Automated Mistrack Detection for Self-Propelled Work Vehicles
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Solution Overview
Problem
Conventional methods for detecting mistrack conditions in self-propelled work vehicles are manual, time-consuming, and prone to human error, lacking real-time automation and accuracy, especially in ensuring track parallelism for accurate measurements.
Innovation Solution
A novel method using onboard sensors and image processing to automatically detect mistrack conditions by determining the position of ground engaging units relative to reference points, calculating mistrack error, and generating output signals for display or alarms, minimizing human interaction and enhancing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used for measuring travel mistrack at the factory, then the process can be performed with conventional tools, but it requires a great deal of repetitive activity (one hour or more per work vehicle) and typically requires two or more trained personnel
Solution Approach 1:
The patent replaces manual mechanical measurement processes with an automated optical measurement system using cameras and image processing. The system automatically captures images of reference objects, processes them computationally to determine track positions, and calculates mistrack conditions without requiring manual measurement activities, thereby dramatically increasing productivity and reducing time per vehicle.
Solution Approach 2:
The measurement system performs self-service by automatically capturing images, processing them through image analysis algorithms, and generating mistrack measurements without requiring continuous human intervention. The system autonomously completes the entire measurement process from image capture to result generation.
2Measurement precision
If manual processes are used for measuring travel mistrack, then conventional tools can be utilized, but the accuracy is compromised due to the human element of the process and inherent flaws therein
Solution Approach 1:
The patent replaces human-operated mechanical measurement tools with an automated optical measurement system that uses cameras and computer vision algorithms. This substitution eliminates human error, subjectivity, and inconsistency inherent in manual processes, thereby improving both measurement precision and reliability through objective, repeatable automated measurements.
Solution Approach 2:
The system creates accurate visual copies (images) of the reference objects and track positions, then processes these copies computationally to determine measurements. This copying approach allows for precise, repeatable measurements that can be verified and re-analyzed without affecting the original measurement conditions.
3Manufacturing precision
If manual processes are used for measuring travel mistrack, then existing equipment can be used, but ensuring track parallelism at the beginning of the test is challenging as it is the most critical criteria for accurate measurement
Solution Approach 1:
The patent replaces manual alignment procedures with an automated optical system that uses cameras to capture images of reference objects and computationally determines track positions and parallelism. The system automatically detects and measures alignment conditions, eliminating the difficulty of manual setup while ensuring precise track parallelism verification before measurements begin.
Solution Approach 2:
The system performs preliminary alignment verification by capturing images and analyzing track positions before the actual mistrack measurement begins. This preliminary action ensures that tracks are properly parallel before measurements start, preventing incorrect results from misaligned initial conditions.
Data Source
AI summary
A system and method are provided for determining mistrack conditions in work vehicles such as excavators having first and second tracks. A controller uses data from onboard sensors (e.g., cameras, lidar) having an external field of view to detect a first position of, e.g., a track of the work vehicle relative to a first external point in a local reference system independent of a global reference system and to detect, upon the work vehicle having advanced from the detected first position a predetermined distance, a second position of the at least first component of the work vehicle relative to a second external point in the local reference system. The controller further determines an amount of mistrack error corresponding to a difference between the detected second position and an expected second position, and generates an output signal based on the determined amount of mistrack error.