Fertilizer Property Detection via Centralized Spreading Data
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Solution Overview
Problem
Existing methods for determining fertilizer type-specific setting parameters are time-consuming and costly, and previously determined parameters become unsuitable due to changes in fertilizer properties over time or during storage, leading to suboptimal spreading results in spreaders without monitoring devices.
Innovation Solution
A method that uses an evaluation device to collect and analyze application information from multiple spreaders to determine if fertilizer properties have changed, allowing for the adjustment of setting parameters to ensure optimal spreading results, even in spreaders without monitoring devices, by evaluating changes in composition, grain size, bulk density, and moisture content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If spreading tests are conducted under laboratory conditions to determine fertilizer type-specific setting parameters, then suitable setting parameters can be obtained, but the parameters become unsuitable over time due to changes in fertilizer properties
Solution Approach 1:
The system continuously collects actual spreading data from multiple spreaders and compares it with the intended spreading parameters. This feedback loop enables detection of deviations caused by fertilizer property changes, allowing for dynamic identification of parameter obsolescence without requiring repeated laboratory tests.
Solution Approach 2:
The evaluation device automatically analyzes spreading data and identifies when setting parameters need updating, eliminating the need for manual intervention or repeated laboratory testing. The system self-monitors and self-updates parameter validity based on real-world performance data.
2Reliability
If spreading tests are conducted under laboratory conditions to determine fertilizer type-specific setting parameters, then suitable setting parameters can be obtained, but the process requires a considerable amount of time and money
Solution Approach 1:
Instead of conducting physical spreading tests under laboratory conditions, the system uses digital copies and simulations of spreading processes based on collected field data. This virtual evaluation approach eliminates the need for repeated physical tests while maintaining parameter reliability.
Solution Approach 2:
The system automatically performs the evaluation of setting parameters using collected spreading data, eliminating the need for manual laboratory testing. This self-evaluating process significantly reduces both time and cost while maintaining parameter accuracy.
3Reliability
If real-time monitoring during application is implemented, then changes in fertilizer properties can be detected, but the solution can only be implemented with spreaders that have a device for monitoring the spread of fertilizer
Solution Approach 1:
The evaluation device serves multiple spreaders simultaneously, consolidating monitoring capabilities into a centralized system. This allows spreaders without individual monitoring devices to benefit from the collective data gathered by the network, reducing per-unit complexity while maintaining detection capability.
Solution Approach 2:
The evaluation device acts as an intermediary that collects data from multiple sources and processes it centrally. This mediator approach allows spreaders to participate in the monitoring network without each requiring full monitoring functionality, reducing individual device complexity while achieving system-wide detection capability.
4Manufacturing precision
If setting parameters determined under laboratory conditions are used, then optimal spreading results can be achieved initially, but the desired lateral distribution and application rate cannot be implemented when fertilizer properties change
Solution Approach 1:
The system transitions from static laboratory-determined parameters to dynamic parameter validation through continuous monitoring. By constantly comparing actual spreading results with intended parameters, the system adapts to fertilizer property changes in real-time, maintaining precision without requiring fixed pre-determined values.
Solution Approach 2:
The continuous comparison between intended and actual spreading parameters creates a feedback mechanism that detects when laboratory-determined parameters become inadequate. This feedback enables the system to identify parameter obsolescence and trigger updates, maintaining spreading precision despite fertilizer property variations.
Data Source
Figure 1
AI summary
The invention relates to a method for recording fertilizer properties, comprising the steps of: receiving application information for a plurality of different application processes of a fertilizer type from different transmitters (100a-100c) by an evaluation device (10) and evaluating the application information received from the different transmitters to record properties of the fertilizer type by the evaluation device.