CN-121978947-A - Orchard frost prevention intelligent ventilation regulation and control method and system based on Internet of things perception

CN121978947ACN 121978947 ACN121978947 ACN 121978947ACN-121978947-A

Abstract

The invention discloses an intelligent orchard frost prevention ventilation regulation and control method and system perceived by the Internet of things, which relate to the technical field of agricultural Internet of things and orchard weather regulation and control, and specifically comprise the following steps: the method comprises the steps of deploying a multi-type sensor to realize multidimensional sensing collection of an orchard, evaluating frost level by combining a coupling risk algorithm, generating a regulation strategy by utilizing a dynamic ventilation algorithm, executing fan cooperative control according to terrain temperature partition, feeding back microclimate and climate data optimization algorithm parameters in real time, and forming a closed-loop regulation system; according to the invention, through multidimensional sensing and risk assessment, the frost risk is scientifically judged, the adaptive ventilation strategy is dynamically generated, accurate regulation and control are realized by combining regional cooperative control, the closed loop feedback optimization mechanism is continuously adapted to environmental changes, the frost prevention effectiveness is improved, the resource waste is reduced, the stable growth of fruit trees is ensured, the frost hazard is reduced, the yield and quality of a booster orchard are improved, and efficient and energy-saving frost prevention management is realized.

Inventors

WANG JIANGTAI
SHI CHENGQI
LEI ZHONGRONG
LIU LIJIAO
WANG YAN
YAO LIJUAN
ZHANG XUPENG
ZHAO LIN
WANG HONG
ZHANG JIDONG
WANG HANQI
Dang Jincai
LUO HONGWEI
Ma Qinjing
LUO ZHUO

Assignees

甘肃林业职业技术大学

Dates

Publication Date: 20260505
Application Date: 20260204

Claims (9)

1. An intelligent orchard frost prevention ventilation regulation and control method perceived by the Internet of things is characterized by comprising the following steps: S100, multidimensional sensing and acquisition, namely arranging a three-dimensional sensor array, a fruit tree climate sensor and a multiparameter environment sensor in an orchard, and synchronously acquiring fruit tree climate period information and three-dimensional microclimate data of the orchard; S200, coupling risk assessment, namely preprocessing the acquired data, calculating a frost risk index by adopting a coupling risk index algorithm, and judging the frost risk level; S300, generating a ventilation strategy, namely calculating a ventilation regulation efficiency coefficient by adopting a dynamic ventilation efficiency algorithm by combining frost prevention thresholds and frost risk grades in different climates, and generating the ventilation strategy according to the dynamic ventilation regulation efficiency coefficient; s400, partitioning and cooperative execution, namely partitioning an anti-frost area according to the terrain and temperature distribution of an orchard, and executing a ventilation strategy through partitioning and cooperative control of a rotatable multi-angle fan group; S500, closed loop feedback optimization, namely acquiring three-dimensional microclimate data and fruit tree climate dynamic information in the ventilation regulation and control process in real time, and dynamically optimizing parameters of a coupling risk index algorithm and a dynamic ventilation efficiency algorithm to form closed loop regulation and control.
2. The intelligent ventilation control method for the frost prevention of the orchard perceived by the Internet of things is characterized in that in S100, in multi-dimensional perception acquisition, a three-dimensional stereo sensor array is deployed in a layered mode along the whole area of the orchard to cover the ground, the middle lower part of a crown, the top of the crown and a reverse temperature layer, a fruit tree weather sensor is deployed at branches and trunk parts of a fruit tree, a multi-parameter environment sensor is deployed corresponding to the three-dimensional stereo sensor array and works synchronously with the three-dimensional stereo sensor array and the fruit tree weather sensor, the three-dimensional stereo sensor array acquires temperature data of different heights of the orchard, the fruit tree weather sensor acquires growth characteristic information of flower bud differentiation period, flower period, young fruit period and fruit swelling period of the fruit tree, and the multi-parameter environment sensor acquires dew point temperature, air humidity, wind speed and wind direction and illumination intensity data of the fruit tree.
3. The intelligent ventilation control method for orchard frost prevention perceived by the internet of things according to claim 1, wherein in the step S200, a mathematical expression of a coupling risk index algorithm in the coupling risk assessment is as follows: Wherein, the Is a frost risk index; Is a dynamic weight coefficient of the physical period; the empirical coefficient of the weight of the three-dimensional temperature gradient; Is the temperature stress intensity weight experience coefficient; is a three-dimensional temperature gradient of an orchard; is the reverse temperature strength of the orchard; Is a humidity correction factor.
4. The intelligent ventilation control method for the orchard frost prevention perceived by the Internet of things is characterized in that in the step S200, the specific process of judging the frost risk level is that the frost risk index RI calculated by a coupling risk index algorithm is firstly obtained, then the judgment of the current frost risk level of the orchard is completed according to a preset RI value interval, the specific judgment rule is that when RI is less than 0.3, the low risk level is judged, when RI is less than or equal to 0.3 and less than 0.7, the medium risk level is judged, when RI is more than or equal to 0.7, the high risk level is judged, the RI value interval is a preset interval, the specific RI value calculated by the coupling risk index algorithm is compared with the preset three value intervals in a preset mode based on the value range of each parameter in the coupling risk index algorithm, the three-dimensional microclimate parameter monitoring range of the orchard and the fruit tree weather parameter range, and the current frost risk level is judged to be the risk level corresponding to the preset value interval.
5. The intelligent ventilation control method for orchard frost prevention perceived by the internet of things according to claim 1, wherein in the generation of the ventilation strategy, the frost prevention thresholds of different weather periods are respectively set for flower bud differentiation period, flower period, young fruit period and fruit expansion period of the fruit tree, wherein the frost prevention threshold of the flower bud differentiation period is set to-3+/-0.1 ℃, the frost prevention threshold of the flower period is set to-2+/-0.1 ℃, the frost prevention threshold of the young fruit period is set to-1+/-0.1 ℃, the frost prevention threshold of the fruit expansion period is set to 0+/-0.1 ℃, the frost prevention threshold of each weather period is determined by combining with the growth characteristics of the corresponding growth period of the fruit tree, the frost prevention threshold of each weather period can be determined by combining with the temperature data of the frost occurrence of the same period of the orchard, the frost prevention threshold of each weather period can be performed according to the cold resistance characteristics of different fruit tree varieties, the amplitude of the frost prevention threshold of each weather period is not more than +/-0.2 ℃, and the dynamic coefficient of the weather fine adjustment in the coupling risk index is updated after fine adjustment.
6. The intelligent orchard frost prevention ventilation control method based on the internet of things perception according to claim 1, wherein in the step S300 of generating the ventilation strategy, a mathematical expression of a dynamic ventilation efficiency algorithm is as follows: Wherein, the The efficiency coefficient is regulated and controlled for ventilation; Is the basic efficiency coefficient; is a frost risk index; Covering efficiency for airflow; Is a rotation speed correction coefficient; For zoned cooperative gain.
7. The intelligent ventilation control method for the orchard frost prevention perceived by the Internet of things according to claim 1, wherein in the step S300 of generating the ventilation strategy, the specific content of the ventilation strategy is that a ventilation control efficiency coefficient VE calculated according to a dynamic ventilation efficiency algorithm corresponds to three preset values The value interval generates an adaptation strategy that, When the temperature is more than or equal to 1.2, starting all rotatable multi-angle fans, adjusting the rotational speed to the rated rotational speed, adapting the horizontal rotational angle to the garden topography, setting the operation time length to be 1.2 times of the duration of low temperature, and controlling the operation time length to be less than or equal to 0.6 When the temperature is less than 1.2, starting part of fans, adjusting the rotation speed to be medium, adjusting the angle of the fans according to the requirement, shortening the operation time length, and setting the operation time length to be 0.8 time of the low-temperature duration time; at <0.6, the fan remains on standby, the temperature of the orchard was continuously monitored.
8. The intelligent ventilation control method for the orchard frost prevention perceived by the Internet of things is characterized in that S400 is performed in a partitioning and cooperative mode, the specific process of partitioning frost prevention areas is that when the areas are partitioned, areas with gradient equal to or larger than 15 degrees, altitude higher and average temperature lower than the frost prevention threshold value of the corresponding weather period are partitioned into ascending frost prevention areas according to the slope gradient, altitude higher and average temperature of the areas lower than the frost prevention threshold value of the corresponding weather period of the orchard, areas with gradient equal to or larger than 15 degrees, altitude middle and average temperature of the areas close to the frost prevention threshold value of the corresponding weather period are partitioned into middle slope frost prevention areas, areas with gradient smaller than 5 degrees and altitude lower than the frost prevention threshold value of the corresponding weather period are partitioned into descending frost prevention areas, the area of each frost prevention area is controlled to be 5-10 mu, buffer zones with the thickness of 5-8m are arranged between adjacent areas, fans are not deployed in the buffer zones, the fan airflow mutual interference of the adjacent areas is avoided, unique identification codes are distributed for each frost prevention area, the fan deployment number, installation position and corresponding reference parameters in the marked areas are stored into a fan group.
9. An intelligent orchard frost prevention and ventilation regulation system perceived by the internet of things, which is suitable for the intelligent orchard frost prevention and ventilation regulation method perceived by the internet of things according to any one of claims 1 to 8, and is characterized in that the system comprises: the multidimensional sensing acquisition module consists of a three-dimensional sensor array, a fruit tree climate sensor and a multiparameter environment sensor and synchronously acquires fruit tree climate period information and three-dimensional microclimate data of an orchard; the coupling risk assessment module is used for preprocessing the acquired data, calculating a frost risk index and judging low, medium and high risk grades; the ventilation strategy generation module is used for pre-storing frost prevention thresholds of different climatic periods, calculating ventilation regulation and control efficiency coefficients by combining the risk grades, and generating an adaptive ventilation strategy; The subarea cooperative execution module is used for dividing an anti-frost area according to the terrain, the altitude and the temperature distribution of an orchard and cooperatively executing a ventilation strategy through rotatable multi-angle fan group subareas; and the closed-loop feedback optimization module is used for collecting related data in the regulation and control process in real time, dynamically optimizing algorithm parameters and forming closed-loop regulation and control.

Description

Orchard frost prevention intelligent ventilation regulation and control method and system based on Internet of things perception Technical Field The invention relates to the technical field of agricultural Internet of things and orchard weather regulation and control, in particular to an orchard frost prevention intelligent ventilation regulation and control method and system perceived by the Internet of things. Background In orchard production, frost is a key meteorological disaster for restricting the growth and development of fruit trees and the quality of fruit yield, the stability of agricultural production is obviously threatened, the tolerance of the fruit trees to low-temperature environments in different growth stages is different, the low-temperature frost can cause the problems of damaged flower buds, flower and fruit dropping, fruit malformation and the like, the branches of the fruit trees are dry and dead as a whole in serious cases, huge economic losses are brought to fruit farmers, the traditional frost prevention mode relying on artificial experience is difficult to meet the requirements of modern orchard management along with the increasingly obvious development trend of agriculture, in recent years, the rapid development of Internet of things technology, sensor technology and intelligent algorithm provides powerful support for agricultural environment monitoring and accurate regulation, and an all-dimensional and intelligent orchard frost prevention system is constructed by integrating multidimensional sensing data, constructing a scientific risk assessment model and realizing intelligent execution of regulation measures, so that the important direction of frost disaster prevention problem and stable production are solved, and a technical path is provided for agricultural modern transformation of the orchard. The traditional orchard frost prevention technology has a plurality of obvious limitations in practical application, high-efficiency and accurate frost prevention is difficult to realize, single-point or small-quantity monitoring equipment is adopted in a data acquisition link, the monitoring range is limited, the dimension is single, the spatial distribution difference of three-dimensional microclimate of an orchard cannot be comprehensively captured, synchronous perception of growth characteristics of a fruit tree in a weather period is lacked, the acquired data integrity and accuracy are insufficient, comprehensive and reliable support cannot be provided for risk assessment, in the aspect of risk assessment, the traditional method is used for judging frost risk only according to a single temperature index, the coupling influence of various key factors such as humidity, reverse temperature intensity, fruit tree growth stage and the like is ignored, the situation of misjudgment or missed judgment is easy to appear in the risk grade judgment, the timeliness and effectiveness of protective measures are influenced, the traditional ventilation frost prevention is mainly realized in a rough mode of a universal unified starting fan in a regulation and control execution link, natural condition differences such as the shape, the air flow coverage is uneven, partial area is not enough, and partial area has waste is not provided, in addition, the traditional orchard dynamic feedback is difficult to adjust and control environment parameters, and the dynamic fluctuation prevention effect cannot be further reduced, and the real-time stability and stability of the dynamic fluctuation prevention mechanism are difficult to be adapted. Disclosure of Invention The invention aims to make up the defects of the prior art, and provides an intelligent ventilation regulation and control method and system for the frost prevention of an orchard perceived by the Internet of things, which are used for synchronously collecting fruit tree climate and microclimate data by deploying a three-dimensional sensor array, evaluating frost risk by adopting a coupling risk index algorithm, generating a dynamic ventilation strategy by combining a frost prevention threshold value in a weather period and executing the dynamic ventilation strategy by rotatable multi-angle fan group partitions. The invention provides the technical scheme for solving the technical problems, wherein the method for intelligent ventilation control of the frost prevention of the orchard perceived by the Internet of things comprises the following steps: S100, multidimensional sensing and acquisition, namely arranging a three-dimensional sensor array, a fruit tree climate sensor and a multiparameter environment sensor in an orchard, and synchronously acquiring fruit tree climate period information and three-dimensional microclimate data of the orchard; S200, coupling risk assessment, namely preprocessing the acquired data, calculating a frost risk index by adopting a coupling risk index algorithm, and judging the frost risk level; S300, generating a