Farming machinery holographic sensing intelligent module based on multi-source fusion

Abstract

The invention, which relates to the technical field of agricultural mechanization, provides a multi-source-fusion-based holographic sensing intelligent module for farming machinery, comprising a plurality of independent sensor units. And the data processing unit is used for receiving and storing various data acquired by the plurality of independent sensor units, the data processing unit adopts a multi-source data fusion algorithm based on a traditional rule, and the various data comprise soil humidity, meteorological conditions, crop growth states, mechanical motion states and energy efficiency data in the cultivation process. According to the multi-source fusion-based holographic sensing intelligent module for the farming machine, the flexibility and response speed of farming operation are remarkably improved, the operation quality is effectively improved, energy consumption and resource waste are reduced, and agricultural production is further promoted to develop towards the efficient and sustainable direction.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of agricultural mechanization, in particular to a holographic perception intelligent module for cultivation machinery based on multi-source fusion. BACKGROUND

[0002] At present, the application of agricultural mechanization is increasingly widespread, and the intelligentization and automation level is continuously improved in cultivation operation. The intelligent system of cultivation machinery usually relies on multiple sensors to monitor the environment and operation state, such as soil humidity, weather conditions, crop growth conditions, etc. The sensors provide real-time data support for agricultural machinery, helping to improve the accuracy and efficiency of operation. Traditional cultivation machinery monitors environmental changes through certain sensors, but lacks the ability to comprehensively integrate different data sources, resulting in inefficient data fusion and processing. Existing technologies focus on the collection and processing of a single data source, ignoring the collaborative work between multi-source data, lacking efficient data fusion strategies, affecting the precision and adaptability of operation.

[0003] The limitation of data fusion algorithm is a obvious defect in the process of multi-source data fusion of existing cultivation machinery intelligent module. Traditional algorithms mostly rely on fixed rules and cannot dynamically adapt to changing cultivation environments. The traditional algorithm leads to insufficient reliability and accuracy of the fusion result, and in the high dynamic and variable agricultural operation environment, the response speed and accuracy of the system are greatly reduced. Some systems try to make up for this defect by increasing the number of sensors, but lack effective dynamic adjustment mechanism, cannot meet the demand of real-time data accurate fusion under complex farmland conditions, resulting in low operation efficiency and resource waste. SUMMARY

[0004] In view of the shortcomings of the prior art, the present application provides a holographic perception intelligent module for cultivation machinery based on multi-source fusion, which solves the problem of how to realize holographic perception and accurate control of cultivation machinery through intelligent decision-making technology of multi-source data fusion.

[0005] To achieve the above purpose, the present application realizes the following technical scheme: a holographic perception intelligent module for cultivation machinery based on multi-source fusion, comprising: a plurality of independent sensor units.

[0006] A data processing unit is used to receive and store a plurality of data collected by a plurality of independent sensor units, the data processing unit adopts a multi-source data fusion algorithm based on traditional rules to realize the spatio-temporal synchronous fusion of data, generate highly reliable holographic perception data of the cultivation process, and the plurality of data includes soil humidity, weather conditions, crop growth state, mechanical motion state and energy efficiency data in the cultivation process.

[0007] An intelligent decision module is connected with the data processing unit, the intelligent decision module receives the energy efficiency data to generate control instructions, and the intelligent decision module automatically sends control instructions to an execution mechanism of the tillage machinery based on the multiple data to ensure the accuracy and efficiency of the tillage operation.

[0008] An execution mechanism is used for executing the decision of the intelligent decision module, the control instructions are automatically sent to the execution mechanism, and the execution mechanism is used for executing the decision of the intelligent decision module.

[0009] An execution control unit is connected between the intelligent decision module and the execution mechanism, the execution control unit dynamically adjusts according to real-time feedback in the tillage process to ensure the tillage quality and the work efficiency.

[0010] A data output and monitoring module is connected with the data processing unit and the intelligent decision module, the data output and monitoring module includes a built-in display interface and a storage module, the data output and monitoring module is connected with the execution control unit through a wireless communication interface to realize whole-process monitoring and optimization of the tillage process and ensure the timeliness and accuracy of the data.

[0011] Preferably, the sensor unit includes a soil humidity sensor, a weather sensor, a crop growth monitoring sensor and a mechanical motion state sensor, the sensor unit is intelligently distributed through an integrated circuit, and the intelligent distribution is collected according to the energy efficiency data and is transmitted to the data processing unit in real time.

[0012] Preferably, the multi-source data fusion algorithm dynamically adjusts the data fusion strategy according to the change of the tillage environment, the dynamic adjustment includes real-time synchronization and fusion of the data processing unit to ensure the optimality of the fusion result.

[0013] Preferably, the multi-source data fusion algorithm is fused through the following formula:

[0014] Among them, represents the time of the fusion data, which represents the comprehensive perception data of the environment and the mechanical state in the tillage process, , , , , respectively represent the perception data of the soil humidity, the weather sensor, the crop growth monitoring and the mechanical motion state from the sensor at the time , , , , , is a weight coefficient of each sensor data, representing the relative importance of different data sources, and satisfying the normalization condition:

[0015] wherein the parameter The weight coefficient of each sensor data is dynamically adjusted according to the reliability and required accuracy.

[0016] Preferably, the control instructions include tillage depth control instructions, seeding density control instructions, irrigation amount control instructions, and fertilization amount control instructions.

[0017] Preferably, the data output and monitoring module receives the energy efficiency data through a wireless communication interface, the wireless communication interface supports Wi-Fi communication mode, and the working frequency band of the wireless communication interface is 2.4 GHz and 5 GHz.

[0018] Preferably, the execution control unit adopts a proportional-integral-derivative control algorithm, which dynamically adjusts the control instructions based on real-time feedback data, and adjusts the proportional-integral-derivative control algorithm through the following steps: S1. Proportional adjustment: according to the feedback data, proportional adjustment is performed.

[0019] S2. Integral adjustment: according to the accumulation of historical errors, the control instructions are adjusted.

[0020] S3. Differential adjustment: according to the rate of error change, the future error change is predicted and the control instructions are adjusted.

[0021] Preferably, the data output and monitoring module displays holographic data in the tillage process in real time through a built-in display interface and a storage module, the built-in display interface supports graphical interface display, real-time curve chart and data table display mode, which is convenient for operators to obtain the tillage state in real time, and the storage module stores the holographic data in local storage such as SD card and solid state disk, which is used for historical data query and analysis.

[0022] The present application provides a kind of based on multi-source fusion's cultivation machinery holographic perception intelligent module.There is following beneficial effect: Through the integration of multiple sensor units and the cooperation of data processing units, soil humidity, weather conditions, crop growth state, mechanical motion state and other data are collected and fused in real time, to provide comprehensive intelligent sensing support for the tillage process.The system can automatically generate accurate control instructions to ensure the efficiency and accuracy of tillage operation, significantly improving the automation and intelligent level of agricultural machinery operation.

[0023] Through the dynamically adjusted data fusion algorithm, it is ensured that the system can adapt to changes and optimize decisions in real time under different farming environments. This technology significantly improves the flexibility and response speed of the cultivation operation, effectively improves the operation quality, reduces energy consumption and resource waste, and further promotes the development of agricultural production towards high efficiency and sustainability. BRIEF DESCRIPTION OF DRAWINGS

[0024] Fig. 1 is a flowchart of the implementation of the application; Fig. 2 is a schematic diagram of the sensor unit structure of the implementation of the application; Fig. 3 is a schematic diagram of the execution control unit of the implementation of the application. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only a part of the embodiments of the application, not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0026] Embodiment one As shown in Figs. 1-3 , the embodiment of the application provides a multi-source fusion-based cultivation machinery holographic perception intelligent module, which comprises a plurality of independent sensor units, including soil humidity sensors, weather sensors, crop growth monitoring sensors and mechanical motion state sensors. The sensor units are intelligently distributed through integrated circuits. The intelligent distribution is based on energy efficiency data collection and real-time transmission to the data processing unit.

[0027] The data processing unit is used for receiving and storing a plurality of data collected by the plurality of independent sensor units. The data processing unit adopts a multi-source data fusion algorithm based on traditional rules. The plurality of data includes soil humidity, weather conditions, crop growth state, mechanical motion state and energy efficiency data in the cultivation process. The multi-source data fusion algorithm dynamically adjusts the data fusion strategy according to the change of the farming environment. The dynamic adjustment includes real-time synchronization and fusion by the data processing unit. The multi-source data fusion algorithm is fused by the following formula:

[0028] wherein, represents the fusion data at time , represents the comprehensive perception data of the environmental and mechanical state in the cultivation process, , , , , respectively represent the soil moisture, weather sensor, crop growth monitoring and mechanical motion state perception data from sensors at time t, , , , , is the weight coefficient of each sensor data, representing the relative importance of different data sources, and satisfying the normalization condition:

[0029] wherein the parameter is dynamically adjusted according to the reliability of each sensor data weight coefficient and the required accuracy.

[0030] An intelligent decision module is connected to the data processing unit, and the intelligent decision module receives the energy efficiency data to generate control instructions.

[0031] An actuator is used to execute the decision of the intelligent decision module, and the control instructions are automatically sent to the actuator to execute the decision of the intelligent decision module. The control instructions include tillage depth control instructions, seeding density control instructions, irrigation amount control instructions and fertilization amount control instructions.

[0032] An execution control unit is connected between the intelligent decision module and the actuator, and the execution control unit dynamically adjusts according to the real-time feedback of the control instructions in the tillage process. The execution control unit adopts a proportional-integral-derivative control algorithm, which dynamically adjusts the control instructions based on real-time feedback data. The proportional-integral-derivative control algorithm adjusts by the following steps: S1. Proportional adjustment: according to the feedback data, proportional adjustment is performed.

[0033] S2. Integral adjustment: according to the accumulation of historical errors, the control instructions are adjusted.

[0034] S3. Differential adjustment: according to the rate of error change, the future error change is predicted and the control instructions are adjusted.

[0035] The data output and monitoring module is connected with the data processing unit and the intelligent decision-making module. The data output and monitoring module includes a built-in display interface and a storage module. The data output and monitoring module is connected with the execution control unit through a wireless communication interface. The data output and monitoring module receives energy efficiency data through the wireless communication interface. The wireless communication interface supports Wi-Fi communication mode. The working frequency band of the wireless communication interface is 2.4 GHz and 5 GHz. The data output and monitoring module displays holographic data in the plowing process in real time through the built-in display interface and the storage module. The built-in display interface supports graphical interface display, real-time curve graph and data table display mode. The storage module stores the holographic data in a local storage such as an SD card and a solid state disk.

[0036] Embodiment two Unlike embodiment one, this embodiment describes the actuator, the execution control unit and the proportional-integral-derivative control algorithm.

[0037] 1. The role of the actuator and control instructions The actuator is the actual operating part of the mechanical system. It receives control instructions sent by the intelligent decision-making module and adjusts the behavior of the machine according to the instructions. For example: Plowing depth control instruction: adjust the plowing depth according to the soil type and plowing needs.

[0038] Seeding density control instruction: adjust the seeding row spacing or number according to the needs of the planted crops.

[0039] Irrigation amount control instruction: adjust the water amount of the irrigation system according to the soil moisture and weather data.

[0040] Fertilizer amount control instruction: accurately control the amount of fertilizer according to the growth status of the crops and the nutrient needs of the soil.

[0041] The instructions are generated by environmental data obtained through sensor monitoring, ensuring fine management during plowing.

[0042] 2. The role of the execution control unit The role of the execution control unit is to adjust the execution instructions according to real-time feedback in actual operation, so that the mechanical system can flexibly respond to dynamic changes in environmental conditions. If the plowing depth is too shallow, the control unit will increase the depth, and vice versa.

[0043] Specific implementation: the execution control unit adjusts the control instructions through real-time feedback to ensure that the system is always in the best working state.

[0044] 3. Specific application of PID control algorithm The PID control algorithm dynamically adjusts the control instructions according to real-time feedback data, which consists of the following three steps: Proportional Control: Based on the current feedback error, proportional control adjusts directly according to the size of the error. If the plowing depth is shallow, the proportional controller will increase the depth, and the adjustment is directly proportional to the error.

[0045] Integral Control: Integral control mainly acts on long-term cumulative errors. It accumulates historical errors to adjust the control command, preventing long-term drift of the system.

[0046] Derivative Control: Derivative control focuses on the rate of error change. For example, if the plowing depth changes too quickly, causing soil compaction or damage to crop roots, derivative control predicts the future trend of error change and adjusts in advance to avoid excessive rapid response.

[0047] Through the comprehensive application of these three control methods, the execution control unit can finely adjust each operation parameter, making the plowing process not only accurate but also efficient.

[0048] Example Three Unlike Example One, this example describes the functions and structure of the data output and monitoring module.

[0049] 1. Role and working principle of wireless communication interface Implementation: The data output and monitoring module is connected to the execution control unit through a wireless communication interface. The role of the wireless communication interface is to ensure that the system can receive energy efficiency data from the execution mechanism in real time during the plowing process. The wireless communication interface supports two working frequency bands, 2.4GHz and 5GHz, and can adapt to different network environments to ensure signal stability and data transmission efficiency.

[0050] 2.4GHz frequency band: suitable for long-distance transmission, suitable for large-scale agricultural machinery operation.

[0051] 5GHz frequency band: suitable for short-distance transmission, can provide faster transmission speed in environments with higher data demand.

[0052] Specific application: In the case of large-area plowing, the 2.4GHz frequency band provides wide coverage, and in smaller fields or operations requiring higher real-time performance, the 5GHz frequency band can provide faster data transmission.

[0053] 2. Functions of built-in display interface Implementation: The built-in display interface is responsible for presenting holographic data during the plowing process in a visual manner to the operator. The built-in display interface displays various parameters of the plowing process in real time through screens, touch displays, etc. The graphical interface can help operators intuitively understand data and make timely adjustments.

[0054] Function specification: Graphical interface display: Display system status, job progress, and various monitoring data.

[0055] Real-time curve display: Show the trend of key data such as soil moisture and crop growth status, so that operators can grasp the dynamic changes of the operation at any time.

[0056] Data table display: Accurately display each item of data at each moment in the form of a table, making it easy for operators to analyze and record in detail.

[0057] For example: When irrigating, the display screen will display the current soil moisture, target moisture, and the amount of water the system has irrigated in real time, helping the operator to determine whether to increase or decrease the irrigation amount.

[0058] 3. Role of the storage module Implementation: The storage module is responsible for saving holographic data in real time during the cultivation process in local storage devices such as SD cards or solid state drives. The storage module provides historical data for later data analysis, debugging, and data support for abnormal situations that occur during the operation process. For example, when a device failure or anomaly occurs, the historical data in the storage module will help technicians diagnose and analyze.

[0059] Function specification: Real-time storage: Whenever environmental data, mechanical state, or energy efficiency data during the cultivation process is updated, the storage module will update the data in real time. The data is time-stamped for subsequent queries.

[0060] Data backup: Once the operation is complete, the stored data is exported through USB, SD card, etc. for detailed analysis and report production.

[0061] Storage format: The stored data is stored in a standard file format for subsequent viewing and processing.

[0062] For example, crops may need to adjust the amount of fertilizer or irrigation at a certain growth stage, and the historical data saved by the storage module can help analyze the relationship between different fertilizer amounts and crop growth, thereby optimizing future operation decisions.

[0063] 4. Integration of data output and monitoring functions Implementation: The data output and monitoring module displays data in real time and communicates with the execution control unit through a wireless communication interface. For example, when the operation of the execution mechanism deviates or feedback is abnormal, the data output module sends an alarm or adjustment instruction to the execution control unit through the wireless communication interface, ensuring continuous optimization during the cultivation process.

[0064] Real-time data monitoring: the operator can view real-time data at any time point through the display interface, ensuring accurate control of the working process.

[0065] Adjustment instruction sending: based on the received real-time monitoring data, the system sends automatic adjustment instructions, such as adjusting irrigation or fertilization amount, to ensure the accuracy of the work.

[0066] Suppose that during the working process, it is monitored that the soil humidity is insufficient, the data output and monitoring module can timely display the low humidity alarm and automatically adjust the irrigation amount instruction through the wireless interface, and the actuator immediately starts to adjust the irrigation.

[0067] Through the effective combination of the built-in display interface, storage module and wireless communication interface, the data output and monitoring module can provide the operator with real-time data display, save historical data as a basis for later analysis, and automatically exchange data and adjust instructions with the execution control unit when an abnormality occurs, thereby realizing an intelligent and efficient cultivation process.

[0068] Although embodiments of the present application have been shown and described, it is to be understood that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A multi-source fusion-based intelligent module for holographic perception of cultivation machinery, characterized in that, The application relates to a data processing system for agricultural cultivation, which comprises the following parts: a plurality of independent sensor units; a data processing unit for receiving and storing a plurality of data collected by the plurality of independent sensor units, wherein the data processing unit adopts a multi-source data fusion algorithm based on traditional rules, and the data includes soil humidity, weather conditions, crop growth status, mechanical motion state and energy efficiency data in the cultivation process; an intelligent decision module connected with the data processing unit, wherein the intelligent decision module receives the energy efficiency data to generate control instructions; an execution mechanism for executing the decision of the intelligent decision module, wherein the control instructions are automatically sent to the execution mechanism to execute the decision of the intelligent decision module; an execution control unit connected between the intelligent decision module and the execution mechanism, wherein the execution control unit dynamically adjusts according to real-time feedback in the cultivation process; a data output and monitoring module connected with the data processing unit and the intelligent decision module, wherein the data output and monitoring module comprises a built-in display interface and a storage module, and the data output and monitoring module is connected with the execution control unit through a wireless communication interface. 2.The multi-source fusion-based holographic perception intelligent module for tillage machinery according to claim 1, characterized in that: The sensor unit comprises a soil humidity sensor, a weather sensor, a crop growth monitoring sensor and a mechanical motion state sensor, and the sensor unit is intelligently distributed through an integrated circuit, and the intelligent distribution is collected according to the energy efficiency data and is transmitted to the data processing unit in real time. 3.The multi-source fusion-based holographic perception intelligent module for tillage machinery according to claim 1, characterized in that: The multi-source data fusion algorithm dynamically adjusts the data fusion strategy according to the change of the cultivation environment, and the dynamic adjustment comprises real-time synchronization and fusion of the data processing unit.

4. The multi-source fusion-based holographic perception intelligent module for cultivation machinery according to claim 3, characterized in that: The multi-source data fusion algorithm is fused through the following formula: wherein, denotes time the fusion data at time , , , , denote the perception data from the sensors of soil moisture, weather sensors, crop growth monitoring and machinery motion state at time , , , , , are the sensor data weight coefficients and satisfy the normalization condition: wherein the parameters The weight coefficients of the data of each sensor are dynamically adjusted according to their reliability and the required accuracy. 5.The multi-source fusion-based intelligent module for holographic perception of tillage machinery according to claim 1, characterized in that: The control instructions include a cultivation depth control instruction, a seeding density control instruction, an irrigation amount control instruction and a fertilization amount control instruction. 6.The multi-source fusion-based intelligent module for holographic perception of tillage machinery according to claim 1, characterized in that: The data output and monitoring module receives the energy efficiency data through a wireless communication interface, the wireless communication interface supports a Wi-Fi communication mode, and the working frequency band of the wireless communication interface is 2.4 GHz and 5 GHz. 7.The multi-source fusion-based intelligent module for holographic perception of tillage machinery according to claim 1, characterized in that: The execution control unit adopts a proportional-integral-derivative control algorithm, the proportional-integral-derivative control algorithm dynamically adjusts the control instructions based on real-time feedback data, and the proportional-integral-derivative control algorithm is adjusted through the following steps: S1. proportional adjustment: proportional adjustment is performed according to the feedback data; S2. integral adjustment: the control instructions are adjusted according to the accumulation of historical errors; S3. differential adjustment: future error changes are predicted according to the rate of error changes, and the control instructions are adjusted. 8.The multi-source fusion-based intelligent module for holographic perception of tillage machinery according to claim 1, characterized in that: The data output and monitoring module displays holographic data in the cultivation process in real time through the built-in display interface and the storage module, the built-in display interface supports graphical interface display, real-time curve diagram and data table display mode, and the storage module stores the holographic data in a local storage such as an SD card and a solid state disk.

Images