Train Speed Estimation via Vibration Cross-Correlation
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Solution Overview
Problem
Current train speed monitoring methods, relying on speed sensors or GNSS, face high energy consumption and accuracy issues in poor signal conditions, particularly in underground environments.
Innovation Solution
A train speed estimation device and method using a sensor pair to sample and analyze vibration signals in a natural frequency band, employing cross-correlation analysis to calculate real-time train speed without relying on speed sensors or GNSS, suitable for various types of trains and track conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speed sensors are used for train speed monitoring, then speed measurement precision is improved, but energy consumption and hardware cost increase
Solution Approach 1:
The patent replaces mechanical speed sensors with a vibration-based measurement system that uses accelerometers to capture train body vibrations and derives speed information through signal processing, thereby eliminating the need for dedicated speed sensors and reducing energy consumption
Solution Approach 2:
The patent introduces vibration signals as an intermediary to indirectly measure train speed. Instead of directly measuring speed, the system captures vibrations caused by wheel-rail interactions and uses cross-correlation analysis to derive speed information from these intermediate vibration signals
2Measurement precision
If GNSS-based systems are used for train speed monitoring, then speed measurement precision is improved, but reliability deteriorates in poor signal conditions such as tunnels
Solution Approach 1:
The patent enables the train to self-measure its speed using onboard vibration sensors and signal processing, making the system independent of external GNSS infrastructure. The train generates its own speed measurement capability through analyzing vibrations from its own wheel-rail interactions, ensuring reliability in tunnel environments where GNSS signals are unavailable
3Use of energy by moving object
If vibration signals in natural frequency band are sampled and analyzed using cross-correlation, then energy consumption is reduced, but device complexity increases
Solution Approach 1:
The patent focuses analysis on the natural frequency band of train vibrations, filtering and processing only the relevant frequency components. This selective parameter approach reduces computational complexity compared to analyzing the full frequency spectrum, thereby lowering device complexity while maintaining energy efficiency
Solution Approach 2:
The patent extracts only the essential vibration characteristics in the natural frequency band that are relevant for speed measurement, discarding irrelevant frequency components. This extraction of essential information simplifies the processing requirements and reduces device complexity
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 reduces energy consumption, enhances precision, and effectively monitors real-time train speed, especially in underground scenarios where GNSS signals are unreliable, while being adaptable to different train and track types.
Implementation Method 1
sampling, at the same sampling frequency, vibration in a natural frequency band experienced by the train as it advances
Implementation Method 2
subject the first set of vibration signals and the second set of vibration signals to cross-correlation analysis, to obtain a target sampling difference
Data Source
AI summary
A train speed estimation device and method are disclosed. Vibration in a natural frequency band experienced by a train as it advances is sampled by means of first and second sensors at the same sampling frequency, to obtain a first set and a second set of sampling signals respectively; a first set and a second set of vibration signals are obtained on the basis of the first set and second set of sampling signals respectively, and the first set and second set of vibration signals are subjected to cross-correlation analysis, to obtain a target sampling difference; and a train speed is calculated on the basis of the target sampling difference. The train speed estimation device and method according to the present disclosure can precisely monitor the real-time train speed without relying on any speed sensor or GNSS.