StemCon – specialists in the diagnostics of pipeline systems and sewers including pipe diagnostics
Diagnostics of pipeline systems and sewers including
pipe diagnostics in pipelines no longer in operation, TV monitoring,
repair of pipelines, trenchless repair projects

Large power systems diagnostics

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Large power systems diagnostics

OpenPredictor system solution

OPENpredictor™ is a supervisory, protective and report-generating system designed to provide crucial information on the state of rotating machinery at power stations. This information is essential to help customers minimise maintenance costs and increase availability.
Maintenance minimisation and availability increases are supported by the OPENpredictor™ damage early-warning system. It is able to determine failures on the basis of symptoms of wear or defect and make a prognosis of when the equipment needs to be serviced. This approach is known as condition-based maintenance (CBM). All these processes are automatic in the OPENpredictor™ system. A change in maintenance strategy from preventative maintenance to CBM will transfer measurement activities only to those machines which really need maintained. In this way, the system user can reduce his need for preventative maintenance (with fixed planned intervals), optimise the intervals between repairs and reduce the need for associated pre-ordered replacement parts.
To achieve maximum availability, it is important to co-ordinate your maintenance activities for all critical machinery. For this reason, all known failures which occur in the equipment are incorporated into the OPENpredictor software system, which significantly simplifies the assessment processes for the OPENpredictor system user. This failure summary is called the failure library and it includes all rotary machinery which exists in power-stations today.
All machinery is composed of a number of components with their own failure frequency. With a knowledge of these frequencies, OPENpredictor™ is configured so it can ’recognise’ any of these failures from its so-called symptoms. Symptoms are used for defining intensity expressions for each determined or existing failure. In order to differentiate between failures which are symptomatically similar, OPENpredictor™ imports not only vibrational data, but also available operating data. Operating data is used in order to differentiate and demarcate operating and transient states and for machinery classification.

This proactive monitoring strategy helps minimise false alarms and also improve the reliability of prognoses created in the OPENpredictor™ software system.