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

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

Structural Health Monitoring in Changing Operational Conditions Using Tranmissibility Measurements

This article uses frequency domain transmissibility functions for detecting and locating damage in operational conditions. 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

Regional Variation in Hemoglobin Distribution Among Individuals With CKD: the ISN International Network of CKD Cohorts

International audienceIntroduction: Despite recognized geographic and sex-based differences in hemoglobin in the general population, these factors are typically ignored in patients with chronic kidney disease (CKD) in whom a single therapeutic range for hemoglobin is recommended. We sought to compare the distribution of hemoglobin across international nondialysis CKD populations and evaluate predictors of hemoglobin. Methods: In this cross-sectional study, hemoglobin distribution was evaluated in each cohort overall and stratified by sex and estimated glomerular filtration rate (eGFR). Relationships between candidate predictors and hemoglobin were assessed from linear regression models in each cohort. Estimates were subsequently pooled in a random effects model. Results: A total of 58,613 participants from 21 adult cohorts (median eGFR range of 17–49 ml/min) and 3 pediatric cohorts (median eGFR range of 26–45 ml/min) were included with broad geographic representation. Hemoglobin values varied substantially among the cohorts, overall and within eGFR categories, with particularly low mean hemoglobin observed in women from Asian and African cohorts. Across the eGFR range, women had a lower hemoglobin compared to men, even at an eGFR of 15 ml/min (mean difference 5.3 g/l, 95% confidence interval [CI] 3.7–6.9). Lower eGFR, female sex, older age, lower body mass index, and diabetic kidney disease were all independent predictors of a lower hemoglobin value; however, this only explained a minority of variance (R2 7%–44% across cohorts). Conclusion: There are substantial regional differences in hemoglobin distribution among individuals with CKD, and the majority of variance is unexplained by demographics, eGFR, or comorbidities. These findings call for a renewed interest in improving our understanding of hemoglobin determinants in specific CKD populations