Industrial Monitoring Data Model for Multi-Source Fault Analysis
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Solution Overview
Problem
Current industrial automation systems face challenges in efficiently integrating and analyzing data across multiple levels and sources, leading to disconnects between hierarchical levels, making it difficult to customize applications for different customers and specialists, and requiring significant engineering effort for fault analysis.
Innovation Solution
A monitoring system that adapts a common predefined data model to organize and convert data from various industrial automation systems into a structured format, allowing for dynamic view creation and integration of multiple data sources, with features like OPC UA protocol configuration, role authorization, and plugin architecture for analytics and data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data from multiple industrial automation systems are integrated using native data models, then data integration capability is improved, but system complexity increases due to multiple protocols and data formats
Solution Approach 1:
The patent introduces an intermediary layer (data model adaptation layer) that sits between multiple industrial automation systems with native data models and the monitoring system. This intermediary adapts and converts various native data models into a common standardized data model, enabling data integration without direct complex point-to-point connections between systems. The intermediary handles protocol translation and data format normalization, reducing overall system complexity while maintaining high adaptability.
Solution Approach 2:
The patent implements a universal common data model that can represent multiple native data models from different industrial automation systems. This common data model serves as a multi-functional interface that can accommodate various protocols (OPC UA, OPC DA, Modbus, etc.) and data formats, allowing a single monitoring system to integrate data from diverse sources without requiring separate integration mechanisms for each system type.
2Adaptability or versatility
If custom applications are developed for different customers and specialists, then application versatility is improved, but engineering effort and development time increase
Solution Approach 1:
The patent implements a dynamic view creation mechanism where graphical views and application configurations can be dynamically generated and customized based on user requirements without requiring extensive reprogramming. The system allows users to create, modify, and configure views dynamically using the adapted common data model, enabling quick customization for different customers and specialists while reducing development time.
Solution Approach 2:
The patent performs preliminary data adaptation and organization by converting all native data models into a common standardized format in advance. This preliminary action creates a unified data foundation that can be easily accessed and configured for different applications. By pre-adapting the data model structure and establishing common data representations, the system reduces the engineering effort required for subsequent application development and customization.
3Measurement precision
If detailed fault analysis is performed across multiple data sources, then fault detection accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent changes the parameter representation by transforming diverse native data models into a unified common data model with standardized parameters and data structures. This parameter transformation enables consistent fault analysis across multiple data sources without dealing with the complexity of varying native formats. The common data model provides a standardized parameter space that simplifies fault detection algorithms while maintaining the ability to perform detailed analysis.
Data Source
AI summary
The invention relates to a method for configuring a monitoring system for monitoring industrial processes and industrial assets. The method comprising, the monitoring system: receiving data associated with operation of industrial plants in native data format, adapting a common predefined data model to organize the data to convert in a common structured data format for use by application functions, receiving a request for data processing, generating a graphical view of the industrial process; identifying specific industrial processes and assets relating to the request of data processing and generating the graphical view; processing of specific data according to data processing request and generating a first graphical view associated for the specific data and associated identifiers according to a preconfigured first view configuration, generating a second graphical view from the first graphical view by incorporating a new view configurations onto the first view configuration based on result of data processing.


