Rice seedling raising precision sowing device, control method and application thereof

Abstract

The present invention proposes a precision seeding device for rice seedlings in pots, a control method and an application thereof, comprising a mounting plate, a seeding device, a seed suction device, a hole cleaning device and a controller. The seeding device realizes seed sowing; the seed suction device absorbs seeds through a negative pressure roller and blows off excess seeds and rice awns; the hole cleaning device can prevent the rice awns from blocking the pores. A camera is provided on the negative pressure roller, and the position and number of rice awns are judged by a rice awn detection model, and the controller adjusts the working parameters of the hole cleaning device accordingly. It also includes a pressure sensor, an airflow sensor and a rice awn detection sensor. The control method includes constructing an adaptive algorithm model and training it, collecting data in real time and outputting a working parameter combination, selecting the optimal combination after evaluation and sending it to the controller to adjust the working parameters of the device, and dynamically adjusting according to the sowing effect. The present invention can realize precision sowing, effectively solve the problem of rice awn blockage, and improve sowing efficiency and quality.

Description

Technical Field

[0001] The present invention relates to the field of agricultural technology, and in particular to a precision seeding device for raising rice seedlings in pots, a control method and application thereof. Background Art

[0002] Rice is one of the main food crops in my country. Improving rice yield and quality is of great significance to ensuring food security. Compared with conventional rice blanket seedling transplanting, pot seedling transplanting has the advantages of no damage to seedlings, no slow seedling period, early and rapid tillering, gentle reduction of group tillers, high fruiting rate and thousand-grain weight, and significantly increased number of panicles and spikelets, which can effectively increase rice yield.

[0003] Hybrid rice emphasizes the cultivation of less capital and sparse planting, and uses the strong tillering ability to increase the yield. The seeding and sowing technology needs to adopt the precision sowing technology of low sowing amount, which is of great significance to improve the multiple cropping index and realize the large-scale planting of rice production. In the process of hybrid rice seedlings, precision sowing becomes an important link, and usually 2-3 seeds are sown per hole. At present, most sowing devices use suction nozzles for sowing. When sucking seeds, the suction box provides negative pressure through the fan to make the suction nozzle absorb seeds. When sowing, the fan provides positive pressure to achieve seed sowing. However, hybrid rice seeds have the characteristics of more rice awns, which leads to the suction nozzle being easily blocked by rice awns during sowing, seriously affecting the adsorption and sowing efficiency of seeds. Specifically, when the rice awns block the suction nozzle, the number of seeds adsorbed by the suction nozzle will be reduced, resulting in insufficient or uneven number of seeds sown per hole, thereby affecting the growth and yield of rice. At the same time, the rice awns are easily sucked into the suction box and are inconvenient to discharge, which not only affects the normal operation of the suction box, but also may cause seeds to accumulate in the suction box, further affecting the continuity and stability of sowing.

[0004] At present, the common method to solve these problems is to regularly clean the suction nozzle and the seed suction box, but this method is not only time-consuming and labor-intensive, but also has unsatisfactory effects and cannot fundamentally solve the problem of rice awn blockage. In addition, some sowing devices use simple filtering devices to prevent rice awns from being sucked into the seed suction box, but these filtering devices are often easily blocked by rice awns and need to be replaced frequently, which increases production costs.

[0005] In order to solve the problem that rice awns block the suction nozzle and are inconvenient to be discharged after being sucked into the seed suction box, and to improve the sowing efficiency, the present invention proposes a rice seedling raising precision sowing device, a control method and an application thereof. Summary of the invention

[0006] The embodiments of the present invention provide a precision seeding device for rice seedlings in pots, a control method and applications thereof, which aim to solve the problems existing in the current technology that hybrid rice seeds have many rice awns, which cause the suction nozzle of the seeding device to be easily blocked, and the rice awns are easily sucked into the seed suction box and are difficult to be discharged, thereby affecting the seeding efficiency and the normal use of the device.

[0007] The core technology of the present invention is mainly to achieve precise sowing of rice seedlings in pots through the coordinated work of the sowing device, the seed suction device, the hole cleaning device and the controller, combined with the rice awn detection algorithm and the adaptive control algorithm, and effectively solve the problem of rice awn blockage, thereby improving the sowing efficiency and quality.

[0008] In a first aspect, the present invention provides a rice seedling raising precision sowing device, comprising:

[0009] Mounting plate;

[0010] The sowing device comprises a profile hole roller driving motor, a profile hole roller transmission gear, a profile hole roller fixed shaft, a profile hole roller, a profile hole inner cylinder, and a sealing block; the profile hole roller driving motor is fixed on a mounting plate, and is driven by the profile hole roller transmission gear to realize the rotation of the profile hole roller; the profile holes on the outer wall of the profile hole roller cooperate with the profile hole inner cylinder to form holes for storing seeds, and during the rotation process, the profile holes scrape the seeds adsorbed on the negative pressure roller into the profile holes, and the seeds fall under the roller to realize sowing; the sealing block can block the profile holes storing seeds to prevent the seeds from falling;

[0011] The seed suction device includes a negative pressure roller driving motor, a negative pressure roller transmission gear, a negative pressure roller fixed shaft, a negative pressure roller, a seed blowing device, a seed box, a vibrator, a guide plate and a paddle motor; the negative pressure roller driving motor is fixed on the mounting plate, the negative pressure roller fixed shaft is connected to the mounting plate through a bearing and is hollow inside, and has holes on the surface for gas circulation; the negative pressure roller transmission gear drives the negative pressure roller to rotate, the air nozzle group on the surface of the negative pressure roller corresponds to the position of the mold hole, each air nozzle group contains multiple air nozzles, and the seeds are adsorbed by negative pressure, and the seed blowing device can blow off excess seeds and rice awns; the paddle motor and the vibrator in the seed box cooperate to evenly distribute the seeds, and the guide plate allows the seeds on the suction hole to fall into the corresponding mold hole;

[0012] The hole cleaning device comprises a partition, a positive pressure hole cleaning device, a sealing strip, a positive pressure sealing air nozzle, a positive pressure hole cleaning air nozzle, a negative pressure hole cleaning device, and a negative pressure hole cleaning air nozzle; the partition is fixed below the fixed shaft of the negative pressure roller, the positive pressure hole cleaning device is fixed below the partition, and the sealing strip is located in a groove below the positive pressure hole cleaning device; the positive pressure sealing air nozzle is fixed on the air hole of the partition, and the air pipe connected to the air pump passes through the inside of the fixed shaft of the negative pressure roller and is connected to the air inlet of the positive pressure sealing air nozzle, generating a positive pressure blowing force to make the sealing strip close to the inner wall of the negative pressure roller, isolating the blowing force of the positive pressure hole cleaning device, and facilitating the seed suction effect; the negative pressure hole cleaning device is located at the rear side of the negative pressure roller, and the negative pressure hole cleaning air nozzle is fixed on its air hole, and is connected to the fan to generate negative pressure suction;

[0013] The controller is electrically connected to the seeding device, the seed suction device and the hole cleaning device respectively.

[0014] Furthermore, a camera electrically connected to the controller is provided on the negative pressure roller for capturing the process of seeds being adsorbed and rolling. The captured images are preprocessed and feature extracted, and then trained using a machine learning model to obtain a rice awn detection model. The rice awn detection model is used to determine whether there are rice awns in the image and output the position and quantity information of the rice awns, so that the working parameters of the positive pressure hole cleaning device or the negative pressure hole cleaning device can be adjusted through the controller to remove the rice awns.

[0015] Furthermore, it also includes a pressure sensor for measuring the adsorption pressure of the negative pressure roller, an airflow sensor for detecting the airflow intensity of the positive pressure hole cleaning device and the negative pressure hole cleaning device, and a rice awn detection sensor for obtaining the output result of the rice awn detection model.

[0016] In a second aspect, the present invention provides a control method for a rice seedling raising precision sowing device, comprising the following steps:

[0017] S00, constructing an adaptive algorithm model, the input of which includes parameters collected by a pressure sensor, an airflow sensor, and a rice awn detection sensor and an output result of a rice awn detection model;

[0018] S10, by collecting data under different sowing conditions, including different seed varieties, rice awn numbers, sowing environments and corresponding optimal working parameter combinations, the adaptive algorithm model is trained through the data so that the model can learn the optimal working parameter combinations under different conditions;

[0019] S20, during the sowing process, collecting data in real time and inputting it into the trained adaptive algorithm model, and outputting a recommended working parameter combination through the adaptive algorithm model;

[0020] S30, evaluating multiple working parameter combinations output by the adaptive algorithm model, and measuring the pros and cons of each combination according to a preset objective function or performance index;

[0021] S40, according to the evaluation result, selecting the best working parameter combination as the decision output, and this combination will be sent to the controller of the sowing device for adjusting the working parameters of each device;

[0022] S50. As the sowing process proceeds, the sowing effect and parameter changes are monitored in real time. If it is found that the actual effect is inconsistent with the expectation, the adaptive algorithm model will make predictions and decisions again, and dynamically adjust the working parameter combination to ensure that the optimal sowing state is always maintained.

[0023] Furthermore, in step S00, a neural network, reinforcement learning or fuzzy logic is used to establish an adaptive algorithm model.

[0024] Furthermore, in step S00, time series analysis or recursive neural network is used to process time-related data in the seeding process.

[0025] Furthermore, the specific steps of time series analysis are:

[0026] Collect relevant parameter data that change over time during the sowing process, including seed flow, number of rice awns, and suction pressure of the negative pressure roller, to form time series data;

[0027] Perform feature extraction on time series data to capture the dynamic characteristics of the data;

[0028] Select an autoregressive moving average model or a differential integrated moving average autoregressive model, train the selected model using historical time series data, and adjust the model parameters to optimize the model's performance;

[0029] Use the trained model to predict future parameter changes and make corresponding working parameter adjustment strategies based on the prediction results.

[0030] Furthermore, the specific steps of the recurrent neural network are:

[0031] Collect relevant parameter data that change over time during the sowing process, including seed flow, number of rice awns, and suction pressure of the negative pressure roller, to form time series data, and organize it into a format suitable for RNN input;

[0032] Build an RNN model, use historical time series data to train the RNN, and update the model's weight parameters through the back-propagation algorithm;

[0033] During the seeding process, real-time data is input into the trained RNN, and the model outputs predictions of future parameter changes, and the adjustment of working parameters is decided based on the prediction results.

[0034] In a third aspect, the present invention provides an electronic device including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the control method of the above-mentioned rice seedling raising precision seeding device.

[0035] In a fourth aspect, the present invention provides a readable storage medium, in which a computer program is stored. The computer program includes a program code for controlling a process to execute the process. The process includes a control method for the rice seedling raising precision seeding device according to the above-mentioned method.

[0036] The main contributions and innovations of the present invention are as follows:

[0037] 1. Effectively solve the problem of rice awn blockage:

[0038] In the prior art, the rice awns of hybrid rice seeds are easy to clog the suction nozzle of the sowing device, and the rice awns are easy to be sucked into the seed suction box and are difficult to be discharged, which seriously affects the sowing efficiency and the normal use of the device.

[0039] The present invention can effectively discharge rice awns by providing a hole cleaning device, including a positive pressure hole cleaning device, a negative pressure hole cleaning device, and related air nozzles, sealing strips and other structures. During the seed suction process, the rice awns can be discharged from the drum through the air pipe connected to the fixed shaft of the negative pressure roller; for the rice awns accumulated inside the drum, they can be blown up by the blowing force of the positive pressure hole cleaning air nozzle, and sucked out through the air pipe connected to the fixed shaft of the negative pressure roller by the negative pressure suction force of the negative pressure roller. In addition, the positive pressure hole cleaning device can act alone or together with the negative pressure hole cleaning device to clean up the rice awns stuck in the air nozzle to avoid clogging the air holes. These measures greatly reduce the impact of rice awns on the sowing device and improve the sowing efficiency.

[0040] 2. Achieve precision seeding:

[0041] The sowing device of the present invention comprises a hole-shaped drum driving motor, a hole-shaped drum transmission gear, a hole-shaped drum fixed shaft, a hole-shaped drum, a hole-shaped inner drum and a sealing block, etc., and can accurately control the sowing of 2-3 seeds per hole. During the sowing process, the holes on the hole-shaped drum can accurately scrape the seeds adsorbed on the negative pressure drum into the holes, and sow the seeds one by one into the holes of the seedling tray under the drum, thereby realizing precise sowing and avoiding seed waste.

[0042] 3. Improve sowing quality:

[0043] The present invention introduces a rice awn detection algorithm, and by setting a camera on the negative pressure roller, the process of seed adsorption and rolling is collected in real time. After preprocessing and feature extraction, the collected image is trained using a machine learning model to obtain a rice awn detection model. The model can accurately determine whether there are rice awns in the image, and output the position and quantity information of the rice awns. According to this information, the controller can timely adjust the working parameters of the positive pressure hole cleaning device or the negative pressure hole cleaning device, effectively remove the rice awns, ensure the normal adsorption and sowing of the seeds, and thus improve the sowing quality.

[0044] 4. Adaptive control:

[0045] The present invention adopts an adaptive control algorithm. By constructing an adaptive algorithm model, it can automatically adjust various working parameters of the sowing device according to real-time data such as parameters collected by pressure sensors, airflow sensors, and rice awn detection sensors, as well as the output results of the rice awn detection model. During the sowing process, the model can output a recommended working parameter combination according to different sowing conditions and real-time data, and evaluate multiple working parameter combinations, select the optimal combination and send it to the controller for adjusting the working parameters of each device. At the same time, as the sowing process proceeds, the model can monitor the sowing effect and parameter changes in real time. Once it is found that the actual effect does not meet expectations, it will make predictions and decisions again, and dynamically adjust the working parameter combination to ensure that the optimal sowing state is always maintained. This adaptive control can enable the sowing device to better adapt to different sowing environments and seed characteristics, and further improve the sowing efficiency and quality.

[0046] 5. Strong versatility:

[0047] The rice seedling raising precision sowing device and control method of the present invention are applicable to different seed varieties and sowing environments, and have strong versatility. Whether in different regions, different climatic conditions, or for different varieties of hybrid rice seeds, the present invention can effectively play a role, realize precision sowing and effective cleaning of rice awns, and improve the yield and quality of rice.

[0048] In summary, the present invention has significant progress and beneficial effects compared with the prior art by solving the problem of rice awn blockage, achieving precision sowing, improving sowing quality, adopting adaptive control and having strong versatility.

[0049] The details of one or more embodiments of the invention are set forth in the following drawings and description so that other features, objects, and advantages of the invention are more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0051] Figure 1 is a stereoscopic diagram of a rice seedling raising precision sowing device according to an embodiment of the present invention;

[0052] Figure 2 yes Figure 1 Another perspective of the picture;

[0053] Figure 3 yes Figure 2 Another perspective view with the seed blowing device removed;

[0054] Figure 42 is a schematic structural diagram of a hole cleaning device for a rice seedling raising precision sowing device according to an embodiment of the present invention;

[0055] Figure 5 A three-dimensional diagram of the hole cleaning device;

[0056] Figure 6 yes Figure 5 Another perspective of the picture;

[0057] Figure 7 It is the internal structure diagram of the seeding device;

[0058] Figure 8 is a three-dimensional diagram of the sealing block;

[0059] Fig. 9 is a flow chart of a control method of a rice seedling raising precision sowing device according to an embodiment of the present invention;

[0060] Fig.10 4 is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention.

[0061] In the figure, 1, mounting plate; 2, sowing device; 3, seed suction device; 4, hole cleaning device; 21, hole roller driving motor; 22, hole roller transmission gear; 23, hole roller fixed shaft; 24, hole roller; 25, hole inner cylinder; 26, sealing block; 31, negative pressure roller driving motor; 32, negative pressure roller transmission gear; 33, negative pressure roller fixed shaft; 34, negative pressure roller; 35, seed blowing device; 36, seed box; 37. Vibrator; 38. Guide plate; 39. Paddle motor; 310. Paddle bracket; 311. Paddle motor transmission plate; 312. Paddle connecting transmission plate; 313. Paddle transmission plate; 314. Paddle; 315. Paddle fixing bracket; 41. Partition; 42. Positive pressure hole cleaning device; 43. Sealing strip; 44. Positive pressure sealing air nozzle; 45. Positive pressure hole cleaning air nozzle; 46. Negative pressure hole cleaning device; 47. Negative pressure hole cleaning air nozzle. DETAILED DESCRIPTION

[0062] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with one or more embodiments of this specification. Instead, they are merely examples of devices and methods consistent with some aspects of one or more embodiments of this specification as detailed in the appended claims.

[0063] It should be noted that: in other embodiments, the steps of the corresponding method are not necessarily performed in the order shown and described in this specification. In some other embodiments, the steps included in the method may be more or less than those described in this specification. In addition, a single step described in this specification may be decomposed into multiple steps for description in other embodiments; and multiple steps described in this specification may be combined into a single step for description in other embodiments.

[0064] Embodiment 1

[0065] The present invention aims to provide a rice seedling raising precision sowing device, specifically, referring to Figure 1-8 , including a mounting plate 1, a sowing device 2, a seed suction device 3, and a hole cleaning device 4. The rice awns can be discharged through the hole cleaning device 4 during the sowing process to avoid clogging of the seed suction device 3 and improve the sowing efficiency.

[0066] In this embodiment, the sowing device 2 includes a hole-shaped roller driving motor 21 , a hole-shaped roller transmission gear 22 , a hole-shaped roller fixing shaft 23 , a hole-shaped roller 24 , a hole-shaped inner cylinder 25 , and a sealing block 26 .

[0067] Among them, the hole roller driving motor 21 is installed on the mounting plate 1; the hole roller fixed shaft 23 is fixedly connected to the mounting plate 1 through a bearing; the driving wheel of the hole roller transmission gear 22 is fixedly connected to the motor shaft of the hole roller driving motor 21, the driven wheel is fixedly connected to the side of the hole roller 24, the hole inner cylinder 25 is fixedly connected to the hole roller fixed shaft 23, and the hole roller 24 is sleeved on the outer surface of the hole inner cylinder 25;

[0068] Among them, a plurality of shaped holes are arranged evenly in the axial and circumferential directions on the outer wall of the shaped hole roller 24, and the outer surface of the shaped hole inner cylinder 25 is smooth and closely attached to the inner wall of the shaped hole roller 24 to form holes for storing seeds; the motor shaft of the shaped hole roller driving motor 21 rotates, and the shaped hole roller 24 is rotated through the shaped hole roller transmission gear 22, and the rotation of the shaped hole roller 24 is realized. During the rotation process, at the intersection of the shaped hole roller 24 and the negative pressure roller 34, the shaped hole will scrape the seeds adsorbed on the negative pressure roller 34 into the shaped hole, and the seeds will fall below the shaped hole roller 24 as the shaped hole roller 24 rotates, thereby realizing sowing;

[0069] Among them, the sealing block 26 is fixedly connected to the mounting plate 1, located in front of the hole roller 24, and is close to the hole roller 24. When the hole containing seeds rotates to the sealing block 26, the sealing block 26 can block the hole to prevent the seeds from falling.

[0070] In this embodiment, the seed suction device 3 includes a negative pressure roller drive motor 31, a negative pressure roller transmission gear 32, a negative pressure roller fixed shaft 33, a negative pressure roller 34, a seed blowing device 35, a seed box 36, a vibrator 37, a guide plate 38, a paddle motor 39, a paddle bracket 310, a paddle motor transmission plate 311, a paddle connecting transmission plate 312, a paddle transmission plate 313, a paddle 314, and a paddle fixing bracket 315.

[0071] Among them, the negative pressure roller driving motor 31 is installed on the mounting plate 1; the negative pressure roller fixed shaft 33 is fixedly connected to the mounting plate 1 through a bearing, the negative pressure roller fixed shaft 33 is hollow inside, and has multiple holes on the surface, which is used to circulate gas; the driving wheel of the negative pressure roller transmission gear 32 is fixedly connected to the motor shaft of the negative pressure roller driving motor 31, and the driven wheel is fixedly connected to the negative pressure roller 34. The surface of the negative pressure roller 34 is provided with multiple air nozzle groups corresponding to the positions of the mold holes on the mold hole roller 24. The air nozzle group at each position contains three air nozzles, which are arranged in an A shape, and can also be arranged in other ways. The negative pressure roller fixed shaft 33 is connected to the external fan through an air pipe, and the gas flows out of the negative pressure roller 34 through the air pipe. The air pressure inside the negative pressure roller 34 is lower than the air pressure outside the roller, so that the negative pressure roller absorbs the seeds through the air nozzles, and one air nozzle absorbs one seed.

[0072] When the motor shaft of the negative pressure roller driving motor 31 rotates, it is transmitted through the negative pressure roller transmission gear 32 to realize the rotation of the fixed shaft 33 of the negative pressure roller; the seed blowing device 35 is fixedly connected to the mounting plate 1, and the seed blowing device 35 is provided with a blowing nozzle which corresponds to the position of the single exhaust nozzle group on the negative pressure roller 34. The air inlet of the seed blowing device 35 is connected to the air pump through an air pipe to introduce gas. The air pressure inside the seed blowing device 35 is higher than the air pressure outside the seed blowing device 35. The negative pressure roller may absorb excess seeds during the seed suction process. The seed blowing device 35 can blow off the excess seeds and the rice awns on the surface at the same time.

[0073] Among them, the seed box 36 is installed on the mounting plate 1 and is connected to the negative pressure roller 34; the vibrator 37 is fixedly connected to the bottom of the seed box 36; the paddle fixing frame 315 is fixedly connected to the top of the seed box 36; the paddle motor 39 is installed above the paddle fixing frame 315; the paddle bracket 310 is installed above the paddle fixing frame 315; the paddle 314 is fixedly connected to the rotating shaft of the paddle bracket 310; the paddle connecting transmission plate 312 is fixedly connected to the rotating shaft of the paddle motor 39 through the paddle motor transmission plate 311; one side of the paddle connecting transmission plate 312 is rotatably connected to the paddle motor transmission plate 311, and one side is rotatably connected to the paddle transmission plate 313, and the other side of the paddle transmission plate 313 is fixedly connected to the rotating shaft of the paddle bracket 310.

[0074] After the seeds are poured into the seed box 36, the rotating shaft of the paddle motor 39 rotates, and through the paddle motor transmission plate 311, the paddle connecting transmission plate 312 and the paddle transmission plate 313 are transmitted, and the paddle 314 swings back and forth. The paddle 314 can spread the larger part of the seeds in the middle of the seed box 36 to both sides, and the vibrator 37 works at the same time, which can make the seeds more evenly distributed in the seed box 36; the guide plate 38 is fixed to the mounting plate 1. During the seed suction process, the seeds on the suction holes can be made to fall into the corresponding shaped holes through the guide plate 38.

[0075] In this embodiment, the hole cleaning device 4 includes a partition 41 , a positive pressure hole cleaning device 42 , a sealing strip 43 , a positive pressure sealing air nozzle 44 , a positive pressure hole cleaning air nozzle 45 , a negative pressure hole cleaning device 46 , and a negative pressure hole cleaning air nozzle 47 .

[0076] Among them, the partition 41 is fixedly connected to the bottom of the negative pressure roller fixed shaft 33; the positive pressure hole cleaning device 42 is fixedly connected to the bottom of the partition 41; the sealing strip 43 is placed in the groove below the positive pressure hole cleaning device 42; the positive pressure sealing air nozzle 44 is fixedly connected to the air hole of the partition 41, and the air pipe connected to the air pump passes through the inside of the negative pressure roller fixed shaft 33 and is connected to the air inlet of the positive pressure sealing air nozzle 44; the positive pressure hole cleaning air nozzle 45 passes through the partition 41 and is fixedly connected to the air hole of the positive pressure hole cleaning device 42, and the air pipe connected to the air pump passes through the inside of the negative pressure roller fixed shaft 33 and is connected to the air inlet of the positive pressure hole cleaning air nozzle 45; the negative pressure hole cleaning device 46 is fixedly placed on the mounting plate 1, and is located at the side and rear of the negative pressure roller 34; the negative pressure hole cleaning air nozzle 47 is fixedly connected to the air hole of the negative pressure hole cleaning device 46, and the air inlet is connected to the fan through the air pipe.

[0077] During the operation of the negative pressure roller, the air pump works to flow gas into the positive pressure sealing air nozzle 44 through the air pipe. The air pressure inside the positive pressure sealing air nozzle 44 is greater than the air pressure in the groove below the positive pressure hole cleaning device 42, generating a positive pressure blowing force, blowing the sealing strip 43 downward to fit tightly against the inner wall of the negative pressure roller 34, isolating the inside of the negative pressure roller 34 from the inside of the positive pressure hole cleaning device 42, so that only negative pressure exists inside the negative pressure roller 34, which is beneficial to the seed suction effect.

[0078] During the process of adsorbing seeds, the negative pressure roller 34 can suck the rice awns of the seeds into the inside of the negative pressure roller 34, and the seed blowing device 35 will blow off the rice awns on the surface during the seed absorption process; if the rice awns are sucked into the inside of the negative pressure roller 34, subsequent effects will be produced; the rice awns stuck in the air nozzle will be applied with suction by the negative pressure hole cleaning device 46 only when the air nozzle is turned to the side and rear of the negative pressure roller 34 after the seeds are scraped into the hole roller 24.

[0079] The rice awns are discharged from the negative pressure roller 34 through the air pipe connected to the fixed shaft 33 of the negative pressure roller; the air pump works to flow the gas through the air pipe into the positive pressure hole cleaning air nozzle 45, and the air pressure in the positive pressure hole cleaning air nozzle 45 is greater than the air pressure in the cavity inside the positive pressure hole cleaning device 42, thereby generating a positive pressure blowing force; some rice awns will be stuck in the air nozzle and cannot be sucked into the negative pressure roller 34. The positive pressure hole cleaning device 42 applies a positive pressure blowing force inside to discharge the rice awns. A baffle is provided under the negative pressure roller 34 to prevent the rice awns from falling into the seedling tray after being blown out from under the negative pressure roller 34.

[0080] Among them, the fan works to make the gas flow out of the negative pressure hole cleaning air nozzle 47 through the air pipe. The air pressure in the negative pressure hole cleaning air nozzle 47 is lower than the air pressure in the negative pressure hole cleaning device 46, thereby generating negative pressure suction. If the positive pressure blowing force of the positive pressure hole cleaning device 42 is not enough to blow out the rice awns, when the negative pressure roller 34 turns to the side and rear with the rice awns, the negative pressure hole cleaning device 46 and the positive pressure hole cleaning device 42 can work together, the positive pressure hole cleaning device 42 applies positive pressure blowing force from the inside, and the negative pressure hole cleaning device 46 applies negative pressure suction from the outside, so as to discharge the rice awns stuck in the suction nozzle out of the negative pressure roller 34.

[0081] When the sowing device stops working, in order to prevent the rice awns from piling up inside the negative pressure roller 34 and affecting the adsorption effect, the air pump connected to the positive pressure sealing air nozzle 44 can be turned off, so that the sealing strip 43 cannot be close to the inner wall of the negative pressure roller 34, and the positive pressure blowing force of the positive pressure hole clearing air nozzle 45 will blow up the rice awns accumulated on the negative pressure roller 34, and then suck out the rice awns through the air pipe connected to the fixed shaft 33 of the negative pressure roller.

[0082] In this embodiment, the controller is electrically connected to the seeding device 2, the seed suction device 3 and the hole cleaning device 4, respectively, and is used to control the coordinated work of each device to achieve precision seeding. The controller can be an industrial computer.

[0083] In this embodiment, the working principle is as follows:

[0084] In the first step, the entire device is set up above the conveying device (the conveyor belt of the existing assembly line), and the seeds are poured into the seed box 36. The vibrator 37 and the paddle 314 work simultaneously to evenly spread the seeds in the seed box 36;

[0085] In the second step, after manually resetting the fixed shaft 23 of the hole roller and the fixed shaft 33 of the negative pressure roller through the controller, the conveyor belt and the seed box 36 are started, and the seedling tray is placed on the conveyor belt and moved toward the sowing device 2.

[0086] Step 3: When the sensor senses that the seedling tray enters below the sowing device 2, it transmits a signal to the controller, and the controller controls the motor shafts of the hole-shaped roller drive motor 21 and the negative pressure roller drive motor 31 to rotate synchronously, and the hole-shaped roller transmission gear 22 and the negative pressure roller transmission gear 32 are transmitted, so that the hole-shaped roller 24 and the seed blowing device 35 rotate synchronously;

[0087] The fan works at the same time, and the air inlet of the negative pressure roller fixed shaft 33 is connected to the fan through an air pipe, which sucks the gas out from the inside of the negative pressure roller fixed shaft 33, so that the air pressure inside the negative pressure roller fixed shaft 33 is lower than the air pressure outside the negative pressure roller fixed shaft 33. In this way, the negative pressure roller 34 can absorb seeds through the air nozzle and suck rice awns into the inside of the negative pressure roller fixed shaft 33, and the rice awns will be discharged from the negative pressure roller fixed shaft 33 through the air pipe. Each air nozzle group can absorb two to three seeds, and the negative pressure roller 34 will blow off the excess seeds.

[0088] Step 4: During the rotation of the negative pressure roller 34, the vibrator 37 will change the orientation of the seeds adsorbed by the fixed shaft 33 of the negative pressure roller to a vertical orientation, and the holes on the hole roller 24 will scrape the seeds adsorbed by the air nozzle group into the holes one by one, and sow the seeds one by one into the holes of the seedling tray under the roller;

[0089] In the process of adsorbing seeds, in order to prevent the positive pressure hole cleaning device 42 from affecting the seed absorption effect, a blowing force can be applied to the sealing strip 43 through the positive pressure sealing air nozzle 44, so that the sealing strip 43 is closely attached to the inner wall of the negative pressure roller 34, so that the inside of the positive pressure hole cleaning device 42 is isolated from the inside of the negative pressure roller 34, and the blowing force generated by the positive pressure hole cleaning device 42 is prevented from affecting the adsorption effect;

[0090] During the adsorption process, some rice awns will not be sucked into the negative pressure roller 34, but will be stuck on the air nozzle of the negative pressure roller 34. When these rice awns are rotated to the rear of the negative pressure roller 34 along with the negative pressure roller 34, the positive pressure hole cleaning device 42 and the negative pressure hole cleaning device 46 work together, and the positive pressure hole cleaning device 42 applies a blowing force from the inside, and the negative pressure hole cleaning device 46 applies a suction force from the outside to clean up the rice awns stuck in the suction nozzle; a baffle is provided under the negative pressure roller 34 to prevent the rice awns from being blown out from under the negative pressure roller 34 and falling into the seedling tray.

[0091] Step 5. When the sowing device 2 stops working, in order to prevent the rice awns from piling up inside the negative pressure roller 34 and affecting the adsorption effect, the air pump connected to the positive pressure sealing air nozzle 44 can be turned off, so that the sealing strip 43 cannot be close to the inner wall of the negative pressure roller 34, and the blowing force of the positive pressure hole clearing air nozzle 45 will blow up the rice awns accumulated on the negative pressure roller 34, and then suck them out through the air pipe connected to the fixed shaft 33 of the negative pressure roller.

[0092] Preferably, a high-definition camera is also installed on the negative pressure roller 34 to collect images of seeds and the roller in real time. The frequency of image acquisition is 30 frames per second to ensure that the rice awns can be captured in time. The collected images are preprocessed and feature extracted, and then trained using a machine learning model to obtain a rice awn detection model. The rice awn detection model is used to determine whether there are rice awns in the image and output the location and quantity information of the rice awns, so as to adjust the working parameters of the positive pressure hole cleaning device or the negative pressure hole cleaning device through the controller to remove the rice awns. The specific steps are:

[0093] 1. Image acquisition:

[0094] The camera is installed near the negative pressure roller and can clearly capture the process of seeds being adsorbed and rolling. The collected images are stored in RGB format and transmitted to the image processing unit.

[0095] 2. Image preprocessing:

[0096] Grayscale each frame to reduce the amount of calculation. Use median filtering to remove noise in the image to make the image smoother. Use histogram equalization to enhance the image contrast and highlight the characteristics of rice awns.

[0097] 3. Feature extraction:

[0098] Use edge detection algorithms, such as Canny edge detection, to extract the edge information of rice awns in the image. Calculate the shape features of rice awns, such as length, width, area, etc. Use color features to determine the color difference between rice awns and seeds.

[0099] 4. Machine Learning Model Training:

[0100] A large number of seed images containing rice awns are collected and annotated to mark the location and characteristics of the rice awns. The convolutional neural network (CNN) model is trained using this annotated data to enable it to learn the characteristic patterns of rice awns. During the training process, the parameters of the model are continuously adjusted to improve the accuracy of detection.

[0101] 5. Real-time detection:

[0102] During the sowing process, the real-time collected images are input into the trained CNN model. The model quickly determines whether there are rice awns in the image and outputs the location and quantity information of the rice awns. For example, when the model detects the presence of rice awns near a certain air nozzle, it will feed back the information to the control system, which can adjust the working parameters of the positive pressure hole cleaning device or the negative pressure hole cleaning device in time to remove the rice awns.

[0103] The code example is as follows:

[0104] importcv2

[0105] # Image preprocessing

[0106] defpreprocess_image(image):

[0107] #Grayscale

[0108] gray=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)

[0109] #Noise Reduction

[0110] blurred=cv2.GaussianBlur(gray,(5,5),0)

[0111] # Binarization

[0112] thresh=cv2.threshold(blurred,127,255,cv2.THRESH_BINARY_INV)[1]

[0113] returnthresh

[0114] #Feature extraction

[0115] defextract_features(image):

[0116] #Edge Detection

[0117] edges=cv2.Canny(image,100,200)

[0118] #Contour extraction

[0119] contours,_=cv2.findContours(edges,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

[0120] #Calculate contour features, such as area, perimeter, etc.

[0121] features=[cv2.contourArea(cnt)forcntincontours]

[0122] returnfeatures

[0123] #Example usage

[0124] image=cv2.imread('image.jpg')

[0125] preprocessed_image=preprocess_image(image)

[0126] features=extract_features(preprocessed_image)

[0127] print(features)

[0128] Preferably, the device further includes a pressure sensor for measuring the adsorption pressure of the negative pressure roller, an airflow sensor for detecting the airflow intensity of the positive pressure hole cleaning device 42 and the negative pressure hole cleaning device 46, and a rice awn detection sensor for obtaining the output result of the rice awn detection model. Of course, it is not limited to these sensors.

[0129] Among them, the fan, conveyor belt, air pipe, camera and various sensors used in this device are all existing equipment and are not the technical points to be protected by the present invention, so their structure and model are not limited.

[0130] Embodiment 2

[0131] Based on the same concept, the present invention also proposes a control method for a precision seeding device for rice seedlings in pots. In the precision seeding device for hybrid rice seedlings in pots, the main goal of the adaptive control algorithm is to automatically adjust various parameters of the seeding device according to real-time seeding conditions and environmental changes to ensure an efficient and accurate seeding process. Fig. 9 As shown, the specific steps include:

[0132] S00, construct an adaptive algorithm model, the input of which includes parameters collected by a pressure sensor, an airflow sensor, and a rice awn detection sensor and the output result of a rice awn detection model. Specifically, the sowing device is equipped with a variety of sensors for monitoring the flow of seeds, the number of rice awns, the adsorption effect of the negative pressure roller, the working status of the positive pressure hole cleaning device and the negative pressure hole cleaning device, etc.

[0133] In this embodiment, constructing the adaptive algorithm model specifically includes:

[0134] 1. Determine input parameters: Collect various parameters related to the operation of the sowing device, such as seed flow, number of rice awns, adsorption pressure of the negative pressure roller 34, airflow intensity of the positive pressure hole cleaning device 42 and the negative pressure hole cleaning device 46, ambient temperature and humidity, etc. These parameters will be used as inputs of the model.

[0135] 2. Choose the right algorithm: You can use machine learning-based algorithms such as neural networks, reinforcement learning, or fuzzy logic. For example, when using neural networks, you can build a multi-layer perceptron (MLP) or convolutional neural network (CNN) to process the input data.

[0136] 3. Define the model structure: According to the selected algorithm, determine the model's structural parameters such as the number of layers, number of neurons, and connection methods. For example, in a neural network, you can set up multiple hidden layers, each containing a certain number of neurons, and optimize the performance of the model by adjusting these parameters.

[0137] 4. Consider dynamic characteristics: Since the seeding process is a dynamic process, the model should be able to capture the dynamic relationship between parameters. Techniques such as time series analysis or recurrent neural networks (RNN) can be introduced to process time-related data.

[0138] S10, by collecting data under different sowing conditions, including different seed varieties, rice awn numbers, sowing environments and corresponding optimal working parameter combinations, the adaptive algorithm model is trained through the data so that the model can learn the optimal working parameter combinations under different conditions;

[0139] In this embodiment, model training specifically includes:

[0140] 1. Collect training data: In the actual operation of this seeding device, a large amount of historical data is collected, including various parameter values ​​under different seeding conditions and the corresponding optimal working parameter combinations. These data will be used to train the model.

[0141] 2. Data preprocessing: Clean, preprocess and label the collected data. Remove abnormal data and perform data normalization or standardization to ensure data quality and consistency.

[0142] 3. Training model: Use the preprocessed training data to train the model. By adjusting the model parameters, the model can learn the mapping relationship between the input parameters and the optimal working parameter combination. Optimization algorithms such as back propagation algorithms can be used to update the model parameters.

[0143] 4. Verification and adjustment: Use the validation set to verify the trained model and evaluate the performance of the model. According to the verification results, adjust and optimize the model, such as adjusting the model structure, hyperparameters or increasing the amount of training data.

[0144] 5. Continuous learning: In actual applications, new data is continuously collected and added to the training data set to continuously update and improve the model. The model should be able to adapt to changes in the seeding device and new seeding environments.

[0145] S20, during the sowing process, collecting data in real time and inputting it into the trained adaptive algorithm model, and outputting a recommended working parameter combination through the adaptive algorithm model;

[0146] S30. Evaluate multiple working parameter combinations output by the adaptive algorithm model, and measure the pros and cons of each combination according to a preset objective function or performance indicator; for example, the objective function may consider factors such as sowing efficiency, seed utilization rate, and rice awn removal effect.

[0147] S40, according to the evaluation result, selecting the best working parameter combination as the decision output, and this combination will be sent to the controller of the sowing device for adjusting the working parameters of each device;

[0148] S50. As the sowing process proceeds, the sowing effect and parameter changes are monitored in real time. If it is found that the actual effect is inconsistent with the expectation, the adaptive algorithm model will make predictions and decisions again, and dynamically adjust the working parameter combination to ensure that the optimal sowing state is always maintained.

[0149] For example, in a specific scenario, the adaptive algorithm model receives input data that the current seed flow rate is a low value, the number of rice awns is large, the adsorption pressure of the negative pressure roller 34 is a normal value, and the ambient temperature is high. The adaptive algorithm model predicts that the rotation speed of the hole roller 24 should be reduced, the adsorption pressure of the negative pressure roller 34 should be increased, and the blowing force of the positive pressure hole cleaning device 42 and the suction force of the negative pressure hole cleaning device 46 should be greatly enhanced. After evaluation, this combination of working parameters can maximize the sowing efficiency and reduce the blockage of rice awns under the current situation, so it is decided to be the optimal combination and applied to the control of this sowing device.

[0150] For example, when the seed flow sensor detects a change in the seed supply speed, the adaptive control algorithm will respond immediately. If the seed supply speed slows down, the algorithm may increase the adsorption pressure of the negative pressure roller 34 to ensure that enough seeds are adsorbed; at the same time, it may adjust the rotation speed of the hole roller 24 to match the seed supply rhythm to avoid empty holes or overseeding. In addition, when the rice awn detection sensor finds that the number of rice awns increases, the algorithm will automatically increase the blowing force of the positive pressure hole cleaning device 42 and the suction force of the negative pressure hole cleaning device 46 to ensure that the rice awns are cleared in time to prevent the suction nozzle from being blocked. At the same time, it will also intelligently adjust the position and angle of the guide plate 38 according to the distribution of the rice awns, so that the seeds can fall into the hole more accurately and improve the accuracy of sowing.

[0151] In addition, environmental factors such as temperature and humidity are also monitored by sensors. If the ambient temperature rises, causing the fluidity of the seeds to change, the algorithm will adjust the vibration frequency and amplitude of the vibrator accordingly to ensure that the seeds are evenly distributed in the seed box.

[0152] For example, at a certain moment, the sensor detects that the seed supply rate suddenly decreases, the number of rice awns increases, and the ambient temperature rises. The adaptive control algorithm will make the following adjustments:

[0153] The adsorption pressure of the negative pressure roller 34 is increased to ensure that enough seeds are adsorbed.

[0154] Reduce the rotation speed of the hole drum 24 to avoid empty seeding.

[0155] The blowing force of the positive pressure hole cleaning device 42 and the suction force of the negative pressure hole cleaning device 46 are enhanced to remove the rice awns.

[0156] The angle of the guide plate 38 is adjusted to ensure that the seeds fall into the molded holes accurately.

[0157] Increase the vibration frequency and amplitude of the vibrator 37 to ensure uniform distribution of the seeds.

[0158] Through such adaptive control, the sowing device 2 can adapt to various changes in real time, always maintain the best sowing state, and improve sowing efficiency and quality.

[0159] Through the above steps, an effective adaptive control algorithm model can be constructed, which can make decisions on the optimal combination of working parameters based on real-time data and improve the performance and adaptability of the hybrid rice seedling precision seeding device.

[0160] The code example is as follows:

[0161] importnumpyasnp

[0162] #Adaptive control algorithm

[0163] classAdaptiveControl:

[0164] def __init__(self):

[0165] # Initialize model parameters

[0166] self.model_params=np.random.rand(10)

[0167] def update_params(self, data):

[0168] #Update model parameters based on data

[0169] #Here we use a simple random update as an example

[0170] self.model_params+=np.random.rand(10)

[0171] defmake_decision(self,data):

[0172] # Make decisions based on model parameters and data

[0173] #Here we use a simple linear model as an example

[0174] decision=np.dot(data,self.model_params)

[0175] returndecision

[0176] #Example usage

[0177] control = AdaptiveControl()

[0178] data = np.array([1,2,3,4,5])

[0179] control.update_params(data)

[0180] decision=control.make_decision(data)

[0181] print(decision)

[0182] Preferably, the specific operation steps of introducing time series analysis or recurrent neural network (RNN) and other technologies to process time-related data in step S00 are:

[0183] 1. Time Series Analysis:

[0184] 1) Data preparation: Collect relevant parameter data that change over time during the sowing process, such as seed flow, number of rice awns, adsorption pressure of the negative pressure roller, etc., to form time series data.

[0185] 2) Feature Engineering: Extract features from time series data, such as calculating moving averages, variances, trends, etc., to capture the dynamic characteristics of the data.

[0186] 3) Model selection: Select a model suitable for time series analysis, such as the autoregressive moving average model (ARMA), the autoregressive integrated moving average model (ARIMA), etc.

[0187] 4) Model training: Use historical time series data to train the selected model and adjust the model parameters to optimize the model's performance.

[0188] 5) Prediction and decision-making: Use the trained model to predict future parameter changes and make corresponding working parameter adjustment strategies based on the prediction results.

[0189] For example, when using the ARIMA model, the model order (p, d, q) can be determined by analyzing historical data, and then the model can be fitted using training data. When forecasting, the parameter values ​​at future moments are forecasted based on the data before the current moment, thus providing a basis for adjusting the working parameters.

[0190] 2. Recurrent Neural Network (RNN):

[0191] 1) Data preparation: Similarly, collect time series data and organize it into a format suitable for RNN input, usually by splitting the data into sequences of fixed length in chronological order.

[0192] 2) Model construction: Build RNN models, such as using variants such as long short-term memory networks (LSTM) or gated recurrent units (GRU). These models can handle long-term dependencies and are suitable for processing time series data.

[0193] 3) Model training: Use historical time series data to train the RNN and update the model’s weight parameters through the back-propagation algorithm.

[0194] 4) Dynamic Capture: RNN can automatically learn the dynamic relationship between parameters and influence current predictions and decisions by memorizing previous information.

[0195] 5) Prediction and decision-making: During the seeding process, real-time data is input into the trained RNN, and the model outputs predictions of future parameter changes. The adjustment of working parameters is decided based on the prediction results.

[0196] For example, when using the LSTM model, it can remember past information, and when new data is input, it can update the state based on the previous state and current input and make predictions. By continuously training and adjusting the model, it can accurately capture the dynamic relationship between parameters, thereby achieving more precise adaptive control.

[0197] In summary, the introduction of techniques such as time series analysis or RNN can help the model better process time-related data in the seeding process and improve its ability to respond to dynamic changes, thereby achieving a more optimized adaptive control strategy.

[0198] Preferably, a fault diagnosis method for the seeding device can also be introduced, and the specific steps are as follows:

[0199] 1) Data collection:

[0200] Sensors such as pressure sensors, temperature sensors, vibration sensors, etc. are installed at key parts of the sowing device to collect real-time operation data of the device, including pressure changes of the negative pressure roller 34, temperatures of various components, vibration frequency of the device, etc. At the same time, relevant information such as the operation time of the device and the number of sowing times are recorded.

[0201] 2) Data preprocessing:

[0202] Clean and preprocess the collected data to remove abnormal data and noise to ensure the accuracy and reliability of the data. Extract features from the data, such as calculating the mean, variance, peak value, etc. of the pressure, as well as the frequency, amplitude and other characteristics of the vibration.

[0203] 3) Model training:

[0204] Use historical data for model training, and you can use machine learning algorithms, such as support vector machines, decision trees, neural networks, etc. Divide the preprocessed data into training sets and test sets, use the training set to train the model, and adjust the model's parameters to improve the accuracy of the model.

[0205] Use the test set to evaluate the trained model to ensure that the performance of the model meets the requirements.

[0206] 4) Real-time monitoring and prediction:

[0207] During the operation of the equipment, data is collected in real time and input into the trained model. The model makes predictions based on the input data to determine whether the equipment is at risk of failure. If a possible failure is predicted, the system will issue an early warning signal to remind the operator to conduct inspection and maintenance.

[0208] 5) Model update and optimization:

[0209] As the equipment is used and data accumulates, the training data is continuously updated and the model is retrained to improve the accuracy and adaptability of the model. The model is optimized and the parameters and algorithms of the model are adjusted to better adapt to the operating characteristics and failure modes of the equipment.

[0210] For example, when the model detects abnormal pressure fluctuations in the negative pressure roller 34, or the vibration frequency of the equipment exceeds the normal range, it may indicate that the equipment is at risk of failure. The system will issue an early warning in time so that the operator can take appropriate measures to avoid the occurrence of failures, reduce equipment downtime, and improve sowing efficiency.

[0211] Embodiment 3

[0212] This embodiment also provides an electronic device, referring to Fig.10 , comprises a memory 404 and a processor 402, wherein the memory 404 stores a computer program, and the processor 402 is configured to run the computer program to execute the steps in any of the above method embodiments.

[0213] Specifically, the processor 402 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiment of the present invention.

[0214] Among them, the memory 404 may include a large capacity memory 404 for data or instructions. For example, but not limitation, the memory 404 may include a hard disk drive (HDD), a floppy disk drive, a solid state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a tape, or a universal serial bus (USB) drive, or a combination of two or more of these. In appropriate cases, the memory 404 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 404 may be inside or outside the data processing device. In a specific embodiment, the memory 404 is a non-volatile memory. In a specific embodiment, the memory 404 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, PROM for short), an erasable PROM (Erasable Programmable Read-Only Memory, EPROM for short), an electrically erasable PROM (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), an electrically alterable ROM (Electrically Alterable Read-Only Memory, EAROM for short) or a flash memory (FLASH) or a combination of two or more of these. In appropriate circumstances, the RAM may be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM may be a fast page mode dynamic random access memory 404 (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0215] The memory 404 may be used to store or cache various data files required for processing and / or communication, as well as possible computer program instructions executed by the processor 402 .

[0216] The processor 402 reads and executes the computer program instructions stored in the memory 404 to implement any one of the control methods of the rice seedling raising precision seeding device in the above embodiments.

[0217] Optionally, the electronic device may further include a transmission device 406 and an input / output device 408 , wherein the transmission device 406 is connected to the processor 402 , and the input / output device 408 is connected to the processor 402 .

[0218] The transmission device 406 can be used to receive or send data via a network. The specific examples of the above-mentioned network may include a wired or wireless network provided by a communication provider of the electronic device. In one example, the transmission device includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 406 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0219] Input / output devices 408 are used to input or output information.

[0220] Embodiment 4

[0221] This embodiment also provides a readable storage medium, in which a computer program is stored. The computer program includes a program code for controlling a process to execute the process. The process includes a control method for the rice seedling raising precision seeding device according to the first embodiment.

[0222] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0223] In general, various embodiments may be implemented in hardware or dedicated circuits, software, logic, or any combination thereof. Some aspects of the invention may be implemented in hardware, while other aspects may be implemented in firmware or software executed by a controller, microprocessor, or other computing device, but the invention is not limited thereto. Although various aspects of the invention may be shown and described as block diagrams, flow charts, or using some other graphical representation, it should be understood that, as non-limiting examples, the boxes, devices, systems, techniques, or methods described herein may be implemented in hardware, software, firmware, dedicated circuits or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0224] Embodiments of the present invention may be implemented by computer software that is executable by a data processor of a mobile device, such as in a processor entity, or by hardware, or by a combination of software and hardware. Computer software or programs (also referred to as program products) including software routines, applets and / or macros may be stored in any device-readable data storage medium, and they include program instructions for performing specific tasks. A computer program product may include one or more computer executable components configured to perform an embodiment when the program is run. One or more computer executable components may be at least one software code or a portion thereof. In addition, at this point, it should be noted that, for example, Fig. 9 Any block of the logic flow in the program may represent program steps, or interconnected logic circuits, blocks and functions, or a combination of program steps and logic circuits, blocks and functions. The software may be stored on physical media such as memory chips or storage blocks implemented within the processor, magnetic media such as hard disk or floppy disks, and optical media such as, for example, DVDs and their data variants, CDs, etc. Physical media are non-transitory media.

[0225] Those skilled in the art should understand that the technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0226] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present invention. It should be pointed out that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A rice seedling raising precision sowing device, characterized in that: include: Mounting plate; The sowing device comprises a profiled hole roller driving motor, a profiled hole roller transmission gear, a profiled hole roller fixed shaft, a profiled hole roller, a profiled hole inner cylinder, and a sealing block; the profiled hole roller driving motor is fixed on a mounting plate, and is driven by the profiled hole roller transmission gear to realize the rotation of the profiled hole roller; the profiled holes on the outer wall of the profiled hole roller cooperate with the profiled hole inner cylinder to form holes for storing seeds, and during the rotation process, the profiled holes scrape the seeds adsorbed on the negative pressure roller into the profiled holes, and the seeds fall under the roller to realize sowing; the sealing block can block the profiled holes storing seeds to prevent the seeds from falling; The seed suction device comprises a negative pressure roller driving motor, a negative pressure roller transmission gear, a negative pressure roller fixed shaft, a negative pressure roller, a seed blowing device, a seed box, a vibrator, a guide plate and a paddle motor; the negative pressure roller driving motor is fixed on the mounting plate, the negative pressure roller fixed shaft is connected to the mounting plate through a bearing and is hollow inside, and has holes on the surface for gas circulation; the negative pressure roller transmission gear drives the negative pressure roller to rotate, the air nozzle group on the surface of the negative pressure roller corresponds to the position of the mold hole, each air nozzle group contains a plurality of air nozzles, and the seeds are adsorbed by negative pressure, and the seed blowing device can blow off excess seeds and rice awns; the paddle motor and the vibrator in the seed box cooperate to evenly distribute the seeds, and the guide plate allows the seeds on the suction hole to fall into the corresponding mold hole; The hole cleaning device comprises a partition, a positive pressure hole cleaning device, a sealing strip, a positive pressure sealing air nozzle, a positive pressure hole cleaning air nozzle, a negative pressure hole cleaning device, and a negative pressure hole cleaning air nozzle; the partition is fixed below the fixed shaft of the negative pressure roller, the positive pressure hole cleaning device is fixed below the partition, and the sealing strip is located in the groove below the positive pressure hole cleaning device; the positive pressure sealing air nozzle is fixed on the air hole of the partition, and the air pipe connected to the air pump passes through the inside of the fixed shaft of the negative pressure roller and is connected to the air inlet of the positive pressure sealing air nozzle, so that the positive pressure blowing force is generated to make the sealing strip close to the inner wall of the negative pressure roller, isolating the blowing force of the positive pressure hole cleaning device, and is beneficial to the suction effect; the negative pressure hole cleaning device is located at the rear side of the negative pressure roller, and the negative pressure hole cleaning air nozzle is fixed on the air hole of the negative pressure hole cleaning device, and is connected to the fan to generate negative pressure suction; the positive pressure hole cleaning air nozzle is fixedly connected to the air hole of the positive pressure hole cleaning device through the partition, and the air pipe connected to the air pump passes through the inside of the fixed shaft of the negative pressure roller and is connected to the air inlet of the positive pressure hole cleaning air nozzle; The controller is electrically connected to the sowing device, the seed suction device and the hole cleaning device respectively.

2. The rice seedling raising precision sowing device according to claim 1, characterized in that: The negative pressure roller is provided with a camera electrically connected to the controller, which is used to collect the process of seeds being adsorbed and rolling. The collected images are preprocessed and feature extracted, and then trained using a machine learning model to obtain a rice awn detection model. The rice awn detection model is used to determine whether there are rice awns in the image and output the position and quantity information of the rice awns, so as to adjust the working parameters of the positive pressure hole cleaning device or the negative pressure hole cleaning device through the controller to remove the rice awns.

3. The rice seedling raising precision sowing device according to claim 2, characterized in that: It also includes a pressure sensor for measuring the adsorption pressure of the negative pressure roller, an airflow sensor for detecting the airflow intensity of the positive pressure hole cleaning device and the negative pressure hole cleaning device, and a rice awn detection sensor for obtaining the output result of the rice awn detection model.

4. The control method for the rice seedling raising precision seeding device according to claim 3, characterized in that: The following steps are involved: S00, constructing an adaptive algorithm model, the input of which includes parameters collected by a pressure sensor, an airflow sensor, and a rice awn detection sensor and an output result of a rice awn detection model; S10, by collecting data under different sowing conditions, including different seed varieties, rice awn numbers, sowing environments and corresponding optimal working parameter combinations, the adaptive algorithm model is trained through the data so that the model can learn the optimal working parameter combinations under different conditions; S20, during the sowing process, collecting data in real time and inputting it into the trained adaptive algorithm model, and outputting a recommended working parameter combination through the adaptive algorithm model; S30, evaluating multiple working parameter combinations output by the adaptive algorithm model, and measuring the pros and cons of each combination according to a preset objective function or performance index; S40, according to the evaluation result, selecting the best working parameter combination as the decision output, and this combination will be sent to the controller of the sowing device for adjusting the working parameters of each device; S50. As the sowing process proceeds, the sowing effect and parameter changes are monitored in real time. If it is found that the actual effect is inconsistent with the expectation, the adaptive algorithm model will make predictions and decisions again, and dynamically adjust the working parameter combination to ensure that the optimal sowing state is always maintained.

5. The control method of the rice seedling raising precision seeding device according to claim 4, characterized in that: In step S00, a neural network, reinforcement learning or fuzzy logic is used to establish an adaptive algorithm model.

6. The control method of the rice seedling raising precision seeding device according to claim 5, characterized in that: In step S00, time-related data in the seeding process are processed by time series analysis or recurrent neural network.

7. The control method of the rice seedling raising precision seeding device according to claim 6, characterized in that: The specific steps of the time series analysis are: Collect relevant parameter data that change over time during the sowing process, including seed flow, number of rice awns, and suction pressure of the negative pressure roller, to form time series data; Performing feature extraction on the time series data to capture dynamic features of the data; Select an autoregressive moving average model or a differential integrated moving average autoregressive model, train the selected model using historical time series data, and adjust the model parameters to optimize the model's performance; Use the trained model to predict future parameter changes and make corresponding working parameter adjustment strategies based on the prediction results.

8. The control method of the rice seedling raising precision seeding device according to claim 6, characterized in that: The specific steps of the recursive neural network are: Collect relevant parameter data that change over time during the sowing process, including seed flow, number of rice awns, and suction pressure of the negative pressure roller, to form time series data, and organize it into a format suitable for RNN input; Build an RNN model, use historical time series data to train the RNN, and update the model's weight parameters through the back-propagation algorithm; During the seeding process, real-time data is input into the trained RNN, and the model outputs predictions of future parameter changes, and the adjustment of working parameters is decided based on the prediction results.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the control method of the rice seedling raising precision seeding device according to any one of claims 4 to 8.

10. A readable storage medium, characterized in that: A computer program is stored in the readable storage medium, and the computer program includes a program code for controlling a process to execute a process, and the process includes a control method for the rice seedling raising precision seeding device according to any one of claims 4 to 8.

Images