A comparison of linear approaches to filter out environmental effects in structural health monitoring

This paper discusses the possibility of using the Mahalanobis squared-distance to perform robust novelty detection in the presence of important environmental variability in a multivariate feature vector. By performing an eigenvalue decomposition of the covariance matrix used to compute that distance, it is shown that the Mahalanobis squared-distance can be written as the sum of independent terms which result from a transformation from the feature vector space to a space of independent variables. In general, especially when the size of the features vector is large, there are dominant eigenvalues and eigenvectors associated with the covariance matrix, so that a set of principal components can be defined. Because the associated eigenvalues are high, their contribution to the Mahalanobis squared-distance is low, while the contribution of the other components is high due to the low value of the associated eigenvalues. This analysis shows that the Mahalanobis distance naturally filters out the variability in the training data. This property can be used to remove the effect of the environment in damage detection, in much the same way as two other established techniques, principal component analysis and factor analysis. The three techniques are compared here using real experimental data from a wooden bridge for which the feature vector consists in eigenfrequencies and modeshapes collected under changing environmental conditions, as well as damaged conditions simulated with an added mass. The results confirm the similarity between the three techniques and the ability to filter out environmental effects, while keeping a high sensitivity to structural changes. The results also show that even after filtering out the environmental effects, the normality assumption cannot be made for the residual feature vector. An alternative is demonstrated here based on extreme value statistics which results in a much better threshold which avoids false positives in the training data, while allowing detection of all damaged cases

Piezoelectric vibration damping using resonant shunt circuits: an exact solution

peer reviewe

Deployment of contact-based ultrasonic thickness measurements using over-actuated UAVs

Unmanned Aerial Vehicles (UAVs) are increasingly being utilized for the structural health assessment of on and off-shore structures. Visual inspection is the usual methodology for acquiring data from these structures, but there is often a need for contact based structural measurements, for example to assess local thickness on corroding structures. Conventional UAV platform dynamics have not traditionally allowed for such contact measurements. The limited dynamic control afforded by fixed plane rotor UAVs means that forward thrust (to apply contact forces for surface transduction) is only possible by tilting the whole platform, thus taking the UAV into a non-stationary state and limiting positional accuracy. An over-actuated UAV platform (with fully vectored thrust capability) may provide the required contact force for such thickness measurements whilst maintaining stable hovering next to the structure. The authors herein present a contact based ultrasonic thickness measurement technique, whereby an ultrasonic wheel probe deployed from a UAV was used to make single point and scanned measurements across a surface to provide a set of local thickness measurements. A 5 MHz, dry-coupled, dual-element, ultrasonic wheel probe is used to measure the thickness of an aluminum sample plate with thicknesses of 8.2 mm, 4.5 mm and 3.2 mm, and a precision stepped calibration block with size from 31.5 mm to 17.5 mm in steps of 1 mm, then steps of 0.1 mm down to 16.5 mm over a total length of 500 mm. The thickness resolution obtainable from the ultrasonic wheel probe was typically 0.1 mm, and the positional accuracy attained from the over-actuated deployment platform was 16.6 mm when performing single point measurements

On the use of the Mahalanobis squared-distance to filter out environmental effects in structural health monitoring

This paper discusses the possibility of using the Mahalanobis squared-distance to perform robust novelty detection in the presence of important variability in a multivariate feature vector. The application of interest is vibration-based structural health monitoring with a focus on data-based damage detection. For this application, the Mahalanobis distance can be used to detect novelty using a multivariate feature vector extracted from vibration measurements from a structure at regular intervals during its lifetime. One of the major problems is that changing environmental conditions induce large variability in the feature vector under normal condition, which usually prevents detection of smaller variations due to damage. In this paper, it is shown that including the variability due to the environment in the training data used to define the Mahalanobis distance results in very efficient filtering of the environmental effects while keeping the sensitivity to structural changes

Experimental localization of small damages using modal filters

info:eu-repo/semantics/publishe

Assessment of damage localization based on spatial filters using numerical crack propagation models

This paper is concerned with vibration based structural health monitoring with a focus on non-model based damage localization. The type of damage investigated is cracking of concrete structures due to the loss of prestress. In previous works, an automated method based on spatial filtering techniques applied to large dynamic strain sensor networks has been proposed and tested using data from numerical simulations. In the simulations, simplified representations of cracks (such as a reduced Young's modulus) have been used. While this gives the general trend for global properties such as eigen frequencies, the change of more local features, such as strains, is not adequately represented. Instead, crack propagation models should be used. In this study, a first attempt is made in this direction for concrete structures (quasi brittle material with softening laws) using crack-band models implemented in the commercial software DIANA. The strategy consists in performing a non-linear computation which leads to cracking of the concrete, followed by a dynamic analysis. The dynamic response is then used as the input to the previously designed damage localization system in order to assess its performances. The approach is illustrated on a simply supported beam modeled with 2D plane stress elements. © 2011 Published under licence by IOP Publishing Ltd.info:eu-repo/semantics/publishe

Damage Detection in Civil Engineering Structure Considering Temperature Effect

This paper concerns damage identification of a bridge located in Luxembourg. Vibration responses were captured from measurable and adjustable harmonic swept sine excitation and hammer impact. Different analysis methods were applied to the data measured from the structure showing interesting results. However, some difficulties arise, especially due to environmental influences (temperature and soil-behaviour variations) which overlay the structural changes caused by damage. These environmental effects are investigated in detail in this work. First, the modal parameters are identified from the response data. In the next step, they are statistically collected and processed through Principal Component Analysis (PCA) and Kernel PCA. Damage indexes are based on outlier analysis

Hybrid Electromagnetic Shunt Damper for Vibration Control

It has been shown that shunting electromagnetic devices with electrical networks can be used to damp vibrations. These absorbers have however limitations that restrict the control performance, i.e., the total damping of the system and robustness versus parameter variations. On the other hand, the electromagnetic devices are widely used in active control techniques as an actuator. The major difficulty that arises in practical implementation of these techniques is the power consumption required for conditioners and control units. In this study, robust hybrid control system is designed to combine the passive electromagnetic shunt damper with an active control in order to improve the performance with low power consumption. Two different active control laws, based on an active voltage source and an active current source, are proposed and compared. The control law of the active voltage source is the direct velocity feedback. However, the control law of the active current source is a revisited direct velocity feedback. The method of maximum damping, i.e., maximizing the exponential time-decay rate of the response subjected to the external impulse forcing function, is employed to optimize the parameters of the passive and the hybrid control systems. The advantage of using the hybrid control configuration in comparison with purely active control system is also investigated in terms of the power consumption. Besides these assets, it is demonstrated that the hybrid control system can tolerate a much higher level of uncertainty than the purely passive control systems. © 2020 by ASME