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2014 | OriginalPaper | Buchkapitel

Non-Clustering Method for Automatic Selection of Machine Operational States

verfasst von : Adam Jablonski, Tomasz Barszcz, Piotr Wiciak

Erschienen in: Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Verlag: Springer Berlin Heidelberg

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Abstract

A reliable evaluation of technical condition of machinery working under non-stationary conditions requires a rigorous tracking of operational parameters. Therefore, modern condition monitoring systems (CMS) enable reading and registering of process parameters (e.g. speed, load, pressure, etc.) in parallel with acquisition of vibroacoustic signals. Although few tries have been undertaken to develop state-free analysis of vibration signals, currently installed systems still do rely on state-preclassified data. The paper shows how the process, referential data might be automatically transformed into proposition of optimal machine operational states in terms of their number and their range. As indicated by the title, the paper shows common pitfalls coming from implementation of popular clustering approach. The proposed algorithm illustrates is verified on real data from a pitch-controlled wind turbine.

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Literatur
2.
Zurück zum Zitat Jablonski A, Barszcz T (2012) Procedure for data acquisition for machinery working under non-stationary operational conditions. The 9th international conference on condition monitoring and machinery failure prevention technologies, London, 12–14 June 2012 Jablonski A, Barszcz T (2012) Procedure for data acquisition for machinery working under non-stationary operational conditions. The 9th international conference on condition monitoring and machinery failure prevention technologies, London, 12–14 June 2012
3.
Zurück zum Zitat Hameed Z et al (2009) Condition monitoring and fault detection of wind turbines and related algorithms: a review. Renew Sustain Energy Rev 13(1):1–39CrossRef Hameed Z et al (2009) Condition monitoring and fault detection of wind turbines and related algorithms: a review. Renew Sustain Energy Rev 13(1):1–39CrossRef
4.
Zurück zum Zitat Mykhaylyshyn V et al. (2010) Classification of wind turbine generator operation states for the purpose of advanced vibration monitoring’ (Mita-Teknik, Denmard). European wind energy conference and exhibition (EWEC), Warsaw, Poland, 20–23 April Mykhaylyshyn V et al. (2010) Classification of wind turbine generator operation states for the purpose of advanced vibration monitoring’ (Mita-Teknik, Denmard). European wind energy conference and exhibition (EWEC), Warsaw, Poland, 20–23 April
5.
Zurück zum Zitat Broda D, Jablonski A, Barszcz T (2012) Optimisation of operational state definition for wind farms: part 1: development of algorithms. The 9th international conference on condition monitoring and machinery failure prevention technologies, London, 12–14 June Broda D, Jablonski A, Barszcz T (2012) Optimisation of operational state definition for wind farms: part 1: development of algorithms. The 9th international conference on condition monitoring and machinery failure prevention technologies, London, 12–14 June
6.
Zurück zum Zitat Zimroz R. et al. (2012) Statistical data processing for wind turbine generator bearing diagnostics. The 2nd international conference condition monitoring of machinery in non-stationary operations, Hammamet, Tunisia, 26–28 March Zimroz R. et al. (2012) Statistical data processing for wind turbine generator bearing diagnostics. The 2nd international conference condition monitoring of machinery in non-stationary operations, Hammamet, Tunisia, 26–28 March
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Zurück zum Zitat Gellermann T (2003) Requirements for condition monitoring systems for wind turbines, AZT Expertentage, Allianz, Nov. 10–11 Gellermann T (2003) Requirements for condition monitoring systems for wind turbines, AZT Expertentage, Allianz, Nov. 10–11
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Zurück zum Zitat Hau E (2006) Wind turbines: fundamentals, technologies, applications, economics, 2nd edn. Springer, Berlin Hau E (2006) Wind turbines: fundamentals, technologies, applications, economics, 2nd edn. Springer, Berlin
Metadaten
Titel
Non-Clustering Method for Automatic Selection of Machine Operational States
verfasst von
Adam Jablonski
Tomasz Barszcz
Piotr Wiciak
Copyright-Jahr
2014
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-39348-8_36

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