Modeling the dynamic behavior of turbine runner blades during transients using indirect measurements

Diagne, Issa; Gagnon, Martin; Tahan, Antoine

doi:10.1088/1755-1315/49/7/072014

Cited by 10 publications

(10 citation statements)

References 6 publications

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“…These methods consist of simplifying as much as possible the on-site measurements tests. Instead of using sensors on the runner, which implies much longer periods of time for the installation, the basic idea is to estimate the same information with sensors installed on the stationary frame (vibration sensors & pressure sensors) or strain gauges on the rotating shaft [68,90], whose installation can take few hours or a couple of days.…”

Section: Indirect Methodsmentioning

confidence: 99%

“…Diagne et al [90] used shaft torsion measurement for this purpose. According to that study, shaft-torsion measurements are highly correlated to stress on the runner and this type of measurements are much cheaper (usually strain gauges on the shaft can be placed in one day without dewatering the runner).…”

Section: Indirect Methodsmentioning

confidence: 99%

“…12. The main idea of many researches reviewed [57,68,85,90], which have experimentally demonstrated to reduce the dynamic stress, is to make a smoother and longer acceleration time.…”

Section: Start Upmentioning

confidence: 99%

See 2 more Smart Citations

Fatigue life estimation of Francis turbines based on experimental strain measurements: Review of the actual data and future trends

Presas

Luo

Wang

et al. 2019

Renewable and Sustainable Energy Reviews

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Due to the massive entrance of new renewable energies such as wind or solar, hydraulic turbines have to work far from its designed point and withstanding multiple transients, such as starts and stops, that shorten the useful life of the machine and cause fatigue damages. The present paper reviews the complex problem of fatigue in Francis turbines particularly focused on the experimental data available for static and dynamic stresses. For this purpose, many researches, which include different Francis turbines covering a wide range of design head and power, have been considered. The experimental stresses characteristics measured with strain gauges installed on the turbine runner and obtained from previous works have been analyzed for the different operating conditions and transient states occurring in the normal life of actual Francis units. The actual computational capabilities and techniques typically used to estimate such stresses have been discussed in detail. Potential future techniques to simplify complex strain measurements on the turbine runner, computational and statistical methods to estimate turbine stresses are reviewed in this paper. Finally, the relative damage of the different operating conditions and useful life estimation of the turbine, based on past strain measurements of the runner, are addressed.

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Section: Indirect Methodsmentioning

confidence: 99%

Section: Indirect Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Fatigue life estimation of Francis turbines based on experimental strain measurements: Review of the actual data and future trends

Presas

Luo

Wang

et al. 2019

Renewable and Sustainable Energy Reviews

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show abstract

“…Next, there is direct measurement [5] during dedicated measurement campaigns, often done during unit commissioning. Then, there is indirect measurement [6], which is more suitable for online monitoring since one of the main limitations of direct measurement relates to the feasibility of permanent instrumentation of runner blades with strain gauges. Currently, strain gauges are laborious to install, have a limited life expectancy and become highly expensive as more detailed spatial information is required.…”

Section: Introductionmentioning

confidence: 99%

Virtual sensors to generate turbine runner blade strains from indirect measurements

Gagnon

Vouligny

Cauchon

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Strain measurements on turbine blades are difficult and costly tasks. Such measurements, when carried out, generally only happen during the runner commissioning. This gives rise to two problems. The first is that some of the sensors often stop functioning properly during the measurement campaign, which leads to distorted data, and the second is that runner blade strains are not available for long-term monitoring after the measurement campaign. To alleviate the consequences of distorted or missing values, we propose the use of neural networks to automate the imputations of missing values in measurement campaign data using virtual sensors. Three types of network architecture are proposed: Long Short-Term Memory (LSTM) in different multi-stage/multi-layer configurations in Nonlinear Auto-Regressive Neural Networks with exogenous input (NARXNN), injector multi-scale attention network (Injector MA-Net), and a combined architecture using both. The performance of these architectures will be compared in four situations: the loss of strain gauge rosette branches; the loss of a complete strain gauge rosette; the loss of data on a complete blade; and the absence of strain data, which is related to the problem of identifying which sensors could be used for long-term monitoring. The performance of the proposed algorithms will be evaluated on real case scenarios from a measurement campaign during a recent unit commissioning.

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“…An experimental study on a 444 MW prototype Francis turbine suggested that the accelerometers located in the turbine guide vane, bearing, head cover, and in the shaft captured more phenomena compared to other sensors installed in other locations of the turbine [ 15 ]. Strain measurements on the shaft of a propeller turbine during start-up operations showed that torsion measurement can be correlated to the strain measured on the blade hotspot and be used for turbine start-up optimization [ 16 ]. Another experimental investigation on a 200 MW prototype Francis turbine showed that shaft oscillation at the lower guide bearings increased at a part load operation when the pressure fluctuations were intense in the draft tube [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

An Indirect Measurement Methodology to Identify Load Fluctuations on Axial Turbine Runner Blades

Dehkharqani

Engström

Aidanpää

et al. 2020

Sensors

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Smooth integration of intermittent energy sources, such as solar and wind power, into the electrical grid induces new operating conditions of the hydraulic turbine by increasing the off-design operations, start/stops, and load variations. Therefore, hydraulic turbines are subject to unstable flow conditions and unfavorable load fluctuations. Predicting load fluctuations on the runner using indirect measurements can allow for optimized operations of the turbine units, increase turbine refurbishment time intervals, and avoid structural failures in extreme cases. This paper investigates an experimental methodology to assess and predict the flow condition and load fluctuations on a Kaplan turbine runner at several steady-state operations by performing measurements on the shaft in the rotating and stationary frame of references. This unit is instrumented with several transducers such as miniature pressure transducers, strain gages, and proximity probes. The results show that for any propeller curve of a Kaplan turbine, the guide vane opening corresponding to the minimum pressure and strain fluctuations on the runner blade can be obtained by axial, torsion, and bending measurements on the shaft. Torsion measurements on the shaft could support index-testing in Kaplan turbines particularly for updating the cam-curve during the unit operation. Furthermore, a signature of every phenomenon observed on the runner blade signals, e.g., runner frequency, rotating vortex rope components, and rotor-stator interaction, is found in the data obtained from the shaft.

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Modeling the dynamic behavior of turbine runner blades during transients using indirect measurements

Cited by 10 publications

References 6 publications

Fatigue life estimation of Francis turbines based on experimental strain measurements: Review of the actual data and future trends

Fatigue life estimation of Francis turbines based on experimental strain measurements: Review of the actual data and future trends

Virtual sensors to generate turbine runner blade strains from indirect measurements

An Indirect Measurement Methodology to Identify Load Fluctuations on Axial Turbine Runner Blades

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