Application of diagnosis and prognosis to wind turbine system based on fatigue load

Beganović, Nejra; Njiri, Jackson G.; Rothe, Sandra; Söffker, Dirk

doi:10.1109/icphm.2015.7245031

Cited by 8 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A control strategy for extending the maintenance interval of wind turbine blades under assumed crack initiation, detected using a data filtering algorithm, is proposed (Beganovic et al, 2015). In (Beganovic et al, 2018;Njiri et al, 2019), a set of switching controllers with varying degrees of load mitigation are engaged sequentially based on the accumulated damage obtained from an online damage evaluation model to extend the lifetime of rotor blades.…”

Section: Introductionmentioning

confidence: 99%

“…Depending on the damage accumulation and the predicted lifetime provided by a online damage evaluation model, the weights of the lifetime controller are varied. However, in (Beganovic et al, 2015(Beganovic et al, , 2018Njiri et al, 2019;Do and Söffker, 2019) fatigue damage is considered in only one turbine component. The lifetime controllers used are not adaptive to varying wind conditions.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prognostics-based adaptive control strategy for lifetime control of wind turbines

Kipchirchir

Hung

Njiri

et al. 2021

Preprint

View full text Add to dashboard Cite

Abstract. Variability of wind profiles in both space and time is responsible for fatigue loading in wind turbine components. Advanced control methods for mitigating structural loading in these components have been proposed in previous works. These also incorporate other objectives like speed and power regulation for above-rated wind speed operation. In recent years, lifetime control and extension strategies have been proposed to guaranty power supply and operational reliability of wind turbines. These control strategies typically rely on a fatigue load evaluation criteria to determine the consumed lifetime of these components, subsequently varying the control set-point to guaranty a desired lifetime of the components. Most of these methods focus on controlling the lifetime of specific structural components of a wind turbine, typically the rotor blade or tower. Additionally, controllers are often designed to be valid about specific operating points, hence exhibit deteriorating performance in varying operating conditions. Therefore, they are not able to guaranty a desired lifetime in varying wind conditions. In this paper an adaptive lifetime control strategy is proposed for controlled ageing of rotor blades to guaranty a desired lifetime, while considering damage accumulation level in the tower. The method relies on an online structural health monitoring system to vary the lifetime controller gains based on a State of Health (SoH) measure by considering the desired lifetime at every time-step. For demonstration, a 1.5 MW National Renewable Energy Laboratory (NREL) reference wind turbine is used. The proposed adaptive lifetime controller regulates structural loading in the rotor blades to guaranty a predefined damage level at the desired lifetime without sacrificing on the speed regulation performance of the wind turbine. Additionally, significant reduction in the tower fatigue damage is observed.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Prognostics-based adaptive control strategy for lifetime control of wind turbines

Kipchirchir

Hung

Njiri

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…For example, Paris law can be combined with KS [74] or PF [77]. Miner rule can be used with KF [81,85]. There are other physical models integrated with PF.…”

Section: Hybrid Modelmentioning

confidence: 99%

A review of failure prognostics for predictive maintenance of offshore wind turbines

Zhang

Vatn

Rasheed³

2022

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Offshore wind turbines (OWTs) are important facilities for wind power generation because of their low land use and high electricity output. However, the harsh environment and remote location of offshore sites make it difficult to conduct maintenance on turbines. To upkeep OWTs cost-effectively, predictive maintenance (PdM) is an appealing strategy for offshore wind industry. The heart of PdM is failure prognostics, which aims to predict an asset’s remaining useful life (RUL) based on condition monitoring (CM). To provide references to PdM of OWTs, this paper presents a systematic review of failure prognostic models for wind turbines. In this review, data-driven models, model-based models, and hybrid models are classified and presented for model selection. The findings reveal that it is promising to develop hybrid models in the future and combine the advantages of data-driven and model-based models. Currently, the internal combinations of machine learning methods and statistical approaches in data-driven models are more common than exterior linkages between data-driven models and model-based models. The limitations and strengths of different models are discussed, and opportunities for developing hybrid models are highlighted in the conclusion.

show abstract

“…(Newman, 1981) developed analytical model of cyclic crack growth that includes the effects of crack closure to correlate crack growth under aircraft spectrum loading on aluminum alloy plate material. Several studies have been conducted for determining the RUL in wind turbine blades through classical fatigue crack propagation laws (Shokrieh & Rafiee, 2006;Beganovic, Njiri, Rothe, & Soffker, 2015;Hayat et al, 2015). (Corbetta, Sbarufatti, Giglio, Saxena, & Goebel, 2018) proposed a particle filter based Bayesian damage prognosis framework extended to multiple damage mechanisms for fatigue life prediction of composite laminates under co-existing matrix cracks and delamination.…”

Section: Fatigue Damage In Wind Turbine Blades and Effect Of Wind Spementioning

confidence: 99%

Remaining Useful Life Estimation of Wind Turbine Blades under Variable Wind Speed Conditions Using Particle Filters

Valeti

Pakzad

2018

PHM_CONF

View full text Add to dashboard Cite

Rotor blades are the most complex structural components in a wind turbine and are subjected to continuous cyclic loads of wind and self-weight variation. The structural maintenance operations in wind farms are moving towards condition based maintenance (CBM) to avoid premature failures. For this, damage prognosis with remaining useful life (RUL) estimation in wind turbine blades is necessary. Wind speed variation plays an important role influencing the loading and consequently the RUL of the structural components. This study investigates the effect of variable wind speed between the cutin and cut-out speeds of a typical wind farm on the RUL of a damage detected wind turbine blade as opposed to average wind speed assumption. RUL of wind turbine blades are estimated for different initial crack sizes using particle filtering method which forecasts the evolution of fatigue crack addressing the non-linearity and uncertainty in crack propagation. The stresses on a numerically simulated life size onshore wind turbine blade subjected to the above wind speed loading cases are used in computing the crack propagation observation data for particle filters. The effects of variable wind speed on the damage propagation rates and RUL in comparison to those at an average wind speed condition are studied and discussed.

show abstract

Application of diagnosis and prognosis to wind turbine system based on fatigue load

Cited by 8 publications

References 15 publications

Prognostics-based adaptive control strategy for lifetime control of wind turbines

Prognostics-based adaptive control strategy for lifetime control of wind turbines

A review of failure prognostics for predictive maintenance of offshore wind turbines

Remaining Useful Life Estimation of Wind Turbine Blades under Variable Wind Speed Conditions Using Particle Filters

Contact Info

Product

Resources

About