We would like to focus on advanced CBM techniques for hydro power plant equipment health check and failure root analysis.

Hydro power plants have been working for several decades by following the scheduled maintenance practice. It can be reasonable in a sort of “base-load” conception, but nowadays flexibility requests load variations, partial loads and working points typically far from the nominal/optimal one. In this scenario, a condition-based monitoring approach is needed, in order to optimize maintenance, stops and machinery/plant efficiency.

The essay we are referring to shows the application developed in Bardi Hydro Power plant (EGP). In this application, in addition to the plant probes, further sensors have been installed. The system manages different kinds of measures simultaneously and continuously and calculates (by using an automatized and accurate procedure, based on mathematical algorithms) health/performance indicators reliable and simple to understand. The scope of this application is to use these indicators in order to prevent breakdowns and to rationalize maintenance. Indeed, malfunctions on generators, bearings, engines, turbines, etc., can be very expensive and it is necessary to reduce the costs of equipment repairs or spare parts management/storage. This system has been installed in site, but all the data are sent to the headquarter and the power plant users can easily detect faults and degradation phenomena before to reach a “no-return point”.

Through the data collection and diagnostic calculations the essay shows how the system monitors the filtered data, compares them to the reference values and performs diagnostic computations to determine the FP_i and SKD_i used by the MCDM calculations.

Its ability to judge different alternatives of malfunctions on various criteria is useful to establish the actual state of plant health, provide potential damage and provide maintenance suggestions to operators.

To go deeper through the paper please contact us.