is kept equal to the reference feeding speed. When the adjustment buffer value is exceeded, a first adjustment amplitude is generated to adjust the reference feeding speed, and the first feeding speed is calculated; The integrated control module is used for performing maximum-minimum normalization on the moisture content and surface roughness of the young coconut, setting a moisture content threshold and a reference surface roughness, and generating a second adjustment range to adjust the first feeding speed based on the normalized moisture content and surface roughness and the moisture content threshold and the reference surface roughness to generate a final feeding speed.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention sets the corresponding reference feeding speed according to the average mass and average diameter of young coconut, effectively matches the characteristics of young coconut with the operation of the feeder, provides a standardized feeding speed reference for the entire feeding process, and helps to improve the accuracy of subsequent speed adjustment; before transporting the young coconut, the mass, moisture content and image data of the young coconut are collected in real time to ensure real-time feedback, thereby reducing the loss caused by delayed feedback. The diameter and roughness of the young coconut are obtained respectively by the canny algorithm and the local binary mode, thereby improving the accuracy of the data.

[0014] The present invention also determines whether the feeding speed needs to be adjusted by comparing the real-time collected coconut mass and coconut diameter with the average mass and average diameter. By setting the adjustment buffer value, the device can flexibly adjust the feeding speed according to the actually collected coconut mass and diameter data, thereby avoiding frequent speed adjustment due to some minor changes and reducing resource loss. When the speed adjustment is required, the reference feeding speed is first adjusted once in consideration of the coconut mass and diameter, thereby avoiding reduced efficiency due to speed mismatch. The feeding speed is adjusted again according to the water content and surface roughness of the coconut, thereby realizing refined control of the feeding speed, ensuring that each batch of coconuts can be personalized according to their characteristics, ensuring that the feeding speed matches the actual state of the coconuts, and by accurately adjusting the feeding speed twice, the first round of adjustment can quickly respond to characteristic changes, and the second round of adjustment is further optimized, thereby ensuring the stability and safety of the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a schematic diagram of a method flow of an embodiment of the present invention; Figure 2 Schematic diagram of a device module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0016] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0017] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0018] Example: See also Figure 1 , the present invention provides a technical solution: A feeding speed control method for a special feeder for young coconut, the specific steps comprising: Step 1: Determine the average mass of a batch of young coconuts to be conveyed into the feeder, and randomly select 10% of the total number of young coconuts in this batch to measure their diameters, generate the average diameter of the young coconut samples, and use it to replace the average diameter of this batch of young coconuts. Determine the base feeding speed based on the average mass and average diameter of the young coconuts; In the present embodiment, the principle that generates the average quality of young coconut and the average diameter is based on is: The average mass is calculated based on the formula: ; in, Indicates the average quality of this batch of young coconuts to be transported, Indicates the total mass of this batch of young coconuts to be transported. Indicates the number of young coconuts to be delivered in this batch; The formula for generating the average diameter of young coconut is: ; in, Indicates the average diameter of young coconut. Indicates the index of the coconut sample. represents the number of young coconut samples, Indicates The diameter of the coconut samples.

[0019] When the average mass and average diameter are known, the benchmark feeding speed is set based on expert decision-making. The benchmark feeding speed must meet the actual transportation efficiency needs and take into account the mass and diameter of the coconuts to avoid feeding too fast or too slow.

[0020] Step 2: Before entering the conveyor belt, each young coconut passes through an electronic weighing sensor, an optical sensor, and an infrared spectrometer to collect the quality and moisture content of the young coconut, as well as the image of the young coconut in real time; Step 3: Grayscale the green coconut image to generate a first recognition image, extract edge pixels of the first recognition image based on the Canny algorithm, measure the distance between the two farthest edge pixels as the diameter of the green coconut, generate an LBP histogram based on the local binary pattern, and generate the surface roughness of the green coconut based on the variance of the LBP histogram; In this embodiment, the principle of extracting edge pixels of the first recognition image based on the Canny algorithm is: For each pixel in the first recognition image, the matrix consisting of the pixel and its neighboring pixels is convolved with the horizontal template and vertical template of the Prewitt operator to generate the grayscale difference of the pixel in the horizontal and vertical directions. The formula is: ; ; ; ; in, Represents the horizontal template of the Prewitt operator, Represents the vertical template of the Prewitt operator, Represents the horizontal difference of the pixel. Represents the vertical difference of the pixel. Represents the coordinates of the pixel; The gradient amplitude of each pixel is generated based on the grayscale difference in the horizontal and vertical directions. The formula is: ; in, The coordinates are The gradient amplitude of the pixel point, Represents the horizontal difference of the pixel. Indicates the vertical difference of the pixel; The edge threshold is preset. When the gradient amplitude of a pixel point is higher than the edge threshold, the pixel point is retained as an edge pixel point, otherwise the pixel point is discarded.

[0021] The principle of the preset edge threshold is: generate a histogram of the gradient amplitude by combining the frequency of occurrence of the gradient amplitude of all pixels, and select the initial edge threshold in the range of 70% to 90% of the histogram. A higher percentile helps to suppress noise and reduce false positives, but may miss subtle edges. A lower percentile can capture more details, but may cause too much noise to be recognized as edges. Therefore, after selecting the initial edge threshold, the edge pixels of the first recognition image are extracted, and the experts in the field judge the extraction effect of the edge pixels, and adjust the edge threshold according to the extraction effect of the edge pixels until the edge extracted according to the edge threshold meets the requirements; The principle of generating the surface roughness of coconut is: Take each pixel in the first recognition image as the center and compare its grayscale value with that of the surrounding neighboring pixels. When the grayscale value of the neighboring pixel is greater than or equal to the central pixel, it is marked as 1, otherwise it is marked as 0. Starting from the neighboring pixel at the upper left corner of the central pixel, all marks are arranged into a binary number in a clockwise direction, and the binary number is converted into decimal as the LBP value of the central pixel. The LBP values ​​of all pixels in the first recognition image are counted to generate an LBP histogram reflecting the probability of occurrence of different LBP values. The variance of the LBP histogram is calculated based on the formula: ; ; ; in, represents the index of the LBP value, and , Indicates The probability of an LBP value appearing, Indicates The number of times the LBP value appears, represents the mean of the LBP histogram, Represents the variance of the LBP histogram; ; in, Indicates the surface roughness of young coconut.

[0022] The larger the variance of the LBP histogram, the more complex the texture and the rougher the surface.

[0023] Step 4: Setting an adjustment buffer value. When the mass and diameter of a single young coconut collected in real time do not exceed the adjustment buffer value relative to the average mass and average diameter of the young coconut, the first feeding speed is kept equal to the reference feeding speed. When the adjustment buffer value is exceeded, a first adjustment amplitude is generated to adjust the reference feeding speed, and the first feeding speed is calculated. In this embodiment, the principle for generating the first adjustment range is: Set the adjustment buffer value to 10% of the average weight and average diameter of the young coconut. and At this time, there is no need to adjust the base feeding speed; Adjust the buffer value to an allowable deviation range. When the deviation between the mass and diameter of a single coconut and the reference value is within the buffer value range, keep the feeding speed unchanged to avoid frequent adjustment of the feeding speed due to slight changes in mass and diameter. in, Indicates the real-time quality of a single young coconut. Indicates the diameter of a single coconut collected in real time; Otherwise, the first adjustment amplitude is generated to adjust the reference feeding speed, and the formula is as follows: ; ; ; in, Indicates the quality adjustment range, represents the quality influence coefficient, Indicates the diameter adjustment range. represents the diameter influence coefficient, Indicates the first adjustment range, , ,and ; according to and There may be four situations: the mass and diameter are lower than the average mass and average diameter, the mass and diameter are higher than the average mass and average diameter, the mass is higher than the average mass and the diameter is lower than the average diameter, the mass is lower than the average mass and the diameter is higher than the average diameter. When the mass of a single coconut exceeds the adjustment buffer value, the larger the mass, the slower the transmission speed. In order to avoid too slow a transmission speed, it is necessary to increase the feeding speed for regulation: When the diameter of a single coconut exceeds the adjustment buffer value, the larger the diameter, the larger the coconut, the slower the transmission speed. It is necessary to increase the feeding speed for regulation. When the value is negative, it means that the reference feeding speed is slowed down. The mass adjustment range is proportional to the difference between the mass of a single coconut collected in real time and the average mass. The diameter adjustment range is proportional to the difference between the diameter of a single coconut collected in real time and the average diameter. The adjustment ranges of mass and diameter for the reference feeding speed are calculated respectively, and the addition is the final adjustment range for the reference speed. The mass directly determines the inertia of the coconut and the load of the conveyor belt, so the mass influence coefficient Larger, Mainly affects the arrangement of coconut, so the diameter affects the coefficient Take a smaller value, , .

[0024] The formula for calculating the first feeding speed is: ; in, Indicates the first feeding speed, Indicates the base feed speed.

[0025] Step 5: Perform maximum-minimum normalization on the moisture content and surface roughness of the young coconut, set a moisture content threshold and a reference surface roughness, and generate a second adjustment range based on the normalized moisture content and surface roughness and the moisture content threshold and the reference surface roughness to adjust the first feeding speed and generate a final feeding speed.

[0026] In this embodiment, the principle for generating the second adjustment range is: ; in, Indicates the second adjustment range, represents the normalized water content, represents the water content threshold, The weight coefficient representing the water content, represents the normalized surface roughness, Indicates the reference surface roughness, represents the weight coefficient of surface roughness, ,and ; The moisture content threshold represents the dividing line where the moisture content has two effects on the feeding speed, namely, accelerating and slowing down. The reference surface roughness represents the value when the surface roughness just does not affect the feeding speed of the young coconut. The moisture content threshold and the reference surface roughness are normalized to the maximum and minimum under the same conditions with the moisture content and the surface roughness, respectively, and are determined based on expert evaluation. When the moisture content is less than or equal to the moisture content threshold, as the moisture content of the young coconut increases, the surface of the young coconut will gradually become wet and sticky, increasing the friction between the young coconut and the conveyor belt of the feeder. If no regulation is performed, the feeding speed will be reduced. At this time, the feeding speed needs to be increased to balance this effect. When the moisture content is greater than the moisture content threshold, there is too much water between the young coconut and the conveyor belt, which causes the surface of the young coconut to become slippery and reduce friction. At this time, the moisture content of the young coconut increases at any time. If no regulation is performed, the conveying speed will be accelerated. The feeding speed needs to be reduced to balance this effect. When the surface roughness is higher than the reference surface roughness, the friction between the young coconut and the feeder conveyor belt is too large. If no regulation is made, the feeding speed will be reduced. The feeding speed needs to be increased to balance this effect. When the surface roughness is lower than or equal to the reference surface roughness, the young coconut is too smooth and the friction between it and the feeder is too small. If no regulation is made, the feeding speed will increase. Therefore, the feeding speed needs to be reduced to balance this effect. The moisture content of young coconut is easily affected by factors such as storage conditions and transportation time, and thus fluctuates. However, the surface roughness is relatively more stable. , .

[0027] The formula used to generate the final feed rate is: ; in, Indicates the final feeding speed.

[0028] See also Figure 2 The present invention also provides a feeding speed control device for a special feeder for young coconuts, and the device is used to implement the feeding speed control method of the special feeder for young coconuts, which specifically includes: The pre-processing module is used to determine the average mass of a batch of young coconuts to be conveyed into the feeder, and randomly select 10% of the total number of young coconuts in the batch to measure the diameter, generate the average diameter of the young coconut samples, and use it to replace the average diameter of the batch of young coconuts. The reference feeding speed is determined based on the average mass and average diameter of the young coconuts; The data acquisition module is used to collect the quality and moisture content of the coconut and the image of the coconut in real time before each coconut enters the conveyor belt through an electronic weighing sensor, an optical sensor and an infrared spectrometer; A data processing module is used to grayscale the green coconut image to generate a first recognition image, extract edge pixels of the first recognition image based on a canny algorithm, measure the distance between the two farthest edge pixels as the diameter of the green coconut, generate an LBP histogram based on a local binary pattern, and generate the surface roughness of the green coconut based on the variance of the LBP histogram; The first control module is used to set an adjustment buffer value. When the mass and diameter of a single coconut collected in real time relative to the average mass and average diameter of the coconut do not exceed the adjustment buffer value, the first feeding speed is kept equal to the reference feeding speed. When the adjustment buffer value is exceeded, a first adjustment amplitude is generated to adjust the reference feeding speed, and the first feeding speed is calculated; The integrated control module is used for performing maximum-minimum normalization on the moisture content and surface roughness of the young coconut, setting a moisture content threshold and a reference surface roughness, and generating a second adjustment range to adjust the first feeding speed based on the normalized moisture content and surface roughness and the moisture content threshold and the reference surface roughness to generate a final feeding speed.

[0029] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0030] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0031] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0032] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A feeding speed control method for a special feeder for young coconut, characterized in that: The specific steps include: Step 1: Determine the average mass of a batch of young coconuts to be conveyed into the feeder, and randomly select 10% of the total number of young coconuts in this batch to measure their diameters, generate the average diameter of the young coconut samples, and use it to replace the average diameter of this batch of young coconuts. Determine the base feeding speed based on the average mass and average diameter of the young coconuts; Step 2: Before entering the conveyor belt, each young coconut passes through an electronic weighing sensor, an optical sensor, and an infrared spectrometer to collect the quality and moisture content of the young coconut, as well as the image of the young coconut in real time; Step 3: Grayscale the green coconut image to generate a first recognition image, extract edge pixels of the first recognition image based on the Canny algorithm, measure the distance between the two farthest edge pixels as the diameter of the green coconut, generate an LBP histogram based on the local binary pattern, and generate the surface roughness of the green coconut based on the variance of the LBP histogram; Step 4: Setting an adjustment buffer value. When the mass and diameter of a single young coconut collected in real time do not exceed the adjustment buffer value relative to the average mass and average diameter of the young coconut, the first feeding speed is kept equal to the reference feeding speed. When the adjustment buffer value is exceeded, a first adjustment amplitude is generated to adjust the reference feeding speed, and the first feeding speed is calculated. Step 5: Perform maximum-minimum normalization on the moisture content and surface roughness of the young coconut, set a moisture content threshold and a reference surface roughness, and generate a second adjustment range based on the normalized moisture content and surface roughness and the moisture content threshold and the reference surface roughness to adjust the first feeding speed and generate a final feeding speed.

2. The feeding speed control method of a special feeder for young coconut according to claim 1, characterized in that: The principle for generating the average mass and average diameter of young coconut in step 1 is: The average mass is calculated based on the formula: ； in, Indicates the average quality of this batch of young coconuts to be transported, Indicates the total mass of this batch of young coconuts to be transported. Indicates the number of young coconuts to be delivered in this batch; The formula for generating the average diameter of young coconut is: ； in, Indicates the average diameter of young coconut. Indicates the index of the coconut sample. represents the number of young coconut samples, Indicates The diameter of the coconut samples.

3. The feeding speed control method of a special feeder for young coconut according to claim 1, characterized in that: The principle of extracting edge pixels of the first recognition image based on the Canny algorithm in step 3 is: For each pixel in the first recognition image, the matrix consisting of the pixel and its neighboring pixels is convolved with the horizontal template and vertical template of the Prewitt operator to generate the grayscale difference of the pixel in the horizontal and vertical directions. The formula is: ； ； ； ； in, Represents the horizontal template of the Prewitt operator, Represents the vertical template of the Prewitt operator, Represents the horizontal difference of the pixel. Represents the vertical difference of the pixel. Represents the coordinates of the pixel; The gradient amplitude of each pixel is generated based on the grayscale difference in the horizontal and vertical directions. The formula is: ； in, The coordinates are The gradient amplitude of the pixel point, Represents the horizontal difference of the pixel. Indicates the vertical difference of the pixel; The edge threshold is preset. When the gradient amplitude of a pixel point is higher than the edge threshold, the pixel point is retained as an edge pixel point, otherwise the pixel point is discarded.

4. The feeding speed control method of a special feeder for young coconut according to claim 1, characterized in that: The principle on which the surface roughness of young coconut is generated in step 3 is based on: Take each pixel in the first recognition image as the center and compare its grayscale value with that of the surrounding neighboring pixels. When the grayscale value of the neighboring pixel is greater than or equal to the central pixel, it is marked as 1, otherwise it is marked as 0. Starting from the neighboring pixel at the upper left corner of the central pixel, all marks are arranged into a binary number in a clockwise direction, and the binary number is converted into decimal as the LBP value of the central pixel. The LBP values ​​of all pixels in the first recognition image are counted to generate an LBP histogram reflecting the probability of occurrence of different LBP values. The variance of the LBP histogram is calculated based on the following formula: ； ； ； in, represents the index of the LBP value, and , Indicates The probability of an LBP value appearing, Indicates The number of times the LBP value appears, represents the mean of the LBP histogram, Represents the variance of the LBP histogram; ； in, Indicates the surface roughness of young coconut.

5. The feeding speed control method of a special feeder for young coconut according to claim 1, characterized in that: The principle for generating the first adjustment range in step 4 is: Set the adjustment buffer value to 10% of the average weight and average diameter of the young coconut. and At this time, there is no need to adjust the base feeding speed; in, Indicates the quality of a single coconut collected in real time. Indicates the diameter of a single coconut collected in real time; Otherwise, the first adjustment amplitude is generated to adjust the reference feeding speed, and the formula is as follows: ； ； ； in, Indicates the quality adjustment range, represents the quality influence coefficient, Indicates the diameter adjustment range. represents the diameter influence coefficient, Indicates the first adjustment range; The formula for calculating the first feeding speed is: ； in, Indicates the first feeding speed, Indicates the base feed speed.

6. The feeding speed control method of a special feeder for young coconut according to claim 5, characterized in that: The principle for generating the second adjustment range in step 5 is: ； in, Indicates the second adjustment range, represents the normalized water content, represents the water content threshold, The weight coefficient representing the water content, represents the normalized surface roughness, Indicates the reference surface roughness, Represents the weight coefficient of surface roughness, ,and ; The formula used to generate the final feed rate is: ； in, Indicates the final feeding speed.

7. A feeding speed control device for a coconut feeder, characterized in that: The device is used to implement the feeding speed control method of the coconut feeder according to any one of claims 1 to 6, specifically comprising: The pre-processing module is used to determine the average mass of a batch of young coconuts to be conveyed into the feeder, and randomly select 10% of the total number of young coconuts in the batch to measure the diameter, generate the average diameter of the young coconut samples, and use it to replace the average diameter of the batch of young coconuts. The reference feeding speed is determined based on the average mass and average diameter of the young coconuts; The data acquisition module is used to collect the quality and moisture content of the coconut and the image of the coconut in real time before each coconut enters the conveyor belt through an electronic weighing sensor, an optical sensor and an infrared spectrometer; A data processing module is used to grayscale the green coconut image to generate a first recognition image, extract edge pixels of the first recognition image based on a canny algorithm, measure the distance between the two farthest edge pixels as the diameter of the green coconut, generate an LBP histogram based on a local binary pattern, and generate the surface roughness of the green coconut based on the variance of the LBP histogram; The first control module is used to set an adjustment buffer value. When the mass and diameter of a single coconut collected in real time relative to the average mass and average diameter of the coconut do not exceed the adjustment buffer value, the first feeding speed is kept equal to the reference feeding speed. When the adjustment buffer value is exceeded, a first adjustment amplitude is generated to adjust the reference feeding speed, and the first feeding speed is calculated; The integrated control module is used for performing maximum-minimum normalization on the moisture content and surface roughness of the young coconut, setting a moisture content threshold and a reference surface roughness, and generating a second adjustment range to adjust the first feeding speed based on the normalized moisture content and surface roughness and the moisture content threshold and the reference surface roughness to generate a final feeding speed.

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