Grain Count Detection Using Rising Edge Signal Analysis
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Solution Overview
Problem
Existing methods for determining grain count in harvesting machines are inaccurate due to environmental influences and machine parameters, requiring complex comparisons and leading to inconsistent results.
Innovation Solution
A method that records rising edges of measurement signals from structure-borne noise sensors to determine grain count, preprocessing signals with smoothing, filtering, and rectification, and differentiating the envelope to generate a pulse train, which allows for precise grain counting independent of environmental and machine factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the partial area below the amplitude of a measurement signal is used to determine grain count, then the measurement method is simple, but the measurement precision deteriorates due to environmental influences and machine parameters affecting vibration amplitude
Solution Approach 1:
The patent changes the evaluation parameter from vibration amplitude (which is affected by environmental factors) to the number of rising edges in the measurement signal. This parameter transformation eliminates the influence of grain moisture, temperature, and humidity on the measurement, thereby resolving the contradiction between simple measurement method and accurate grain count determination
Solution Approach 2:
The patent uses a simple structure-borne noise sensor with piezo elements that converts mechanical vibrations directly into electrical signals. This inexpensive sensor provides reliable rising edge detection without requiring complex reference signal comparisons, achieving accurate grain counting through a simple, cost-effective measurement approach
2Measurement precision
If the measurement signal is compared with a characteristic reference signal to count particles, then measurement precision may be improved, but the device complexity increases due to the need for reference signal generation and comparison
Solution Approach 1:
The patent extracts only the rising edges from the measurement signal for grain count determination, discarding the amplitude information that requires complex reference signal comparison. This extraction approach simplifies the measurement method while maintaining accuracy by focusing only on the essential feature (rising edges) that indicates grain impact
Solution Approach 2:
The measurement signal itself contains all necessary information for accurate grain counting through its rising edges. The system does not require external reference signals or complex comparison mechanisms - the signal's inherent characteristics (rising edges) are sufficient for precise grain count determination, making the system self-sufficient and simpler
3Ease of operation
If vibration amplitude is used to determine grain number, then the measurement approach is straightforward, but reliability deteriorates because grains with different amplitudes are weighted differently due to environmental influences
Solution Approach 1:
The patent transforms the measurement parameter from vibration amplitude (which varies with environmental conditions) to the count of rising edges in the signal. This parameter change ensures that each grain impact is counted equally regardless of amplitude variations caused by moisture, temperature, or humidity, thereby improving measurement reliability while maintaining operational simplicity
Solution Approach 2:
The patent segments the measurement signal into discrete rising edge events, where each rising edge represents a individual grain impact. This segmentation approach treats all grain impacts uniformly without weighting by amplitude, ensuring consistent and reliable grain count determination across varying environmental conditions
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 approach enables precise grain counting by filtering out noise and non-grain components, reducing errors and improving accuracy, allowing for optimized adjustment of harvesting machine operations to increase throughput and reduce grain losses.
Implementation Method 1
Its functional principle is based on recording the impact energy of a grain hitting an impact surface. This leads to mechanical vibrations, which are converted into an electrical measurement signal by means of a sound transducer/piezo element.
Data Source
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Figure 3(a)~3(c)
AI summary
A method for determining the grain count (26) of a harvested crop stream (50-58), wherein a sensor (23) of a measuring device (22) detects grains impacting a surface of the sensor (23) by means of a measurement signal (27), and a processing unit (30) of the measuring device (22) is configured to determine the grain count (26) based on the measurement signal (27), wherein the rising edges (37) of the measurement signal (27) are detected and form a measure of the grain count (26). The present invention further relates to a measuring device (22) for determining the grain count (26) using such a method, and to a self-propelled harvesting machine (2) with such a measuring device.