A smart adjustment system for maintenance spraying in landscaping

Abstract

This application relates to the field of landscape maintenance technology, specifically to an intelligent adjustment system for landscape maintenance spraying; it addresses the technical problem that existing landscape spraying systems struggle to balance aesthetic appeal with ground drying requirements under complex operating conditions. The system includes: a data acquisition unit that collects pipeline pressure data from the pump station outlet and environmental meteorological data from the spraying area; a risk calculation unit that calculates particle size risk factors and accumulation risk factors based on the pipeline pressure data and environmental meteorological data, and synthesizes these factors into a ground moisture index; and a control unit that, when the ground moisture index reaches a first threshold, increases the pump's operating frequency to increase pipeline pressure and reduces the solenoid valve's duty cycle to decrease spray flow.

Description

Technical Field

[0001] This application relates to the field of landscape maintenance technology, specifically to an intelligent adjustment system for maintenance spraying in landscape gardens. Background Technology

[0002] High-pressure spray systems utilize high-pressure plunger pumps to pressurize and atomize water before spraying it out. This effectively achieves landscaping effects and microclimate regulation in gardens and is a widely used technology in garden landscape maintenance. The high-pressure spray system delivers pressurized water to the spray nozzles through a pipeline network. The pressure breaks the water into fine droplets, which evaporate in the air, lowering the surrounding temperature. The resulting mist effect enhances the aesthetic appeal of the garden landscape, combining practicality and beauty.

[0003] Existing high-pressure spray systems for landscaping typically control the start and stop of the equipment based on preset thresholds for ambient temperature and humidity. In actual operation, this control method is not sufficiently adaptable to fluctuations in pipeline hydraulics and environmental meteorological conditions, and cannot accurately control the risk of ground moisture, easily leading to slippery ground conditions. This not only affects the safety of the landscaping site but may also adversely affect the growth of vegetation. At the same time, under adverse weather conditions such as calm winds and high humidity, existing systems struggle to balance atomization effect and spray flux, significantly reducing system performance. The continuity and stability of the landscape mist effect cannot be guaranteed, making it difficult to balance the landscape effect with the need for ground dryness. Summary of the Invention

[0004] To address the technical problem that existing garden misting systems struggle to balance aesthetic appeal with ground drying requirements under complex conditions, this application aims to provide an intelligent adjustment system for garden landscape maintenance misting, comprising: The data acquisition unit is used to collect pipeline pressure data at the pump station outlet and environmental meteorological data in the spray area; The risk calculation unit is used to calculate the particle size risk factor and the accumulation risk factor based on pipeline pressure data and environmental meteorological data, and to synthesize the particle size risk factor and the accumulation risk factor into the ground wetness index; the particle size risk factor is used to characterize the risk of droplet size deterioration due to pressure pulsation; the accumulation risk factor is used to characterize the risk of local accumulation of water mist due to insufficient environmental transport capacity. The control unit is used to increase the operating frequency of the water pump to increase the pipeline pressure and reduce the duty cycle of the solenoid valve to reduce the spray flow when the ground humidity index reaches a first threshold.

[0005] In one possible implementation, the risk calculation unit includes a first risk factor calculation unit, which is used to: determine the pressure pulsation coefficient and the average pressure of the pipeline network based on pipeline pressure data; determine the air hygroscopic potential based on environmental meteorological data; determine the positive driving effect of the average pressure of the pipeline network and the air hygroscopic potential on droplet evaporation; determine the negative hindering effect of the pressure pulsation coefficient on the generation of large, difficult-to-evaporate droplets; wherein the negative hindering effect increases nonlinearly with the pressure pulsation coefficient; and calculate the particle size risk factor based on the competitive relationship between the positive driving effect and the negative hindering effect.

[0006] In one possible implementation, the risk calculation unit includes a second risk factor calculation unit, which is used to: determine the average pressure and pressure pulsation coefficient of the pipeline network based on pipeline pressure data; determine the ambient air transport velocity based on environmental meteorological data and perform lower limit clamping on the ambient air transport velocity; determine the spray base flow level based on the average pipeline network pressure and determine the instantaneous flow fluctuation based on the pressure pulsation coefficient; and determine the accumulation risk factor based on the spray base flow level, instantaneous flow fluctuation, and the clamped ambient air transport velocity.

[0007] In one possible implementation, the risk calculation unit includes an index synthesis subunit, which is used to: calculate the product of particle size risk factor and accumulation risk factor; obtain the installation height of the spray nozzle and a pre-calibrated comprehensive calibration constant; the comprehensive calibration constant is a constant determined by back-calculation based on the rated operating parameters of the spray system and the critical wetting state under standard operating conditions, and is used for benchmark normalization of different system configurations; determine a height adjustment coefficient based on the installation height and the comprehensive calibration constant; and adjust the product based on the height adjustment coefficient to determine the ground wetting index.

[0008] In one possible implementation, the control unit is specifically configured to: maintain the current operating frequency of the water pump and the current duty cycle of the solenoid valve when the ground humidity index is lower than a second threshold; maintain the current operating frequency of the water pump and reduce the duty cycle according to the ground humidity index when the ground humidity index is greater than or equal to the second threshold and less than the first threshold; and increase the operating frequency and reduce the duty cycle when the ground humidity index is greater than or equal to the first threshold; wherein the second threshold is less than the first threshold.

[0009] In one possible implementation, the control unit is specifically configured to: increase the operating frequency of the water pump to a preset multiple of the rated frequency when the ground humidity index is greater than or equal to a first threshold; calculate a pressure compensation term to compensate for the natural increase in flow caused by the frequency increase; calculate a risk suppression term to reduce the flux based on the degree to which the ground humidity index exceeds the first threshold; and calculate the target duty cycle of the solenoid valve based on the pressure compensation term and the risk suppression term.

[0010] In one possible implementation, the pressure compensation term is inversely proportional to the square root of the increase in operating frequency; the risk suppression term is the ratio of the first threshold to the current ground moisture index, and the ratio does not exceed 1.

[0011] In one possible implementation, the system also includes a start-up control unit, which is used to: set the average pressure of the pipeline network to the rated pressure value and the pressure pulsation coefficient to zero when the system is shut down; calculate the theoretical ground humidity index by combining real-time environmental meteorological data; allow the system to start when the theoretical ground humidity index is lower than the start-up threshold; and prohibit the system from starting when the theoretical ground humidity index is greater than or equal to the start-up threshold.

[0012] In one possible implementation, the data acquisition unit includes: a high-frequency pressure sensor located at the pump station outlet for collecting pipeline pressure data; and a meteorological monitoring unit located at the center of the spray area for collecting environmental meteorological data including wind speed, temperature, and humidity.

[0013] In one possible implementation, the system further includes a data preprocessing unit for: calculating the average pressure value and pressure pulsation coefficient within a sliding window based on the collected pipeline pressure data; calculating the air transport velocity and air moisture absorption potential based on the collected environmental meteorological data; and normalizing the average pressure value, air transport velocity, and air moisture absorption potential by quoting them with their corresponding benchmark calibration values.

[0014] This application has the following beneficial effects: By constructing a dual-scale competitive model that includes particle size risk factors and accumulation risk factors, this application can simultaneously quantify the risk of atomization quality deterioration caused by microscopic pressure pulsation and the risk of local accumulation caused by insufficient macroscopic environmental transport capacity, thus solving the problem that a single meteorological parameter cannot reflect the true wetting risk; by adopting a decoupled control strategy of "increasing frequency and decreasing valve", while increasing the pump operating frequency to force particle size refinement using high-pressure shear force and turbulent entrainment effect, the duty cycle of the solenoid valve is simultaneously reduced to reduce the total spray flux, breaking the linear locking relationship between pressure and flow in the traditional hydraulic system and realizing wet-free operation under severe weather conditions; by performing risk prediction based on theoretical preset values ​​before system startup, the immediate wet phenomenon caused by blind startup is avoided, significantly improving the system's availability and environmental adaptability. In this way, the system effectively avoids the risk of ground moisture, and at the same time, it can balance the atomization effect and spray flux under adverse weather conditions such as calm wind and high humidity, ensuring the operation of the spray system, improving the continuity and stability of the landscape fog effect, and meeting the dual needs of spray landscaping and site drying in garden landscape maintenance. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A schematic diagram of the system architecture of an intelligent adjustment system for maintenance spraying in landscaping provided in one embodiment of this application; Figure 2 This is a schematic diagram of the structure of a risk calculation unit provided in one embodiment of this application; Figure 3 This is a schematic diagram of the structure of a data acquisition unit provided in one embodiment of this application. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an intelligent adjustment system for maintenance spraying in landscaping according to this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0019] Unless otherwise specified, the normalization function Norm() mentioned in this application uses maximum and minimum value normalization. The maximum and minimum values ​​are preset empirical extreme values ​​derived from a large amount of historical experimental data. If the calculation result exceeds the [0,1] interval, a truncation function is used to limit it to the [0,1] range (i.e., if the result is less than 0, it is taken as 0; if it is greater than 1, it is taken as 1) to eliminate the influence of outliers on the evaluation index.

[0020] The following description, in conjunction with the accompanying drawings, details a specific scheme for an intelligent adjustment system for maintenance spraying in landscaping provided in this application.

[0021] Please see Figure 1The diagram illustrates a system architecture of an intelligent adjustment system for maintenance spraying in landscaping, according to an embodiment of the present invention. This intelligent adjustment system includes a data acquisition unit 101, a risk calculation unit 102, and a control unit 103. The units communicate bidirectionally via a communication link, ensuring real-time interaction of collected data and analysis results. The communication link can employ wired or wireless transmission methods to meet the communication needs of different monitoring scenarios.

[0022] Data acquisition unit 101 is used to collect pipeline pressure data at the pump station outlet and environmental meteorological data of the spray area. The pipeline pressure data reflects the water supply dynamics of the spray system, while the environmental meteorological data reflects the environmental absorption capacity of the spray area. By simultaneously collecting hydraulic status data from the supply side and environmental status data from the demand side, data acquisition unit 101 can establish a complete basis for operational condition assessment.

[0023] The risk calculation unit 102 is used to calculate the particle size risk factor and the accumulation risk factor based on pipeline pressure data and environmental meteorological data, and then synthesizes the particle size risk factor and the accumulation risk factor into a surface wetness index. The particle size risk factor characterizes the risk of droplet size deterioration due to pressure fluctuations, reflecting the negative impact of hydraulic fluctuations on atomization quality at the microscale. The accumulation risk factor characterizes the risk of localized water mist accumulation due to insufficient environmental transport capacity, reflecting the constraint of environmental conditions on water mist diffusion at the macroscale. By constructing a dual-scale competitive model that includes both microscopic particle size risk and macroscopic accumulation risk, the risk calculation unit 102 can comprehensively quantify the antagonistic relationship between supply-side quality defects and demand-side absorption capacity, solving the technical problem that a single meteorological parameter cannot reflect the true wetness risk.

[0024] Control unit 103 is used to increase the operating frequency of the water pump to increase the pipeline pressure and reduce the duty cycle of the solenoid valve to reduce the spray flow when the ground humidity index reaches a first threshold. The first threshold is used to define the critical state of dangerous working conditions. When the system detects that the ground humidity index reaches or exceeds the threshold, it indicates that there is a sudden high-risk working condition (such as severe pressure fluctuations or instantaneous calm winds). At this time, the system triggers a forced intervention mode. By executing the decoupled control action of "increasing frequency and decreasing valve", the system increases the operating frequency of the water pump to force the particle size to be refined and accelerate evaporation by utilizing the high-pressure shear force and the strong turbulent entrainment effect induced by the jet. At the same time, it simultaneously reduces the duty cycle of the solenoid valve to offset the natural flow increase caused by the pressure increase and further reduce the total spray flux. This breaks the linear locking relationship between pressure and flow in the traditional hydraulic system and achieves wet-free operation under extreme working conditions.

[0025] Based on the above technical solutions, this application constructs a dual-scale competitive model that includes particle size risk factors and accumulation risk factors. This model can simultaneously quantify the risk of atomization quality deterioration caused by microscopic pressure pulsation and the risk of local accumulation caused by insufficient macroscopic environmental transport capacity, thus solving the problem that a single meteorological parameter cannot reflect the true wetting risk. By adopting a decoupled control strategy of "increasing frequency and decreasing valve," the pump operating frequency is increased to force particle size refinement using high-pressure shear force and turbulent entrainment effect, while the solenoid valve duty cycle is simultaneously reduced to decrease the total spray flux. This breaks the linear locking relationship between pressure and flow in traditional hydraulic systems, enabling wet-free operation under severe weather conditions. By predicting risks based on theoretical preset values ​​before system startup, the immediate wet phenomenon caused by blind startup is avoided, significantly improving the system's availability and environmental adaptability. In this way, the system effectively avoids the risk of ground moisture, and at the same time, it can balance the atomization effect and spray flux under adverse weather conditions such as calm wind and high humidity, ensuring the operation of the spray system, improving the continuity and stability of the landscape fog effect, and meeting the dual needs of spray landscaping and site drying in garden landscape maintenance.

[0026] In one possible implementation, such as Figure 1 As shown, the system also includes a data preprocessing unit 104, used for: calculating the average pressure value and pressure pulsation coefficient within the sliding window based on the collected pipeline pressure data; calculating the air transport velocity and air moisture absorption potential based on the collected environmental meteorological data; and normalizing the average pressure value, air transport velocity, and air moisture absorption potential by quoting them with their corresponding benchmark calibration values.

[0027] Specifically, the data preprocessing unit 104 calculates the average pressure value and pressure pulsation coefficient within a sliding window based on the collected pipeline pressure data. The duration of the sliding window is set to 1.0 second. Within each control cycle (e.g., 100 milliseconds), the system extracts all historical sampling data falling within that time period for statistical calculation, thereby forcibly aligning the data characteristics of different frequency sensors on the time axis.

[0028] The data preprocessing unit 104 calculates the air transport velocity and air moisture absorption potential based on the collected environmental meteorological data. The calculation of the air transport velocity requires the addition of a natural diffusion compensation term, while the calculation of the air moisture absorption potential is based on the Magnus formula.

[0029] Following this, the data preprocessing unit 104 normalizes the average pressure value, air transport velocity, and air moisture absorption potential by comparing them with their corresponding reference calibration values. The system pre-sets a set of reference calibration parameters: system rated pressure... The value is 5.0 MPa, the standard air handling speed. The value is 2.0 m / s, which represents the standard moisture absorption potential. The value is 1.0 kPa.

[0030] For example, the normalized state vector is: Normalized pressure: Normalized wind speed: Normalized moisture absorption potential: Ultimately, the system generated a document containing... The dimensionless standardized data vector is transmitted in real time to the risk calculation unit for risk calculation.

[0031] Based on the above technical solution, this embodiment eliminates the differences in physical dimensions of pressure (MPa), wind speed (m / s), and moisture absorption potential (kPa) by introducing benchmark normalization processing, and constructs a unified dimensionless competition model, which enables the quantitative analysis of the competition relationship of parameters with different physical properties under the same mathematical framework, providing standardized data input for subsequent risk calculation.

[0032] In one possible implementation, please refer to Figure 2 The risk calculation unit 102 includes a first risk factor calculation unit 201, which is used to calculate the particle size risk factor based on pipeline pressure data and environmental meteorological data. In other words, the first risk factor calculation unit 201 is used to determine the pressure fluctuation coefficient and average pipeline pressure based on the pipeline pressure data; determine the air hygroscopic potential based on the environmental meteorological data; determine the positive driving effect of the average pipeline pressure and air hygroscopic potential on droplet evaporation; determine the negative hindering effect of the pressure fluctuation coefficient on the generation of large, difficult-to-evaporate droplets; wherein the negative hindering effect increases non-linearly with the pressure fluctuation coefficient; and calculate the particle size risk factor based on the competitive relationship between the positive driving effect and the negative hindering effect.

[0033] Specifically, the first risk factor calculation unit 201 first determines the pressure pulsation coefficient and the average pressure of the pipeline network based on the pipeline network pressure data. The pipeline network pressure data is acquired by a high-frequency pressure sensor installed at the pump station outlet, with a sampling frequency of no less than 200Hz. Due to the mechanical reciprocating motion characteristics of the high-pressure plunger pump, the pipeline network pressure exhibits high-frequency pulsations at the millisecond level. This pressure fluctuation can cause the nozzle to generate large droplets with a particle size exceeding the design range at pressure troughs. To accurately quantify this microscopic instability, the system employs a sliding window statistical method, acquiring a discrete pressure sequence containing N data points within a preset state statistical period (e.g., 1.0 second). The average pressure of the pipeline network is calculated as a baseline representation of the work done at the nozzle inlet. Simultaneously, the ratio of the pressure standard deviation to the average pressure is calculated as the pressure pulsation coefficient, used to characterize the degree of instability in the water supply pressure.

[0034] For example, the average pressure of the pipeline network The calculation formula is: in, For the first in the sliding window The instantaneous pressure value at each sampling time. This represents the total number of sampling points within the sliding window. It represents the average work done by the pipeline network during the statistical period, and the unit is MPa.

[0035] Pressure pulsation coefficient The calculation formula is: The numerator is the standard deviation of the pressure sequence, which characterizes the dispersion of pressure fluctuations; the denominator is the sum of the average pressure and the minimum positive number ε, where ε is a parameter tuning coefficient with a minimum positive value (e.g., 0.001), used to prevent the denominator from approaching zero at the initial stage of system startup or when the pressure is extremely low, which would cause the calculation results to diverge. It is a dimensionless parameter that characterizes the relative intensity of pressure fluctuations with respect to the average pressure.

[0036] After determining the pressure pulsation coefficient and the average pressure of the pipeline network, the first risk factor calculation unit 201 determines the air moisture absorption potential based on environmental meteorological data. This environmental meteorological data includes air temperature and relative humidity. The air moisture absorption potential characterizes the physical capacity of a unit volume of air to absorb water vapor, reflecting the driving force of the environment on fog droplet evaporation.

[0037] For example, air moisture absorption potential The calculation formula is: in, The measured air temperature is in °C. The relative humidity is measured and expressed in %; It is an exponential function; The saturated water vapor pressure difference of air is represented by kPa. If the calculated result is less than 0.1 kPa, the system clamps it to 0.1 kPa to prevent model failure under high humidity saturation conditions.

[0038] After determining the aforementioned air moisture absorption potential, the first risk factor calculation unit 201 determines the positive driving effect of the average pipeline pressure and air moisture absorption potential on droplet evaporation, and the negative hindering effect of the pressure pulsation coefficient on the generation of large, difficult-to-evaporate droplets. A higher average pipeline pressure means a finer basic atomized particle size, and a higher air moisture absorption potential means a faster phase change rate; the product of these two factors represents the "positive driving force" that promotes droplet reduction and disappearance. Conversely, an increase in the pressure pulsation coefficient leads to the instantaneous generation of a large number of large droplets during pressure troughs, representing the "negative resistance" that hinders droplet disappearance. Furthermore, due to the geometrical physical property that droplet volume increases cubically with increasing diameter while surface area increases quadratically, this negative hindering effect increases non-linearly (quadraticly) with increasing pressure pulsation coefficient.

[0039] Based on the competitive relationship between positive driving forces and negative hindering forces, the first risk factor calculation unit 201 calculates the particle size risk factor. For example, the particle size risk factor... The calculation formula is: in, Normalized pressure is equal to the average pressure of the pipeline network. With system rated pressure The ratio; Normalized moisture absorption potential equals the moisture absorption potential of air. Compared with standard moisture absorption potential The ratio; The pressure sensitivity calibration coefficient, obtained through fitting tests using a laser particle size analyzer under standard operating conditions, characterizes the response of the particle size distribution width of a specific nozzle model to pressure fluctuations; in this embodiment, it is set to 3.0; The numerator term... Characterized by negative hindering effect, the denominator term Characterizes the positive driving effect; This is a dimensionless parameter; a larger value indicates that the droplets remain in the air longer and the higher the risk of them landing. Optional, pressure sensitivity calibration coefficient. The methods for obtaining the data include: measuring the droplet size distribution under different pressure pulsation amplitudes using a laser particle size analyzer under rated pressure and standard temperature and humidity conditions; fitting the relationship curve between the pressure pulsation coefficient and the standard deviation of the droplet size distribution using the least squares method to determine the distribution. Values.

[0040] Based on the above technical solution, this embodiment establishes a quantitative relationship between micro-hydraulic fluctuations and atomization quality deterioration by introducing a pressure pulsation coefficient and a particle size risk model. This enables the system to identify and respond to millisecond-level hydraulic fluctuations. Even when the average pressure meets the standard, it can detect the risk of large particles caused by mechanical pulsation of the pump station, thereby suppressing the ground wetting phenomenon caused by the sedimentation of "long-tailed" droplets from the source.

[0041] like Figure 2 As shown, in one possible implementation, the risk calculation unit 102 includes a second risk factor calculation unit 202, which is used to: determine the average pressure and pressure pulsation coefficient of the pipeline network based on pipeline pressure data; determine the ambient air transport velocity based on environmental meteorological data and perform lower limit clamping on the ambient air transport velocity; determine the spray base flow level based on the average pipeline network pressure and determine the instantaneous flow fluctuation based on the pressure pulsation coefficient; and determine the accumulation risk factor based on the spray base flow level, instantaneous flow fluctuation, and the clamped ambient air transport velocity.

[0042] Specifically, the second risk factor calculation unit 202 first determines the average pipeline pressure and pressure pulsation coefficient based on the pipeline pressure data. The method for determining the average pipeline pressure and pressure pulsation coefficient is the same as that used by the first risk factor calculation unit 201 in Example 2, and will not be repeated here.

[0043] Following this, the second risk factor calculation unit 202 determines the ambient air transport velocity based on environmental meteorological data and performs lower limit clamping on the ambient air transport velocity. The ambient air transport velocity reflects the actual transport and absorption capacity of the ambient airflow for water mist, and is obtained by collecting data from an ultrasonic anemometer placed at the center of the spray area. To prevent overflow of calculation results under extremely calm wind conditions, the system performs lower limit clamping on the normalized wind speed to ensure that the denominator is not zero and retains its physical meaning.

[0044] For example, ambient air transport speed The calculation formula is: in, For the first in the sliding window The instantaneous wind speed value at each sampling time. This represents the total number of sampling points within the sliding window. This is a natural diffusion compensation term, used to characterize the minimum transport capacity of water mist by the Brownian motion of gas molecules and the entrainment effect of the nozzle jet under absolutely calm conditions. In this embodiment, it is taken as 0.1 m / s, which also prevents numerical singularities with zero denominator in subsequent calculations.

[0045] Normalized wind speed after clamping The calculation formula is: in, Normalized wind speed is equal to the ambient air transport speed. Compared with standard air transport speed The ratio; The minimum wind speed threshold is set to 0.1 in this embodiment, corresponding to an actual wind speed of 0.2 m / s.

[0046] After determining the aforementioned physical quantities, the second risk factor calculation unit 202 determines the basic spray flow rate level based on the average pipeline pressure and the instantaneous flow fluctuation based on the pressure pulsation coefficient. Specifically, based on the orifice outflow principle, the basic spray flow rate level is proportional to the square root of the average pipeline pressure; simultaneously, pressure pulsation causes instantaneous flow fluctuations, which need to be corrected in the risk calculation.

[0047] Based on the basic spray flow rate level, instantaneous flow rate fluctuations, and the ambient air transport velocity after clamping, the second risk factor calculation unit 202 determines the stacking risk factor. For example, the calculation formula for the stacking risk factor F_heap is: in, Characterizes the trend of spray baseline flow rate level as a function of pressure; This is a flow pulsation correction term. The flow pulsation calibration coefficient, in this embodiment, is set to 1.0, used to characterize the instantaneous flow surge caused by pressure ripple; the denominator is... Characterizes the environment's physical dilution ability of water mist; This is a dimensionless parameter; a larger value indicates a greater excess of water volume injected into the local space per unit time relative to the environment's dissipation capacity, and a higher degree of water vapor congestion. Optionally, the flow pulsation calibration coefficient... The methods for obtaining the data include: measuring the instantaneous peak flow rate under different pressure pulsation conditions using a flow meter, fitting the relationship between the pressure pulsation coefficient and the flow fluctuation amplitude, and determining... The value of .

[0048] Based on the above technical solution, this embodiment quantifies the antagonistic relationship between spray supply rate and environmental transport capacity at the macroscopic field scale by establishing an accumulation risk factor, enabling the system to identify the risk of local water mist accumulation caused by insufficient environmental wind speed, and providing a macroscopic decision-making basis for subsequent decoupling control.

[0049] like Figure 2As shown, in one possible implementation, the risk calculation unit 102 further includes an index synthesis subunit 203, which is used to: calculate the product of the particle size risk factor and the accumulation risk factor; obtain the installation height of the spray nozzle and a pre-calibrated comprehensive calibration constant; the comprehensive calibration constant is a constant determined by back-calculation based on the rated operating parameters of the spray system and the critical wetting state under standard operating conditions, and is used to perform benchmark normalization for different system configurations; determine the height adjustment coefficient based on the installation height and the comprehensive calibration constant; and adjust the product based on the height adjustment coefficient to determine the ground wetting index.

[0050] In some embodiments, the index synthesis subunit 203 first calculates the product of the particle size risk factor and the packing risk factor. Wherein, the particle size risk factor... Characterizing the risk of microscopic particle size degradation, stacking risk factor It represents macroeconomic accumulation risk, and the product of the two reflects the combined effect when the two risks work together.

[0051] Following this, the exponential synthesis subunit 203 acquires the installation height of the spray nozzle and a pre-calibrated comprehensive calibration constant. The installation height is the vertical distance from the nozzle to the ground measured on-site during system installation; in this embodiment, it is set to 2.5 meters. This parameter serves as a fixed physical constraint input controller, characterizing the maximum theoretical time window for droplets to settle from the nozzle outlet to the ground. The comprehensive calibration constant is a constant determined by back-calculation based on the rated operating parameters of the spray system and the critical wetting state under standard operating conditions. It is used to eliminate benchmark differences caused by different equipment specifications and achieve benchmark normalization between different system configurations; in this embodiment, it is set to 2.0 meters based on standard operating condition test data. Optionally, the comprehensive calibration constant... The methods for obtaining the value include: under rated pressure, no wind, and critical humidity conditions, experimentally determining the actual critical humidity point, and then using the formula... Determining the comprehensive calibration constant by reverse calculation .

[0052] Based on the installation height and comprehensive calibration constant, the exponential synthesis subunit 203 determines the height adjustment coefficient. This height adjustment coefficient reflects the physical constraint of the nozzle's height above the ground on droplet settling time; the higher the height, the longer the droplets have time to remain suspended in the air, theoretically increasing the chances of evaporation and correspondingly lowering the risk of wetting.

[0053] The index synthesis subunit 203 determines the ground moisture index by adjusting the product based on an altitude adjustment coefficient. For example, the ground moisture index... The calculation formula is: in, This is the system comprehensive calibration constant, in meters; The installation height of the spray nozzle is in meters. Particle size risk factor; To accumulate risk factors; This is a dimensionless comprehensive criterion, and its value directly corresponds to the current humidity risk level. In this embodiment, when A value <0.8 indicates a safe zone, signifying sufficient environmental absorption capacity; when 0.8 ≤ A value <1.0 indicates a warning zone, suggesting a slight risk of flux accumulation; when A value ≥1.0 indicates a danger zone, meaning the ground is highly susceptible to wetting.

[0054] Based on the above technical solution, this embodiment introduces the nozzle installation height as a physical constraint parameter, and synthesizes the micro-particle size risk and macro-accumulation risk into a unified ground wetness index, enabling the system to make hierarchical control decisions based on a single comprehensive criterion, simplifying the control logic while ensuring the comprehensiveness of risk assessment.

[0055] In one possible implementation, the control unit 103 is specifically configured to: maintain the current operating frequency of the water pump and the current duty cycle of the solenoid valve when the ground humidity index is lower than a second threshold; maintain the current operating frequency of the water pump and reduce the duty cycle according to the ground humidity index when the ground humidity index is greater than or equal to the second threshold and less than the first threshold; and increase the operating frequency and reduce the duty cycle when the ground humidity index is greater than or equal to the first threshold; wherein the second threshold is less than the first threshold.

[0056] Specifically, when the ground humidity index is below the second threshold, the control unit 103 maintains the current operating frequency of the water pump and the current duty cycle of the solenoid valve. The second threshold is less than the first threshold, and in this embodiment, it is set to 0.8. When the system detects that the ground humidity index is below this threshold, it indicates that the current environmental absorption capacity is sufficient and the hydraulic fluctuations in the pipe network are within a controllable range. At this time, the system executes a parameter maintenance strategy to maximize the continuity of the landscape fog effect and avoid unnecessary parameter fluctuations that could cause wear and tear on the equipment.

[0057] When the ground humidity index is greater than or equal to the second threshold and less than the first threshold, the control unit 103 maintains the current operating frequency of the water pump and adjusts the duty cycle according to the ground humidity index. In this embodiment, the first threshold is set to 1.0. When the system detects that the ground humidity index is within this range, it indicates that the main humidity risk comes from the total spray volume slightly exceeding the environment's dilution capacity, but the atomized particle size is still within a safe range. At this time, there is no need to change the pressure; only a fine-tuning of the flux is required. The system maintains a constant water pump operating frequency to maintain stable pipeline pressure and consistent basic particle size. Simultaneously, based on the current risk value, it linearly reduces the duty cycle of the solenoid valve in an inverse relationship. By reducing the effective spray duration per unit time, it linearly reduces the macroscopic water mist flux, thereby reducing the accumulation risk factor and causing the ground humidity index to fall below the safe threshold.

[0058] For example, duty cycle The calculation formula is: in, The duty cycle before adjustment. This represents the current ground moisture index. The adjusted duty cycle. To prevent the calculated duty cycle from overflowing or causing the valve to malfunction, the system performs a limiting process on the adjusted duty cycle to ensure that it is between the minimum dead zone duty cycle (e.g., 10%) and 100%.

[0059] When the ground humidity index is greater than or equal to the first threshold, the control unit 103 increases the operating frequency and decreases the duty cycle. This indicates a sudden high-risk operating condition, and simply reducing the flow rate is insufficient to eliminate the risk, because pressure troughs may cause a sharp deterioration in particle size, or extremely low wind speeds may cause regular flow to accumulate. The system triggers a forced intervention mode, executing the "frequency increase and valve reduction" decoupling action.

[0060] More specifically, when the ground humidity index is greater than or equal to a first threshold, the operating frequency of the water pump is increased to a preset multiple of the rated frequency; a pressure compensation term is calculated to compensate for the natural increase in flow rate caused by the frequency increase; a risk suppression term is calculated to reduce flux based on the degree to which the ground humidity index exceeds the first threshold; and the target duty cycle of the solenoid valve is calculated based on the pressure compensation term and the risk suppression term. The pressure compensation term is inversely proportional to the square root of the frequency increase factor; the risk suppression term is the ratio of the first threshold to the current ground humidity index, and the ratio does not exceed 1.

[0061] In other words, when the ground humidity index is greater than or equal to the first threshold, the control unit 103 increases the operating frequency of the water pump to a preset multiple of the rated frequency. Among them, the preset multiple In this embodiment, the value is set to 1.2, which means increasing the frequency to 1.2 times the rated frequency. The physical significance of this action is to use the increased high-pressure shear force to break up large droplets, significantly reducing the atomization particle size. At the same time, the strong turbulent entrainment effect induced by the high-pressure jet significantly accelerates the mass exchange rate between the droplets and the surrounding unsaturated air, effectively shortening the droplet's lifespan.

[0062] While increasing the operating frequency, the control unit 103 calculates a pressure compensation term to compensate for the natural increase in flow rate caused by the frequency increase. According to the orifice outflow principle, an increase in pressure will cause a natural increase in flow rate. This pressure compensation term is used to accurately offset the increase in physical flow rate caused by the frequency increase, maintaining the basic flux unchanged.

[0063] For example, the pressure compensation term is inversely proportional to the square root of the operating frequency increase factor. When the operating frequency is increased to the rated frequency... When the pressure increases by a factor of two, the corresponding pressure increase is also [missing information]. According to the orifice outflow formula, times, The traffic will naturally increase to the original level. Therefore, the pressure compensation item is [number] times ... .

[0064] Simultaneously, the control unit 103 calculates a risk mitigation term for flux reduction based on the degree to which the surface moisture index exceeds a first threshold. This risk mitigation term further forces flux reduction based on the current degree of risk exceeding the threshold, ensuring that the surface moisture index quickly converges below a safe threshold.

[0065] For example, the risk mitigation term = ;in, The target ground moisture index is set to 0.8 in this embodiment.

[0066] Based on the pressure compensation term and the risk suppression term, the control unit 103 calculates the target duty cycle of the solenoid valve. For example, the formula for calculating the target duty cycle is: Among them, the first item This is a pressure compensation item, used to offset the natural increase in traffic caused by the frequency increase; the second item... This is a risk mitigation term used to forcibly reduce flux based on the degree of exceedance.

[0067] Based on the above technical solution, this embodiment establishes a three-level control strategy based on the ground moisture index, realizing a smooth transition from safe maintenance to flow fine-tuning and then to forced intervention. This ensures both the continuity of landscape effects under normal working conditions and the safety of ground drying under high-risk working conditions.

[0068] like Figure 1As shown, in one possible implementation, the system further includes a start control unit 105, used to: set the average pressure of the pipeline network to the rated pressure value and the pressure pulsation coefficient to zero when the system is shut down; calculate the theoretical ground humidity index by combining real-time environmental meteorological data; allow the system to start when the theoretical ground humidity index is lower than the start threshold; and prohibit the system from starting when the theoretical ground humidity index is greater than or equal to the start threshold.

[0069] In other words, when the system is in a standby state, the water pump is not running and the pipeline has no pressure. If sensor readings are used directly for calculation at this time, the average pressure of the pipeline will be close to zero, which will lead to divergence in the calculation of particle size risk factors or meaningless ground moisture index. In order to prevent the system from blindly starting up in an unsuitable environment and causing immediate wetlands, the start control unit 105 performs a start access check based on theoretical preset values.

[0070] Specifically, when the system is shut down, the start control unit 105 sets the average pressure of the pipeline network to the rated pressure value and the pressure pulsation coefficient to zero. At this time, the inputs in the calculation model are forcibly assigned the rated operating parameters under the ideal pulsation-free state, while the meteorological data still uses real-time collected values.

[0071] Based on real-time environmental meteorological data, the control unit 105 calculates the theoretical ground humidity index. This theoretical ground humidity index represents the theoretical risk value of "whether the current environment can fully absorb the system if it is started now with rated parameters," reflecting the constraint of the current environmental severity (such as calm winds or high humidity) on system startup.

[0072] When the theoretical ground humidity index is lower than the start-up threshold, the start-up control unit 105 allows the system to start. In this embodiment, the start-up threshold is set to 0.9. At this time, the system determines that the environment has the capacity to absorb the moisture, controls the water pump to start at the rated frequency, and controls the solenoid valve to open at the default duty cycle.

[0073] When the theoretical ground humidity index is greater than or equal to the start-up threshold, the start-up control unit 105 prevents the system from starting. At this time, the system determines that the current environment is harsh, prohibits starting, and remains in standby mode, while triggering an alarm to notify the operator.

[0074] Based on the above technical solution, this embodiment introduces a theoretical risk prediction mechanism during the startup phase, which realizes a smooth transition and risk control from the static state to the operational state, avoids the phenomenon of wetlands upon startup caused by blind startup, and improves the environmental adaptability and intelligence level of the system.

[0075] like Figure 3As shown, in one possible implementation, the data acquisition unit 101 further includes a high-frequency pressure sensor 1011 and a meteorological monitoring unit 1012. The high-frequency pressure sensor 1011 is located at the pump station outlet and is used to collect pipeline pressure data; the meteorological monitoring unit 1012 is located at the center of the spray area and is used to collect environmental meteorological data including wind speed, temperature, and humidity.

[0076] Optionally, the sampling frequency of the high-frequency pressure sensor 1011 should be no less than 200Hz. It should be installed at the pump station outlet main pipe, preferably on a straight pipe section within 5 meters of the high-pressure plunger pump outlet. This location is the source of pressure pulsations in the entire pipeline network, enabling the most accurate capture of hydraulic ripples generated by the mechanical reciprocating motion of the plunger pump, thus avoiding the attenuation and smoothing effect of long-distance pipeline damping on the high-frequency pulsation signal.

[0077] The meteorological monitoring unit 1012 includes an ultrasonic anemometer and a temperature and humidity transmitter, installed at the geometric center of the spray coverage area, at a height of 2.0 to 3.0 meters above the ground. This location is in the main hang and evaporation area of ​​the fog droplets, and the data collected therein can represent the actual transport and absorption capacity of the ambient airflow for water mist.

[0078] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0079] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A kind of intelligent adjustment system of maintenance spray for landscape, it is characterized in that, The system includes: The data acquisition unit is used to collect pipeline pressure data at the pump station outlet and environmental meteorological data in the spray area; The risk calculation unit is used to calculate the particle size risk factor and the accumulation risk factor based on the pipeline pressure data and the environmental meteorological data, and to synthesize the particle size risk factor and the accumulation risk factor into a ground wetness index; the particle size risk factor is used to characterize the risk of droplet size deterioration due to pressure pulsation; the accumulation risk factor is used to characterize the risk of local accumulation of water mist due to insufficient environmental transport capacity. The control unit is used to increase the operating frequency of the water pump to increase the pipeline pressure and reduce the duty cycle of the solenoid valve to reduce the spray flow when the ground humidity index reaches a first threshold.

2. The intelligent adjustment system for maintenance spraying in landscaping according to claim 1, characterized in that, The risk calculation unit includes a first risk factor calculation unit, which is used for: The pressure pulsation coefficient and the average pressure of the pipeline network are determined based on the pipeline network pressure data. The air moisture absorption potential is determined based on the aforementioned environmental meteorological data; The positive driving effect of the average pressure of the pipeline network and the moisture absorption potential of the air on droplet evaporation was determined. The negative hindering effect of the pressure pulsation coefficient on the generation of large, difficult-to-evaporate liquid droplets was determined; wherein the negative hindering effect increases non-linearly with the pressure pulsation coefficient. The particle size risk factor is calculated based on the competitive relationship between the positive driving force and the negative hindering force.

3. The intelligent adjustment system for maintenance spraying in landscaping according to claim 1, characterized in that, The risk calculation unit includes a second risk factor calculation unit, which is used for: The average pressure and pressure pulsation coefficient of the pipeline network are determined based on the pipeline network pressure data. The ambient air transport velocity is determined based on the environmental meteorological data, and a lower limit clamping process is applied to the ambient air transport velocity. The basic spray flow rate level is determined based on the average pressure of the pipeline network, and the instantaneous flow rate fluctuation is determined based on the pressure pulsation coefficient. The accumulation risk factor is determined based on the spray base flow rate level, the instantaneous flow rate fluctuation, and the ambient air transport velocity after clamping.

4. The intelligent adjustment system for maintenance spraying in landscaping according to claim 1, characterized in that, The risk calculation unit includes an index synthesis subunit, which is used for: Calculate the product of the particle size risk factor and the packing risk factor; The installation height of the spray nozzle and the pre-calibrated comprehensive calibration constant are obtained; the comprehensive calibration constant is a constant determined by back-calculation based on the rated operating parameters of the spray system and the critical wetting state under standard operating conditions, and is used to perform benchmark normalization for different system configurations; Based on the installation height and the comprehensive calibration constant, a height adjustment coefficient is determined; The product is adjusted based on the height adjustment coefficient to determine the ground moisture index.

5. The intelligent adjustment system for maintenance spraying in landscaping according to claim 1, characterized in that, The control unit is specifically used for: When the ground moisture index is below the second threshold, maintain the current operating frequency of the water pump and the current duty cycle of the solenoid valve. When the ground moisture index is greater than or equal to the second threshold and less than the first threshold, the current operating frequency of the water pump is maintained, and the duty cycle is reduced according to the ground moisture index. When the ground moisture index is greater than or equal to the first threshold, the operating frequency is increased and the duty cycle is decreased; wherein the second threshold is less than the first threshold.

6. The intelligent adjustment system for maintenance spraying in landscaping according to claim 5, characterized in that, The control unit is specifically used for: When the ground moisture index is greater than or equal to the first threshold, the operating frequency of the water pump is increased to a preset multiple of the rated frequency; Calculate the pressure compensation term used to compensate for the natural increase in traffic caused by the frequency increase; Calculate a risk mitigation term for flux reduction based on the extent to which the ground moisture index exceeds the first threshold; Based on the pressure compensation term and the risk suppression term, the target duty cycle of the solenoid valve is calculated.

7. The intelligent adjustment system for maintenance spraying in landscaping according to claim 6, characterized in that, The pressure compensation term is inversely proportional to the square root of the operating frequency increase factor; The risk suppression term is the ratio of the first threshold to the current ground moisture index, and the ratio does not exceed 1.

8. The intelligent adjustment system for maintenance spraying in landscaping according to claim 1, characterized in that, The system also includes a start control unit, used for: When the system is shut down, set the average pressure of the pipeline network to the rated pressure value and the pressure pulsation coefficient to zero. The theoretical ground humidity index is calculated by combining real-time environmental meteorological data; The system is allowed to start when the theoretical ground humidity index is lower than the start-up threshold; The system is prohibited from starting when the theoretical ground humidity index is greater than or equal to the start-up threshold.

9. The intelligent adjustment system for maintenance spraying in landscaping according to claim 1, characterized in that, The data acquisition unit includes: A high-frequency pressure sensor is installed at the pump station outlet to collect the pipeline pressure data; A meteorological monitoring unit is located at the center of the spray area and is used to collect the environmental meteorological data, including wind speed, temperature and humidity.

10. The intelligent adjustment system for maintenance spraying in landscaping according to claim 1, characterized in that, The system also includes a data preprocessing unit for: Based on the collected pipeline pressure data, the average pressure value and pressure pulsation coefficient within the sliding window are calculated. Based on the collected environmental meteorological data, the air transport velocity and air moisture absorption potential are calculated. The average pressure value, air transport speed, and air moisture absorption potential are each normalized by quoting their corresponding benchmark values.

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