Harvester Obstacle Detection With Height-Based Sensor Selection
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Solution Overview
Problem
Existing harvesting machines face challenges in accurately detecting obstacles forward of the machine body due to the upward and downward swinging of the harvesting unit, and imaging systems are prone to reduced accuracy in fog or dust conditions.
Innovation Solution
Implementing multiple sensors at different vertical positions, with a selection unit to choose the most accurate sensor based on the harvesting unit's height position, and combining imaging with alternative detection methods like temperature distribution sensors or short-wavelength infrared sensors to enhance obstacle detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single sensor is used for obstacle detection, then the device complexity is low, but the obstacle detection accuracy deteriorates when the harvesting unit height changes
Solution Approach 1:
The obstacle detection function is segmented across multiple sensors positioned at different heights. Each sensor covers a specific vertical detection range, and the system divides the overall detection task among these segmented sensor units to maintain accuracy across varying harvesting unit heights
Solution Approach 2:
The system dynamically selects which sensor data to use based on the current harvesting unit height position. The selection unit adapts the detection system in real-time by switching between different sensor data sources according to the vertical position of the harvesting unit, ensuring optimal detection accuracy for each operational state
2Reliability
If imaging devices are used for obstacle detection, then the detection coverage is comprehensive, but the detection accuracy deteriorates in fog or dust conditions
Solution Approach 1:
The system merges multiple types of detection devices including imaging devices, temperature distribution sensors, and short-wavelength infrared sensors. This combination allows the system to switch between different detection modalities depending on environmental conditions, maintaining reliability when fog or dust degrades imaging performance
Solution Approach 2:
The system changes the detection parameter by switching from visible light imaging to thermal infrared detection when environmental conditions deteriorate. Temperature distribution sensors and short-wavelength infrared sensors detect obstacles through thermal radiation rather than reflected light, making them immune to fog and dust interference
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
Ensures accurate obstacle detection regardless of the harvesting unit's height position and improves detection accuracy even in adverse weather conditions, enabling reliable operation and control.
Implementation Method 1
temperature distribution sensor that detects a temperature distribution in a detection area
Implementation Method 2
short-wavelength infrared sensor that detects short-wavelength infrared light in a detection area
Data Source
AI summary
A harvesting machine includes: a machine main body; a harvesting unit provided forward of the machine main body and capable of swinging upward and downward relative to the machine main body; a height detection unit capable of detecting a height position at which the harvesting unit is located; and an obstacle detection unit capable of detecting an obstacle located forward thereof in a travel direction. The obstacle detection unit includes: a first sensor and a second sensor provided at different positions in a vertical direction, and output detection information regarding a detection area located forward thereof in the travel direction; a selection unit that selects at least either the detection information from the first sensor or the detection information from the second sensor based on the height position of the harvesting unit and a determination unit that determines the obstacle based on the detection information selected by the selection unit.