Track Circuit Current Signal Normalization for Railway Vehicle Positioning
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Solution Overview
Problem
Existing methods for determining the relationship between a track-circuit transmitted current signal and a railway vehicle location are inefficient due to non-linear relationships that vary by geographical location and are sensitive to irregular vehicle movements, such as speed profiles with biased acceleration/deceleration values.
Innovation Solution
The method employs a Weighted Dynamic Time Warping Barycenter Averaging (WDBA) algorithm, which normalizes current signals using global min-max values and initializes a reference curve, then uses Dynamic Time Warping to align and calculate a final reference curve, improving accuracy and reducing computational time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a Dynamic Time Warping algorithm is used to estimate railway vehicle position with reference to a track-circuit current signal, then the measurement precision is improved, but the loss of time increases due to time-consuming reference curve initialization
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing reference current signals at known axle positions during a calibration phase. This pre-computation eliminates the need for time-consuming reference curve initialization during actual vehicle position estimation, as the system can directly compare measured currents against the pre-established reference signals.
Solution Approach 2:
The patent creates simplified copies of the complex Dynamic Time Warping approach by using pre-stored reference current signals that represent typical vehicle positions. Instead of performing full DTW alignment operations during real-time estimation, the system uses these reference copies to rapidly determine position, significantly reducing computational time while maintaining accuracy.
2Adaptability or versatility
If a Dynamic Time Warping algorithm is used to estimate railway vehicle position, then the adaptability to different speed profiles is improved, but the sensitivity to irregular railway vehicle movements increases
Solution Approach 1:
The patent extracts and removes the problematic sensitivity to irregular movements by separating the position estimation function from the speed profile characteristics. By using reference current signals that are independent of specific speed variations, the system eliminates the amplification of measurement errors that occurs with irregular accelerations and decelerations in DTW-based methods.
Solution Approach 2:
The patent uses simple, robust current signal comparisons rather than complex DTW algorithms that are sensitive to disturbances. This simpler approach, while less adaptable to extreme variations, provides sufficient accuracy for normal operations and is much more reliable in the presence of irregular vehicle movements.
3Productivity
If track circuits use measured current to determine vehicle location with smaller resolution, then the productivity of the railway system is improved, but the measurement precision requirements increase due to non-linear relationship variations
Solution Approach 1:
The patent changes the measurement parameters by using current signals at multiple discrete axle positions rather than attempting to directly invert the non-linear current-location relationship. By measuring currents at predetermined positions and using these as reference points, the system achieves high precision location determination that accounts for non-linear variations in the electrical characteristics of different track sections.
Data Source
AI summary
Method for determining the relationship between a track-circuit current signal and a railway vehicle location, including sending, by a track circuit, a current signal across a railway track block, measuring the current signal for different railway vehicles running successively on the railway track block, thus obtaining a plurality of railway vehicle move samples, normalizing the railway vehicle move samples, initializing a reference curve, and applying a Weighted Dynamic Time Warping Barycenter Averaging algorithm to calculate a final reference curve representing the relationship between the measured track-circuit current signal and the railway vehicle location on the railway track block.


