Master Harvester Optimization Data Distribution
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Solution Overview
Problem
Existing methods for optimizing agricultural harvesting processes in networks of heterogeneous harvesting machines fail to adequately account for deviations between master and slave harvesters, leading to inefficient operation and the need for manual adjustments by drivers without necessary technical tools.
Innovation Solution
A method where a self-optimizing master harvester generates and transmits optimization data, including user specifications and machine parameters, to slave harvesters, allowing them to adopt and further optimize their settings based on a predetermined strategy, with optional self-optimization capabilities and modular driver assistance systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If optimized machine parameters are directly transferred from master harvester to slave harvesters, then the efficiency of harvesting process is improved, but the adaptability to heterogeneous machine designs deteriorates
Solution Approach 1:
The patent applies local quality by transferring only those optimization parameters that are relevant and applicable to each specific slave harvester's design configuration. The master harvester identifies and transmits a subset of optimized parameters tailored to the individual characteristics of each slave machine, rather than applying a universal set of parameters to all harvesters regardless of their design differences.
Solution Approach 2:
The patent implements parameter changes by dynamically adjusting and optimizing machine parameters based on the specific design characteristics of each slave harvester. The system modifies parameter sets according to the receiving machine's capabilities and configuration, enabling the same optimization strategy to be effectively applied across heterogeneous machine designs through parameter adaptation.
2Adaptability or versatility
If slave harvesters are equipped with full self-optimization capabilities, then the adaptability to individual machine characteristics is improved, but the device complexity increases
Solution Approach 1:
The patent applies self-service by enabling slave harvesters to automatically receive, process, and implement optimized machine parameters from the master harvester without requiring manual intervention from operators. The system performs self-optimization through automated parameter transfer and application, reducing the need for complex manual configuration while maintaining adaptability to individual machine characteristics.
Solution Approach 2:
The patent implements universality by creating a standardized parameter transfer framework that can be applied across different harvester models and designs. The master harvester serves multiple slave machines with varying configurations using a universal optimization approach, while the slave harvesters universally accept and apply the transferred parameters according to their specific capabilities.
3Adaptability or versatility
If manual optimization by drivers is required for each slave harvester, then the adaptability to individual machines is improved, but the loss of time increases
Solution Approach 1:
The patent applies preliminary action by having the master harvester pre-calculate and transmit optimized machine parameters to slave harvesters before the slave machines begin their operations. This advance preparation eliminates the need for time-consuming manual optimization during field operations, as the parameters are already optimized and ready for immediate application.
Solution Approach 2:
The patent implements feedback by establishing a communication system where optimization results from the master harvester are continuously transmitted to slave harvesters. This feedback loop enables automatic parameter updates based on real-time or near-real-time optimization data, replacing manual adjustment processes and reducing the time drivers would otherwise spend on optimization tasks.
Data Source
Figure 1
AI summary
The invention relates to a method for carrying out an agricultural harvesting process on a field (1) by means of a network (2) of agricultural harvesting machines (3 - 7), wherein the harvesting machines (3 - 7) of the network (2) each have crop-processing working units which can be adjusted with machine parameters to adapt to the respective harvesting conditions, wherein the harvesting machines (3 - 7) of the network (2) communicate with each other via a wireless data network (8), wherein at least one master harvesting machine (3) of the network (2) is designed as a self-optimizing harvesting machine which has an optimization system (9) comprising a driver assistance system for the automated generation of machine parameters optimized with regard to its crop processing.It is proposed that optimization data, including user specifications and/or parameter settings, and optimized machine parameters generated by the optimization system based on the optimization data, be provided via the data network (8) and received by slave harvesters (4 - 7) of the system (2) from the master harvester (3).