Forestry Vehicle Crane Log Identification
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Solution Overview
Problem
Current methods for identifying and matching harvested logs in the forestry industry are prone to errors due to reliance on skilled operators and are affected by external factors such as snow cover, leading to a need for improved accuracy and efficiency in log identification and matching.
Innovation Solution
A method and system using a forestry vehicle equipped with a crane and control unit that measures slew angles, boom angles, and positional data to precisely identify and match logs, incorporating sensors and imaging devices for enhanced accuracy, and calculates optimal engagement positions for the engagement unit based on log data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification and matching by skilled operators is used, then operational flexibility is maintained, but identification accuracy deteriorates due to human error and external factors like snow cover
Solution Approach 1:
The patent replaces the manual visual identification system with an automated optical measurement system. The system uses imaging devices to capture images of logs and automatically processes these images to identify and match logs with tree data, eliminating reliance on operator skills and visual conditions.
Solution Approach 2:
The patent introduces an automated control system as an intermediary between the logs and the operator. This control system processes imaging data, calculates positional information, and provides automated log identification, serving as a mediator that eliminates the direct dependency on operator visual assessment.
2Measurement precision
If automated identification using imaging devices and control units is implemented, then log identification accuracy improves, but device complexity increases
Solution Approach 1:
The patent integrates multiple functions into the existing forestry vehicle system. The control unit not only identifies logs but also calculates positional information, matches logs with tree data, and guides the loading operation, making the system multi-functional and reducing the need for separate specialized devices.
Solution Approach 2:
The system uses the forestry vehicle's own imaging devices and existing structural data to perform log identification. The vehicle's crane position and orientation data are utilized in the calculation process, allowing the system to identify logs using its own resources without requiring extensive external equipment.
3Productivity
If manual log matching is performed, then equipment cost is lower, but productivity deteriorates due to time-consuming manual processes
Solution Approach 1:
The patent enables continuous automated log identification and matching during the loading operation. The control system continuously processes imaging data and provides real-time log identification, allowing the loading process to proceed without interruption or delays for manual assessment.
Solution Approach 2:
The system performs preliminary automated identification and matching of logs before the loading operation begins. By pre-processing the identification and matching tasks, the system eliminates time-consuming manual assessment during the actual loading process, improving overall productivity.
Data Source
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AI summary
Method (100) to match a log using a forestry vehicle comprising a body, a crane mounted on the body, and a control unit, wherein the crane comprises a first boom. The method comprises receiving (110) a log data set indicating a position of at least one log, selecting (120) a log from the at least one log, and generating (130) vehicle positional data indicating the position of the forestry vehicle. The method further comprises measuring (140) a slew angle, α1, of the crane relative the body in a third plane extending in the longitudinal direction and the width direction of the forestry vehicle, measuring (150) a first boom angle, α2, of the first boom relative the body, and identifying (160) the selected log by the control unit based on the log data set, the vehicle positional data, the slew angle, and the first boom angle.