Rail Vehicle Movement Detection with Sensor-Specific Deviation Thresholds

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Solution Overview

Problem

Existing methods for determining movement variables of ground-based vehicles, particularly rail-based vehicles, struggle with systematic deviations due to varying sensor error characteristics, leading to operational restrictions and inaccuracies in speed and position calculations.

Innovation Solution

A method that distinguishes systematic deviations from random errors by using statistical sensor accuracy values and a timer to assess the presence of systematic deviations, employing a movement model and transfer model to determine probable system states and form test variable values.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If uniform thresholds are used to detect systematic deviations across different sensor types, then the detection method is simple and consistent, but measurement precision deteriorates because sensor-specific error characteristics cannot be accounted for

Engineering Contradiction:
Improvedetection method complexityVSAvoidsystematic deviation detection accuracy
Core Design Contradiction:
Device complexityVSMeasurement precision

Solution Approach 1:

The patent applies local quality by assigning sensor-specific accuracy values to each sensor type rather than using uniform thresholds. Each sensor's systematic deviation detection uses its own characteristic accuracy value, allowing the detection method to adapt to local error characteristics of different sensor types while maintaining a consistent overall detection framework.

Inventive Principle:
Principle #3Local quality

2Reliability

If sensor readings are smoothed before comparison with thresholds, then random errors are reduced, but detection precision deteriorates because sudden acceleration and braking events cannot be detected

Engineering Contradiction:
Improveerror reductionVSAvoidsudden event detection accuracy
Core Design Contradiction:
ReliabilityVSMeasurement precision

Solution Approach 1:

The patent applies dynamics by making the detection threshold adaptive rather than static. The threshold is dynamically adjusted based on the statistical sensor accuracy value and the expected movement variable value, allowing the system to detect sudden events while still filtering random errors. The timer mechanism also introduces dynamic behavior by temporarily adjusting thresholds after systematic deviations are detected.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The patent changes the parameter of the detection threshold from a fixed uniform value to a dynamic value that depends on sensor-specific accuracy characteristics and expected movement values. This parameter change allows the system to adapt to different operating conditions and sensor types without losing the ability to detect sudden events.

Inventive Principle:
Principle #35Parameter changes

3Reliability

If confidence interval limits are increased to account for possible systematic deviations, then reliability improves, but productivity deteriorates due to operational restrictions and speed limitations

Engineering Contradiction:
Improvepositioning reliabilityVSAvoidvehicle operational efficiency
Core Design Contradiction:
ReliabilityVSProductivity

Solution Approach 1:

The patent applies periodic action through the timer mechanism that temporarily increases confidence interval limits only when systematic deviations are detected. After a predetermined time period without detected deviations, the limits are reduced back to normal levels, allowing the system to maintain high reliability when needed while preserving productivity during normal operation.

Inventive Principle:
Principle #19Periodic action

4Measurement precision

If sensor-specific accuracy values are used to detect systematic deviations, then measurement precision improves, but device complexity increases due to additional statistical evaluations

Engineering Contradiction:
Improvesystematic deviation detection accuracyVSAvoiddetection system complexity
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies universality by creating a detection framework that works with multiple sensor types using a common statistical approach. The same detection method and threshold calculation formula are applied universally across different sensor types, with each sensor contributing its specific accuracy value. This reduces complexity compared to having separate detection systems for each sensor type.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentEP3927593B1Method for detecting systematic deviations during determination of a movement variable of a ground-based, more particularly rail-based, vehicle, and corresponding apparatus and vehicle
Publication Date: 2025.08.06 SIEMENS MOBILITY GMBH
  • EP3927593B1 patent drawingFigure 1
  • EP3927593B1 patent drawingFigure 2
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AI summary

The invention relates to a method for detecting systematic deviations (sA) during determination of a movement variable (v) of a ground-based, more particularly rail-based, vehicle (F). To optimise the operation of the vehicle (F), more particularly to minimise operational restrictions during operation of the vehicle (F), the method according to the invention proposes that – based on a measurement value (nS1.t), assigned to a time (t), of at least one sensor (S1), a value (vS1.t), assigned to the time (t), of the movement variable (v) is determined and – subject to the value (vS1.t), assigned to the time (t), of the movement variable (v) and a statistical sensor accuracy value (σs_vS1.t), determined for this value (vS1.t), of the at least one sensor (S1), a test variable value (TGS1.t), assigned to the time (t), is formed and is compared in a comparison with a predefined test bound (TS) in order to make an assumption (A1, A2, A3) regarding an existence of a systematic deviation (sA), said assumption being subject to a comparison result obtained from the comparison.