Alfredo Güemes

Q-statistic and T2-statistic PCA-based measures for damage assessment in structures

This article explores the use of principal component analysis (PCA) and T2 and Q-statistic measures to detect and distinguish damages in structures. For this study, two structures are used for experimental assessment: a steel sheet and a turbine blade of an aircraft. The analysis has been performed in two ways: (i) by exciting the structure with low-frequency vibrations using a shaker and using several piezoelectric (PZT) sensors attached on the surface, and (ii) by exciting at high-frequency vibrations using a single PZT as actuator and several PZTs as sensors. A known vibration signal is applied and the dynamical responses are analyzed. A PCA model is built using data from the undamaged structure as a reference base line. The defects in the turbine blade are simulated by attaching a mass on the surface at different positions. Instead, a progressive crack is produced to the steel sheet. Data from sets of experiments for undamaged and damaged scenarios are projected into the PCA model. The first two projections, and the Q-statistic and T2-statistic indices are analyzed. Q-statistic indicates how well each sample conforms to the PCA model. It is a measure of the difference or residual between a sample and its projection into the principal components retained in the model. T2-statistic index is a measure of the variation of each sample within the PCA model. Results of each scenario are presented and discussed demonstrating the feasibility and potential of using this formulation in structural health monitoring.

Optical Fiber Distributed Sensing - Physical Principles and Applications

Obtaining the strain data all along the optical fiber, with adequate spatial resolution and strain accuracy, opens new possibilities for structural tests and for structural health monitoring. Formerly, only point sensors, as strain gages or fiber Bragg grating, were available, and information about the response to loads was restricted only to those points on which the sensors were bonded. Unless a sensor was located near the damage initiation point, details about the failure initiation and growth were lost. With a distributed system, the information is given as an array of data with the position in the optical fiber and the strain or temperature data at this point. In this article, the physical principles underlying the different techniques for distributed sensing are discussed, a classification is done based on the backscattered wavelength; this is important to understand its possibilities and performances. The definition of performance for distributed sensors is more difficult than for traditional point sensors because the performance depends on a combination of related measurement parameters. For example, accuracy depends on the spatial resolution, acquisition time, distance range, or cumulated loss prior to measurement location. The field of applications of this new technology is very wide; results of the structural tests of a 40 m long wind turbine blade, detecting the location and load of onset of buckling, and the results of the delamination detection in a composite plate, are presented as examples.

A structural damage detection indicator based on principal component analysis and statistical hypothesis testing

A comprehensive statistical analysis is performed for structural health monitoring (SHM). The analysis starts by obtaining the baseline principal component analysis (PCA) model and projections using measurements from the healthy or undamaged structure. PCA is used in this framework as a way to compress and extract information from the sensor-data stored for the structure which summarizes most of the variance in a few (new) variables into the baseline model space. When the structure needs to be inspected, new experiments are performed and they are projected into the baseline PCA model. Each experiment is considered as a random process and, consequently, each projection into the PCA model is treated as a random variable. Then, using a random sample of a limited number of experiments on the healthy structure, it can be inferred using the ?2 test that the population or baseline projection is normally distributed with mean ?h and standard deviation ?h. The objective is then to analyse whether the distribution of samples that come from the current structure (healthy or not) is related to the healthy one. More precisely, a test for the equality of population means is performed with a random sample, that is, the equality of the sample mean ?s and the population mean ?h is tested. The results of the test can determine that the hypothesis is rejected (?h????c and the structure is damaged) or that there is no evidence to suggest that the two means are different, so the structure can be considered as healthy. The results indicate that the test is able to accurately classify random samples as healthy or not.

Structural damage detection using principal component analysis and damage indices

One of the most important tasks in structural health monitoring corresponds to damage detection. In this task, the existence of damage should be determined. In the literature, several potentially useful techniques for damage detection can be found, and their applicability to a particular situation depends on the size of the critical damages that are admissible in the structure. Almost all of these techniques follow the same general procedure: the structure is excited using actuators, and the dynamical response is sensed at different locations throughout the structure. Any damage will change this vibrational response. The state of the structure is diagnosed by means of the processing of these data. Several studies have shown that the detection of changes in a structure depends on the distance from the damage to the actuator as well as the configuration of the sensor network. In this article, the authors considered the advantage of using an active piezoelectric system, where the lead zirconate titanate transducers are used as actuator and sensors in different actuation phases. In each actuation phase of the diagnosis procedure, one lead zirconate titanate transducer is used as actuator (a known electrical signal is applied), and the others are used as sensors (collecting the wave propagated through the structure at different points). An initial baseline model for undamaged structure is built applying principal component analysis to the data collected by several experiments and after the current structure (damaged or not) is subjected to the same experiments, and the collected data are projected into the principal component analysis models. Two of these projections and four damage indices (T 2-statistic, Q-statistic, combined index, and I 2 index) by each actuation phase are used to determine the presence of damages and to distinguish between them. These indices are calculated based on the analysis of the residual data matrix to represent the variability of the data projected within the residual subspace and the new space of the principal components. To validate the approach, data from two aeronautical structures—an aircraft skin panel and an aircraft turbine blade—are used.

Damage detection by using FBGs and strain field pattern recognition techniques

A novel methodology for damage detection and location in structures is proposed. The methodology is based on strain measurements and consists in the development of strain field pattern recognition techniques. The aforementioned are based on PCA (principal component analysis) and damage indices (T2 and Q). We propose the use of fiber Bragg gratings (FBGs) as strain sensors.

Application of Statistical Energy Analysis for Damage Detection in Spacecraft Structures

This paper analyses the applicability of the Statistical Energy Analysis (SEA) for detecting incipient damages in a typical spacecraft structure, as a stiffened panel. The damage on attachment element is investigated by analyzing its influence on the system characteristics. Because of incipient damage affects mainly on highest modes, rather than on lowest, the coupling loss factor between sub-elements can be used to detect and localize the damage.

Novel approach to percolation threshold on electrical conductivity of carbon nanotube reinforced nanocomposites

To date, most analytical models used to calculate electrical conductivity in carbon nanotube (CNT) reinforced nanocomposites are not able to predict electrical properties for contents much higher than the percolation threshold. This is because these models do not take into account many critical factors, such as nanotube waviness, dispersion state and process parameters. In the present paper, a novel analytical model based on an equivalent percolation threshold concept, valid for all CNT contents, is developed for this approach. To achieve this, the influence of all these factors has been investigated and several experimental tests have been conducted in order to validate the model. The electrical conductivity varies by several orders of magnitude depending on the value of these parameters, increasing with carbon nanotube content and aspect ratio and decreasing with its waviness. From experimental data, it is found that the waviness increases with carbon nanotube content. Besides, functionalization also causes a local distortion of CNTs, producing more entanglement. When comparing two different dispersion procedures, calendering and toroidal milling, it is noticed that the first method has a greater stretching effect because the shear forces induced are much higher, causing the breakage of carbon nanotubes.

Use of carbon nanotubes for strain and damage sensing of epoxy-based composites

The interest in structural health monitoring of carbon fiber-reinforced polymers using electrical methods to detect damage in structures is growing because once the material is fabricated the evaluation of strain and damage is simple and feasible. In order to obtain the conductivity, the polymer matrix must be conductive and the use of nanoreinforcement seems to be the most feasible method. In this work, the behavior of nanoreinforced polymer with carbon nanotubes (CNTs) and composites with glass and carbon fibers with nanoreinforced matrices was investigated. These composites were evaluated in tensile tests by simultaneously measuring stress, strain and resistivity. During elastic deformation, a linear increase in resistance was observed and during fracture of the composite fibers, stronger and discontinuous changes in the resistivity were observed. Among other factors, the percentage of nanotubes incorporated in the matrix turned out to be an important factor in the sensitivity of the method.

Damage detection in composite materials structures under variable loads conditions by using fiber Bragg gratings and principal component analysis, involving new unfolding and scaling methods

An innovative methodology based on the use of fiber Bragg gratings as strain sensors and strain field pattern recognition is proposed for damage detection in composite materials structures. The strain field pattern recognition technique is based on principal component analysis. Damage indices (T2 and Q) and detection thresholds are presented. New techniques for unfolding and scaling tridimensional matrices arrays obtained from structures working under variable load conditions are presented.

Bamboo–Polylactic Acid (PLA) Composite Material for Structural Applications

Developing an eco-friendly industry based on green materials, sustainable technologies, and optimum processes with low environmental impact is a general societal goal, but this remains a considerable challenge to achieve. Despite the large number of research on green structural composites, limited investigation into the most appropriate manufacturing methodology to develop a structural material at industrial level has taken place. Laboratory panels have been manufactured with different natural fibers but the methodologies and values obtained could not be extrapolated at industrial level. Bamboo industry panels have increased in the secondary structural sector such as building application, flooring and sport device, because it is one of the cheapest raw materials. At industrial level, the panels are manufactured with only the inner and intermediate region of the bamboo culm. However, it has been found that the mechanical properties of the external shells of bamboo culm are much better than the average cross-sectional properties. Thin strips of bamboo (1.5 mm thick and 1500 mm long) were machined and arranged with the desired lay-up and shape to obtain laminates with specific properties better than those of conventional E-Glass/Epoxy laminates in terms of both strength and stiffness. The strips of bamboo were bonded together by a natural thermoplastic polylactic acid (PLA) matrix to meet biodegradability requirements. The innovative mechanical extraction process developed in this study can extract natural strip reinforcements with high performance, low cost, and high rate, with no negative environmental impact, as no chemical treatments are used. The process can be performed at the industrial level. Furthermore, in order to validate the structural applications of the composite, the mechanical properties were analyzed under ageing conditions. This material could satisfy the requirements for adequate mechanical properties and life cycle costs at industrial sectors such as energy or automotive.