Remote Network Diagnostics via Parameter Filtering
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Solution Overview
Problem
Remote operators face challenges in accurately and efficiently diagnosing and correcting errors in control system networks due to overwhelming and potentially erroneous data, which can lead to network slowness or failure, requiring early detection and automatic correction mechanisms to prevent complications.
Innovation Solution
The method involves monitoring control system networks for diagnostic messages, collecting and prioritizing data, automatically correcting abnormal parameters, and alerting users to abnormalities, allowing for efficient identification and resolution of issues without disrupting the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive data collection is performed from the control system network, then diagnostic accuracy is improved, but network load increases causing slowness or failure
Solution Approach 1:
The patent extracts only the necessary diagnostic parameters from the control system network rather than collecting all available data. The system identifies and collects specific parameters related to abnormal operations, reducing network load while maintaining diagnostic accuracy. This is achieved by filtering and selecting only relevant data points for remote monitoring.
Solution Approach 2:
The patent applies different data collection strategies to different parts of the network based on their specific characteristics. Critical components with abnormal operations receive focused monitoring attention, while normal components use reduced monitoring. This localized approach optimizes diagnostic precision for problematic areas without unnecessarily loading the entire network.
2Ease of repair
If remote operators manually review and diagnose network data, then error correction capability is improved, but time consumption increases
Solution Approach 1:
The system performs preliminary data processing, filtering, and analysis before presenting information to remote operators. Abnormal parameters are identified and highlighted in advance, so operators don't need to manually review all raw data. This preliminary preparation significantly reduces diagnosis time while maintaining correction capability.
Solution Approach 2:
The patent implements automated feedback mechanisms that monitor network parameters continuously and alert operators only when abnormalities are detected. This feedback system provides operators with pre-processed information about issues requiring attention, eliminating the need for manual review of normal operations and reducing overall diagnosis time.
3Adaptability or versatility
If additional subscriptions are added for data collection, then monitoring capability is improved, but network performance deteriorates
Solution Approach 1:
The patent creates a universal data collection framework that can adapt to different monitoring needs without requiring separate subscriptions for each parameter type. The system uses a single optimized communication interface that handles multiple diagnostic functions, reducing the number of network subscriptions needed while maintaining comprehensive monitoring capability.
Data Source
AI summary
Devices, methods, and systems for remotely monitoring network diagnostics are described herein. One method includes monitoring a control system network of a site for a plurality of diagnostic messages, wherein the diagnostic messages include a set of parameters, collecting diagnostic data associated with the diagnostic messages, correcting a parameter within the set of parameters to conform to a parameter threshold limit, and alerting a user upon the collected diagnostic data having an abnormal parameter within the set of parameters.