Rail Frog Geometry Measurement Using Oscillation-Corrected Light Sectioning
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Solution Overview
Problem
Existing rail profile monitoring systems face challenges in accurately measuring wear and deformation of turnout components like the frog without mechanical contact, while compensating for horizontal and vertical oscillations of the measuring train, especially at high speeds.
Innovation Solution
A method using multiple light beams projected onto the frog, simultaneously detected by cameras, applies correction factors based on train oscillations to ensure accurate measurements, allowing for real-time, high-speed data acquisition without mechanical contact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple light beams and cameras are used to measure frog geometry, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The measurement system is divided into multiple independent light sources and camera units, each responsible for specific measurement tasks. This segmentation allows parallel data acquisition from different angles, improving precision while maintaining manageable system complexity through modular architecture
Solution Approach 2:
Multiple light beams and cameras are merged into a coordinated measurement system where data from all sensors is integrated through image processing algorithms. The combining of multiple measurement streams enables comprehensive frog geometry analysis with enhanced precision
2Productivity
If the measuring train moves at high speed, then productivity is improved, but measurement precision deteriorates due to oscillations
Solution Approach 1:
The system uses real-time image data from multiple cameras as feedback to dynamically adjust measurements. By continuously monitoring the frog geometry from multiple angles during high-speed movement, the system compensates for oscillations and maintains precision through adaptive processing
Solution Approach 2:
The system acquires more measurement data than strictly necessary by using multiple light beams and cameras, creating redundant measurements that can be processed to filter out oscillation effects. This excessive data acquisition ensures precision is maintained even at high speeds
3Ease of operation
If non-contact measurement method is used, then ease of operation is improved, but measurement precision deteriorates due to train oscillations
Solution Approach 1:
The system transitions from single-point measurements to multi-dimensional spatial measurements by projecting light beams along the frog and capturing images from multiple camera positions. This dimensional expansion allows oscillation effects to be separated and corrected through spatial analysis
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
Achieves measurement inaccuracy of less than 0.1 millimeter, providing precise wear and deformation data for turnout components with real-time accuracy and speed.
Implementation Method 1
emitting a light blade onto a plane which could be substantially orthogonal to the longitudinal axis of the rail
Implementation Method 2
acquire an image containing a light row or light line generated by the intersection between the light blade and the rail
Implementation Method 3
a processing module adapted to process the light line contained in the image to determine, according to the light line itself, a value correlated to the dimension of the rail
Data Source
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AI summary
Method and system for profile or geometry measurement of a railway object, e.g. rail or switch or turnout component, e.g. frog, by using optical means measuring the object, preferably by triangulation or light sectioning, wherein preferably a correction factor is applied which is dependent from the horizontal and/or vertical oscillating movement of the measuring train and which correction factor is applied to computer calculations for a geometric feature of interest of the measured track object or an associated track object, which correction factor is determined by the use of additional optical means measuring the object.