Grain Loss Sensor Plate Frequency Analysis
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Solution Overview
Problem
Existing grain loss sensors in combine harvesters are inaccurate in distinguishing between grain and straw impacts, leading to inappropriate adjustments and inefficiencies in harvesting operations, as they fail to differentiate between similar frequency responses and are limited to assessing frequency ranges below 20 kHz.
Innovation Solution
A method and apparatus that analyze vibrations induced by impacts on a sensor plate, using variance calculations and frequency domain analysis up to 50 kHz to differentiate between grain, straw, and straw tip impacts, generating more accurate signals for grain loss and material other than grain (MOG) content, enabling better machine control and overloading prevention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prior art frequency filtering techniques are used to eliminate horizontally falling straw, then horizontally falling straw can be filtered, but vertically falling straw tips cannot be distinguished from grain impacts
Solution Approach 1:
The patent extends the frequency analysis from the traditional time domain to the frequency domain by implementing a Fast Fourier Transform (FFT) with analysis up to 50 kHz. This dimensional change in signal processing allows differentiation of vertically falling straw tips from grain impacts based on their distinct frequency signatures, resolving the limitation of prior art filtering techniques.
Solution Approach 2:
The patent changes the analysis parameters by implementing variance calculations over consecutive sub-periods and extending frequency analysis beyond 20 kHz to 50 kHz. These parameter changes enable the system to capture and distinguish the subtle frequency differences between various impact types that were previously indistinguishable within the limited 20 kHz range.
2Device complexity
If frequency analysis is limited to below 20 kHz, then processing is simpler, but accuracy in distinguishing grain from straw tips is insufficient
Solution Approach 1:
The patent transitions from time-domain analysis to frequency-domain analysis using FFT, extending the analysis bandwidth from 20 kHz to 50 kHz. This dimensional transformation in signal processing provides additional frequency information that improves measurement precision without proportionally increasing system complexity.
Solution Approach 2:
The patent replaces complex mechanical or hardware-based differentiation methods with computational signal processing techniques. By using digital signal processing algorithms including FFT and variance calculations, the system achieves high-precision impact type differentiation through software-based analysis rather than complex mechanical systems.
3Quantity of substance
If grain loss sensors are located downstream of the cleaning section, then they detect grain loss, but the detected grain is mingled with rejected material making differentiation difficult
Solution Approach 1:
The patent replaces physical separation methods with computational signal processing to differentiate grain from straw tips in the mixed material stream. By analyzing the frequency characteristics and variance patterns of impacts using FFT up to 50 kHz, the system can identify and quantify grain impacts even when mingled with rejected material from the cleaning section.
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
The solution significantly improves the accuracy of grain loss detection, allowing for precise adjustment of harvesting machine sub-systems and preventing overloading by distinguishing between different types of impacts, resulting in enhanced operational efficiency and reduced grain loss.
Implementation Method 1
The sensor plate includes mounted thereon or embedded below its surface one or more piezoelectric crystals. As grain falls onto the plate the distortion of the latter induces voltages in the piezoelectric crystals.
Data Source
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AI summary
A method of determining the content of a desired component in a stream of material including two or more types of component, comprises the steps of: causing or permitting a said stream, comprising plural particles of material, to impact a sensor member (14) located in a path of the material thereby inducing vibration of the sensor member; analysing vibrations of the sensor member and from the analysis determining whether individual impacts caused by the stream are one of any two or more types selected from three possible impact types; and performing an operation based on the result of the analysis. The invention is of particular use in determining the content of material streams in combine harvesters.