Windrow Yield Estimation Using Sensor Profiles

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Solution Overview

Problem

Conventional yield monitoring systems used during harvesting are ineffective for crops placed in windrows, such as almonds and hay, as they fail to accurately estimate the volume or yield of these crops.

Innovation Solution

A system comprising a sensor on the harvesting machine that estimates the profile of a windrow, using technologies like 2D optical scanners, 3D ToF devices, or ultrasonic sensors, to determine cross-sectional areas and volumes, which are then used to generate georeferenced yield maps.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional yield monitors are used on combines, then yield monitoring is effective for crops like corn and wheat, but the monitors do not work well with crops that are placed in windrows

Engineering Contradiction:
Improveyield monitoring effectivenessVSAvoidcompatibility with windrow crops
Core Design Contradiction:
ReliabilityVSAdaptability or versatility

Solution Approach 1:

Instead of using conventional yield monitors on combines that work for harvested crops, the patent inverts the approach by placing sensors on the windrowing machine itself to monitor crops as they are being placed in windrows. This allows the system to capture data from the windrow formation process rather than attempting to adapt combine harvesters for windrow crops.

Inventive Principle:
Principle #13The other way round (Inversion)

Solution Approach 2:

The patent creates a universal yield monitoring solution that works for both harvested crops and windrow crops by using a multi-functional sensor system that can detect and measure different crop types in different harvesting configurations. The sensor system on the windrowing machine can handle various crop types (corn, wheat, hay, alfalfa) whether they are being harvested or windrowed.

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Measurement precision

If sensors are placed on the bottom of the harvesting machine to estimate windrow profiles, then cross-sectional area and volume can be determined, but the measurement of relatively small portions of the windrow must be extrapolated to the entire windrow

Engineering Contradiction:
Improvewindrow profile measurement accuracyVSAvoidincomplete windrow data
Core Design Contradiction:
Measurement precisionVSLoss of information

Solution Approach 1:

The patent uses feedback by continuously measuring windrow profiles as the machine moves along and using these measurements to continuously update and refine the estimated total volume. The system processes sequential profile data and uses integration methods to accumulate accurate total volume measurements from the series of partial measurements.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The system performs preliminary measurements of windrow profiles during the windrowing process itself, before the harvesting is complete. By measuring and recording profile data as the windrow is being formed, the system captures information that can be used to calculate total yield without requiring post-harvest measurement.

Inventive Principle:
Principle #10Preliminary action

3Loss of information

If georeferenced yield maps are generated from windrow volume data, then valuable crop management information is provided, but the system requires integration of sensor data with machine position data

Engineering Contradiction:
Improvecrop management informationVSAvoiddata integration requirements
Core Design Contradiction:
Loss of informationVSDevice complexity

Solution Approach 1:

The patent merges the sensor system that measures windrow profiles with the geographic position system that tracks machine location. By combining these two data streams into a single integrated system, the patent creates yield maps that correlate volume measurements with specific geographic locations, enabling precise crop management without requiring separate data collection and processing systems.

Inventive Principle:
Principle #5Merging (Combining)

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 method provides improved accuracy and quicker data acquisition of crop volume and yield, enabling better management of chemical and irrigation applications.

Implementation Method 1

a two-dimensional (2D) optical scanner configured to scan a laser beam across the width of the windrow and to receive reflected portions of the laser beam

Methodology Applied
Scientific EffectLaser: Laser

Implementation Method 2

scan a laser beam across the width of the windrow and to receive reflected portions of the laser beam

Methodology Applied
Scientific EffectLight reflection: Reflection

Implementation Method 3

a three-dimensional (3D) time of flight (ToF) optical device configured to emit radiation toward each of the segments of the windrow and to receive reflected portions of the radiation

Methodology Applied
Scientific EffectTime of flight: Time of Flight

Implementation Method 4

ultrasonic sensors configured to use sound waves to determine distances to the ground and to the windrow

Methodology Applied
Scientific EffectSound wave propagation: Sound

Data Source

PatentEP3649844B1Estimating yield of agricultural crops
Publication Date: 2022.08.24 TRIMBLE INC
  • EP3649844B1 patent drawingFigure 1A~1B
  • EP3649844B1 patent drawingFigure 2
  • EP3649844B1 patent drawingFigure 3

AI summary

Methods and systems for estimating volumes of agricultural crops are provided. A geographic position sensor (644, 1154) provides positions of a harvesting machine (608) as it gathers an agricultural crop (606) and places the crop on the ground in a windrow (610). A speed of the harvesting machine is determined using the geographic position sensor (644, 1154). Signals are received from a sensor system (622, 1152) disposed at a bottom of the harvesting machine (608). The signals are indicative of profiles of segments of the windrow (610) on the ground. Cross-sectional areas of the windrow (610) are estimated using the signals. Volumes of the agricultural crop are estimated using the speed of the harvesting machine (608) and the estimated cross-sectional areas of the windrow (610).