1 / 19

Failure Detection with Statistical Process Control

Failure Detection with Statistical Process Control. Dr. Tomasz Kaminski. Partly automatic, early and realiable detection of changes. Our target?. SR::SPC. Control room. Air ingress. 07.09.2006 plausible alarm.

tadita
Download Presentation

Failure Detection with Statistical Process Control

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Failure Detection with Statistical Process Control Dr. Tomasz Kaminski

  2. Partly automatic, early and realiable detection of changes Our target? SR::SPC Control room Air ingress 07.09.2006 plausible alarm Feb 2008 | Annual Technical Meeting

  3. Key Performance Indicators (KPIs) can be used to detect component failures and to enable condition based maintainance. KPI should depend only on component condition but not on load, ambient conditions or operation mode Key Performance Indicators Feb 2008 | Annual Technical Meeting

  4. protection limit Properties of key measurements Key measurements in power plants usually depend on - load,- operation mode - fuel quality - ambient conditions - etc.And are superposed by noise. Feb 2008 | Annual Technical Meeting

  5. key performance indicators by Act / Ref-comparison (KPI) KPIs measure the qualitiy of the process / component. They do not depend on external disturbance variables KPI = act-value / ref-value protectionlimit “KPI“-limit normalizedparameter= KPI Feb 2008 | Annual Technical Meeting

  6. Reference values- based on data or first principles Dataminingoder first principles models as a basis to calculate references to normalize measurements to KPIs The reference values describe the expected dependency of the key measurements on disturbencies using historical data Feb 2008 | Annual Technical Meeting

  7. Monitoring of noisy KPIs- false alarms vs. sensitivity Fixed limiits on noisy KPIs will results in frequent false alarms or less sensitivity. The consequence is poor aceptance of the monitoring system. Fluegas Reheater Beispiel: REA-Gavo Beispiel: Luftvorwärmer Airheater Feb 2008 | Annual Technical Meeting

  8. Statistical process control (SPC) - transform data into information Control charts of KPIs Feb 2008 | Annual Technical Meeting

  9. A simple example: condenser pressure Long term trend in PIMS short term trend in DCS system 07.09.2006 air ingress 07.09.2006 air ingress Feb 2008 | Annual Technical Meeting

  10. A simple example: condenser pressure SR::SPC evaluation KPIfrom PADO false alarms 07.09.2006 plausible alarm air ingress 07.09.2006 plausible alarm air ingress Feb 2008 | Annual Technical Meeting

  11. More examplesFailure of boiler feed pump Feb 2008 | Annual Technical Meeting

  12. Benefits of SPC in power generation application field, active principle and benefit of SPC process quality control fault detection / sensor monitoring App-licationfieldactiveprinciplebenefit converting of unplanned to planned outages extension of maintanance cycles and improved operation scheduling automatic detection of process losses improvement of image by raising of reliability cost reduction byreliable fulfill of delivery obligations increase of profit by improvement of productivity reduction of maintainance costs reduction of fuel and CO2 costs Feb 2008 | Annual Technical Meeting

  13. Benefits of SPC in power generation Early and reliable detection of component failures • Saves by reducing fuel and CO2 costs • Saves by avoiding unplanned outtages • . . . . . . Feb 2008 | Annual Technical Meeting

  14. Alarm center of SR::SPC Feb 2008 | Annual Technical Meeting

  15. KPI for power plants • process quality control - SR::EPOS quality fgactors - pressure loss: air preheater, GT-inlet filter, - temperatures: MS, RH, fluegas upstream air-preheater …, - quality factors: condensor, ESP*, heating surfaces, GT-compressor, - heatrate*, • condition monitoring • sound / vibrations, temperatures, power consumption / generation • of drives, gears, bearings, rotors … • of turbines, fans, pumps etc. • Tube-Leakage* • sensor failure detection • - e.g. important emission sensors • )* Machbarkeitsstudie bzw. in Vorbereitung Feb 2008 | Annual Technical Meeting

  16. SR::SPCFault Tree • fault tree modul for automatic fault detection Feb 2008 | Annual Technical Meeting

  17. Thank You for your attention !!! Feb 2008 | Annual Technical Meeting

  18. Thank You for your attention !!! Feb 2008 | Annual Technical Meeting

  19. Various methods permit a handling of different situations. Feb 2008 | Annual Technical Meeting

More Related