Securities Code:430215

This system assists power plants in building data assets for supervised equipment, improving underlying management data, and enhancing standardization and refinement from the ground up. It establishes and integrates a technical supervision and controlplatform that utilizes big data to quantitatively evaluate the reliability of supervised equipment. Comprehensive, multi-perspective management is achieved across aspects such as installation standards, quality grades, technical documentation, logicalreliability, personnel skills, periodic tasks, scheduled maintenance, operational quality, technical management, and time-based accumulation. This drives a qualitative leap in existing technical supervision practices.
Furthermore, the system enablesseamless connectivity with electric power research institutes (CEPRI), reduces management costs, and ensures accurate monitoring of abnormal data dynamics.
◆Integration with the SIS enables automatic pushing of periodic tasks and automatic generation of technical supervision reports. Online and offline data from technical supervision management are stored in a structured manner, allowing trend analysis and early warnings for various supervision indicators. ◆By integrating data related to equipment reliability and economy, multi-parameter and multi-dimensional coupled modeling and analysis are performed, with diagnostic conclusions automatically delivered. ◆Group-wide deployment allows the Electric Power Research Institute (EPRI) to conduct remote diagnosis of unit operational status and remote evaluation of technical supervision tasks, thereby enhancing the effectiveness and efficiency of technical supervision management.
◆Visualization of technical supervision status Standardize and dynamic equipment ledgers; ◆Standardization of test reports and statements; Regular work is automatically triggered; Optimize data collection and processing; ◆Intelligent diagnosis: Automation of equipment condition assessment, automation of equipment risk assessment, automation of equipment lifespan assessment, and automation of equipment economic assessment.
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