VIPER: VIsualization for PrEdictive maintenance Recommendation
VIPER enhances predictive maintenance in nuclear power plants by providing advanced machine-learning diagnostics, explainability metrics, and actionable recommendations through an intuitive visualization interface.
VIPER: VIsualization for PrEdictive maintenance Recommendation
VIPER is a sophisticated tool for nuclear power plant system engineers and monitoring analysts. It presents comprehensive system health diagnostics, explainability metrics, and actionable recommendations, enabling informed decision-making through an easy-to-use visualization interface.
Maintaining optimal system performance and safety is critical in the context of nuclear power plants. Traditional maintenance approaches can be reactive and less efficient, leading to unplanned downtimes and increased operational costs. VIPER was developed to address these challenges by leveraging machine learning to predict maintenance needs and provide clear, actionable insights.
VIPER is a visualization tool that integrates pre-trained machine learning models for diagnosing and predicting system health. VIPER utilizes SHAP and LIME for explainability and ARIMA for prognostic capabilities and provides comparative and historical context plots to assist in fault diagnosis. The latest version, VIPER 2.0, includes multi-model selection, model voting, and LLM support, enhancing its diagnostic robustness and user interaction.
Advantages:
- Advanced Diagnostics: Leverages multiple machine-learning models for accurate fault detection.
- Explainability Metrics: Utilizes SHAP and LIME to provide transparency in model decisions.
- Prognostic Capabilities: Uses ARIMA to predict future system states.
- Enhanced User Interaction: Incorporates LLM support for expanded definitions and user engagement.
- Comprehensive Analysis: Offers comparative and historical context plots for detailed data analysis.
- Multi-Model Voting: Increases diagnosis robustness through model consensus.
Applications:
- Nuclear Power Plants: Diagnose and predict maintenance needs in circulating water systems.
- System Monitoring: Continuously monitor plant systems for early fault detection.
- Research and Development: Use in academic and research settings to study predictive maintenance models.
This software is under copyright. To purchase a license, please use the 'Contact Us' form on this page. We will respond as promptly as possible.