Signal Assignment in Superimposed Data Streams
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Solution Overview
Problem
In rail transport systems, superimposed signals from multiple components transmitted via a common bus are difficult to process due to the complexity of manually breaking down and assigning data strings to individual components, making it unclear which component transmitted each signal, leading to inefficient and costly data processing.
Innovation Solution
A method is introduced to automatically or semi-automatically assign individual signals in a data string to different components by determining change points, grouping similar change behaviors, and using triggers to divide the data string into sections, each assigned to a component, thereby forming recognizable signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual breakdown and assignment of data strings to components is performed, then signal assignment can be achieved, but processing time and costs increase significantly
Solution Approach 1:
The system performs self-service by automatically analyzing the data string, detecting change points, determining change behaviors, and assigning sections to components without requiring manual intervention. The evaluation device autonomously completes the entire signal assignment process, eliminating the need for manual breakdown and assignment while maintaining high accuracy.
Solution Approach 2:
The manual mechanical process of breaking down and assigning data strings is replaced by an automated electronic evaluation device that uses algorithmic analysis of change points and change behaviors. This substitution of manual operations with automated computational methods dramatically reduces processing time while maintaining assignment accuracy.
2Loss of information
If manual assignment of signals to components is performed, then signal identification is possible, but the process becomes complex and difficult
Solution Approach 1:
The evaluation device autonomously identifies the origin of each signal by automatically analyzing change points and their behaviors, determining which component transmitted each section of the data string without requiring manual intervention or complex procedural steps.
Solution Approach 2:
The system simplifies the complex assignment process by focusing on detecting and analyzing specific parameter changes (change points and change behaviors) in the data string. By monitoring these critical parameters and their patterns, the system can automatically identify signal origins without requiring complex manual analysis of the entire data structure.
3Productivity
If automated signal assignment is implemented, then processing efficiency increases, but the system requires sophisticated analysis methods
Solution Approach 1:
The automated analysis method divides the data string into manageable sections at detected change points, allowing the system to process and analyze each section independently. This segmentation enables efficient automated handling of large data volumes while using relatively simple analysis techniques focused on identifying change points and their behaviors rather than analyzing the entire data string as a single complex unit.
Data Source
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AI summary
The invention relates to a method for assigning signals (28) to different components, wherein the signals (28) are superimposed in a data stream (4). To provide a time-efficient and cost-effective method for assigning signals (28) to different components, it is proposed that several change points (6) are identified within the data stream (4) (8), that a change behavior (10) is determined for each change point (6) (12), and that those change points (6) for which a similar change behavior (10) is determined are each assigned to a common group (14) (16). Furthermore, according to the invention, a trigger (18) for the respective change behavior (10) is determined for each group (14) of change points (6) (20). The data stream (4) is divided into several sections (22) by means of the change points (6) (24).Using the identified triggers (18), each section (22) is assigned to a component (26), with the sections (22) assigned to each component forming a signal (28).