Virtual Fault Mitigation Modeling for Technical Installations
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Solution Overview
Problem
Current machine learning model-based systems in technical installations are inadequate for accurately identifying fault causes and predicting the effectiveness of mitigation actions, leading to inefficient fault resolution and potential shutdowns due to insufficient training data and lack of root cause analysis.
Innovation Solution
A method and system that uses sensor data processing with machine learning models, decision matrices, and virtual models to determine fault causes and predict the outcomes of mitigation actions before implementation, enabling efficient identification and execution of corrective measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If machine learning model-based monitoring systems are used for fault detection, then continuous evaluation of parameters and alarm generation is improved, but insufficient training data causes incorrect fault identification leading to shutdowns
Solution Approach 1:
The system performs preliminary actions by simulating mitigation actions in a virtual model before implementing them in the technical installation. This allows the system to evaluate potential outcomes and select the most appropriate mitigation action, thereby improving both reliability and accuracy of fault resolution without causing unnecessary shutdowns.
Solution Approach 2:
The patent creates a virtual model (copy) of the technical installation that mirrors the real system's structure and behavior. This virtual copy is used to test mitigation actions and predict outcomes, allowing accurate fault identification and resolution without affecting the actual installation, thus improving both reliability and measurement precision.
2Loss of information
If machine learning model-based systems generate alarms for detected fault conditions, then fault detection capability is improved, but root cause analysis and mitigation action prediction are not provided
Solution Approach 1:
The system implements feedback by using the virtual model to simulate mitigation actions and feed back the predicted outcomes to the decision-making process. This feedback loop enables root cause analysis by evaluating which mitigation actions would be most effective, thereby providing complete fault information and improving mitigation action effectiveness.
Solution Approach 2:
The system performs preliminary analysis by simulating various mitigation actions in the virtual model before actual implementation. This preliminary action provides root cause analysis by identifying which simulated actions would most effectively resolve the fault, ensuring reliable mitigation without unnecessary trial-and-error in the real system.
3Loss of time
If mitigation actions are implemented directly in the technical installation, then fault resolution speed is improved, but the impact and effectiveness of mitigation actions cannot be predicted
Solution Approach 1:
The system performs preliminary simulation of mitigation actions in the virtual model before implementing them in the real technical installation. This preliminary action predicts the outcome of each mitigation action, allowing the system to select the most effective one and implement it quickly, thereby reducing fault resolution time while maintaining high predictability and reliability.
Solution Approach 2:
The virtual model serves as a copy of the technical installation, allowing mitigation actions to be tested and their outcomes predicted without affecting the real system. This copying approach enables accurate outcome prediction while maintaining the ability to implement effective mitigation actions quickly in the actual installation.
4Measurement precision
If comprehensive fault analysis and mitigation simulation are performed, then fault detection accuracy and mitigation effectiveness are improved, but system complexity and computational requirements increase
Solution Approach 1:
The patent creates a virtual model (copy) of the technical installation that replicates its structure and behavior. This virtual copy handles the complex simulations and analyses, keeping the actual system structure relatively simple while achieving high fault detection accuracy through comprehensive analysis in the virtual environment.
Data Source
AI summary
A method and system for eliminating a fault condition in a technical installation is provided. In one aspect, the method includes predicting an occurrence of the fault condition in at least a portion of the technical installation. The method also includes determining a root cause of the predicted fault condition. Additionally, the method includes identifying one or more mitigation actions to resolve the fault condition. Furthermore, the method includes determining an outcome associated with at least one of the one or more mitigation actions on the technical installation. The method also includes outputting on a device associated with a user at least one mitigation action to be implemented in the technical installation based on the determined impact.