Wind turbines are a cost-effective alternative energy source; however, their blades are susceptible to damage. Therefore, damage detection of wind turbine blades is of great importance for condition monitoring of wind turbines. Many vibration-based structural damage detection techniques have been proposed in the last two decades. The local flexibility method, which can determine local stiffness variations of beam-like structures by using measured modal parameters, is one of the most promising vibration-based approaches. The local flexibility method does not require a finite element model of the structure. A few structural modal parameters identified from the ambient vibration signals both before and after damage are required for this method. In this study, we propose a damage detection approach for rotating wind turbine blades using the local flexibility method based on the dynamic macro-strain signals measured by long-gauge fiber Bragg grating (FBG)-based sensors. A small wind turbine structure was constructed and excited using a shaking table to generate vibration signals. The structure was designed to have natural frequencies as close as possible to those of a typical 1.5 MW wind turbine in real scale. The optical fiber signal of the rotating blades was transmitted to the data acquisition system through a rotary joint fixed inside the hollow shaft of the wind turbine. Reversible damage was simulated by aluminum plates attached to some sections of the wind turbine blades. The damaged locations of the rotating blades were successfully detected using the proposed approach, with the extent of damage somewhat over-estimated. Nevertheless, although the specimen of wind turbine blades cannot represent a real one, the results still manifest that FBG-based macro-strain measurement has potential to be employed to obtain the modal parameters of the rotating wind turbines and then locations of wind turbine segments with a change of rigidity can be estimated effectively by utilizing these identified parameters.

Summary Vibration‐based damage detection methods make use of structural features extracted from vibration signals to perform damage diagnosis. The local flexibility method, which can determine local stiffness variations of beam structures by using measured modal parameters, is one of the more promising vibration‐based approaches. The local flexibility method is founded on ‘local’ virtual forces that cause nonzero stresses within a local part of the structure. In this study, this basic rule has been broken. The ‘pseudo‐local’ virtual forces that cause concentrated stresses in a local part and nonzero stresses in the other parts of a structure are employed. The theoretical basis of the proposed ‘pseudo local flexibility method’ (PLFM) is derived. The effects of the number of modes on the damage detection results are studied using both numerical and experimental hyperstatic beam models. The results show that significantly fewer modes are required for the PLFM to estimate the damage location and extent with acceptable accuracy. Therefore, the feasibility of the PLFM is higher because only a limited number of high‐quality modes can be identified in real world applications. Furthermore, it was also found that when damage occurs close to the support, the PLFM is more likely to detect it, which is credited to the smaller local region induced by the PLFM. Copyright © 2014 John Wiley & Sons, Ltd.

The structural health monitoring of power transmission towers (PTTs) has drawn increasing attention from researchers in recent years; however, no long-term monitoring of the dynamic parameters of PTTs has previously been reported in the literature. This study performed the long-term monitoring of an instrumented PTT. An automated subspace identification technique was used to extract the dynamic parameters of the PTT from ambient vibration measurements taken over approximately ten months in 2017. Ten target modal frequencies were selected to explore the effects of environmental factors, such as temperature and wind speed, as well as the root-mean-square (RMS) acceleration response of the PTT. Variations in the modal frequencies of approximately 2% to 8% were observed during the study period. In general, among the environmental factors, the temperature was found to be the primary cause of decreases in the modal frequencies, except in the case of some of the higher modes. Typhoon Nesat, which affected the PTT on July 29th, 2017, seems to have decreased the modal frequencies of the PTT, especially for the higher modes. This reduction in the modal frequencies seems to have lasted for approximately two and a half months, after which they recovered to their normal state, probably due to a seasonal cool down in temperature. The reduction percentages in the modal frequencies due to Typhoon Nesat were quantified as approximately −0.89% to −1.34% for the higher modes, but only −0.07% to −0.46% for the remaining lower modes. Although the unusual reductions in the modal frequencies are reported in this study, the reason for this phenomenon is not clear yet. Further studies would be required in the future in order to find the cause.

In current bridge maintenance practice, condition grades are assigned to individual bridges, based on regularly performed inspections. One of the main limitations to this approach is the subjective nature of grade assignment. To overcome this drawback, major bridge authorities are developing new methods for condition assessment based on collecting and evaluating sensor data. A major challenge in this context is to correctly model the impact of local deteriorations on the entire bridge's state. In this research, a system model-based approach has been developed to accurately model the correlations between the deterioration mechanisms and the measurement values indicating the progress of the deterioration. In addition, the system model describes the impact of the condition of individual bridge components on the condition of the overall bridge system. To this end, the bridge is hierarchically decomposed into modules, components and subcomponents, taking the structural system and mutual dependencies into account. The system model consists of three levels: The lowest level provides elements for modelling the input parameters provided by sensors or manual measurements. The mid-level models the deterioration mechanisms, taking the output of the parameter level into account. The topmost level models the structure of the bridge in a hierarchical manner, starting at the element parts up to the complete bridge system. The bridge´s condition is determined by state propagation mechanisms on the basis of logical elements connecting the aforementioned elements. In the end, the system model can be used to simulate the propagation of conditions assignments from the leaves (the sensors) to the top (the entire bridge). The developed system model approach is based on the application of the Systems Modelling Language (SysML). The paper will discuss in detail the advantages and limitations of the developed method and present a number of ostensive examples.

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