SafeCBM: Safety-Constrained Condition-Based Monitoring and Optimization in Power Plants for Nuclear, Solar, Wind, Coal, and Hydro systems

SafeCBM

Safety-Constrained Condition-Based Monitoring and Optimization in Power Plants for Nuclear, Solar, Wind, Coal, and Hydro

What does SafeCBM do?

Systems in power plants suffer from gradual deterioration due environmental factors, operational stresses,and aging effects. This calls for advanced power plant Prognostics and Health Management (PHM) technology to achieve sustainable electricity generation and supply in a safe and economic way.

To fill this gap, InfoBeyond proposes SafeCBM to provide cost-effective Predictive Maintenance capability subject to strict safety and reliability constraints of energy power plants. SafeCBM enables condition-based monitoring with dynamic-scheduled inspection for power plant components.

SafeCBM is the first safety-integrated PHM solution that leverages AI-based process automation, machine intelligence, and computer aided decision making for power plants modernization that enhances both core operations and PHM activities.

SafeCBM: Safety-Constrained Condition-Based Monitoring and Optimization in Power Plants

SafeCBM Features

SafeCBM is sponsored by DoE (Department of Energy) Office of Nuclear Energy (NE) to promote nuclear power plant modernization in a way to address nuclear power plant economic viability in current and future energy markets through innovation.

Improved Reliability

The two key maintenance parameters to ensure reliability are potential failure time and function failure time. According to theoretical and practical study, Potential Failure time and function failure time. The current business is to estimate these times by inspecting the asset material, test the degradation process, manufacturer’s suggestion, and time-based inspection. These physical and experience based approaches have a high uncertainty of the reliability, due to estimation bias. Differently, SafeCBM takes advantage of Big Data and deep learning to accurately learn RUL, denoted by the Reminding Useful Time, Reminding Time before Failure, and the Probability of Failure at a given time instance, This allows power plants to schedule a Predictive Maintenance on time to prevent functional failure under a given reliability requirement of a NPP equipment.

Improved Power Plant Safety

SafeCBM is a risk-integrated CBM that fuses both risk-based maintenance and condition-based maintenance to meet power plant safety requirements. Based on big data and deep learning, power plant maintenance strategies can be automatically generated in a combination of different maintenance methods (e.g., inspection, detection, TBM, and CBM) to avoid potential power plant risk of equipment failure. This novel and unique capability will be a key proposition value for promoting our power plant maintenance business.

Improved Availability of Components in Power Plant

Reduce unavailability of equipment and components due to maintenance activity and failure. Improve safety system performance indicators and maximize unit availability to optimize outage duration.

Reduce Power Plant Maintenance Cost

SafeCBM adapts risk-based CBM analysis which is conducive to the arrangement of maintenance work to become more scientific and meet the actual needs. It can significantly reduce the number of periodical disintegration or replacement for equipment so as to decrease the human cost, spare parts cost, and the corresponding management cost, and thus cut down the overall maintenance cost. The expected cost-saving can generally reach 20% to 40% based on our experimental case study.

SafeCBM Case Studies

SafeCBM in a Nuclear Power Plants

NPP is the world’s second-largest anthropogenic low-carbon power source that provides more than one-quarter of annual low-carbon electricity supply worldwide and has avoided about 60 gigatons of GHG emissions over the past 50 years according to the International Energy Agency (IEA) in 2019. However, the NPP industry is facing an uncertain future, not only due to the March 2011 Fukushima accident in Japan, but also more fundamentally due to economic reasons like weak growth in electricity demand. A joint report by IEA and Nuclear Energy Agency (NEA) concludes that prolonging the operation of existing nuclear plants, instead of building new large nuclear plants, known as long-term operation (LTO), is the most affordable low-carbon solution in comparison with renewable energy and fossil fuels.

SafeCBM ensures that NPP structures, systems and components (SSCs) can always operate in a long-term safe, reliable, readily available, and economical manner by means of big data and AI.

In general, SafeCBM can be applied to a variety of NPP critical units for improved safety/reliability and reduced cost:

NPP Core System
Steam Generator
Turbines
Water Pumps
Condenser
Electric Generator
And Others

Advanced Oil, Gas, Power Plant and Other Energy Facility Maintenance

SafeCBM can be used for Oil & gas plants, Hydroelectric plants, Coal, solar, and wind plants, power stations, and other energy facilities, which have limited capabilities for automatic and cost-saving troubleshooting and diagnosis to achieve the timeliness and effectiveness of response to emergent degraded conditions. SafeCBM offers them an Artificial Intelligence-based technique to provide facility self-diagnosis, condition-based monitoring, and dynamic-scheduled inspection for automated assessment and correction that improves their reliability and saves the maintenance financial and human cost.

Contact Us

Are you interested in learning more about InfoBeyond's SafeCBM solution? Please contact us with any questions, comments, and concerns regarding how you can partner with InfoBeyond to implement SafeCBM to optimize your power plant operations.