Hilly irrigated area drip irrigation control method and system based on internet of things

Abstract

This invention relates to the field of crop drip irrigation technology and provides a method and system for drip irrigation control in hilly irrigation areas based on the Internet of Things (IoT). The method includes the following steps: based on real-time environmental data, crop type, and growth stage of the target irrigation zone, determining the crop water requirement and irrigation mode for the target irrigation zone, and generating irrigation decision instructions; responding to the irrigation decision instructions, retrieving the digital elevation model and pipeline network topology of the irrigation area, performing hydraulic calculations, and determining the target pressure setpoint of the pressure regulating valve at the inlet of the target irrigation zone; remotely controlling a PLC controller to drive the pressure regulating valve to stabilize the pressure at the downstream end of the valve at the target pressure setpoint; analyzing pressure gradient changes, pressure change rate, and the timing logic of associated valve operation instructions to detect pipeline leakage. This invention can provide appropriate water according to the actual needs of the crop, satisfying the crop's growth requirements while avoiding water waste and improving resource utilization efficiency.

Description

Technical Field

[0001] This invention relates to the field of crop drip irrigation technology, specifically to a drip irrigation control method and system for hilly irrigation areas based on the Internet of Things. Background Technology

[0002] With the rapid development of IoT technology, its application in agriculture is becoming increasingly widespread, providing new ideas and methods for solving irrigation problems in hilly irrigation areas. Drip irrigation, as a highly efficient water-saving irrigation method, has broad application prospects in hilly irrigation areas. However, how to achieve precise control of drip irrigation systems, ensure their stable operation, and promptly identify and address potential problems has become a key issue that urgently needs to be addressed in the development of drip irrigation technology in hilly irrigation areas. Most existing drip irrigation control methods in hilly irrigation areas lack precise consideration of the actual water requirements of crops and cannot dynamically adjust irrigation strategies according to real-time environment, crop type, and growth stage. Furthermore, they have shortcomings in hydraulic calculation, pressure regulation, pipeline monitoring, and anti-clogging, making it difficult to ensure the efficient and stable operation of drip irrigation systems. Therefore, there is a need to provide an IoT-based drip irrigation control method and system for hilly irrigation areas, aiming to solve the above problems. Summary of the Invention

[0003] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a drip irrigation control method and system for hilly irrigation areas based on the Internet of Things, so as to solve the problems existing in the above-mentioned background technology.

[0004] This invention is implemented as follows: a drip irrigation control method for hilly irrigation areas based on the Internet of Things, the method comprising the following steps:

[0005] Based on real-time environmental data, crop types, and growth stages of the target irrigation zone, the crop water requirements and irrigation patterns of the target irrigation zone are determined, and irrigation decision instructions are generated.

[0006] In response to the irrigation decision command, the digital elevation model and pipeline network topology of the irrigation area are retrieved, hydraulic calculations are performed, and the target pressure setting value of the pressure regulating valve at the inlet of the target irrigation zone is determined.

[0007] The remote control PLC controller drives the pressure regulating valve to stabilize the pressure at the back end of the pressure regulating valve at the target pressure setting value.

[0008] Real-time acquisition of pressure data from each pipeline, analysis of pressure gradient changes, pressure change rate, and timing logic of associated valve operation commands to detect pipeline leakage;

[0009] Monitor the pressure and flow data at the end of each pipeline, and implement anti-clogging control based on the pressure-to-flow ratio.

[0010] As a further aspect of the present invention, the step of determining the crop water requirement and irrigation pattern of the target irrigation zone specifically includes:

[0011] Based on the real-time environmental data, the crop evapotranspiration ET is calculated; the real-time environmental data includes soil volumetric water content, atmospheric temperature, atmospheric relative humidity, and wind speed.

[0012] Retrieve the crop coefficient Kc corresponding to the crop type and growth stage, and obtain the crop water requirement based on the crop coefficient and crop evapotranspiration. Crop water requirement = Kc × ET;

[0013] The irrigation pattern should be determined based on the crop type, growth stage, and water requirements of the crop.

[0014] A humidity threshold is determined based on the crop's water requirements. Soil moisture is compared with the humidity threshold. When the soil moisture is lower than the humidity threshold, an irrigation decision instruction is generated.

[0015] As a further aspect of the present invention, the step of performing hydraulic calculations to determine the target pressure setting value of the pressure regulating valve at the inlet of the target irrigation zone specifically includes:

[0016] The minimum operating pressure Pmin is calculated based on the emitter at the hydraulically most unfavorable point within the target irrigation zone.

[0017] The static pressure head ρgΔH generated by the elevation difference between the pressure regulating valve and the water emitter is calculated based on the digital elevation model, where ρ is the density of water, g is the gravitational acceleration, and ΔH is the elevation difference between the pressure regulating valve and the water emitter at the most unfavorable point.

[0018] Calculate the head loss along the pipe from the pressure regulating valve to the water emitter, hf, and the local head loss, hj, based on the pipe material, pipe diameter, length, and flow rate.

[0019] The target pressure setting value of the pressure regulating valve is calculated by using the target pressure setting value = Pmin + ρgΔH + ρghf + ρghj.

[0020] As a further aspect of the present invention, the step of calculating the minimum operating pressure required based on the emitter at the hydraulically most unfavorable point within the target irrigation zone specifically includes:

[0021] Determine the elevation information of the emitters within the target irrigation zone, and determine the pipeline path length from the emitters to the pressure regulating valve;

[0022] Based on elevation information and pipeline path length, a weighted scoring method is used to determine the irrigator at the most unfavorable point;

[0023] Determine the rated working pressure and safety margin of the water emitter at the most unfavorable point to obtain the minimum working pressure.

[0024] As a further aspect of the present invention, the step of analyzing pressure gradient changes, pressure change rates, and the timing logic of associated valve operation commands to perform pipeline leakage detection specifically includes:

[0025] The pressure difference ΔP of each pipe segment is calculated by using data from pressure sensors deployed at the beginning and end of the pipeline; when ΔP continuously exceeds the first threshold for a first preset time, the pressure is determined to be abnormal, and the corresponding pipe segment is marked as a primary leakage segment.

[0026] Calculate the rate of change of upstream pressure in the primary leakage section within the most recent short time window; if the absolute value of the rate of change of pressure is less than the water hammer characteristic threshold, the pressure is determined to be slowly decreasing, and the pipe section is upgraded to an intermediate leakage section.

[0027] Check whether the valves of the intermediate leakage section and adjacent pipe sections have received operation instructions within a second preset time period before the start time of the pressure anomaly. If no valve operation instructions are found, the pipe section is upgraded to an advanced leakage section.

[0028] A confirmation window is initiated. If the ΔP of the pipe segment remains higher than the second threshold during the confirmation window, it is determined to be a real leakage segment.

[0029] As a further aspect of the present invention, the step of performing anti-clogging control based on the pressure-to-flow ratio specifically includes:

[0030] When the pressure-to-flow ratio continuously deviates from the normal range and the pressure rises abnormally, it is determined that the corresponding pipeline is at risk of blockage.

[0031] The pulse flushing mode is activated, and the solenoid valve at the inlet of the pipeline is controlled by the PLC to perform a rapid opening and closing operation, generating a pressure pulse wave.

[0032] Another objective of this invention is to provide an Internet of Things-based drip irrigation control system for hilly irrigation areas, the system comprising:

[0033] The irrigation decision generation module is used to determine the crop water requirement and irrigation mode of the target irrigation zone based on real-time environmental data, crop type and growth stage, and generate irrigation decision instructions.

[0034] The target pressure setting module is used to respond to the irrigation decision command, retrieve the digital elevation model and pipeline network topology of the irrigation area, perform hydraulic calculations, and determine the target pressure setting value of the pressure regulating valve at the inlet of the target irrigation zone.

[0035] The pressure remote control module is used to remotely control the PLC controller to drive the pressure regulating valve to stabilize the pressure at the downstream end of the pressure regulating valve at the target pressure set value.

[0036] The pipeline leakage detection module is used to collect pressure data of each pipeline in real time, analyze pressure gradient changes, pressure change rate and the timing logic of related valve operation commands, and perform pipeline leakage detection.

[0037] The pipeline anti-clogging control module is used to monitor the pressure and flow data at the end of each pipeline and to perform anti-clogging control based on the pressure-to-flow ratio.

[0038] As a further embodiment of the present invention, the irrigation decision generation module includes:

[0039] The evapotranspiration calculation unit is used to calculate the crop evapotranspiration ET based on the real-time environmental data; the real-time environmental data includes soil volumetric water content, atmospheric temperature, atmospheric relative humidity, and wind speed.

[0040] The water requirement calculation unit is used to retrieve the crop coefficient Kc corresponding to the crop type and growth stage, and to obtain the crop water requirement based on the crop coefficient and crop evapotranspiration. Crop water requirement = Kc × ET;

[0041] The irrigation pattern determination unit is used to determine the irrigation pattern based on crop type, growth stage, and crop water requirement.

[0042] The irrigation decision generation unit is used to determine the humidity threshold based on the crop's water requirements, compare the soil moisture with the humidity threshold, and generate an irrigation decision instruction when the soil moisture is lower than the humidity threshold.

[0043] As a further embodiment of the present invention, the target pressure setting module includes:

[0044] Minimum working pressure unit, used to calculate the minimum working pressure Pmin required based on the emitter at the hydraulically most unfavorable point within the target irrigation zone;

[0045] The static pressure head calculation unit is used to calculate the static pressure head ρgΔH generated by the elevation difference between the pressure regulating valve and the irrigator based on the digital elevation model, where ρ is the density of water, g is the gravitational acceleration, and ΔH is the elevation difference between the pressure regulating valve and the most unfavorable irrigator.

[0046] The head loss determination unit is used to calculate the friction head loss hf and local head loss hj from the pressure regulating valve to the water emitter based on the pipe material, pipe diameter, length and flow rate.

[0047] The target pressure calculation unit is used to calculate the target pressure setting value of the pressure regulating valve by using the target pressure setting value = Pmin + ρgΔH + ρghf + ρghj.

[0048] As a further embodiment of the present invention, the pipeline leakage detection module includes:

[0049] The primary leakage detection unit is used to calculate the pressure difference ΔP of each pipe segment using data from pressure sensors deployed at the beginning and end of the pipeline. When ΔP continuously exceeds the first threshold for a first preset duration, the pressure is determined to be abnormal, and the corresponding pipe segment is marked as a primary leakage segment.

[0050] The intermediate leakage determination unit is used to calculate the pressure change rate of the upstream pressure of the primary leakage section within the most recent short time window; if the absolute value of the pressure change rate is less than the water hammer characteristic threshold, the pressure is determined to be slowly decreasing, and the pipe section is upgraded to an intermediate leakage section.

[0051] The advanced leakage section determination unit is used to query whether the valves of the intermediate leakage section and adjacent pipe sections have received operation instructions within a second preset time period before the start time of the pressure anomaly. If no valve operation instructions are found, the pipe section is upgraded to an advanced leakage section.

[0052] The actual leakage section determination unit initiates a confirmation window period. If the ΔP of the pipe section remains higher than the second threshold during the confirmation window period, it is determined to be an actual leakage section.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] This invention determines crop water requirements and irrigation patterns based on real-time environmental data, crop type, and growth stage of the target irrigation zone, generating irrigation decision instructions. It can provide appropriate water according to the actual needs of the crop, satisfying crop growth requirements while avoiding water waste and improving water resource utilization efficiency. By retrieving the digital elevation model and pipeline network topology of the irrigation area for hydraulic calculations, the target pressure setpoint of the pressure regulating valve at the inlet of the target irrigation zone is determined. This fully considers the impact of hilly terrain on water pressure, ensuring stable pressure in all areas of the drip irrigation system under complex terrain, ensuring uniformity of drip irrigation, and improving drip irrigation effect. Pipeline leakage detection is performed by collecting real-time pressure data from each pipeline and analyzing pressure gradient changes, pressure change rates, and the timing logic of associated valve operation instructions. This allows for timely detection of pipeline leakage problems, facilitating timely maintenance measures and ensuring the normal operation of the drip irrigation system. Attached Figure Description

[0055] Figure 1 This is a flowchart of an IoT-based drip irrigation control method for hilly irrigation areas.

[0056] Figure 2 This is a schematic diagram of a drip irrigation system for hilly irrigation areas based on the Internet of Things (IoT).

[0057] Figure 3This is a flowchart illustrating the process of determining crop water requirements in an IoT-based drip irrigation control method for hilly irrigation areas.

[0058] Figure 4 This is a flowchart illustrating the determination of the target pressure setpoint in an IoT-based drip irrigation control method for hilly irrigation areas.

[0059] Figure 5 This is a flowchart illustrating pipeline leakage detection in an IoT-based drip irrigation control method for hilly irrigation areas.

[0060] Figure 6 This is a flowchart illustrating anti-clogging control in an IoT-based drip irrigation control method for hilly irrigation areas.

[0061] Figure 7 This is a schematic diagram of a drip irrigation control system for hilly irrigation areas based on the Internet of Things. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0063] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0064] like Figure 1 and Figure 2 As shown in the figure, this embodiment of the invention provides a drip irrigation control method for hilly irrigation areas based on the Internet of Things, the method including the following steps:

[0065] S100: Based on the real-time environmental data, crop type and growth stage of the target irrigation zone, determine the crop water requirement and irrigation mode of the target irrigation zone, and generate irrigation decision instructions.

[0066] S200, in response to the irrigation decision command, retrieve the digital elevation model and pipeline network topology of the irrigation area, perform hydraulic calculations, and determine the target pressure setting value of the pressure regulating valve at the inlet of the target irrigation zone;

[0067] S300, the remote control PLC controller drives the pressure regulating valve to stabilize the pressure at the back end of the pressure regulating valve at the target pressure setting value.

[0068] The S400 collects pressure data from each pipeline in real time, analyzes pressure gradient changes, pressure change rate, and the timing logic of associated valve operation commands, and performs pipeline leakage detection.

[0069] The S500 monitors the pressure and flow data at the ends of each pipeline and performs anti-clogging control based on the pressure-to-flow ratio.

[0070] It should be noted that existing technologies fail to fully consider various factors such as real-time environmental data, crop type, and growth stage of the target irrigation zone, resulting in inaccurate determination of crop water requirements and irrigation patterns. Currently, when determining the target pressure setpoint of the pressure regulating valve at the inlet of the target irrigation zone, the digital elevation model and pipeline network topology of the irrigation area are not fully utilized for hydraulic calculations, leading to unreasonable pressure setpoints. This makes it impossible to guarantee pressure stability in different areas of the drip irrigation system in hilly terrain, affecting the drip irrigation effect. The embodiments of this invention aim to solve the above problems.

[0071] In this embodiment of the invention, a sensor network is set up in each irrigation zone to collect real-time environmental data and obtain the crop type and growth stage of each irrigation zone. Thus, based on the real-time environmental data, crop type, and growth stage, the water requirement and irrigation mode of the target irrigation zone can be determined, generating irrigation decision instructions. This allows for the provision of appropriate water according to the actual needs of the crops, satisfying their growth requirements while avoiding water waste and improving water resource utilization efficiency. Then, the digital elevation model and pipeline network topology of the irrigation area are retrieved. These models need to be prepared in advance, and hydraulic calculations are performed to determine the target pressure setting value of the pressure regulating valve at the inlet of the target irrigation zone. Next, the remotely controlled PLC controller drives the pressure regulating valve to stabilize the pressure at the target pressure setting value. This process fully considers the influence of hilly terrain on water pressure, ensuring stable pressure in various areas of the drip irrigation system under complex terrain, ensuring drip irrigation uniformity, and improving drip irrigation effect. Furthermore, this embodiment of the invention also collects real-time pressure data from each pipeline. By analyzing pressure gradient changes, pressure change rates, and the timing logic of associated valve operation commands, pipeline leakage detection is performed. This allows for timely identification of pipeline leakage problems, facilitating prompt maintenance and reducing water waste. Additionally, it monitors pressure and flow data at the ends of each pipeline. Based on the pressure-to-flow ratio, anti-clogging control is implemented, enabling timely detection of pipeline blockages and the implementation of corresponding measures. This ensures the smooth operation of the drip irrigation system, providing uniform water supply to crops in all areas, further improving the stability and uniformity of crop growth, and enhancing the overall efficiency of agricultural production.

[0072] like Figure 3 As shown, in a preferred embodiment of the present invention, the steps of determining the crop water requirement and irrigation pattern of the target irrigation zone specifically include:

[0073] S101, based on the real-time environmental data, the crop evapotranspiration ET is calculated; the real-time environmental data includes soil volumetric water content, atmospheric temperature, atmospheric relative humidity, and wind speed, etc.

[0074] S102, retrieve the crop coefficient Kc corresponding to the crop type and growth stage, and obtain the crop water requirement based on the crop coefficient and crop evapotranspiration. Crop water requirement = Kc × ET;

[0075] S103, determine the irrigation mode based on crop type, growth stage and crop water requirement;

[0076] S104: Determine the humidity threshold based on the crop's water requirement, compare the soil moisture with the humidity threshold, and generate an irrigation decision instruction when the soil moisture is lower than the humidity threshold.

[0077] In this embodiment of the invention, the reference crop evapotranspiration is calculated using the Penman-Montes formula, ET= Where Rn is net solar radiation, G is soil heat flux, Δ is saturated vapor pressure slope, γ is humidity constant, T is temperature, u2 is wind speed, es is saturated vapor pressure, and ea is actual vapor pressure. Additionally, crop coefficients are pre-defined for each growth stage of each crop type. This allows for the real-time calculation of crop water requirement based on the crop coefficient and crop evapotranspiration: Crop water requirement = Crop coefficient × Crop evapotranspiration. Furthermore, appropriate irrigation patterns need to be pre-defined for each water requirement range at each growth stage of each crop type. Finally, a mapping table between water requirement and humidity thresholds is used to determine the corresponding humidity threshold. Soil moisture is compared to the humidity threshold; when soil moisture falls below the threshold, irrigation is required, and an irrigation decision instruction is generated.

[0078] like Figure 4 As shown, in a preferred embodiment of the present invention, the step of performing hydraulic calculations to determine the target pressure setpoint of the pressure regulating valve at the inlet of the target irrigation zone specifically includes:

[0079] S201, calculate the minimum working pressure Pmin required based on the emitter at the hydraulically most unfavorable point in the target irrigation zone;

[0080] S202, Calculate the static pressure head ρgΔH generated by the elevation difference between the pressure regulating valve and the water emitter based on the digital elevation model, where ρ is the density of water, g is the gravitational acceleration, and ΔH is the elevation difference between the pressure regulating valve and the water emitter at the most unfavorable point.

[0081] S203, calculate the head loss along the pipe from the pressure regulating valve to the water emitter hf and the local head loss hj based on the pipe material, pipe diameter, length and flow rate;

[0082] S204, the target pressure setting value of the pressure regulating valve is calculated by using the target pressure setting value = Pmin + ρgΔH + ρghf + ρghj.

[0083] In this embodiment of the invention, to determine the target pressure setting value, the minimum working pressure required is calculated based on the emitter at the hydraulically most unfavorable point within the target irrigation zone. Specifically, firstly, the elevation information of all emitters within the target irrigation zone is determined, and the pipeline path length from each emitter to the pressure regulating valve is also determined. Based on the elevation information and pipeline path length, a weighted scoring method is used to determine the emitter at the most unfavorable point. Then, the rated working pressure and safety margin corresponding to the emitter at the most unfavorable point are retrieved. The rated working pressure plus the safety margin equals the minimum working pressure. To overcome the gravitational influence caused by terrain elevation differences, in hilly areas, additional energy (pressure) is required to transport water from low to high altitudes. Furthermore, the gravity of water is converted into pressure when descending a slope. The calculation of static head is to quantitatively determine this pressure change caused by the pure elevation difference. Based on the elevation difference and basic principles of fluid mechanics, the static head can be obtained. The static head is ρgΔH, where ρ is the density of water, g is the acceleration due to gravity, and ΔH is the elevation difference between the pressure regulating valve and the emitter at the most unfavorable point. In addition, to compensate for pressure losses caused by frictional resistance and flow through pipe fittings, the roughness coefficient C is determined based on the pipe material, and the pipe diameter D, length L, and flow rate Q are obtained. The head loss along the pipe, hf, is then calculated using the Hassen-Williams formula: hf = 10.67∙L∙Q 1.852 / (C 1.852 ∙D 4.871 In addition, all pipe fittings that generate eddies and resistance along the pipeline path, such as elbows, tees, valves, reducers, and filters, are statistically analyzed. Using the equivalent length method, the equivalent length of local resistance for length L is defined as Le. Combined with the Hassen-Williams formula, the local head loss hj = hf∙Le / L is calculated. Finally, the target pressure setpoint of the pressure regulating valve is calculated using the target pressure setpoint = Pmin + ρgΔH + ρghf + ρghj, where Pmin is the minimum operating pressure required by the emitter at the most unfavorable point.

[0084] like Figure 5 As shown, in a preferred embodiment of the present invention, the steps for detecting pipeline leakage by analyzing pressure gradient changes, pressure change rates, and the timing logic of associated valve operation commands specifically include:

[0085] S401, calculate the pressure difference ΔP of each pipe segment using data from pressure sensors deployed at the beginning and end of the pipeline; when ΔP continuously exceeds the first threshold for a first preset time, determine that the pressure is abnormal and mark the corresponding pipe segment as the primary leakage segment;

[0086] S402, calculate the pressure change rate of the upstream pressure of the primary leakage section within the most recent short time window; if the absolute value of the pressure change rate is less than the water hammer characteristic threshold, the pressure is determined to be slowly decreasing, and the pipe section is upgraded to an intermediate leakage section.

[0087] S403, query whether the valves of the intermediate leakage section and the adjacent pipe section have received operation instructions within the second preset time period before the start time of the pressure anomaly. If no valve operation instructions are found, upgrade the pipe section to the advanced leakage section.

[0088] S404. Initiate a confirmation window period. If the ΔP of the pipe segment remains higher than the second threshold during the confirmation window period, it is determined to be a real leakage segment.

[0089] It should be noted that in hilly irrigation areas, the terrain has a large elevation difference, resulting in strong water flow energy within the pipelines. When a solenoid valve in a certain area suddenly opens or closes, a violent pressure shock wave (water hammer) is generated within the pipeline. The manifestation of this pressure fluctuation on the sensor is very similar to the initial symptoms of a sudden pipeline rupture or severe leakage, thus easily leading to false leak detection. To address this issue, this embodiment of the invention calculates the pressure difference ΔP for each pipe segment. When ΔP continuously exceeds a first threshold for a first preset duration, such as 5 seconds, a pressure anomaly is determined, and the corresponding pipe segment is marked as a primary leakage segment. This step aims to detect any minute pressure anomalies, capturing "water hammer," "normal start-stop," and "real leakage" to ensure no missed detections. Then, the pressure change rate r of the upstream pressure of all primary leakage segments within the most recent short time window (e.g., 2 seconds) is calculated. , Let P(t) represent the pipe segment pressure at time t, indicating the most recent short time window. If the absolute value of the pressure change rate is less than the water hammer characteristic threshold, it indicates that the problem is not caused by water hammer, and the pipe segment is upgraded to a medium-level leakage segment. Next, for the medium-level leakage segment, it is checked whether the valves of the medium-level leakage segment and adjacent pipe segments have received operation commands, such as closing or opening commands, within a second preset time period (e.g., 30 seconds) before the start time of the pressure anomaly. If there are corresponding valve operation commands and they are highly correlated in time, the event is determined to be a planned normal pressure fluctuation; if no valve operation commands are found, the pipe segment is upgraded to a high-level leakage segment. Finally, for the high-level leakage segment, a confirmation window period (e.g., 60 seconds) is initiated. If, within the confirmation window period, the ΔP of the pipe segment is continuously higher than the second threshold, it is determined to be a real leakage segment. The second threshold is more stringent than the first threshold.

[0090] like Figure 6 As shown, in a preferred embodiment of the present invention, the step of performing anti-clogging control based on the pressure-to-flow ratio specifically includes:

[0091] S501, when the pressure-to-flow ratio continues to deviate from the normal range and the pressure rises abnormally, it is determined that the corresponding pipeline is at risk of blockage.

[0092] S502, start the pulse flushing mode. The PLC controls the solenoid valve at the inlet of the pipeline to perform a rapid opening and closing operation, generating a pressure pulse wave.

[0093] In this embodiment of the invention, when a certain pipeline is determined to be at risk of blockage, a pulse flushing mode will be automatically activated. The solenoid valve at the inlet of the pipeline is controlled by the PLC to perform a rapid opening and closing operation, generating a pressure pulse wave. At the same time, during the pulse flushing, the pressure setting value of the adjacent branch pipe is temporarily adjusted to avoid drastic fluctuations in system pressure and extend the service life of the pipeline.

[0094] like Figure 7 As shown in the figure, this embodiment of the invention also provides an IoT-based drip irrigation control system for hilly irrigation areas, the system comprising:

[0095] The irrigation decision generation module 100 is used to determine the crop water requirement and irrigation mode of the target irrigation zone based on real-time environmental data, crop type and growth stage, and generate irrigation decision instructions.

[0096] The target pressure setting module 200 is used to respond to the irrigation decision command, retrieve the digital elevation model and pipeline network topology of the irrigation area, perform hydraulic calculations, and determine the target pressure setting value of the pressure regulating valve at the inlet of the target irrigation zone.

[0097] The pressure remote control module 300 is used to remotely control the PLC controller to drive the pressure regulating valve to stabilize the pressure at the downstream end of the pressure regulating valve at the target pressure set value.

[0098] The pipeline leakage detection module 400 is used to collect pressure data of each pipeline in real time, analyze pressure gradient changes, pressure change rate and the timing logic of related valve operation commands, and perform pipeline leakage detection.

[0099] The pipeline anti-clogging control module 500 is used to monitor the pressure and flow data at the end of each pipeline and to perform anti-clogging control based on the pressure-to-flow ratio.

[0100] In a preferred embodiment of the present invention, the irrigation decision generation module 100 includes:

[0101] The evapotranspiration calculation unit is used to calculate the crop evapotranspiration ET based on the real-time environmental data; the real-time environmental data includes soil volumetric water content, atmospheric temperature, atmospheric relative humidity, and wind speed.

[0102] The water requirement calculation unit is used to retrieve the crop coefficient Kc corresponding to the crop type and growth stage, and to obtain the crop water requirement based on the crop coefficient and crop evapotranspiration. Crop water requirement = Kc × ET;

[0103] The irrigation pattern determination unit is used to determine the irrigation pattern based on crop type, growth stage, and crop water requirement.

[0104] The irrigation decision generation unit is used to determine the humidity threshold based on the crop's water requirements, compare the soil moisture with the humidity threshold, and generate an irrigation decision instruction when the soil moisture is lower than the humidity threshold.

[0105] In a preferred embodiment of the present invention, the target pressure setting module 200 includes:

[0106] Minimum working pressure unit, used to calculate the minimum working pressure Pmin required based on the emitter at the hydraulically most unfavorable point within the target irrigation zone;

[0107] The static pressure head calculation unit is used to calculate the static pressure head ρgΔH generated by the elevation difference between the pressure regulating valve and the irrigator based on the digital elevation model, where ρ is the density of water, g is the gravitational acceleration, and ΔH is the elevation difference between the pressure regulating valve and the most unfavorable irrigator.

[0108] The head loss determination unit is used to calculate the friction head loss hf and local head loss hj from the pressure regulating valve to the water emitter based on the pipe material, pipe diameter, length and flow rate.

[0109] The target pressure calculation unit is used to calculate the target pressure setting value of the pressure regulating valve by using the target pressure setting value = Pmin + ρgΔH + ρghf + ρghj.

[0110] In a preferred embodiment of the present invention, the pipeline leakage detection module 400 includes:

[0111] The primary leakage detection unit is used to calculate the pressure difference ΔP of each pipe segment using data from pressure sensors deployed at the beginning and end of the pipeline. When ΔP continuously exceeds the first threshold for a first preset duration, the pressure is determined to be abnormal, and the corresponding pipe segment is marked as a primary leakage segment.

[0112] The intermediate leakage determination unit is used to calculate the pressure change rate of the upstream pressure of the primary leakage section within the most recent short time window; if the absolute value of the pressure change rate is less than the water hammer characteristic threshold, the pressure is determined to be slowly decreasing, and the pipe section is upgraded to an intermediate leakage section.

[0113] The advanced leakage section determination unit is used to query whether the valves of the intermediate leakage section and adjacent pipe sections have received operation instructions within a second preset time period before the start time of the pressure anomaly. If no valve operation instructions are found, the pipe section is upgraded to an advanced leakage section.

[0114] The actual leakage section determination unit initiates a confirmation window period. If the ΔP of the pipe section remains higher than the second threshold during the confirmation window period, it is determined to be an actual leakage section.

[0115] The above description only details the preferred embodiments of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0116] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0117] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the disclosure in the specification and embodiments. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

Claims

1. A drip irrigation control method for hilly irrigation areas based on the Internet of Things, characterized in that, The method includes the following steps: Based on real-time environmental data, crop types, and growth stages of the target irrigation zone, the crop water requirements and irrigation patterns of the target irrigation zone are determined, and irrigation decision instructions are generated. In response to the irrigation decision command, the digital elevation model and pipeline network topology of the irrigation area are retrieved, hydraulic calculations are performed, and the target pressure setting value of the pressure regulating valve at the inlet of the target irrigation zone is determined. The remote control PLC controller drives the pressure regulating valve to stabilize the pressure at the back end of the pressure regulating valve at the target pressure setting value. Real-time acquisition of pressure data from each pipeline, analysis of pressure gradient changes, pressure change rate, and timing logic of associated valve operation commands to detect pipeline leakage; Monitor the pressure and flow data at the end of each pipeline, and implement anti-clogging control based on the pressure-to-flow ratio; The step of performing hydraulic calculations to determine the target pressure setting value of the pressure regulating valve at the inlet of the target irrigation zone specifically includes: calculating the minimum working pressure Pmin required based on the emitter at the most hydraulically unfavorable point within the target irrigation zone; calculating the static pressure head ρgΔH generated by the elevation difference between the pressure regulating valve and the emitter based on the digital elevation model, where ρ is the density of water, g is the acceleration due to gravity, and ΔH is the elevation difference between the pressure regulating valve and the emitter at the most unfavorable point; calculating the head loss along the pipe from the pressure regulating valve to the emitter and the local head loss hf based on the pipe material, pipe diameter, length, and flow rate; and calculating the target pressure setting value of the pressure regulating valve using the formula: target pressure setting value = Pmin + ρgΔH + ρghf + ρghj. The step of calculating the minimum working pressure required based on the emitter at the hydraulically most unfavorable point within the target irrigation zone specifically includes: determining the elevation information of the emitters within the target irrigation zone; determining the pipeline path length from the emitter to the pressure regulating valve; determining the emitter at the most unfavorable point using a weighted scoring method based on the elevation information and pipeline path length; and determining the rated working pressure and safety margin corresponding to the emitter at the most unfavorable point to obtain the minimum working pressure. The steps for detecting pipeline leaks, including analyzing pressure gradient changes, pressure change rates, and the timing logic of associated valve operation commands, specifically include: calculating the pressure difference ΔP for each pipe segment using data from pressure sensors deployed at the beginning and end of the pipeline; determining a pressure anomaly when ΔP continuously exceeds a first threshold for a first preset duration, and marking the corresponding pipe segment as a primary leak segment; calculating the pressure change rate of the upstream pressure of the primary leak segment within the most recent short time window; if the absolute value of the pressure change rate is less than the water hammer characteristic threshold, determining that the pressure is slowly decreasing, and upgrading the pipe segment to an intermediate leak segment; querying whether the valves of the intermediate leak segment and adjacent pipe segments have received operation commands within a second preset duration before the pressure anomaly start time; if no valve operation commands are found, upgrading the pipe segment to a high-level leak segment; initiating a confirmation window period; if the ΔP of the pipe segment continuously exceeds the second threshold during the confirmation window period, it is determined to be a true leak segment.

2. The IoT-based drip irrigation control method for hilly irrigation areas according to claim 1, characterized in that, The steps for determining the crop water requirement and irrigation pattern of the target irrigation zone specifically include: Based on the real-time environmental data, the crop evapotranspiration ET is calculated; the real-time environmental data includes soil volumetric water content, atmospheric temperature, atmospheric relative humidity, and wind speed. Retrieve the crop coefficient Kc corresponding to the crop type and growth stage, and obtain the crop water requirement based on the crop coefficient and crop evapotranspiration. Crop water requirement = Kc × ET; The irrigation pattern should be determined based on the crop type, growth stage, and water requirements of the crop. A humidity threshold is determined based on the crop's water requirements. Soil moisture is compared with the humidity threshold. When the soil moisture is lower than the humidity threshold, an irrigation decision instruction is generated.

3. The IoT-based drip irrigation control method for hilly irrigation areas according to claim 1, characterized in that, The step of implementing anti-clogging control based on the pressure-to-flow ratio specifically includes: When the pressure-to-flow ratio continuously deviates from the normal range and the pressure rises abnormally, it is determined that the corresponding pipeline is at risk of blockage. The pulse flushing mode is activated, and the solenoid valve at the inlet of the pipeline is controlled by the PLC to perform a rapid opening and closing operation, generating a pressure pulse wave.

4. A drip irrigation control system for hilly irrigation areas based on the Internet of Things, characterized in that, The system includes: The irrigation decision generation module is used to determine the crop water requirement and irrigation mode of the target irrigation zone based on real-time environmental data, crop type and growth stage, and generate irrigation decision instructions. The target pressure setting module is used to respond to the irrigation decision command, retrieve the digital elevation model and pipeline network topology of the irrigation area, perform hydraulic calculations, and determine the target pressure setting value of the pressure regulating valve at the inlet of the target irrigation zone. The pressure remote control module is used to remotely control the PLC controller to drive the pressure regulating valve to stabilize the pressure at the downstream end of the pressure regulating valve at the target pressure set value. The pipeline leakage detection module is used to collect pressure data of each pipeline in real time, analyze pressure gradient changes, pressure change rate and the timing logic of related valve operation commands, and perform pipeline leakage detection. The pipeline anti-clogging control module is used to monitor the pressure and flow data at the end of each pipeline and to perform anti-clogging control based on the pressure-to-flow ratio. The target pressure setting module includes: a minimum working pressure unit, used to calculate the required minimum working pressure Pmin based on the emitter at the hydraulically most unfavorable point within the target irrigation zone; a static head calculation unit, used to calculate the static head ρgΔH generated by the elevation difference between the pressure regulating valve and the emitter based on the digital elevation model, where ρ is the density of water, g is the acceleration due to gravity, and ΔH is the elevation difference between the pressure regulating valve and the emitter at the most unfavorable point; a head loss determination unit, used to calculate the friction head loss hf and local head loss hj from the pressure regulating valve to the emitter based on the pipe material, pipe diameter, length, and flow rate; and a target pressure calculation unit, used to calculate the target pressure setting value of the pressure regulating valve using the target pressure setting value = Pmin + ρgΔH + ρghf + ρghj. The step of calculating the minimum working pressure required based on the emitter at the hydraulically most unfavorable point within the target irrigation zone specifically includes: determining the elevation information of the emitters within the target irrigation zone; determining the pipeline path length from the emitter to the pressure regulating valve; determining the emitter at the most unfavorable point using a weighted scoring method based on the elevation information and pipeline path length; and determining the rated working pressure and safety margin corresponding to the emitter at the most unfavorable point to obtain the minimum working pressure. The pipeline leakage detection module includes: a primary leakage determination unit, used to calculate the pressure difference ΔP of each pipe segment using pressure sensor data deployed at the beginning and end of the pipeline; when ΔP continuously exceeds a first threshold for a first preset duration, the pressure is determined to be abnormal, and the corresponding pipe segment is marked as a primary leakage segment; an intermediate leakage determination unit, used to calculate the pressure change rate of the upstream pressure of the primary leakage segment within the most recent short time window; if the absolute value of the pressure change rate is less than the water hammer characteristic threshold, the pressure is determined to be slowly decreasing, and the pipe segment is upgraded to an intermediate leakage segment; an advanced leakage segment determination unit, used to query whether the valves of the intermediate leakage segment and adjacent pipe segments have received operation instructions within a second preset duration before the pressure abnormality start time; if no valve operation instructions are found, the pipe segment is upgraded to an advanced leakage segment; and a true leakage segment determination unit, which initiates a confirmation window period; if the ΔP of the pipe segment continuously exceeds a second threshold within the confirmation window period, it is determined to be a true leakage segment.

5. The IoT-based drip irrigation control system for hilly irrigation areas according to claim 4, characterized in that, The irrigation decision generation module includes: The evapotranspiration calculation unit is used to calculate the crop evapotranspiration ET based on the real-time environmental data; the real-time environmental data includes soil volumetric water content, atmospheric temperature, atmospheric relative humidity, and wind speed. The water requirement calculation unit is used to retrieve the crop coefficient Kc corresponding to the crop type and growth stage, and to obtain the crop water requirement based on the crop coefficient and crop evapotranspiration. Crop water requirement = Kc × ET; The irrigation pattern determination unit is used to determine the irrigation pattern based on crop type, growth stage, and crop water requirement. The irrigation decision generation unit is used to determine the humidity threshold based on the crop's water requirements, compare the soil moisture with the humidity threshold, and generate an irrigation decision instruction when the soil moisture is lower than the humidity threshold.

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