PSI - Issue 28

Evgeniia Georgievskaia et al. / Procedia Structural Integrity 28 (2020) 836–842 Evgeniia Georgievskaia/ Structural Integrity Procedia 00 (2020) 000–000

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analytics system. Demo Version of the proposed predictive system on the example of the runner for the large Francis hydraulic turbine you can find by link http://bi.vdi-service.ru:443/. The influence of off-design operational modes on the equipment lifetime can be seen by comparing the operating time and exhausted lifetime for base and peak modes under equal operating time for the prognostic period. The peak modes are characterized by long-term operation at off-design modes and a large number of starts/stops. The operating in base mode supposes the long-term work in the BEP area with 10-12 starts/stops per year. Figure 4 shows the distribution of the lifetime on the different operational modes for two scenarios. As you can see, the exhausted and residual lifetime vary greatly for different ranges of modes. In addition, there is a significant margin in the lifetime between “Base” and “Peak” scenarios (see Table 1). Comparison of operating time and exhausted lifetime allows us to detect non-optimal operating modes and take into account their influences on long term forecasts for technical conditions predicting the appearance of hidden defects at an early stage.

Table 1. Comparison lifetime at base and peak modes. Lifetime, % Total operating time for the prognostic period, hours

Base mode

Peak mode

37230

Average operating time per year for the prognostic period, hours Average number of startup and shutdown per year for the prognostic period, pc.

5 319

214

29

Exhausted lifetime, % Residual lifetime, % Residual lifetime, years

71.9 28.1  300

98.7

1.3 4.6

Residual lifetime, thousand hours

>1 000

 22

Fig. 4. The distribution of lifetime on the different operational modes for Base and Peak scenarios