OPC UA Diagnostic Metadata for Automated Plant Data Collection
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Solution Overview
Problem
Existing methods for setting up diagnostic and monitoring data collection in industrial plants, particularly in distributed control systems, require substantial manual configuration efforts and are prone to errors, making them costly and inefficient.
Innovation Solution
A computer-implemented method utilizing OPC UA servers and clients to automate the configuration of data collection units, enabling seamless integration of diagnostic data into time-series databases by providing diagnostic metadata, discovering OPC UA servers, generating configuration files, and connecting data collection units to time-series databases, thereby reducing manual intervention and potential errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual configuration methods are used for setting up diagnostic data collection in distributed control systems, then configuration accuracy can be maintained through human review, but substantial manual configuration efforts and time are required
Solution Approach 1:
The system enables automatic self-configuration by having the diagnostic unit autonomously discover OPC UA servers, retrieve their diagnostic metadata, generate appropriate configuration files, and establish database connections without requiring manual human configuration. This self-service approach eliminates manual configuration efforts while maintaining reliability through automated error-free configuration generation.
Solution Approach 2:
The diagnostic unit performs preliminary actions by automatically discovering OPC UA servers and retrieving their diagnostic metadata before configuration is needed. This advance preparation allows the system to have configuration files ready automatically, eliminating the need for manual configuration setup and reducing overall configuration time while maintaining accuracy.
2Adaptability or versatility
If manual configuration methods are used for setting up diagnostic data collection, then flexibility in handling complex scenarios can be maintained, but the process becomes error-prone and costly
Solution Approach 1:
The automatic configuration system retrieves diagnostic metadata directly from OPC UA servers and generates configuration files autonomously, eliminating manual configuration steps that are prone to errors. The system adapts to different OPC UA servers by automatically discovering their specific diagnostic capabilities and generating appropriate configurations, thereby maintaining flexibility while reducing error rates.
Solution Approach 2:
The diagnostic unit receives feedback from OPC UA servers through their diagnostic metadata, which automatically informs the configuration generation process. This feedback mechanism ensures that the generated configuration files accurately reflect the actual capabilities and requirements of each OPC UA server, maintaining adaptability while eliminating manual configuration errors.
3Productivity
If automated configuration is implemented using OPC UA servers and clients, then configuration time and effort are significantly reduced, but integration complexity between different systems increases
Solution Approach 1:
The diagnostic unit serves as an intermediary between OPC UA servers and the database system. It automatically discovers OPC UA servers, retrieves their diagnostic metadata, generates appropriate configuration files, and establishes database connections. This intermediary approach simplifies the overall integration by providing a single automated component that handles all configuration tasks, reducing the perceived complexity while maintaining high productivity.
Solution Approach 2:
The diagnostic unit performs multiple functions automatically: discovering OPC UA servers, retrieving diagnostic metadata, generating configuration files, and establishing database connections. This multi-functional automated component handles diverse configuration tasks through a single unified process, improving productivity while managing integration complexity through standardization.
4Ease of operation
If existing OPC UA servers are modified to enable diagnostic data collection, then seamless integration can be achieved, but the risk of disrupting existing server functionality increases
Solution Approach 1:
The diagnostic unit acts as an intermediary that connects to existing OPC UA servers without requiring any modifications to the servers themselves. It retrieves diagnostic metadata from the servers and uses this information to generate configuration files for data collection. This approach maintains the seamlessness of integration while preserving the stability of existing server functionality, as no changes are made to the servers.
Solution Approach 2:
The diagnostic unit creates a copy or representation of the diagnostic data structure from the OPC UA server's metadata to generate configuration files. This copying approach allows the system to work with diagnostic data without modifying the original server, thereby maintaining integration seamlessness while ensuring server functionality stability through non-invasive data access.
Data Source
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AI summary
The invention relates to a computer-implemented method for providing diagnostic data (240.1) of a component (200.1) in an industrial plant, the component (200.1) comprising an OPC UA server (202.1). The method comprises the steps of: providing, on the OPC UA server (202.1), diagnostic metadata, which describe the diagnostic data (240.1) of the component (200.1); discovering, by a diagnostic unit (110), the OPC UA server (202.1) of the component (200. 1); creating, by the diagnostic unit (110), a corresponding data collection unit (120.1) for the component (200.1), the data collection unit (120.1) comprising an OPC UA client (122.1); generating, by the diagnostic unit (110), a configuration file (122.1) for the data collection unit (120.1), by using the diagnostic metadata; transferring, by the diagnostic unit (110), the configuration file to the data collection unit (120.1); modifying, by the diagnostic unit (110), a configuration file (320) of the time-series database (300) by adding a URI of the data collection unit (120.1); connecting, by the data collection unit (120.1), to the time-series database (300); delivering diagnostic data (240.1) of the component (200.1), via the data collection unit (120.1), to the time-series database (300); and storing the diagnostic data (240.1) of the component (200.1) to a diagnostic data repository (340) of the time-series database (300).