Improvement of the preventive maintenance system at hydroelectric power plants through the use of diagnostic algorithms for assessing the actual technical condition of equipment

   The preventive maintenance system (PMS) is the primary and regulatorily mandated approach to the maintenance of hydroelectric power plants and power enterprises, aimed at ensuring the reliable and safe operation of primary equipment [1]. The calendar-based nature of the PMS makes it possible to maintain the required level of operational reliability; however, it does not fully take into account the actual technical condition of individual hydropower unit components during the inter-repair period. Under changing operating conditions and individual operational characteristics, this may result either in the performance of excessive maintenance interventions or in delayed detection of developing defects, increasing the risk of unplanned repairs. A diagnostic approach is presented, based on the analysis of indirect operational parameters of a hydropower unit recorded by standard automated process control systems (APCS). The proposed algorithm identifies parameter deviations from their characteristic values at early stages of defect development and forms diagnostic indications deterioration in the technical condition of critical hydropower unit components. The effectiveness and informativeness of the approach are demonstrated through the analysis of operational data from hydropower units at a hydroelectric power plant. It is shown that the use of diagnostic algorithms of this class does not require the installation of additional measuring equipment and can be implemented at operating hydroelectric power plants without significant capital expenditures. The application of the proposed approach expands the possibilities for assessing the actual technical condition of equipment, improves the validity of repair planning, promotes the transition to a more flexible and adaptive maintenance model oriented toward real operational indicators and risk-based equipment life management, and enhances the overall industrial safety of the plant.

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