Structural health monitoring

About: Structural health monitoring is a research topic. Over the lifetime, 11727 publications have been published within this topic receiving 186231 citations.

A review of full-scale structural testing of wind turbine blades

Abstract: The blades that play a key role to collect wind energy are the most critical components of a wind turbine system Meanwhile, they are also the parts most susceptible to damage Structural health monitoring (SHM) system has been proposed to continuously monitor the wind turbine Nevertheless, no system has yet been developed to a stage compatible with the requirements of commercial wind turbines Therefore, full-scale structural testing is the main means available so far for validating the comprehensive performance of wind turbine blades It is now normally used as part of a blade certification process It also allows an insight into the failure mechanisms of wind turbine blades, which are essential to the success of SHM Furthermore, it provides a unique opportunity to exercise SHM and non-destructive testing (NDT) techniques Recognizing these practical significances, this paper therefore aims to carry out an extensive review of full-scale structural testing of wind turbine blades, including static testing and fatigue testing In particular, the current status in China is presented One focus of this review is on the failure mechanisms of wind turbine blades, which are vital for optimizing the design of themselves as well as the design of their SHM system Another focus is on the strengths and weaknesses of various SHM and NDT techniques, which are useful for evaluating their applicability on wind turbine blades In addition, recent advances in photogrammetry and digital image correlation have allowed new opportunities for blade monitoring These techniques are currently being explored on a few wind turbine blade applications and can provide a wealth of additional information that was previously unobtainable These works are also summarized in this paper in order to discover the pros and cons of these techniques

The effect of time synchronization of wireless sensors on the modal analysis of structures

Abstract: Driven by the need to reduce the installation cost and maintenance cost of structural health monitoring (SHM) systems, wireless sensor networks (WSNs) are becoming increasingly popular. Perfect time synchronization amongst the wireless sensors is a key factor enabling the use of low-cost, low-power WSNs for structural health monitoring applications based on output-only modal analysis of structures. In this paper we present a theoretical framework for analysis of the impact created by time delays in the measured system response on the reconstruction of mode shapes using the popular frequency domain decomposition (FDD) technique. This methodology directly estimates the change in mode shape values based on sensor synchronicity. We confirm the proposed theoretical model by experimental validation in modal identification experiments performed on an aluminum beam. The experimental validation was performed using a wireless intelligent sensor and actuator network (WISAN) which allows for close time synchronization between sensors (0.6‐10 μ si n the tested configuration) and guarantees lossless data delivery under normal conditions. The experimental results closely match theoretical predictions and show that even very small delays in output response impact the mode shapes. (Some figures in this article are in colour only in the electronic version)

Damage detection sensitivity characterization of acousto-ultrasound-based structural health monitoring techniques:

Abstract: Reliability quantification is a critical and necessary process for the evaluation and assessment of any inspection technology that may be classified either as a nondestructive evaluation or structural health monitoring technique. Based on the sensitivity characterization of nondestructive evaluation techniques, appropriate processes have been developed and established for the reliability quantification of their performance with respect to damage/flaw detection in materials or structures. However, in the case of structural health monitoring methods, no such well-defined and general applicable approaches have been established for neither active nor passive sensing techniques that allow for their accurate reliability quantification. The objective of this study is to characterize the sensitivity of active-sensing acousto-ultrasound-based structural health monitoring techniques with respect to damage detection, as well as to identify the parameters that influence their sensitivity. With such an understanding, ...

Structural damage detection using fuzzy cognitive maps and Hebbian learning

Abstract: A new algorithmic approach for structural damage detection based on the fuzzy cognitive map (FCM) is developed in this paper. Structural damage is modeled using the continuum mechanics approach as a loss of stiffness at the damaged location. A finite element model of a cantilever beam is used to calculate the change in the first six beam frequencies because of structural damage. The measurement deviations due to damage are fuzzified and then mapped to a set of faults using FCM. The input concepts for the FCM are the frequency deviations and the output of the FCM is at five possible damage locations along the beam. The FCM works quite well for structural damage detection for ideal and noisy data. Further improvement in performance is obtained when an unsupervised neural network approach based on Hebbian learning is used to evolve the FCM. Numerical results clearly show that the use of FCM and Hebbian learning results in accurate damage detection and represents a powerful tool for structural health monitoring.