Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements
ABSTRACT In efforts to reduce the operation and maintenance cost of wind turbines, there is an increasing interest to monitor key turbine quantities such as the torque load on the gearbox. Monitoring the torque paves the way for the calculation of remaining useful lifetime, leading to cost reduction...
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| Format: | Article |
| Language: | English |
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Wiley
2025-02-01
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| Series: | Wind Energy |
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| Online Access: | https://doi.org/10.1002/we.2955 |
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| _version_ | 1832581032996503552 |
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| author | Jelle Bosmans Simone Gallas Victor Smeets Matteo Kirchner Luk Geens Jan Croes Wim Desmet |
| author_facet | Jelle Bosmans Simone Gallas Victor Smeets Matteo Kirchner Luk Geens Jan Croes Wim Desmet |
| author_sort | Jelle Bosmans |
| collection | DOAJ |
| description | ABSTRACT In efforts to reduce the operation and maintenance cost of wind turbines, there is an increasing interest to monitor key turbine quantities such as the torque load on the gearbox. Monitoring the torque paves the way for the calculation of remaining useful lifetime, leading to cost reductions through improved reliability and maintenance planning. In order to avoid expensive direct torque sensors, this paper investigates the potential of virtual torque sensing, a technique based on 3 basic components: first, a set of non‐intrusive sensors installed on the gearbox. Three groups of strain gauges on the gearbox as well an angular encoder are considered in this paper. Second is a physics‐based model, capable of predicting the response of aforementioned sensors. These models are constructed with a purposeful balance between accuracy and computational cost. Model validation and updating are performed to ensure efficient and accurate prediction of the sensor output. Finally, an augmented extended Kalman filter (AEKF) is used to combine the measured response with predictions from the model to infer the gearbox input torque. Since a key factor determining the performance of the AEKF is the tuning of the AEKF covariance matrices, multiple methods are introduced to systematically tune the covariance matrices. Experimental validation results show that the virtual torque sensor can detect the load torque with a normalized mean absolute error (NMAE) between 3.41% and 7.47%, depending on the sensor set. The influence of the amount of sensors used and the tuning method are also investigated. |
| format | Article |
| id | doaj-art-2fdf7a84dca744fcbf3d84a68d3b8209 |
| institution | Kabale University |
| issn | 1095-4244 1099-1824 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Wind Energy |
| spelling | doaj-art-2fdf7a84dca744fcbf3d84a68d3b82092025-01-30T10:32:38ZengWileyWind Energy1095-42441099-18242025-02-01282n/an/a10.1002/we.2955Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain MeasurementsJelle Bosmans0Simone Gallas1Victor Smeets2Matteo Kirchner3Luk Geens4Jan Croes5Wim Desmet6Department of Mechanical Engineering KU Leuven Leuven BelgiumDepartment of Mechanical Engineering KU Leuven Leuven BelgiumDepartment of Mechanical Engineering KU Leuven Leuven BelgiumDepartment of Mechanical Engineering KU Leuven Leuven BelgiumZF Wind Power Antwerpen NV Lommel BelgiumForcebit BV Kessel‐Lo BelgiumDepartment of Mechanical Engineering KU Leuven Leuven BelgiumABSTRACT In efforts to reduce the operation and maintenance cost of wind turbines, there is an increasing interest to monitor key turbine quantities such as the torque load on the gearbox. Monitoring the torque paves the way for the calculation of remaining useful lifetime, leading to cost reductions through improved reliability and maintenance planning. In order to avoid expensive direct torque sensors, this paper investigates the potential of virtual torque sensing, a technique based on 3 basic components: first, a set of non‐intrusive sensors installed on the gearbox. Three groups of strain gauges on the gearbox as well an angular encoder are considered in this paper. Second is a physics‐based model, capable of predicting the response of aforementioned sensors. These models are constructed with a purposeful balance between accuracy and computational cost. Model validation and updating are performed to ensure efficient and accurate prediction of the sensor output. Finally, an augmented extended Kalman filter (AEKF) is used to combine the measured response with predictions from the model to infer the gearbox input torque. Since a key factor determining the performance of the AEKF is the tuning of the AEKF covariance matrices, multiple methods are introduced to systematically tune the covariance matrices. Experimental validation results show that the virtual torque sensor can detect the load torque with a normalized mean absolute error (NMAE) between 3.41% and 7.47%, depending on the sensor set. The influence of the amount of sensors used and the tuning method are also investigated.https://doi.org/10.1002/we.2955extended Kalman filtergearboxstrain gaugesvirtual torque sensing |
| spellingShingle | Jelle Bosmans Simone Gallas Victor Smeets Matteo Kirchner Luk Geens Jan Croes Wim Desmet Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements Wind Energy extended Kalman filter gearbox strain gauges virtual torque sensing |
| title | Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements |
| title_full | Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements |
| title_fullStr | Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements |
| title_full_unstemmed | Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements |
| title_short | Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements |
| title_sort | experimental validation of virtual torque sensing for wind turbine gearboxes based on strain measurements |
| topic | extended Kalman filter gearbox strain gauges virtual torque sensing |
| url | https://doi.org/10.1002/we.2955 |
| work_keys_str_mv | AT jellebosmans experimentalvalidationofvirtualtorquesensingforwindturbinegearboxesbasedonstrainmeasurements AT simonegallas experimentalvalidationofvirtualtorquesensingforwindturbinegearboxesbasedonstrainmeasurements AT victorsmeets experimentalvalidationofvirtualtorquesensingforwindturbinegearboxesbasedonstrainmeasurements AT matteokirchner experimentalvalidationofvirtualtorquesensingforwindturbinegearboxesbasedonstrainmeasurements AT lukgeens experimentalvalidationofvirtualtorquesensingforwindturbinegearboxesbasedonstrainmeasurements AT jancroes experimentalvalidationofvirtualtorquesensingforwindturbinegearboxesbasedonstrainmeasurements AT wimdesmet experimentalvalidationofvirtualtorquesensingforwindturbinegearboxesbasedonstrainmeasurements |