Forage Harvester Corn Cracker Control via Multidimensional Map
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Solution Overview
Problem
Existing forage harvesters face limitations in achieving consistent processing quality of grain components due to sequential adjustments based on chaff length and moisture, which are expensive and time-consuming, and do not consider interdependencies of multiple parameters during the harvesting process.
Innovation Solution
A forage harvester with a driver assistance system that uses a multidimensional characteristic map to control the corn cracker's machine parameters, such as rotational speed and gap width, to achieve a predetermined processing quality by considering multiple input parameters like chaff length, moisture, and throughput, allowing for global optimization and adaptive adjustments during the harvesting process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the corn cracker is adjusted to reliably comminute all grain components, then processing quality is improved, but energy consumption increases unnecessarily
Solution Approach 1:
The system dynamically adjusts the gap width of the corn cracker based on real-time measurements of chaff length and moisture content. The driver assistance system continuously monitors these parameters and modifies the cracker settings accordingly, transitioning from static to dynamic control to optimize energy consumption while maintaining processing quality.
Solution Approach 2:
The system changes physical parameters (gap width, rotational speed) of the corn cracker based on measured conditions. By adjusting these parameters according to actual chaff length and moisture content, the system avoids unnecessary energy consumption while ensuring adequate comminution of grain components.
2Manufacturing precision
If sequential adjustment of gap width based on chaff length and moisture is used, then processing quality can be improved, but the system does not consider interdependencies of multiple parameters
Solution Approach 1:
The system merges multiple adjustment considerations (chaff length, moisture content, and their interdependencies) into a single integrated control routine. The driver assistance system evaluates all parameters simultaneously and determines optimal gap width adjustments that account for the interactions between different factors, rather than treating them separately.
Solution Approach 2:
The system implements feedback control by continuously measuring chaff length and moisture content, comparing these measurements against target values, and adjusting the corn cracker settings accordingly. This closed-loop control ensures that processing quality is maintained while accounting for the complex interdependencies between multiple parameters.
3Manufacturing precision
If optical recognition of processing quality is used to regulate gap width, then processing quality can be maintained, but the method is expensive and time-consuming
Solution Approach 1:
The system performs preliminary measurements of chaff length and moisture content before the material reaches the corn cracker. Based on these advance measurements, the driver assistance system pre-adjusts the gap width settings, eliminating the need for time-consuming optical recognition and quality verification during the harvesting process.
Solution Approach 2:
The system replaces expensive and time-consuming optical recognition systems with simpler mechanical or electromagnetic sensors that measure chaff length and moisture content. This substitution maintains processing quality control while significantly reducing cost and time requirements.
Data Source
AI summary
A forage harvester with at least one work assembly is disclosed. The forage harvester has a corn cracker to process grain components and a driver assistance system. The driver assistance system controls the corn cracker by adjusting the machine parameters of the corn cracker. In particular, the driver assistance system has an optimization model which includes a multidimensional characteristic map that represents a relationship between a processing quality of the grain components and at least three parameters that comprise an input parameter representing a current harvesting process state and at least one machine parameter of the corn cracker as an output parameter. Thus, the driver assistance system determines the output parameter in the control routine during the harvesting process based on the varying input parameter from the optimization model and adjusts it in the corn cracker to achieve a uniform given processing quality of the grain components during the harvesting process.

