Use of novel algorithms for Predictive Maintenance in wind turbines

Rauvl Ruiz De La Hermosa González-Carrato; Fausto Pedro García Márquez; Mayorkinos Papaelias

Use of novel algorithms for Predictive Maintenance in wind turbines

Rauvl Ruiz De La Hermosa González-Carrato
, Fausto Pedro García Márquez
, Mayorkinos Papaelias

Metallurgy and Materials

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The increased of the reliability, availability, maintainability and safety (RAMS) for wind turbines (WT) has become a key factor in the field of renewable energies. Supervisory Control and Data Acquisition (SCADA) systems applied to WTs guarantee the correct levels of Reliability, Availability, Maintainability and Safety (RAMS). This paper describes a novel method for Predictive Maintenance in a WT. The sound, current, rotor speed, wind speed, time, temperature, etc. signals have been collected. The main objective has been to analyse the signals for Fault Detection and Diagnosis using the wavelet decomposition technique together with others, e.g. Fast Fourier transform. This paper has carried for different types of maintenance that involves the existence of rolling elements in order to find potential faults in driven systems, as engines or cooling devices. Therefore it is possible to associate the conclusions reached for sound and vibration in previous experimental tests with this new data.

Original language	English
Title of host publication	10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013
Publisher	British Institute of Non-Destructive Testing
Pages	310-322
Number of pages	13
ISBN (Print)	9781629939926
Publication status	Published - 2013
Event	10th International Conference on Condition Monitoring, CM 2013 and Machinery Failure Prevention Technologies 2013, MFPT 2013 - Krakow, United Kingdom Duration: 18 Jun 2013 → 20 Jun 2013

Publication series

Name	10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013
Volume	1

Conference

Conference	10th International Conference on Condition Monitoring, CM 2013 and Machinery Failure Prevention Technologies 2013, MFPT 2013
Country/Territory	United Kingdom
City	Krakow
Period	18/06/13 → 20/06/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Maintenance management
Pattern recognition
Wavelet transform
Wind turbines

ASJC Scopus subject areas

Mechanical Engineering
Safety, Risk, Reliability and Quality

Cite this

De La Hermosa González-Carrato, R. R., Márquez, F. P. G., & Papaelias, M. (2013). Use of novel algorithms for Predictive Maintenance in wind turbines. In 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013 (pp. 310-322). (10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013; Vol. 1). British Institute of Non-Destructive Testing.

De La Hermosa González-Carrato, Rauvl Ruiz ; Márquez, Fausto Pedro García ; Papaelias, Mayorkinos. / Use of novel algorithms for Predictive Maintenance in wind turbines. 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013. British Institute of Non-Destructive Testing, 2013. pp. 310-322 (10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013).

@inproceedings{a5fdab01f2ec452483239569fbe778a7,

title = "Use of novel algorithms for Predictive Maintenance in wind turbines",

abstract = "The increased of the reliability, availability, maintainability and safety (RAMS) for wind turbines (WT) has become a key factor in the field of renewable energies. Supervisory Control and Data Acquisition (SCADA) systems applied to WTs guarantee the correct levels of Reliability, Availability, Maintainability and Safety (RAMS). This paper describes a novel method for Predictive Maintenance in a WT. The sound, current, rotor speed, wind speed, time, temperature, etc. signals have been collected. The main objective has been to analyse the signals for Fault Detection and Diagnosis using the wavelet decomposition technique together with others, e.g. Fast Fourier transform. This paper has carried for different types of maintenance that involves the existence of rolling elements in order to find potential faults in driven systems, as engines or cooling devices. Therefore it is possible to associate the conclusions reached for sound and vibration in previous experimental tests with this new data.",

keywords = "Maintenance management, Pattern recognition, Wavelet transform, Wind turbines",

author = "\{De La Hermosa Gonz{\'a}lez-Carrato\}, \{Rauvl Ruiz\} and M{\'a}rquez, \{Fausto Pedro Garc{\'i}a\} and Mayorkinos Papaelias",

year = "2013",

language = "English",

isbn = "9781629939926",

series = "10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013",

publisher = "British Institute of Non-Destructive Testing",

pages = "310--322",

booktitle = "10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013",

note = "10th International Conference on Condition Monitoring, CM 2013 and Machinery Failure Prevention Technologies 2013, MFPT 2013 ; Conference date: 18-06-2013 Through 20-06-2013",

}

De La Hermosa González-Carrato, RR, Márquez, FPG & Papaelias, M 2013, Use of novel algorithms for Predictive Maintenance in wind turbines. in 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013. 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013, vol. 1, British Institute of Non-Destructive Testing, pp. 310-322, 10th International Conference on Condition Monitoring, CM 2013 and Machinery Failure Prevention Technologies 2013, MFPT 2013, Krakow, United Kingdom, 18/06/13.

Use of novel algorithms for Predictive Maintenance in wind turbines. / De La Hermosa González-Carrato, Rauvl Ruiz; Márquez, Fausto Pedro García; Papaelias, Mayorkinos.
10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013. British Institute of Non-Destructive Testing, 2013. p. 310-322 (10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Use of novel algorithms for Predictive Maintenance in wind turbines

AU - De La Hermosa González-Carrato, Rauvl Ruiz

AU - Márquez, Fausto Pedro García

AU - Papaelias, Mayorkinos

PY - 2013

Y1 - 2013

N2 - The increased of the reliability, availability, maintainability and safety (RAMS) for wind turbines (WT) has become a key factor in the field of renewable energies. Supervisory Control and Data Acquisition (SCADA) systems applied to WTs guarantee the correct levels of Reliability, Availability, Maintainability and Safety (RAMS). This paper describes a novel method for Predictive Maintenance in a WT. The sound, current, rotor speed, wind speed, time, temperature, etc. signals have been collected. The main objective has been to analyse the signals for Fault Detection and Diagnosis using the wavelet decomposition technique together with others, e.g. Fast Fourier transform. This paper has carried for different types of maintenance that involves the existence of rolling elements in order to find potential faults in driven systems, as engines or cooling devices. Therefore it is possible to associate the conclusions reached for sound and vibration in previous experimental tests with this new data.

AB - The increased of the reliability, availability, maintainability and safety (RAMS) for wind turbines (WT) has become a key factor in the field of renewable energies. Supervisory Control and Data Acquisition (SCADA) systems applied to WTs guarantee the correct levels of Reliability, Availability, Maintainability and Safety (RAMS). This paper describes a novel method for Predictive Maintenance in a WT. The sound, current, rotor speed, wind speed, time, temperature, etc. signals have been collected. The main objective has been to analyse the signals for Fault Detection and Diagnosis using the wavelet decomposition technique together with others, e.g. Fast Fourier transform. This paper has carried for different types of maintenance that involves the existence of rolling elements in order to find potential faults in driven systems, as engines or cooling devices. Therefore it is possible to associate the conclusions reached for sound and vibration in previous experimental tests with this new data.

KW - Maintenance management

KW - Pattern recognition

KW - Wavelet transform

KW - Wind turbines

UR - https://www.scopus.com/pages/publications/84905824283

M3 - Conference contribution

AN - SCOPUS:84905824283

SN - 9781629939926

T3 - 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013

SP - 310

EP - 322

BT - 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013

PB - British Institute of Non-Destructive Testing

T2 - 10th International Conference on Condition Monitoring, CM 2013 and Machinery Failure Prevention Technologies 2013, MFPT 2013

Y2 - 18 June 2013 through 20 June 2013

ER -

De La Hermosa González-Carrato RR, Márquez FPG, Papaelias M. Use of novel algorithms for Predictive Maintenance in wind turbines. In 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013. British Institute of Non-Destructive Testing. 2013. p. 310-322. (10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013).

Use of novel algorithms for Predictive Maintenance in wind turbines

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Fingerprint

Cite this