Cable Signal Noise Correlation for Control Source Identification
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Solution Overview
Problem
Existing technologies cannot derive correlations between noise and normal operation of potential noise sources in a loopback system, making it difficult to specify the generation source of noise in a signal received through a cable.
Innovation Solution
An information processing device that acquires time-series data of signal quality and control data, and uses a correlation derivation unit to determine the correlation between variations in signal quality and control data, thereby identifying the source of noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a loopback system is used to detect noise by switching connection and disconnection of candidate generation sources, then noise detection capability is improved, but system complexity and operational disruption increase
Solution Approach 1:
The system uses its own normal operation control data to identify noise sources, eliminating the need for external loopback testing equipment and complex switching mechanisms. The control device serves itself by analyzing the correlation between its control outputs and received signal quality during regular operations.
Solution Approach 2:
The patent replaces mechanical switching and physical loopback connections with data correlation analysis. Instead of physically connecting/disconnecting cables to test noise sources, the system uses computational analysis of time-series data to identify noise correlations during normal operation.
2Measurement precision
If switching connection and disconnection of candidate generation sources is performed for noise detection, then noise source identification is improved, but normal operation is disrupted and time is lost
Solution Approach 1:
The system continuously analyzes control data and signal quality during normal operations without interruption. The correlation derivation unit processes time-series data as it is generated, maintaining continuous useful action while identifying noise sources, thus avoiding operational disruptions.
Solution Approach 2:
The system performs noise source identification as a preliminary analysis of existing operational data rather than as a separate testing phase. By analyzing control data and signal quality correlations during normal operation, the system identifies noise sources before they cause operational problems.
3Measurement precision
If loopback testing with switching is used to detect noise, then noise detection accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The control device automatically performs noise source identification using its own control data and received signal quality data. The system serves itself by autonomously analyzing correlations without requiring external testing equipment or manual intervention, greatly improving ease of operation.
Solution Approach 2:
The system uses feedback from received signal quality data correlated with control data to automatically identify noise sources. The correlation derivation unit continuously receives feedback on signal quality and uses this information to pinpoint noise sources without manual testing procedures.
Data Source
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AI summary
The present invention acquires, from control data for an apparatus to be controlled in a normal operation, a relationship between a noise included in a reception signal from a cable and the apparatus to be controlled. An information processing device (13) is provided with a correlation derivation unit (13212, 13212d) for deriving a correlation value between a variation of a time-series data (1331) of a noise included in a signal input through a cable in a network and a variation of a time-series data (1332) of control data of an apparatus to be controlled (11, 16) in the network.