{"id":10732,"date":"2023-12-05T14:10:13","date_gmt":"2023-12-05T14:10:13","guid":{"rendered":"https:\/\/annea.ai\/?p=10732"},"modified":"2024-05-06T15:03:05","modified_gmt":"2024-05-06T15:03:05","slug":"using-scada-alarms-to-complement-incomplete-failure-data","status":"publish","type":"post","link":"https:\/\/annea.ai\/de\/using-scada-alarms-to-complement-incomplete-failure-data\/","title":{"rendered":"How SCADA alarms are used to complete failure data"},"content":{"rendered":"
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Over the past decades, the wind energy sector has grown significantly, leading to a worldwide effort to minimise the overall cost of a wind farm. One of the main cost drivers is directly related to operation and maintenance (O&M) actions. Current tendencies in O&M practice are shifting from rather costly corrective strategies to preventive and predictive approaches. Crucial for setting up these cost effective strategies is understanding profoundly when and how wind turbine (WT) components fail. The failure severity, in terms of caused downtime and repair cost, as well as the frequency of failure occurrences are also important. These are available from analysing historical failure databases and maintenance logbooks from manufacturers and operators. The classification of the components and their sub-assemblies regarding their physical location and functionality is essential, using a so called taxonomy or component breakdown. One proposed way to optimise this is by using SCADA alarms.<\/p>\n

Then, the failure base allows for the calculation of the frequencies of component failures and the resulting WT downtimes. Using the outcome of the analysis to build reliability models and failure prediction tools allows us to estimate the WT component degradation over time and to anticipate failures. However, there are still serious problems regarding recent practices and one of the main issues is lack of available failure data. Due to the lack of available data, many reliability models and maintenance decision tools are based on assumed failure rates, which do not sufficiently represent reality. Supervisory Control and Data Acquisition (SCADA) alarms can complement available failure logs with additional information. Most modern WTs are equipped with SCADA systems, generating a huge amount of information for use, mostly free of additional cost.<\/p>\n<\/section>\n<\/section>\n

How SCADA can help predict failures: A study<\/h2>\n
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In order to investigate the correlation between the alarms extracted from the SCADA system and the actual failure occurrences, an analysis of the data from the most widely installed modern technologies was necessary. As older turbines are not necessarily equipped with SCADA systems or only operate relatively limited ones, they were excluded. The different technologies are indicated by their rated power and drive train setup \u2013 being either direct drive or geared WTs.<\/p>\n

As for confidentially reasons no manufacturer names can be published, the letters A to G indicate the WT makes. The numbers 1 to 5 refer to the respective SCADA system used within these turbines. Turbine types A, D, E, F, G have a DFIG and types B and C have a synchronous generator. In the study analysed a total of 440 WTs over a period of three years, resulting in 1320 operational years. It registered and processed an overall number of 653 failures and 1345036 alarms. The failures and alarms per turbine are displayed as rounded values.<\/p>\n

Figures 1 & 2<\/h2>\n

Abbildung 1 zeigt die m\u00f6glichen Alarme f\u00fcr jedes SCADA-System. Abbildung 2 zeigt die Zusammensetzung der tats\u00e4chlich aufgezeichneten Alarme f\u00fcr jedes System innerhalb des gegebenen Beobachtungszeitraums. Sie bestehen aus Alarmen, die sich auf eine bestimmte WEA-Komponente beziehen, aus Alarmen, die auf extreme Umweltbedingungen zur\u00fcckzuf\u00fchren sind, und aus anderen, die keiner Komponente zugeordnet werden konnten, z. B. Netzeinschr\u00e4nkungen. Ein Vergleich der beiden Abbildungen zeigt, dass f\u00fcr die WEA-Typen A, B, C und D viele wetterbedingte Alarme aufgezeichnet wurden, die auf extreme Bedingungen hinweisen, die f\u00fcr bestimmte Komponentenausf\u00e4lle verantwortlich sein k\u00f6nnten. Bei den Anlagen B, C und D war der Anteil der drei aufgezeichneten Alarmkategorien recht \u00e4hnlich. Auch der Anteil der m\u00f6glichen Alarme dieser beiden SCADA-Systeme ist \u00e4hnlich.<\/p>\n

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Figure reference: \u201cWind Turbine Failures \u2013 Tackling current Problems in Failure Data Analysis\u201d by M D Reder et al (2016 J. Phys.: Conf. Ser. 753 072027). View the\u00a0article online\u00a0for updates and enhancements<\/figcaption><\/figure>\n

Figures 3 & 4<\/h2>\n<\/section>\n<\/section>\n
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Figures 3 and 4 represent the contribution of the component related alarms to the total number of recorded alarms. This is compared to the failures per year and turbine, normalised to the total number of failure occurrences. It is taken for granted that the CMS is connected to the SCADA system and functioning well in monitoring the turbine. This means that high numbers of alarms indicate a problem. Showing many alarms but few failures, indicates that the component is well monitored and failures are prevented by shutting down the turbine before they occur.<\/p>\n

It is remarkable that many alarms due to environmental conditions but hardly any blades and controller alarms were recorded. At the same time, however, a large number of blade and controller failures appeared in the data set. The generator also showed relatively high failure rates as well as the second highest number of alarms. The alarms assigned to the generator had the highest share of all component related alarms. It is assumed that the generator is equipped with an extensive CMS to prevent failures. Being direct drive turbines, types B and C showed the lowest total number of failures. Many alarms were assigned to the controller and yaw system. The frequency converter also showed a large number of alarms, however, did not have any failures.<\/p>\n

The SCADA system actually indicated generator problems fairly well by reporting many alarms while very few generator failures occurred. Similar to type A, a high number of alarms due to heavy weather conditions can be related to controller and blade failures. Hence, it is assumed that for direct drive technologies the controller, yaw system and blades are suffering more likely from unfavourable weather conditions than other components.<\/p>\n<\/section>\n<\/section>\n

Type D Turbines<\/h4>\n
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Type D turbines, represented the oldest technology with the lowest rated capacity per turbine. They showed the highest number of failures per WT, and a fairly high number of alarms due to environmental conditions. Many blade failures occurred, however, no alarm could be associated to the blades. The number of alarms related to the gearbox, the communication system and the bearings were quite high, indicating that the latter are well monitored by the SCADA system. The pitch system, the controller and the generator, however, did not provoke many alarms, although showing relatively high failure rates. This could be due to the fact, that the SCADA system in the older technology is not as advanced as it is in newer ones.<\/p>\n

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Figure reference: \u201cWind Turbine Failures \u2013 Tackling current Problems in Failure Data Analysis\u201d by M D Reder et al (2016 J. Phys.: Conf. Ser. 753 072027). View the article online for updates and enhancements<\/figcaption><\/figure>\n

Type E turbines<\/h4>\n<\/section>\n

The highest number of alarms was registered for WTs of type E. Similar to types A and D, the generator caused many failures whilst very few alarms were registered. Especially the hydraulic system showed an extremely large number of alarms. This leads to the theory, that for type E turbines the hydraulic system alarms can indicate failures of other components. Very few weather related alarms were observed. Like others, type E also showed very few alarms for the pitch and yaw system whilst su\ufb00ering from many failures of these components.<\/p>\n

For WT types F, G no blade alarms but many yaw system and weather related ones were recorded. Vibrations in the foundation were indicated by the SCADA system as well as several failures of this part. Showing many alarms and very few failures, the pitch system, the generator and the hydraulic group seemed to be well monitored. The gearbox showed the most critical behaviour, with very few alarms but very high failure rates, and should be monitored better.<\/p>\n

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Figure reference: \u201cWind Turbine Failures \u2013 Tackling current Problems in Failure Data Analysis\u201d by M D Reder et al (2016 J. Phys.: Conf. Ser. 753 072027). View the\u00a0article online\u00a0for updates and enhancements.<\/figcaption><\/figure>\n<\/section>\n

Conclusion<\/h2>\n

The comparison of recorded alarms and historical failure data for five different SCADA systems and WT types showed that for certain components there are significantly more alarms than actual failures \u2013 and contrariwise. In general, high numbers of component alarms and low failure rates indicate that the SCADA system is helping to avoid failures from occurring. Blade and controller failures showed to occur frequently in the presence of alarms indicating harsh environmental conditions. Nonetheless, it is very hard to obtain a global conclusion on how much the SCADA system is adding value to (missing) failure data, as the information provided by the different systems vary strongly. Thus, for each SCADA type the relation between component failures and the respective alarms was demonstrated.<\/p>\n

This is a summary of the original article: \u201cWind Turbine Failures \u2013 Tackling current Problems in Failure Data Analysis\u201d by M D Reder et al (2016 J. Phys.: Conf. Ser. 753 072027).\u00a0View the\u00a0Artikel online.<\/a>\u00a0f\u00fcr Updates und Erweiterungen.<\/em><\/section>\n<\/section>\n
\u00a0<\/section>","protected":false},"excerpt":{"rendered":"

Over the past decades, the wind energy sector has been growing significantly and efforts are being made to minimise the overall cost of a wind farm. 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