Track-Guided Vehicle Axle Counting With Dual Evaluation
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Solution Overview
Problem
Existing axle counting systems face challenges in achieving both high functional reliability and improved error detection, with current methods either providing reliable counting but limited error detection or vice versa.
Innovation Solution
Implementing a method that utilizes two evaluation routines for axle counting sensors, where the first routine checks for threshold exceedance and the second routine performs pattern comparison with tolerance, ensuring redundant evaluation to generate an error signal only when inconsistent results occur.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If threshold-based axle counting method is used, then functional reliability is improved, but error detection capability deteriorates
Solution Approach 1:
The axle counting process is segmented into two independent evaluation routines: a threshold-based routine (first evaluation routine) and a pattern recognition routine (second evaluation routine). Each routine processes the measurement signal independently and generates separate axle counting results. This segmentation allows each routine to excel at its specific function while the combination provides both reliability and error detection capability.
Solution Approach 2:
The system implements feedback by comparing the axle counting results from both evaluation routines. When the results differ, an error signal is generated, providing feedback about potential measurement errors. This feedback mechanism enables the system to detect and flag erroneous measurements without compromising the primary counting function.
2Measurement precision
If AI-based solutions are implemented, then error detection potential is improved, but functional reliability deteriorates
Solution Approach 1:
The AI-based pattern recognition is segmented as a separate second evaluation routine that operates independently from the primary threshold-based counting. This ensures that the AI component enhances error detection without interfering with the proven reliability of the traditional method. The two routines work in parallel, with the AI routine providing additional verification.
Solution Approach 2:
The comparison mechanism acts as an intermediary that reconciles the outputs of both evaluation routines. Rather than directly replacing the threshold method with AI, the system uses the comparison of results as an intermediary step to determine whether AI-detected patterns represent actual errors or valid variations, thus maintaining functional reliability while enabling error detection.
3Measurement precision
If two evaluation routines are implemented, then error detection is improved, but device complexity increases
Solution Approach 1:
The evaluation system is designed with multi-functionality where the same hardware infrastructure supports both evaluation routines. The computing resources process both threshold-based and pattern-based analysis using the same sensor inputs, making the system universal rather than requiring separate dedicated systems for each function.
Solution Approach 2:
The two evaluation routines are merged into a single integrated axle counting system that processes measurements from the same sensors. The results from both routines are combined through comparison logic, creating a unified error detection mechanism rather than separate independent systems. This merging reduces overall complexity while maintaining the benefits of dual evaluation.
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 approach enhances the reliability of axle counting by ensuring accurate detection of axle numbers while maintaining functional safety, preventing safety-critical incidents through redundant evaluation.
Implementation Method 1
Typically, an electromagnetic field is generated, which changes when a wheel of a vehicle passes over the axle counting sensor.
Data Source
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AI summary
The invention encompasses the following subject matter: a method for counting axles of a track-guided vehicle. Furthermore, the invention encompasses a railway system with multiple axle counting sensors (AZ, AZ1, AZ2) installed on a track (GL). Furthermore, the invention encompasses a computer program product containing program instructions. Furthermore, the invention encompasses a computer-readable storage medium containing data.