Rail Vehicle Roll Motion Detection via Dynamic Bandpass Filtering

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Solution Overview

Problem

Existing methods fail to reliably detect permanent rolling movements of a rail vehicle body relative to the chassis, distinguishing them from transient movements, which can be intentionally induced by passengers or due to mechanical issues, posing safety risks, especially in driverless vehicles where these conditions are not immediately apparent.

Innovation Solution

A method involving a signal proportional to the car body's rotation about the longitudinal axis, filtered using a bandpass filter tuned to the natural rolling frequency, with a timer counting limit value violations to differentiate between transient and persistent rolling movements, triggering a warning signal for persistent vibrations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If a bandpass filter is used to detect roll motion, then measurement precision is improved, but false alarms from transient movements increase

Engineering Contradiction:
Improveroll motion detection accuracyVSAvoidfalse alarm rate
Core Design Contradiction:
Measurement precisionVSReliability

Solution Approach 1:

The system dynamically adjusts the center frequency of the bandpass filter to match the actual roll natural frequency of the vehicle, which varies with load conditions. This dynamic adaptation ensures accurate detection while maintaining reliability across different operating conditions.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system uses feedback from pressure sensors monitoring the air springs to continuously track the roll natural frequency and adjust the filter parameters accordingly. This feedback mechanism enables the system to distinguish between transient disturbances and genuine roll motions, reducing false alarms while maintaining detection precision.

Inventive Principle:
Principle #23Feedback

2Adaptability or versatility

If the roll natural frequency is adjusted based on air spring pressure, then adaptability is improved, but device complexity increases

Engineering Contradiction:
Improveroll detection accuracy under varying loadVSAvoidfilter parameter adjustment mechanism
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system automatically determines the roll natural frequency by monitoring the pressure differences in the air springs, eliminating the need for manual calibration or complex external adjustment mechanisms. The system self-adjusts the filter parameters based on the measured pressure data, maintaining adaptability while minimizing added complexity.

Inventive Principle:
Principle #25Self-service

3Manufacturing precision

If pressure differences in air springs are used to measure roll angle, then manufacturing precision is improved, but reliability decreases due to out-of-phase movements

Engineering Contradiction:
Improveroll angle measurement accuracyVSAvoiddetection accuracy during out-of-phase roll
Core Design Contradiction:
Manufacturing precisionVSReliability

Solution Approach 1:

The system combines the roll angle measurements from both left and right air springs by summing their pressure differences. This merging approach ensures that out-of-phase roll movements cancel each other out, while in-phase movements (indicating genuine roll) are reinforced, thereby improving reliability without sacrificing measurement precision.

Inventive Principle:
Principle #5Merging (Combining)

Data Source

PatentEP3487747B1Method and device for detecting roll motion of a rail vehicle car body relative to the bogie
Publication Date: 2020.08.05 SIEMENS MOBILITY AUSTRIA GMBH
  • EP3487747B1 patent drawingFigure 1~2
  • EP3487747B1 patent drawingFigure 3

AI summary

The invention relates to a method and to a device for detecting roll motion of a rail vehicle car body (1) relative to the bogie (2) of a rail vehicle (3), wherein a signal ( S ) proportional to the roll motion is bandpass-filtered and the magnitude of the bandpass-filtered signal ( S filter) is compared with a limit value ( S lim) and rolling is determined on the basis of the limit value ( S lim) being exceeded several times within an observation time period ( T ).