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Further Research

  • Tomasz Barszcz
Chapter
Part of the Applied Condition Monitoring book series (ACM, volume 14)

Abstract

Writing a chapter about further research recalls an old Danish proverb: “It is difficult to make predictions, especially about the future”. Certainly, there is no crystal ball which can tell us what the most important directions of the development of the techniques of wind turbine fault detection in the years to come will be. In this short chapter the author is aiming to present a few directions which seem to be the most important. The first one is understanding and description of the Varying Operational Conditions themselves. The other one refers to building the real understanding of how faults influence vibration signals or, in the other words, modelling of faults. Better understanding is necessary for improved condition monitoring. The third direction has become very popular in recent years and includes researching all the methods used for automated analysis of data collected on wind farms by both vibration based condition monitoring systems and SCADA. Terabytes of data have created an avalanche of data and there are many claims that we only need the proper method to discover the hidden gems in it. The most widely known tools here are machine learning methods, but they are also accompanied by methods for automatic signal validation or definition of optimal operational states. The fourth—and last—direction is the prognostics of machinery lifetime. It is the “holy grail” of machinery maintenance and despite intensive research it is the hardest one to grasp.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.AGH University of Science and TechnologyKrakówPoland

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