Estimation of prepressure in hydraulic piston accumulators for industrial wind turbines using multi-model adaptive estimation

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

Failures in pitch systems may cause fatal damage to industrial wind turbines. One of the main reasons for failures in pitch systems is gas leakages of hydraulic accumulators. Due to the limited accessibility of offshore turbines, automated fault detection algorithms potentially increase turbine availability. The
gas leakage is detected without downtime by using a modelbased approach together with a bank and extended Kalman filters (EKF’s). The residual is analyzed using multi-model adaptive estimation (MMAE). The applied accumulator model relies on a thermal time constant describing the heat flux from the gas to the surroundings. The thermal time constant has been empirically derived from a prepressure of 50 to 172 bar. The fault detection algorithm is tested experimentally in a laboratory on a 25 liters piston accumulator using a load scenario obtained from real turbine data and a prepressure range of 50-140 bar. The Bank of EKF’s can classify the prepressure within a range and thereby detect if a gas leakage has occurred before it results
in failure.
Original languageEnglish
Title of host publicationProceedings of the ASME/BATH 2019 Symposium on Fluid Power and Motion Control
Number of pages11
PublisherAmerican Society of Mechanical Engineers
Publication date2019
Article numberFPMC2019-1665
Publication statusPublished - 2019
EventASME/BATH 2019 Symposium on Fluid Power and Motion Control - Zota Beach Resort, Longboat Key, United States
Duration: 7 Oct 20199 Oct 2019
http://event.asme.org/FPMC

Conference

ConferenceASME/BATH 2019 Symposium on Fluid Power and Motion Control
LocationZota Beach Resort
CountryUnited States
CityLongboat Key
Period07/10/201909/10/2019
Internet address

Fingerprint

Pistons
Wind turbines
Turbines
Leakage (fluid)
Hydraulics
Extended Kalman filters
Fault detection
Hydraulic accumulators
Gases
Heat flux
Availability
Hot Temperature

Keywords

  • Hydraulic accumulator
  • Wind turbine pitch system;
  • Leakage Detection
  • Model-based FDD

Cite this

Sørensen, F. F., von Benzon, M. S. R., Klemmensen, S. S., Schmidt, K., & Liniger, J. (2019). Estimation of prepressure in hydraulic piston accumulators for industrial wind turbines using multi-model adaptive estimation. In Proceedings of the ASME/BATH 2019 Symposium on Fluid Power and Motion Control [FPMC2019-1665] American Society of Mechanical Engineers.
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title = "Estimation of prepressure in hydraulic piston accumulators for industrial wind turbines using multi-model adaptive estimation",
abstract = "Failures in pitch systems may cause fatal damage to industrial wind turbines. One of the main reasons for failures in pitch systems is gas leakages of hydraulic accumulators. Due to the limited accessibility of offshore turbines, automated fault detection algorithms potentially increase turbine availability. Thegas leakage is detected without downtime by using a modelbased approach together with a bank and extended Kalman filters (EKF’s). The residual is analyzed using multi-model adaptive estimation (MMAE). The applied accumulator model relies on a thermal time constant describing the heat flux from the gas to the surroundings. The thermal time constant has been empirically derived from a prepressure of 50 to 172 bar. The fault detection algorithm is tested experimentally in a laboratory on a 25 liters piston accumulator using a load scenario obtained from real turbine data and a prepressure range of 50-140 bar. The Bank of EKF’s can classify the prepressure within a range and thereby detect if a gas leakage has occurred before it resultsin failure.",
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Sørensen, FF, von Benzon, MSR, Klemmensen, SS, Schmidt, K & Liniger, J 2019, Estimation of prepressure in hydraulic piston accumulators for industrial wind turbines using multi-model adaptive estimation. in Proceedings of the ASME/BATH 2019 Symposium on Fluid Power and Motion Control., FPMC2019-1665, American Society of Mechanical Engineers, ASME/BATH 2019 Symposium on Fluid Power and Motion Control, Longboat Key, United States, 07/10/2019.

Estimation of prepressure in hydraulic piston accumulators for industrial wind turbines using multi-model adaptive estimation. / Sørensen, Fredrik Fogh; von Benzon, Malte Severin Rosencrone; Klemmensen, Sigurd Stoltenberg; Schmidt, Kenneth; Liniger, Jesper.

Proceedings of the ASME/BATH 2019 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2019. FPMC2019-1665.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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AU - Schmidt, Kenneth

AU - Liniger, Jesper

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AB - Failures in pitch systems may cause fatal damage to industrial wind turbines. One of the main reasons for failures in pitch systems is gas leakages of hydraulic accumulators. Due to the limited accessibility of offshore turbines, automated fault detection algorithms potentially increase turbine availability. Thegas leakage is detected without downtime by using a modelbased approach together with a bank and extended Kalman filters (EKF’s). The residual is analyzed using multi-model adaptive estimation (MMAE). The applied accumulator model relies on a thermal time constant describing the heat flux from the gas to the surroundings. The thermal time constant has been empirically derived from a prepressure of 50 to 172 bar. The fault detection algorithm is tested experimentally in a laboratory on a 25 liters piston accumulator using a load scenario obtained from real turbine data and a prepressure range of 50-140 bar. The Bank of EKF’s can classify the prepressure within a range and thereby detect if a gas leakage has occurred before it resultsin failure.

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KW - Model-based FDD

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Sørensen FF, von Benzon MSR, Klemmensen SS, Schmidt K, Liniger J. Estimation of prepressure in hydraulic piston accumulators for industrial wind turbines using multi-model adaptive estimation. In Proceedings of the ASME/BATH 2019 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers. 2019. FPMC2019-1665