Christof Devriendt

Operational modal parameter estimation of MIMO systems using transmissibility functions

Operational modal parameter estimation (OMA) techniques perform system identification without or with only limited knowledge of the operational inputs acting on the system. However, most of the current operational identification techniques impose multiple conditions on the spectral content of the unknown inputs. As a consequence, modeling errors occur if these assumptions are not met. Therefore, there is a general interest in operational identification techniques that can operate independent of the unknown input spectra. This paper introduces poly-reference Transmissibility based Operational Modal Analysis (pTOMA). pTOMA uses parametrically estimated transmissibility functions associated with different loading conditions to obtain the system eigenvalues and eigenvectors using output-only data. Unlike most OMA techniques no strong assumptions are necessary considering the input spectrum. The method is therefore able to correctly identify the system parameters while the excitation may contain (varying) harmonics or strong coloration. A framework to use pTOMA is formulated, the algorithm is introduced and the claimed properties are illustrated by means of a numerical experiment.

Structural health monitoring of offshore wind turbines using automated operational modal analysis

This article will present and discuss the approach and the first results of a long-term dynamic monitoring campaign on an offshore wind turbine in the Belgian North Sea. It focuses on the vibration levels and modal parameters of the fundamental modes of the support structure. These parameters are crucial to minimize the operation and maintenance costs and to extend the lifetime of offshore wind turbine structure and mechanical systems. In order to perform a proper continuous monitoring during operation, a fast and reliable solution, applicable on an industrial scale, has been developed. It will be shown that the use of appropriate vibration measurement equipment together with state-of-the art operational modal analysis techniques can provide accurate estimates of natural frequencies, damping ratios, and mode shapes of offshore wind turbines. The identification methods have been automated and their reliability has been improved, so that the system can track small changes in the dynamic behavior of offshore wind turbines. The advanced modal analysis tools used in this application include the poly-reference least squares complex frequency-domain estimator, commercially known as PolyMAX, and the covariance-driven stochastic subspace identification method. The implemented processing strategy will be demonstrated on data continuously collected during 2 weeks, while the wind turbine was idling or parked.

Foundation structural health monitoring of an offshore wind turbine—a full-scale case study

In this contribution, first, the results in the development of a structural health monitoring approach for the foundations of an offshore wind turbine based on its resonance frequencies will be presented. Key problems are the operational and environmental variability of the resonance frequencies of the turbine that potentially conceal any structural change. This article uses a (non-)linear regression model to compensate for the environmental variations. An operational case-by-case monitoring strategy is suggested to cope with the dynamic variability between different operational cases of the turbine. Real-life data obtained from an offshore turbine on a monopile foundation are used to validate the presented strategy and to demonstrate the performance of the presented approach. First, the results indicate an overall stiffening of the investigated structure.

Structural Health Monitoring in Changing Operational Conditions Using Tranmissibility Measurements

This article uses frequency domain transmissibility functions for detecting and locating damage in operational con- ditions. In recent articles numerical and experimental examples were presented and the possibility to use the transmissibility concept for damage detection seemed quite promising. In the work discussed so far, it was assumed that the operational conditions were constant, the structure was excited by a single input in a fixed location. Transmissibility functions, defined as a simple ratio between two measured responses, do depend on the amplitudes or locations of the operational forces. The current techniques fail in the case of changing operational conditions. A suitable operational damage detection method should however be able to detect damage in a very early stage even in the case of changing operational conditions. It will be demonstrated in this paper that, by using only a small frequency band around the resonance frequencies of the structure, the existing methods can still be used in a more robust way. The idea is based on the specific property that the transmissibility functions become independent of the loading condition in the system poles. A numerical and experimental validation will be given.

Data-driven multivariate power curve modeling of offshore wind turbines

Performance monitoring of offshore wind turbines is an essential first step in the condition monitoring process. This paper provides three novelties regarding power curve modeling. The first consists of illustrating that univariate power curve modeling can be improved by the use of non-parametric methods such as stochastic gradient boosted regression trees, extremely randomized forest, random forest, K-nearest neighbors, and the method of bins according to the IEC standard 61,400-12-1. This is confirmed on both a synthetic data set and a real live data set containing data from three offshore wind turbines. The second novelty consists of an improvement regarding overall power curve modeling results by the use of multivariate models which incorporate the wind direction, rotations per minute of the rotor, yaw, wind direction and pitch additional to the wind speed. The best improvement is achieved by the stochastic gradient boosted regression trees method for which the mean absolute error can be decreased by up to 27.66%. The third novelty consists of making a synthetic data set available for bench-marking purposes. Data-driven non-parametric power curve models perform the best.Multivariate model outperforms univariate models.Data-driven multivariate models capture the phenomena in the data.

Full load estimation of an offshore wind turbine based on SCADA and accelerometer data

As offshore wind farms (OWFs) grow older, the optimal use of the actual fatigue lifetime of an offshore wind turbine (OWT) and predominantly its foundation will get more important. In case of OWTs, both quasi-static wind/thrust loads and dynamic loads, as induced by turbulence, waves and the turbines dynamics, contribute to its fatigue life progression. To estimate the remaining useful life of an OWT, the stresses acting on the fatigue critical locations within the structure should be monitored continuously. Unfortunately, in case of the most common monopile foundations these locations are often situated below sea-level and near the mud line and thus difficult or even impossible to access for existing OWTs. Actual strain measurements taken at accessible locations above the sea level show a correlation between thrust load and several SCADA parameters. Therefore a model is created to estimate the thrust load using SCADA data and strain measurements. Afterwards the thrust load acting on the OWT is estimated using the created model and SCADA data only. From this model the quasi static loads on the foundation can be estimated over the lifetime of the OWT. To estimate the contribution of the dynamic loads a modal decomposition and expansion based virtual sensing technique is applied. This method only uses acceleration measurements recorded at accessible locations on the tower. Superimposing both contributions leads to a so-called multi-band virtual sensing. The result is a method that allows to estimate the strain history at any location on the foundation and thus the full load, being a combination of both quasi-static and dynamic loads, acting on the entire structure. This approach is validated using data from an operating Belgian OWF. An initial good match between measured and predicted strains for a short period of time proofs the concept.

Long-Term Dynamic Monitoring of an Offshore Wind Turbine

Future Offshore Wind Turbines will be hardly accessible; therefore, in order to minimize O&M costs and to extend their lifetime, it will be of high interest to continuously monitor the vibration levels and the evolution of the frequencies and damping ratios of the first modes of the foundation and tower structures. Wind turbines are complex structures and their dynamics vary significantly in operation in comparison to stand still parked conditions due to changes in operating conditions or changing ambient conditions. State-of-the-art operational modal analysis techniques can provide accurate estimates of natural frequencies, damping ratios and mode shapes. To allow a proper continuous monitoring during operation, the methods have been automated and their reliability improved, so that no human-interaction is required and the system can track changes in the dynamic behaviour of the offshore wind turbine. This paper will present and discuss the approach and the first results of a long-term monitoring campaign on an offshore wind turbine in the Belgian North Sea.

How to Achieve a Rapid Deployment of Mobile Substations and to Guarantee Its Integrity During Transport

A mobile substation is a fully equipped electrical substation mounted on a semitrailer. The substation components are ideally mounted in their operational position on the semitrailer. The equipment must be fixed considering the space limitation, insulation distances and not only static but dynamic loads due to transport. The equipment must be fitted in a way to allow a fast installation requiring minimum work. This paper describes the application of mobile substations, it discusses their specific technical considerations at the design stage, and it presents experimental and analytical results of the vibration of the equipment during transport motion.

Transmissibility-Based Operational Modal Analysis: Enhanced Stabilisation Diagrams

Recently it has been shown that also transmissibilities can be used to identify the modal parameters. This approach has several advantages: because of the deterministic character of the transmissibility functions, the estimated parameters are more accurate than the results obtained with the power spectra based operational modal analysis techniques. Another advantage is that the transmissibility functions do not depend on the colouring of the unknown forces. A disadvantage of the transmissibility based operational modal analysis techniques is that non-physical modes show up in the stabilisation diagrams. In this contribution it will first be shown that those non-physical modes will show up when traditional stabilisation diagrams are used. In a second step, a new approach of selecting the physical modes out of a set of estimated modes will be discussed and the new approach will be validated using data generated with an acoustical Finite Element Model. Finally, the approach will be validated using real acoustical data.

Transmissibilty-Based Operational Modal Analysis for Flight Flutter Testing Using Exogenous Inputs

During the recent years several new tools have been introduced by the Vrije Universiteit Brussel in the field of Operational Modal Analysis (OMA) such as the transmissibility based approach and the the frequency-domain OMAX concept. One advantage of the transmissibility based approach is that the ambient forces may be coloured (non-white), if they are fully correlated. The main advantage of the OMAX concept is the fact that it combines the advantages of Operational and Experimental Modal Analysis: ambient (unknown) forces as well as artificial (known) forces are processed simultaneously resulting in improved modal parameters. In this paper, the transmissibility based output-only approach is combined with the input/output OMAX concept. This results in a new methodology in the field of operational modal analysis allowing the estimation of (scaled) modal parameters in the presence of arbitrary ambient (unknown) forces and artificial (known) forces.