Control method and system of automatic mulberry harvesting device

Abstract

The invention relates to a control method and system of an automatic mulberry harvesting device, and belongs to the technical field of automatic mulberry harvesting. Real-time image data information of mulberries is acquired through an image acquisition device installed on the automatic mulberry harvesting device in a related recommended harvesting period; and finally, preprocessing the real-time image data information of the mulberry to obtain mulberry twig image features of the mulberry, configuring working frequency and cutting working power for the automatic mulberry harvesting device according to the mulberry twig image features of the mulberry, and controlling the automatic mulberry harvesting device according to the working frequency and the cutting working power. According to the mulberry twig image features of the mulberry and the infection probability value when the mulberry twig of the mulberry is damaged within the preset time, the mulberry harvesting time period and the working parameters of the automatic mulberry harvesting device are formulated, and the control reasonability of the automatic mulberry harvesting device and the reasonability when the mulberry is harvested can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mulberry harvesting, and in particular to a control method and system of an automatic mulberry harvesting device. Background Art

[0002] Sericulture is a traditional agriculture with strong seasonality, high labor intensity, and high demand for labor in a short period of time. At present, according to the physiological characteristics of mulberry trees, Hezhou, Guangxi Zhuang Autonomous Region, now adopts the branch cutting method to raise silkworms. Compared with the traditional leaf picking method, it is more efficient and better adapted to the season, especially in summer. When the branches are piled together, there are many gaps, which play a role in ventilation and heat dissipation, avoiding the problem of mulberry leaves piled together and prone to heat and deterioration. The pruning method of raising silkworms improves labor efficiency and adapts to the seasons, which is the development trend of the silkworm industry. After the mulberry trees are harvested, within 45 days, mulberry buds grow from the roots and grow into new mulberry trees, which can be harvested. However, in the current mulberry harvesting process, it is impossible to switch the cutting power and cutting frequency according to the size of the mulberry branches, which leads to the inability of the mulberry automatic harvesting device to achieve the set goals during the harvesting process. Repeated cutting is required, and the cutting efficiency is low, resulting in excessive energy consumption. Summary of the invention

[0003] The invention overcomes the deficiencies of the prior art and provides a control method and system for an automatic mulberry tree harvesting device.

[0004] To achieve the above object, the technical solution adopted by the present invention is: A first aspect of the present invention provides a control method for a mulberry tree automatic harvesting device, comprising the following steps: Obtain infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data through big data, and calculate infection probabilities when mulberry branches are damaged under various temperature and humidity data based on the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data, and construct a knowledge graph based on the infection probabilities when mulberry branches are damaged under various temperature and humidity data; Acquire temperature and humidity data of the area where the current mulberry tree is located within a preset time, and acquire the infection probability value when the mulberry branch of the mulberry tree is damaged within the preset time according to the temperature and humidity data of the area where the current mulberry tree is located within the preset time and the knowledge graph; Formulate a mulberry tree harvesting period according to the infection probability value when the mulberry branches of the mulberry tree are damaged within the preset time, generate a related recommended harvesting period according to the mulberry tree harvesting period, and obtain real-time image data information of the mulberry tree through an image acquisition device installed on the mulberry tree automatic harvesting device during the related recommended harvesting period; By preprocessing the real-time image data information of the mulberry tree, the image features of the mulberry branches of the mulberry tree are obtained, the working frequency and cutting working power of the mulberry tree automatic harvesting device are configured according to the image features of the mulberry branches of the mulberry tree, and the mulberry tree automatic harvesting device is controlled according to the working frequency and cutting working power.

[0005] Furthermore, in this method, the infection data of the mulberry tree when the mulberry branch is damaged under various temperature and humidity data are obtained through big data, and the infection probability when the mulberry branch is damaged under various temperature and humidity data is statistically calculated based on the infection data of the mulberry tree when the mulberry branch is damaged under various temperature and humidity data, specifically: Obtain infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data through big data, and obtain the number of times of infection and the number of times of non-infection when mulberry branches are damaged under various temperature and humidity data according to the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data; The number of times of infection when the mulberry branch is damaged under the temperature and humidity data and the number of times of non-infection when the mulberry branch is damaged under the temperature and humidity data are counted to obtain a total statistical number, and the number of times of infection when the mulberry branch is damaged under the temperature and humidity data is used as a numerator; The total statistical times are used as the denominator to calculate the infection probability when the mulberry branches are damaged under each temperature and humidity data, and the infection probability when the mulberry branches are damaged under each temperature and humidity data is output.

[0006] Furthermore, in this method, a knowledge graph is constructed based on the infection probability of mulberry branches when damaged under various temperature and humidity data, specifically including: Constructing a knowledge graph, configuring a plurality of storage spaces for the knowledge graph, taking temperature and humidity data and infection probability when mulberry branches are damaged as nodes, and constructing an undirected heterogeneous graph based on the nodes; The undirected heterogeneous graph is input into the knowledge graph for storage, and the knowledge graph is represented by nodes.

[0007] Furthermore, in this method, the temperature and humidity data of the area where the current mulberry tree is located within a preset time are obtained, and the infection probability value of the mulberry branch of the mulberry tree when it is damaged within the preset time is obtained according to the temperature and humidity data of the area where the current mulberry tree is located within the preset time and the knowledge graph, specifically including: Acquire the temperature and humidity data of the area where the current mulberry tree is located within a preset time, and input the temperature and humidity data of the area where the current mulberry tree is located within the preset time into the knowledge graph for data matching; Through data matching, the infection probability value when the mulberry branch of the mulberry tree is damaged within a preset time is obtained, and the infection probability value when the mulberry branch of the mulberry tree is damaged within the preset time is output.

[0008] Furthermore, in the present method, a mulberry tree harvesting period is formulated according to the infection probability value of the mulberry branches of the mulberry tree when they are damaged within the preset time, and a related recommended harvesting period is generated according to the mulberry tree harvesting period, specifically including: Setting an infection probability threshold, and determining whether the infection probability value when the mulberry branch of the mulberry tree is damaged within a preset time is greater than the infection probability threshold; Acquire a time period in which the infection probability value is not greater than the infection probability threshold, and use the time period in which the infection probability value is not greater than the infection probability threshold as a mulberry tree harvesting time period; The relevant recommended harvesting time period is generated according to the mulberry tree harvesting time period, and the relevant recommended harvesting time period is displayed in a preset manner, and the mulberry tree automatic harvesting device is controlled to harvest during the relevant recommended harvesting time period.

[0009] Furthermore, in the present method, the real-time image data information of the mulberry tree is preprocessed to obtain the image features of the mulberry branches of the mulberry tree, which specifically includes: By filtering and denoising the real-time image data information of the mulberry tree, pre-processed image data is obtained, and a feature pyramid network is introduced, and the pre-processed image data is input into the feature pyramid network for feature extraction; The contour feature data of the mulberry branch of the mulberry tree is obtained by feature extraction, and the image features of the mulberry branch of the mulberry tree are obtained by performing contour reconstruction processing on the contour feature data of the mulberry branch of the mulberry tree, and the image features of the mulberry branch of the mulberry tree are output.

[0010] Furthermore, in the present method, the operating frequency and cutting working power of the mulberry tree automatic harvesting device are configured according to the image features of the mulberry branches of the mulberry tree, specifically including: Constructing a morphological feature model diagram of a mulberry branch of a mulberry tree according to the image features of the mulberry branch of the mulberry tree, and estimating hardness feature data of the mulberry branch of the mulberry tree based on the morphological feature model diagram of the mulberry branch of the mulberry tree; Initializing the operating frequency and cutting power of the mulberry tree automatic harvesting device based on the hardness characteristic data of the mulberry branches of the mulberry tree, and performing a cutting simulation based on the operating frequency and cutting power of the mulberry tree automatic harvesting device; Obtaining estimated cutting efficiency information of the mulberry tree automated harvesting device through cutting simulation, and determining whether the cutting efficiency is greater than a preset cutting efficiency threshold; When the cutting efficiency is greater than a preset cutting efficiency threshold, cutting control is performed according to the working frequency and cutting working power of the mulberry tree automatic harvesting device; when the cutting efficiency is not greater than the preset cutting efficiency threshold, the working frequency and cutting working power of the mulberry tree automatic harvesting device are increased.

[0011] A second aspect of the present invention provides a control system for an automatic mulberry harvesting device, comprising a memory and a processor, wherein the memory comprises a control method program for the automatic mulberry harvesting device, and when the control method program for the automatic mulberry harvesting device is executed by the processor, the steps of any one of the control methods for the automatic mulberry harvesting device are implemented.

[0012] A third aspect of the present invention provides a computer-readable storage medium, comprising a control method program for an automated mulberry harvesting device. When the control method program for the automated mulberry harvesting device is executed by a processor, the steps of any one of the control methods for the automated mulberry harvesting device are implemented.

[0013] The present invention solves the defects existing in the background technology and has the following beneficial effects: The present invention obtains infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data through big data, and statistics infection probability when mulberry branches are damaged under various temperature and humidity data based on the infection data when mulberry branches are damaged under various temperature and humidity data, and constructs a knowledge graph based on the infection probability when mulberry branches are damaged under various temperature and humidity data, and then obtains temperature and humidity data of the area where the current mulberry tree is located within a preset time, and obtains infection probability values ​​of mulberry branches of mulberry trees when they are damaged within a preset time according to the temperature and humidity data of the area where the current mulberry tree is located within the preset time and the knowledge graph, so as to obtain infection probability values ​​of mulberry branches of mulberry trees when they are damaged within the preset time according to the temperature and humidity data of the area where the current mulberry tree is located within the preset time. The present invention formulates the mulberry harvesting period according to the infection probability value when the mulberry branches of the mulberry tree are damaged within a preset time, generates the relevant recommended harvesting period according to the mulberry harvesting period, obtains the real-time image data information of the mulberry tree through the image acquisition device installed on the mulberry automatic harvesting device in the relevant recommended harvesting period, and finally obtains the image features of the mulberry branches of the mulberry tree by preprocessing the real-time image data information of the mulberry tree, configures the working frequency and cutting working power of the mulberry automatic harvesting device according to the image features of the mulberry branches of the mulberry tree, and controls the mulberry automatic harvesting device according to the working frequency and cutting working power. The present invention can improve the control rationality of the mulberry automatic harvesting device and the rationality of mulberry harvesting by formulating the mulberry harvesting period and the working parameters of the mulberry automatic harvesting device according to the image features of the mulberry branches of the mulberry tree and the infection probability value when the mulberry branches of the mulberry tree are damaged within a preset time. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0015] Figure 1The overall flow chart of the control method of the mulberry tree automatic harvesting device is shown; Figure 2 A partial method flow chart of a control method of a mulberry tree automated harvesting device is shown; Figure 3 The system block diagram of the control system of the mulberry tree automatic harvesting device is shown. DETAILED DESCRIPTION

[0016] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0017] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0018] like Figure 1 As shown, the first aspect of the present invention provides a control method for a mulberry tree automatic harvesting device, comprising the following steps: S102: obtaining infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data through big data, and calculating infection probabilities when mulberry branches are damaged under various temperature and humidity data based on infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data, and constructing a knowledge graph based on infection probabilities when mulberry branches are damaged under various temperature and humidity data; S104: obtaining temperature and humidity data of the area where the current mulberry tree is located within a preset time, and obtaining an infection probability value when the mulberry branches of the mulberry tree are damaged within the preset time according to the temperature and humidity data of the area where the current mulberry tree is located within the preset time and the knowledge graph; S106: formulating a mulberry tree harvesting period according to the infection probability value when the mulberry branches of the mulberry tree are damaged within a preset time, generating a relevant recommended harvesting period according to the mulberry tree harvesting period, and acquiring real-time image data information of the mulberry tree through an image acquisition device installed on the mulberry tree automatic harvesting device during the relevant recommended harvesting period; S108: Preprocessing the real-time image data information of the mulberry tree to obtain the image features of the mulberry branches of the mulberry tree, configuring the working frequency and cutting working power of the mulberry tree automatic harvesting device according to the image features of the mulberry branches of the mulberry tree, and controlling the mulberry tree automatic harvesting device according to the working frequency and cutting working power.

[0019] It should be noted that the present invention can improve the control rationality of the automatic mulberry harvesting device and the rationality of mulberry harvesting by formulating the mulberry harvesting time period and the working parameters of the automatic mulberry harvesting device according to the image characteristics of the mulberry branches of the mulberry trees and the infection probability value when the mulberry branches of the mulberry trees are damaged within a preset time.

[0020] Furthermore, in this method, the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data are obtained through big data, and the infection probability of mulberry branches when mulberry branches are damaged under various temperature and humidity data is statistically calculated based on the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data, specifically: The infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data are obtained through big data, and the number of times of infection and the number of times of non-infection when mulberry branches are damaged under various temperature and humidity data are obtained according to the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data; The number of times of infection when the mulberry branches are damaged under each temperature and humidity data and the number of times of non-infection when the mulberry branches are damaged under each temperature and humidity data are counted to obtain the total number of statistics, and the number of times of infection when the mulberry branches are damaged under each temperature and humidity data is used as the numerator; The total number of statistics is used as the denominator to calculate the infection probability when the mulberry branches are damaged under various temperature and humidity data, and the infection probability when the mulberry branches are damaged under various temperature and humidity data is output.

[0021] It should be noted that mechanical damage to mulberry branches (such as pruning, insect bites, and wind and rain breakage) will form wounds, which become invasion channels for fungi, bacteria or viruses. For example: mulberry blight (bacterial disease): quickly invades through wounds, causing branches to wither. Mulberry branch blight (fungal disease): conidia are spread by wind and rain and infect from wounds. Mulberry white rot: When the temperature is high and the humidity is high, the pathogen is easy to infect from the wound. Secondly, temperature and humidity also affect and accelerate the reproduction of pathogens, increasing the risk of infection. This method can be used to obtain information that will accelerate the reproduction of pathogens and increase the risk of infection, thereby optimizing the control of the mulberry automated harvesting device.

[0022] Furthermore, in this method, a knowledge graph is constructed based on the infection probability of mulberry branches when damaged under various temperature and humidity data, specifically including: Construct a knowledge graph and configure several storage spaces for the knowledge graph. Use temperature and humidity data and infection probability when mulberry branches are damaged as nodes, and construct an undirected heterogeneous graph based on the nodes. The undirected heterogeneous graph is input into the knowledge graph for storage, and the knowledge graph is represented by nodes.

[0023] Furthermore, in this method, the temperature and humidity data of the area where the current mulberry tree is located within a preset time are obtained, and the infection probability value of the mulberry branch of the mulberry tree when it is damaged within the preset time is obtained according to the temperature and humidity data of the area where the current mulberry tree is located within the preset time and the knowledge graph, which specifically includes: Obtain the temperature and humidity data of the area where the current mulberry tree is located within a preset time, and input the temperature and humidity data of the area where the current mulberry tree is located within the preset time into the knowledge graph for data matching; Through data matching, the infection probability value when the mulberry branch of the mulberry tree is damaged within the preset time is obtained, and the infection probability value when the mulberry branch of the mulberry tree is damaged within the preset time is output.

[0024] Furthermore, in this method, a mulberry tree harvesting period is formulated according to the infection probability value of the mulberry branches of the mulberry tree when they are damaged within a preset time, and a related recommended harvesting period is generated according to the mulberry tree harvesting period, specifically including: Setting an infection probability threshold, and determining whether the infection probability value when the mulberry branch of the mulberry tree is damaged within a preset time is greater than the infection probability threshold; Obtaining a time period when the infection probability value is not greater than the infection probability threshold, and using the time period when the infection probability value is not greater than the infection probability threshold as a mulberry tree harvesting time period; The relevant recommended harvesting time period is generated according to the harvesting time period of the mulberry trees, and the relevant recommended harvesting time period is displayed in a preset manner, and the mulberry tree automatic harvesting device is controlled to harvest during the relevant recommended harvesting time period.

[0025] It should be noted that the method can generate relevant recommended harvesting time periods to avoid mulberry branches from being infected during periodic harvesting, thereby improving the rationality of mulberry branch harvesting.

[0026] Furthermore, in the present method, the real-time image data information of the mulberry tree is preprocessed to obtain the image features of the mulberry branch of the mulberry tree, which specifically includes: By filtering and denoising the real-time image data of the mulberry tree, the pre-processed image data is obtained, and the feature pyramid network is introduced, and the pre-processed image data is input into the feature pyramid network for feature extraction; The contour feature data of the mulberry branch of the mulberry tree is obtained by feature extraction, and the image features of the mulberry branch of the mulberry tree are obtained by performing contour reconstruction processing on the contour feature data of the mulberry branch of the mulberry tree, and the image features of the mulberry branch of the mulberry tree are output.

[0027] It should be noted that the method is used to obtain the image features of the mulberry branches of the mulberry tree, so as to identify the size of the mulberry branches, and then configure the working frequency and cutting power of the mulberry harvester according to the size of the mulberry branches.

[0028] like Figure 2 As shown, further, in this method, the working frequency and cutting working power of the mulberry tree automatic harvesting device are configured according to the image features of the mulberry branches of the mulberry tree, specifically including: S202: constructing a mulberry branch morphological feature model diagram according to the mulberry branch image features of the mulberry tree, and estimating hardness feature data of the mulberry branch of the mulberry tree based on the mulberry branch morphological feature model diagram; S204: Initializing the operating frequency and cutting power of the mulberry tree automatic harvesting device based on the hardness characteristic data of the mulberry branches of the mulberry tree, and performing a cutting simulation based on the operating frequency and cutting power of the mulberry tree automatic harvesting device; S206: Obtaining estimated cutting efficiency information of the mulberry tree automated harvesting device through cutting simulation, and determining whether the cutting efficiency is greater than a preset cutting efficiency threshold; S208: When the cutting efficiency is greater than the preset cutting efficiency threshold, cutting control is performed according to the working frequency and cutting working power of the mulberry tree automatic harvesting device; when the cutting efficiency is not greater than the preset cutting efficiency threshold, the working frequency and cutting working power of the mulberry tree automatic harvesting device are increased.

[0029] It should be noted that by using virtual reality technology and three-dimensional modeling technology to perform cutting simulation based on the working frequency and cutting working power of the mulberry automatic harvesting device, it is possible to simulate the estimated cutting efficiency information of the mulberry automatic harvesting device, thereby optimizing the cutting working parameters of the mulberry automatic harvesting device and improving the rationality of cutting.

[0030] In addition, the method further comprises the following steps: Obtain historical cutting performance characteristic change data of the cutting blade in the mulberry tree automated harvesting device through big data, build a cutting performance characteristic prediction model based on a deep neural network, and input the historical cutting performance characteristic change data of the cutting blade in the mulberry tree automated harvesting device into the cutting performance characteristic prediction model for training; Through training, a cutting performance characteristic prediction model that has been trained is obtained, and cutting performance characteristic change data of a cutting blade in an automatic mulberry tree harvesting device within a preset time is obtained; Inputting the cutting performance characteristic change data of the cutting blade in the mulberry tree automatic harvesting device within the preset time into the trained cutting performance characteristic prediction model for prediction, and obtaining the cutting performance characteristic data of the cutting blade in the mulberry tree automatic harvesting device at the current timestamp through prediction; The estimated cutting efficiency information of the automatic mulberry harvesting device is updated according to the cutting performance characteristic data of the cutting blade in the automatic mulberry harvesting device in the current timestamp, and the working frequency and cutting working power of the automatic mulberry harvesting device are dynamically readjusted.

[0031] It should be noted that the historical cutting performance characteristic change data of the cutting blades in the mulberry tree automated harvesting device include cutting efficiency information, cutting amount information per unit time under the same working parameters and other data. Through this method, the estimated cutting efficiency information of the mulberry tree automated harvesting device can be updated, and the working frequency and cutting working power of the mulberry tree automated harvesting device can be dynamically readjusted to optimize the control of the mulberry tree automated harvesting device.

[0032] In addition, the method further comprises: Obtain the type of propagating organisms related to the type of disease generated when the mulberry branches are damaged, and build a propagating organism type recognition model based on a deep neural network, and obtain image feature data of the type of propagating organisms related to the type of disease generated when the mulberry branches are damaged through big data; Inputting the image feature data of the propagation organism type related to the disease type generated when the mulberry branch is damaged into the propagation organism type recognition model for training, and obtaining the trained propagation organism type recognition model; Acquire image data information in the mulberry branch harvesting area by using a camera device provided on the mulberry tree automatic harvester, and input the image data information in the mulberry branch harvesting area into the trained propagation biological type recognition model for recognition; When the image data information in the mulberry branch harvesting area contains a propagating biological type related to the disease type caused when the mulberry branch is damaged, an early warning is issued for the corresponding mulberry branch harvesting area, and recommended measures for wound treatment are generated.

[0033] It should be noted that wounds are prone to diseases, such as mulberry blight and mulberry branch blight. These pathogens are usually spread by wind and rain or insects (such as controlling longhorn beetles, mulberry borers and other stem-boring pests). Wounds increase the chance of infection. This method can remind growers to handle the wounds while harvesting, thereby reducing the occurrence of diseases.

[0034] A second aspect of the present invention provides a control system 4 of an automatic mulberry harvesting device, comprising a memory 41 and a processor 42. The memory 41 includes a control method program of the automatic mulberry harvesting device. When the control method program of the automatic mulberry harvesting device is executed by the processor 42, the following steps are implemented: The infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data are obtained through big data, and the infection probability of mulberry branches when mulberry branches are damaged under various temperature and humidity data is calculated based on the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data, and a knowledge graph is constructed based on the infection probability of mulberry branches when mulberry branches are damaged under various temperature and humidity data; Obtain the temperature and humidity data of the area where the current mulberry tree is located within the preset time, and obtain the infection probability value when the mulberry branch of the mulberry tree is damaged within the preset time according to the temperature and humidity data of the area where the current mulberry tree is located within the preset time and the knowledge graph; A mulberry tree harvesting period is formulated according to the infection probability value when the mulberry branches of the mulberry tree are damaged within a preset time, and a relevant recommended harvesting period is generated according to the mulberry tree harvesting period, and real-time image data information of the mulberry tree is obtained by an image acquisition device installed on the mulberry tree automatic harvesting device during the relevant recommended harvesting period; By preprocessing the real-time image data information of the mulberry tree, the image features of the mulberry branches of the mulberry tree are obtained, the working frequency and cutting working power of the mulberry tree automatic harvesting device are configured according to the image features of the mulberry branches of the mulberry tree, and the mulberry tree automatic harvesting device is controlled according to the working frequency and cutting working power.

[0035] It should be noted that the present invention can improve the control rationality of the automatic mulberry harvesting device and the rationality of mulberry harvesting by formulating the mulberry harvesting time period and the working parameters of the automatic mulberry harvesting device according to the image characteristics of the mulberry branches of the mulberry trees and the infection probability value when the mulberry branches of the mulberry trees are damaged within a preset time.

[0036] Furthermore, in this system, the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data are obtained through big data, and the infection probability of mulberry branches when mulberry branches are damaged under various temperature and humidity data is calculated based on the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data, specifically: The infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data are obtained through big data, and the number of times of infection and the number of times of non-infection when mulberry branches are damaged under various temperature and humidity data are obtained according to the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data; The number of times of infection when the mulberry branches are damaged under each temperature and humidity data and the number of times of non-infection when the mulberry branches are damaged under each temperature and humidity data are counted to obtain the total number of statistics, and the number of times of infection when the mulberry branches are damaged under each temperature and humidity data is used as the numerator; The total number of statistics is used as the denominator to calculate the infection probability when the mulberry branches are damaged under various temperature and humidity data, and the infection probability when the mulberry branches are damaged under various temperature and humidity data is output.

[0037] It should be noted that mechanical damage to mulberry branches (such as pruning, insect bites, and wind and rain breakage) will form wounds, which become invasion channels for fungi, bacteria or viruses. For example: mulberry blight (bacterial disease): quickly invades through wounds, causing branches to wither. Mulberry branch blight (fungal disease): conidia are spread by wind and rain and infect from wounds. Mulberry white rot: When the temperature is high and the humidity is high, the pathogen is easy to infect from the wound. Secondly, temperature and humidity also affect and accelerate the reproduction of pathogens, increasing the risk of infection. This method can be used to obtain information that will accelerate the reproduction of pathogens and increase the risk of infection, thereby optimizing the control of the mulberry automated harvesting device.

[0038] Furthermore, in this system, a knowledge graph is constructed based on the infection probability of mulberry branches when damaged under various temperature and humidity data, specifically including: Construct a knowledge graph and configure several storage spaces for the knowledge graph. Use temperature and humidity data and infection probability when mulberry branches are damaged as nodes, and construct an undirected heterogeneous graph based on the nodes. The undirected heterogeneous graph is input into the knowledge graph for storage, and the knowledge graph is represented by nodes.

[0039] Furthermore, in this system, the temperature and humidity data of the area where the current mulberry tree is located within the preset time are obtained, and the infection probability value of the mulberry tree when the mulberry branch is damaged within the preset time is obtained according to the temperature and humidity data of the area where the current mulberry tree is located within the preset time and the knowledge graph, specifically including: Obtain the temperature and humidity data of the area where the current mulberry tree is located within a preset time, and input the temperature and humidity data of the area where the current mulberry tree is located within the preset time into the knowledge graph for data matching; Through data matching, the infection probability value when the mulberry branch of the mulberry tree is damaged within the preset time is obtained, and the infection probability value when the mulberry branch of the mulberry tree is damaged within the preset time is output.

[0040] Furthermore, in the present system, a mulberry tree harvesting period is formulated according to the infection probability value of the mulberry branches of the mulberry tree when they are damaged within a preset time, and a relevant recommended harvesting period is generated according to the mulberry tree harvesting period, specifically including: Setting an infection probability threshold, and determining whether the infection probability value when the mulberry branch of the mulberry tree is damaged within a preset time is greater than the infection probability threshold; Obtaining a time period when the infection probability value is not greater than the infection probability threshold, and using the time period when the infection probability value is not greater than the infection probability threshold as a mulberry tree harvesting time period; The relevant recommended harvesting time period is generated according to the harvesting time period of the mulberry trees, and the relevant recommended harvesting time period is displayed in a preset manner, and the mulberry tree automatic harvesting device is controlled to harvest during the relevant recommended harvesting time period.

[0041] It should be noted that the method can generate relevant recommended harvesting time periods to avoid mulberry branches from being infected during periodic harvesting, thereby improving the rationality of mulberry branch harvesting.

[0042] Furthermore, in this system, by preprocessing the real-time image data information of the mulberry tree, the image features of the mulberry branch of the mulberry tree are obtained, which specifically includes: By filtering and denoising the real-time image data of the mulberry tree, the pre-processed image data is obtained, and the feature pyramid network is introduced, and the pre-processed image data is input into the feature pyramid network for feature extraction; The contour feature data of the mulberry branch of the mulberry tree is obtained by feature extraction, and the image features of the mulberry branch of the mulberry tree are obtained by performing contour reconstruction processing on the contour feature data of the mulberry branch of the mulberry tree, and the image features of the mulberry branch of the mulberry tree are output.

[0043] It should be noted that the method is used to obtain the image features of the mulberry branches of the mulberry tree, so as to identify the size of the mulberry branches, and then configure the working frequency and cutting power of the mulberry harvester according to the size of the mulberry branches.

[0044] Furthermore, in the present system, the operating frequency and cutting working power of the mulberry tree automatic harvesting device are configured according to the image features of the mulberry branches of the mulberry tree, specifically including: Constructing a morphological feature model diagram of a mulberry branch according to the image features of the mulberry branch, and estimating hardness feature data of the mulberry branch based on the morphological feature model diagram of the mulberry branch; Initializing the working frequency and cutting power of the mulberry tree automatic harvesting device based on the hardness characteristic data of the mulberry branches of the mulberry tree, and performing a cutting simulation based on the working frequency and cutting power of the mulberry tree automatic harvesting device; Through cutting simulation, the estimated cutting efficiency information of the mulberry tree automatic harvesting device is obtained, and it is determined whether the cutting efficiency is greater than a preset cutting efficiency threshold; When the cutting efficiency is greater than a preset cutting efficiency threshold, cutting control is performed according to the working frequency and cutting working power of the mulberry tree automatic harvesting device; when the cutting efficiency is not greater than the preset cutting efficiency threshold, the working frequency and cutting working power of the mulberry tree automatic harvesting device are increased.

[0045] It should be noted that by using virtual reality technology and three-dimensional modeling technology to perform cutting simulation based on the working frequency and cutting working power of the mulberry automatic harvesting device, it is possible to simulate the estimated cutting efficiency information of the mulberry automatic harvesting device, thereby optimizing the cutting working parameters of the mulberry automatic harvesting device and improving the rationality of cutting.

[0046] A third aspect of the present invention provides a computer-readable storage medium, comprising a control method program for an automated mulberry harvesting device. When the control method program for the automated mulberry harvesting device is executed by a processor, any step of the control method for the automated mulberry harvesting device is implemented.

[0047] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0048] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they 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 present embodiment.

[0049] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0050] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: a mobile storage device, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0051] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0052] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A control method for a mulberry tree automatic harvesting device, characterized in that: The following steps are involved: Obtain infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data through big data, and calculate infection probabilities when mulberry branches are damaged under various temperature and humidity data based on the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data, and construct a knowledge graph based on the infection probabilities when mulberry branches are damaged under various temperature and humidity data; Acquire temperature and humidity data of the area where the current mulberry tree is located within a preset time, and acquire the infection probability value when the mulberry branch of the mulberry tree is damaged within the preset time according to the temperature and humidity data of the area where the current mulberry tree is located within the preset time and the knowledge graph; Formulate a mulberry tree harvesting period according to the infection probability value when the mulberry branches of the mulberry tree are damaged within the preset time, generate a related recommended harvesting period according to the mulberry tree harvesting period, and obtain real-time image data information of the mulberry tree through an image acquisition device installed on the mulberry tree automatic harvesting device during the related recommended harvesting period; By preprocessing the real-time image data information of the mulberry tree, the image features of the mulberry branches of the mulberry tree are obtained, the working frequency and cutting working power of the mulberry tree automatic harvesting device are configured according to the image features of the mulberry branches of the mulberry tree, and the mulberry tree automatic harvesting device is controlled according to the working frequency and cutting working power.

2. The control method of a mulberry tree automatic harvesting device according to claim 1, characterized in that: The infection data of the mulberry tree when the mulberry branch is damaged under various temperature and humidity data are obtained through big data, and the infection probability when the mulberry branch is damaged under various temperature and humidity data is calculated based on the infection data of the mulberry tree when the mulberry branch is damaged under various temperature and humidity data, specifically: Obtain infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data through big data, and obtain the number of times of infection and the number of times of non-infection when mulberry branches are damaged under various temperature and humidity data according to the infection data of mulberry trees when mulberry branches are damaged under various temperature and humidity data; The number of times of infection when the mulberry branch is damaged under the temperature and humidity data and the number of times of non-infection when the mulberry branch is damaged under the temperature and humidity data are counted to obtain a total statistical number, and the number of times of infection when the mulberry branch is damaged under the temperature and humidity data is used as a numerator; The total statistical times are used as the denominator to calculate the infection probability when the mulberry branches are damaged under each temperature and humidity data, and the infection probability when the mulberry branches are damaged under each temperature and humidity data is output.

3. The control method of a mulberry tree automatic harvesting device according to claim 1, characterized in that: Based on the infection probability of mulberry branches when damaged under various temperature and humidity data, a knowledge graph is constructed, specifically including: Constructing a knowledge graph, configuring a plurality of storage spaces for the knowledge graph, taking temperature and humidity data and infection probability when mulberry branches are damaged as nodes, and constructing an undirected heterogeneous graph based on the nodes; The undirected heterogeneous graph is input into the knowledge graph for storage, and the knowledge graph is represented by nodes.

4. The control method of a mulberry tree automatic harvesting device according to claim 1, characterized in that: Acquiring temperature and humidity data of the area where the current mulberry tree is located within a preset time, and acquiring the infection probability value when the mulberry branch of the mulberry tree is damaged within the preset time according to the temperature and humidity data of the area where the current mulberry tree is located within the preset time and the knowledge graph, specifically including: Acquire the temperature and humidity data of the area where the current mulberry tree is located within a preset time, and input the temperature and humidity data of the area where the current mulberry tree is located within the preset time into the knowledge graph for data matching; Through data matching, the infection probability value when the mulberry branch of the mulberry tree is damaged within a preset time is obtained, and the infection probability value when the mulberry branch of the mulberry tree is damaged within the preset time is output.

5. The control method of a mulberry tree automatic harvesting device according to claim 1, characterized in that: According to the infection probability value of the mulberry branches of the mulberry trees when they are damaged within the preset time, a mulberry tree harvesting period is formulated, and according to the mulberry tree harvesting period, a related recommended harvesting period is generated, specifically including: Setting an infection probability threshold, and determining whether the infection probability value when the mulberry branch of the mulberry tree is damaged within a preset time is greater than the infection probability threshold; Acquire a time period in which the infection probability value is not greater than the infection probability threshold, and use the time period in which the infection probability value is not greater than the infection probability threshold as a mulberry tree harvesting time period; The relevant recommended harvesting time period is generated according to the mulberry tree harvesting time period, and the relevant recommended harvesting time period is displayed in a preset manner, and the mulberry tree automatic harvesting device is controlled to harvest during the relevant recommended harvesting time period.

6. The control method of a mulberry tree automatic harvesting device according to claim 1, characterized in that: By preprocessing the real-time image data information of the mulberry tree, the image features of the mulberry branches of the mulberry tree are obtained, which specifically includes: By filtering and denoising the real-time image data information of the mulberry tree, pre-processed image data is obtained, and a feature pyramid network is introduced, and the pre-processed image data is input into the feature pyramid network for feature extraction; The contour feature data of the mulberry branch of the mulberry tree is obtained by feature extraction, and the image features of the mulberry branch of the mulberry tree are obtained by performing contour reconstruction processing on the contour feature data of the mulberry branch of the mulberry tree, and the image features of the mulberry branch of the mulberry tree are output.

7. The control method of the mulberry tree automatic harvesting device according to claim 1, characterized in that: The method configures the working frequency and cutting working power of the mulberry tree automatic harvesting device according to the mulberry branch image features of the mulberry tree, specifically including: Constructing a morphological feature model diagram of a mulberry branch of a mulberry tree according to the image features of the mulberry branch of the mulberry tree, and estimating hardness feature data of the mulberry branch of the mulberry tree based on the morphological feature model diagram of the mulberry branch of the mulberry tree; Initializing the operating frequency and cutting power of the mulberry tree automatic harvesting device based on the hardness characteristic data of the mulberry branches of the mulberry tree, and performing a cutting simulation based on the operating frequency and cutting power of the mulberry tree automatic harvesting device; Obtaining estimated cutting efficiency information of the mulberry tree automated harvesting device through cutting simulation, and determining whether the cutting efficiency is greater than a preset cutting efficiency threshold; When the cutting efficiency is greater than a preset cutting efficiency threshold, cutting control is performed according to the working frequency and cutting working power of the mulberry tree automatic harvesting device; when the cutting efficiency is not greater than the preset cutting efficiency threshold, the working frequency and cutting working power of the mulberry tree automatic harvesting device are increased.

8. A control system for an automatic mulberry harvesting device, characterized in that: It comprises a memory and a processor, wherein the memory comprises a control method program of an automatic mulberry harvesting device, and when the control method program of the automatic mulberry harvesting device is executed by the processor, the steps of the control method of the automatic mulberry harvesting device according to any one of claims 1 to 7 are implemented.

9. A computer-readable storage medium, characterized in that: It comprises a control method program of an automatic mulberry harvesting device, and when the control method program of the automatic mulberry harvesting device is executed by a processor, the steps of the control method of the automatic mulberry harvesting device according to any one of claims 1 to 7 are implemented.

Images