Russia Launches Pilot Operation of Predictive Analytics System, Achieving Advance Unit Fault Warning Based on Digital Foundation

The Novovoronezh Phase II Nuclear Power Plant, Leningrad Phase II Nuclear Power Plant, and Beloyarsk Nuclear Power Plant under the Electric Power Division of Rosatom officially launched the pilot operation of a new-generation domestically developed industrial-grade predictive analytics system on October 22. The system is designed to identify potential anomalies in advance before substantive mechanical or electrical failures occur in equipment, marking Russia's entry into a stage of in-depth application of digital intelligent operation and maintenance for in-service nuclear power units.

The system is built on the "AtomIntellect" industrial digital foundation independently developed by the Fuel Division of Rosatom, integrating cutting-edge machine learning algorithms and deep neural network modeling technologies, and possesses strong large-scale multi-dimensional operating condition data processing capabilities. The system can collect and analyze process parameters of key main and auxiliary equipment in real time during long-cycle unit operation, sensitively capture minor state drift, automatically trace the causes of anomalies, predict degradation trends, and precisely push operating condition diagnostic reports to on-site technical experts.

Viktor Tsaranu, head of nuclear power digital operations advancement at Rosenergoatom, pointed out that the platform does not merely trigger simple audible and visual alarms, but directly provides operators and maintenance personnel with causal attribution of parameter evolution, future state projection, and structural weaknesses requiring priority attention, thereby securing sufficient engineering assessment time for operating personnel and significantly improving the precision of preventive response measures. Artyom Golovaty, IT Director of Rosenergoatom, also stated that the self-developed predictive analytics tool can discover early degradation signs that are difficult for humans to detect from complex massive industrial data streams, providing objective data support for core decision-making.

Through practical verification on different types of units such as pressurized water reactors and fast neutron breeder reactors, this technology will strongly promote the transformation of nuclear power operation and maintenance mode from traditional "periodic scheduled maintenance" to "predictive maintenance based on actual operating conditions," thereby substantially reducing the probability of unplanned equipment outages and extending the service life of core equipment. This cross-plant grid-connected pilot operation will comprehensively test the stability of the algorithms under complex electromagnetic environments and harsh production conditions, paving the way for subsequent large-scale promotion to nuclear power units across Russia.

At present, predictive analytics has been established as one of the strategic pillar directions of Rosatom's digital transformation. Relying on the professional data analysis and prediction capability center established at the All-Russian Research Institute for Nuclear Power Plant Operation, relevant institutions will continue to collect cross-unit operating experience feedback and accelerate the independent iteration of domestic industrial software in extreme nuclear-related scenarios.