Multiviewer Sensor Signal Arrangement via Feature Vector Optimization
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Solution Overview
Problem
Configuring a multiviewer to visualize and arrange sensor signals from multiple services is a tedious and time-consuming task that requires manual effort, as existing methods lack an efficient automatic configuration process.
Innovation Solution
A method that specifies characteristic features of sensor signals, extracts feature vectors, and arranges them in a two-dimensional matrix to minimize distance between neighboring signals, using techniques like Euclidean or Manhattan distance functions, stochastic optimization, or artificial neural networks to automate the configuration process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration is used to arrange sensor signals in a multiviewer, then the arrangement can be customized according to user preferences, but the configuration process becomes tedious and time-consuming
Solution Approach 1:
The system performs automatic arrangement of sensor signals by extracting characteristic features and computing optimal positions based on feature similarity, eliminating the need for manual user configuration. The multiviewer automatically services itself by organizing signals according to the minimized distance criterion without human intervention.
Solution Approach 2:
The system transforms the configuration problem into a mathematical optimization problem by defining characteristic features of sensor signals and computing a distance metric based on these features. By changing from manual positioning to automated parameter-based positioning, the system resolves the contradiction between ease of operation and time consumption.
2Loss of time
If automatic arrangement based on characteristic features is implemented, then configuration time is reduced, but the device complexity increases due to feature extraction and distance calculation requirements
Solution Approach 1:
The patent replaces the manual mechanical configuration process with an automated computational system. Instead of users manually dragging and dropping signals, the system uses feature extraction algorithms and distance calculation to automatically determine optimal positions, substituting mechanical interaction with computational processing.
Solution Approach 2:
Characteristic feature vectors serve as intermediaries between the raw sensor signals and their visual arrangement. The system extracts features from signals, computes distances between feature vectors, and uses these intermediate representations to determine spatial positioning, simplifying the overall complexity through a structured intermediate step.
3Manufacturing precision
If sensor signals are arranged by minimizing distance between characteristic feature vectors, then similar signals are grouped together for better analysis, but the arrangement becomes computationally intensive
Solution Approach 1:
The system computes distances between characteristic feature vectors of sensor signals to determine their spatial arrangement. By focusing computation on the essential characteristic features rather than entire signal data, the system achieves precise arrangement with manageable computational requirements.
Data Source
AI summary
A method for configuring a multiviewer of at least one service having at least one sensor providing a sensor signal, comprising: specifying at least one characteristic feature, extracting for each of the at least one sensor signals at least one characteristic feature vector representing at least the at least one characteristic feature of the sensor signal, and arranging the sensors signals in a two-dimensional matrix in such a manner that a distance is minimized, the distance being the distance between at least one characteristic feature vector of one of the sensor signals and the corresponding characteristic feature vector of at least one neighboring sensor signal, the at least one neighboring sensor signal being an adjacent neighbor to the one sensor signal in the matrix. Further, a multiviewer is shown.