{"id":106074,"date":"2019-11-07T03:06:03","date_gmt":"2019-11-07T02:06:03","guid":{"rendered":"https:\/\/forwind.de\/develop\/project\/wisabigdata-research-project\/"},"modified":"2026-05-05T13:30:40","modified_gmt":"2026-05-05T11:30:40","slug":"wisabigdata-research-project","status":"publish","type":"project","link":"https:\/\/forwind.de\/en\/project\/wisabigdata-research-project\/","title":{"rendered":"WiSAbigdata research project"},"content":{"rendered":"

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WiSAbigdata research project<\/h1>\n

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Project title: WiSAbigdata – Wind farm virtual Site Assistant for O&M decision support – advanced methods for big data analysis.<\/h4>\n

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Summary:<\/p>\n

In modern wind turbines (WTGs), large amounts of operating data are already being collected in high temporal resolution, and this will continue to increase in the future due to developments in measurement technology and digitization. So far, these data are archived and evaluated only very incompletely and often only in the form of 10-minute averages. In contrast, the use of high temporal resolution operational data is a promising approach. However, there is still a considerable need for research in this area in order to identify and tap the potential of the information contained in these data.<\/div>\n

Content and Methodology:<\/p>\n

The aim of the ‘WiSA big data’ project is to contribute to the early detection and diagnosis of faults in wind turbines by analyzing operating data with high temporal resolution and thus to support decisions in maintenance planning and implementation. To this end, on the one hand, methods that have proven effective on the basis of 10-minute averaged operating data are being elaborated and tested for application to temporally high-resolution data. On the other hand, novel methods for early fault detection are transferred to wind energy applications. The developed and tested methods are subjected to a practice-oriented quantitative comparative evaluation. Based on this, an automatic selection of the most suitable methods for the respective application is aimed at. For common data management, analysis and evaluation, a general software and hardware platform will be built as the core system for WiSA. Powerful methods will be implemented for industrial use in a WiSA demonstrator to enable predictive maintenance and detailed analysis of operational events. The connection to the core system for WiSA should make it possible to integrate further innovative methods for early fault detection into the WiSA demonstrator in the future, thereby allowing long-term usability.<\/p>\n

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