Damage detection using robust PCA

Postprint (published version

Temperature robust PCA based stress monitoring approach

In this paper, a guided wave temperature robust PCA-based stress monitoring methodology is proposed. It is based on the analysis of the longitudinal guided wave propagating along the path under stress. Slight changes in the wave are detected by means of PCA via statistical T2 and Q indices. Experimental and numerical simulations of the guided wave propagating in material under different temperatures have shown significant variations in the amplitude and the velocity of the wave. This condition can jeopardize the discrimination of the different stress scenarios detected by the PCA indices. Thus, it is proposed a methodology based on an extended knowledge base, composed by a PCA statistical model for different discrete temperatures to produce a robust classification of stress states under variable environmental conditions. Experimental results have shown a good agreement between the predicted scenarios and the real onesPostprint (author's final draft

Flow estimation in a steel pipe using guided waves

In this investigation, a flow rate estimation guided wave based scheme in pipes is proposed. The effect of the fluid over the propagation of longitudinal waves has been experimentally studied by using several laminar flows of water transported by a steel pipe. Results have shown a decrease of the guided wave pattern repeatability and the signal energy as the flow rate increase as a result of the energy leakage from the pipe to the fluid. A Matlab® script is used to excite the PZT actuator via picoscope 2208 of Picotech®, the captured signal is acquired also by the picoscope and the data is processed in Matlab. The test bench utilized is composed by a 1” sch 40 A-106 pipe, a needle valve and a centrifugal pump provides the flow energy. A couple of PZTs are used in a picth-catch configuration to produce and capture the longitudinal waves along the cross section of the pipe.Postprint (author's final draft

A review of impact damage detection in structures using strain data

This paper aims to provide a state-of-the-art review on impact damage detection techniques in structures using strain data. An overview of impact detection systems is provided. These include sensors, specimens, and impact sources used for developing and testing strategies. The review is focused on approaches that use impact strain data (passive approach) to determine simultaneously the location and/or energy of an impact at the time it occurs. These approaches can be classed into two main groups, one based on analytical models and the other based on data-driven models. The former uses a first-principle model obtained from physical laws, whereas the latter describes complex relationships between input and output data obtained by experiments or simulations. Although some weaknesses and strengths are cited, we did not attempt to compare these approaches, and we do not comment the quantitative results.Peer ReviewedPostprint (author's final draft

Evaluation of piezodiagnostics approach for leaks detection in a pipe loop

Pipe leaks detection has a great economic, environmental and safety impact. Although several methods have been developed to solve the leak detection problem, some drawbacks such as continuous monitoring and robustness should be addressed yet. Thus, this paper presents the main results of using a leaks detection and classification methodology, which takes advantage of piezodiagnostics principle. It consists of: i) transmitting/sensing guided waves along the pipe surface by means of piezoelectric device ii) representing statistically the cross-correlated piezoelectric measurements by using Principal Component Analysis iii) identifying leaks by using error indexes computed from a statistical baseline model and iv) verifying the performance of the methodology by using a Self Organizing Map as visualization tool and considering different leak scenario. In this sense, the methodology was experimentally evaluated in a carbon-steel pipe loop under different leaks scenarios, with several sizes and locations. In addition, the sensitivity of the methodology to temperature, humidity and pressure variations was experimentally validated. Therefore, the effectiveness of the methodology to detect and classify pipe leaks, under varying environmental and operational conditions, was demonstrated. As a result, the combination of piezodiagnostics approach, cross-correlation analysis, principal component analysis, and Self Organizing Maps, become as promising solution in the field of structural health monitoring and specifically to achieve robust solution for pipe leak detection.Peer ReviewedPostprint (author's final draft

Structural health monitoring based on principal component analysis: damage detection, localization and classification

Postprint (published version

PCA based stress monitoring of cylindrical specimens using PZTs and guidedwaves

Since mechanical stress in structures affects issues such as strength, expected operational life and dimensional stability, a continuous stress monitoring scheme is necessary for a complete integrity assessment. Consequently, this paper proposes a stress monitoring scheme for cylindrical specimens, which are widely used in structures such as pipelines, wind turbines or bridges. The approach consists of tracking guided wave variations due to load changes, by comparing wave statistical patterns via Principal Component Analysis (PCA). Each load scenario is projected to the PCA space by means of a baseline model and represented using the Q-statistical indices. Experimental validation of the proposed methodology is conducted on two specimens: (i) a 12.7 mm (1/2”) diameter, 0.4 m length, AISI 1020 steel rod, and (ii) a 25.4 mm (1”) diameter, 6m length, schedule 40, A-106, hollow cylinder. Specimen 1 was subjected to axial loads, meanwhile specimen 2 to flexion. In both cases, simultaneous longitudinal and flexural guided waves were generated via piezoelectric devices (PZTs) in a pitch-catch configuration. Experimental results show the feasibility of the approach and its potential use as in-situ continuous stress monitoring application.Peer ReviewedPostprint (published version

Multiway partial least square (MPLS) to estimate impact localization in structures

This paper presents results from the application of Multiway Partial Least Square (MPLS) as a regressor tool in order to estimate the localization of impacts in an aircraft structure. MPLS is a technique that maximizes the covariance between the predictor matrix X and the predicted matrix Y for each component of the space. The structure can be considered as a small scale version of part of a wing aircraft. 574 experiments were performed impacting the wing over its surface and receiving vibration signals from nine sensors. Experiments are divided in four groups depending on their localization and probability of occurrence. A PLS model is build using three of these groups and tested using the remaining group. Results are presented, discussed and compared with results of other methods.Postprint (published version

Combined and I indices based on principal component analysis for damage detection and localization

In this paper, two indices (combined or phi index and I index), different to the presented in [1][2][3] are used to detect damages; these indices are calculated from the information obtained from the projection of the experiments into the PCA models (baseline). They give us a measurement about the difference between the tested and the healthy structure. The experiments are taken from an active piezoelectric system which is excited with lamb waves in different phases and the fact that any defect in the structure changes its vibrational response is exploited. For localization, five different methods of contribution analysis are used (complete decomposition contribution, partial decomposition contribution, angle based contribution, reconstruction based contribution and diagonal contribution). With these methods, the contribution of each sensor to each index is analyzed, in this way, sensor with largest contribution suggests the path where the damage could be located (from the actuator to this sensor). The combination of all indices and all contributions (a total of 2 x 5) are analyzed and compared. To validate the approaches, they are applied to an aircraft turbine blade instrumented with seven PZT’s. Different damages are simulated.Peer ReviewedPostprint (published version

Considering temperature effect on robust principal component analysis orthogonal distance as a damage detector

In previous works, the authors have shown the feasibility of using classical and robust principal component analysis for damage detection on structures when ultrasonic guided waves are used. It has also been demonstrated that robust principal component analysis presents a higher probability of detection accuracy when data are corrupted. In the present work, a robust principal component analysis orthogonal distance is proposed as a new feature for damage detection strategy based on ultrasonic guided waves on structures subjected to uniform temperature changes. The effect of this temperature fluctuation on the signal propagation and also in the new feature is analyzed. Temperature compensation is applied to mitigate the effect of temperature changes on the reliability of the damage detection methodology. The proposed feature and damage detection strategy that considers these effects are tested on two structures: a laboratory scale composite plate and a large-scale complex composite that is representative of a component from an aerospace application. The promising result proves the ability of the new feature as a damage detection tool.Postprint (author's final draft