Sprayer Modeling Parameter Auto-Determination
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Solution Overview
Problem
Current spreading systems for soil or crop treatment products face challenges in accurately determining modeling parameters, leading to metering errors, overconsumption, and inability to detect nozzle clogging, due to reliance on manufacturer-provided coefficients and lack of pressure measurement at the nozzle level.
Innovation Solution
An automatic method for determining a modeling parameter by setting a reference nozzle supply pressure, measuring flow rate and pressure, and calculating the coefficient of proportionality, which is then used to adjust the supply pressure and detect potential nozzle clogging, incorporating a flow meter and pressure sensor for precise control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manufacturer-provided proportionality coefficients are used to model the spreading system, then the system can operate without complex calibration procedures, but the accuracy of the modeling parameter determination deteriorates due to variations in actual nozzle performance and system configuration
Solution Approach 1:
The spreading system performs self-calibration by automatically measuring its own flow rate and pressure characteristics during normal operation. The system uses its integrated flow meter and pressure sensor to determine the actual proportionality coefficient between flow rate and pressure, eliminating the need for external calibration equipment or manufacturer-provided coefficients. This self-service approach resolves the contradiction by enabling accurate parameter determination without complicating the operation process.
Solution Approach 2:
The system continuously monitors actual flow rate and pressure measurements during spreading operations and uses this feedback to calculate and update the proportionality coefficient. The control unit receives real-time data from the flow meter and pressure sensor, processes this information to determine the actual system characteristics, and adjusts the modeling parameters accordingly. This feedback mechanism enables continuous improvement of modeling accuracy while maintaining ease of operation.
2Measurement precision
If pressure and flow rate are measured during product projection to determine modeling parameters, then the proportionality coefficient can be calculated, but overconsumption of coating product occurs due to lack of precise control
Solution Approach 1:
The system performs preliminary calibration measurements during normal spreading operations to determine the proportionality coefficient before actual product application. By measuring flow rate and pressure characteristics in advance and using these data to calculate the correct proportionality coefficient, the system establishes accurate modeling parameters prior to full-scale product projection. This preliminary action prevents overconsumption by ensuring that pressure control is based on precise, actual system characteristics rather than theoretical values.
Solution Approach 2:
The system continuously monitors actual flow rate and pressure measurements during spreading operations and uses this feedback to calculate and update the proportionality coefficient. The control unit receives real-time data from the flow meter and pressure sensor, processes this information to determine the actual system characteristics, and adjusts the modeling parameters accordingly. This feedback mechanism enables continuous improvement of modeling accuracy while maintaining ease of operation.
3Measurement precision
If the number of nozzles per section is memorized to accurately measure actual volume spread, then precise application rate control is achieved, but the device complexity increases due to the need to store and manage nozzle configuration data
Solution Approach 1:
The system automatically determines the actual volume spread by measuring flow rate and pressure characteristics during operation, eliminating the need to store or manage nozzle configuration data. The flow meter and pressure sensor provide real-time data that the control unit processes to calculate the proportionality coefficient and determine actual volume spread. This self-service approach resolves the contradiction by achieving precise measurement without requiring the system to memorize or manage complex nozzle configuration information.
4Ease of manufacture
If proportionality coefficient k is determined from manufacturer data, then the system can be configured without field calibration, but inaccuracies occur due to dispersion in actual nozzle coefficients compared to nominal values
Solution Approach 1:
The spreading system performs self-calibration by automatically measuring its own flow rate and pressure characteristics during normal operation. The system uses its integrated flow meter and pressure sensor to determine the actual proportionality coefficient between flow rate and pressure, eliminating the need for external calibration equipment or manufacturer-provided coefficients. This self-service approach resolves the contradiction by enabling accurate parameter determination without complicating the operation process.
Solution Approach 2:
The system continuously monitors actual flow rate and pressure measurements during spreading operations and uses this feedback to calculate and update the proportionality coefficient. The control unit receives real-time data from the flow meter and pressure sensor, processes this information to determine the actual system characteristics, and adjusts the modeling parameters accordingly. This feedback mechanism enables continuous improvement of modeling accuracy while maintaining ease of operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method allows for accurate determination of the modeling parameter, ensuring consistent dosing and detecting nozzle clogging, thereby improving the precision and efficiency of the spreading process without requiring operator expertise.
Implementation Method 1
measuring, using a flow meter, the flow rate of treatment product feeding the boom
Implementation Method 2
measuring the nozzle supply pressure
Implementation Method 3
a spray boom equipped with nozzles designed to project the product onto the soil or crop
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
The method involves setting (1001) supply reference pressure (Pr) for tubes. A product i.e. water, is pulverized (1002) using supply setpoint pressure of the tubes as the reference pressure and by measuring supply pressure of the tubes. Flow of pesticide to a slope is measured (1003) using a flow meter. A modeling parameter is calculated (1004) according to a value of the measured flow and a value of the measured supply pressure of the tubes or reference pressure. A value of the calculated parameter is corrected (1006) by taking account of density of the pesticide. Independent claims are also included for the following: (1) a method for controlling a system of spreading of pesticide of ground or culture (2) a spreading system.