Lamb Waves Signal Analysis in Structural Health Monitoring Systems

2011 ◽  
Vol 368-373 ◽  
pp. 2402-2405
Author(s):  
Nai Zhi Zhao ◽  
Chang Tie Huang ◽  
Xin Chen
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Structural Changes ◽  
Lamb Waves ◽  
Detection Algorithm ◽  
Operational Conditions ◽  
Structural Health ◽  
Detection Algorithms ◽  
Baseline Subtraction

Many of the wave propagation based structural health monitoring techniques rely on some knowledge of the structure in a healthy state in order to identify damage. Baseline measurements are recorded when a structure is pristine and are stored for comparison to future data. A concern with the use of baseline subtraction methods is the ability to discern structural changes from the effects of varying environmental and operational conditions when analyzing the vibration response of a system. The use of a standard baseline subtraction technique may falsely indicate damage when environmental or operational variations are present between baseline measurements and new measurements. A procedure was outlined for the method, including excitation and recording of Lamb waves, and the use of damage detection algorithms. In this paper, several tests are performed and the results are used to help develop the damage detection algorithms previously described, and to evaluate the performance of the instantaneous baseline SHM technique. Analytical testing is first performed by feeding known input signals into each damage detection algorithm and analyzing the output data. The results of the analytical testing are used to help develop the damage detection algorithms.

Use of delay and sum for sparse reconstruction improvement for structural health monitoring

2019 ◽  
Vol 30 (18-19) ◽  
pp. 2919-2931 ◽  
Author(s):  
Ali Nokhbatolfoghahai ◽  
Hossein M Navazi ◽  
Roger M Groves
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Guided Waves ◽  
Lamb Waves ◽  
Spot Size ◽  
Sparse Reconstruction ◽  
Reconstruction Method ◽  
Structural Health ◽  
Computational Performance

To perform active structural health monitoring, guided Lamb waves for damage detection have recently gained extensive attention. Many algorithms are used for damage detection with guided waves and among them, the delay-and-sum method is the most commonly used algorithm because of its robustness and simplicity. However, delay-and-sum images tend to have poor accuracy with a large spot size and a high noise floor, especially in the presence of multiple damages. To overcome these problems, another method that is based on sparse reconstruction can be used. Although the images produced by the sparse reconstruction method are superior to the conventional delay-and-sum method, it has the challenges of the time and cost of computations in comparison with the delay-and-sum method. Also, in some cases in multi-damage detection, the sparse reconstruction method totally fails. In this article, using prior support information of the structure achieved by the delay-and-sum method, a hybrid method based on sparse reconstruction method is proposed to improve the computational performance and robustness of sparse reconstruction method in the case of multi-damage presence. The effectiveness of the proposed method in detecting damages is demonstrated experimentally and numerically on a simple aluminum plate. The technique is also shown to accurately identify and localize multi-site damages as well as single damage with low sampled signals.

SHM System Based on Modal Filtration

2012 ◽  
Vol 518 ◽  
pp. 289-297 ◽  
Author(s):  
Krzysztof Mendrok ◽  
Tadeusz Uhl ◽  
Wojciech Maj ◽  
Paweł Paćko
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Structural Modification ◽  
Structural Changes ◽  
Environmental Changes ◽  
Practical Implementation ◽  
Health Monitoring System ◽  
Structural Health ◽  
Changes Detection

The modal filter has various applications, among the others for damage detection. It was shown, that a structural modification (e.g. drop of stiffness due to a crack) causes an appearance of peaks on the output of the modal filter. This peaks result from not perfect modal filtration due to system local structural changes. That makes it a great indicator for damage detection, which has fallowing advantages: low computational afford due to the data reduction, the structural health monitoring system based on it, is easy to automate. Furthermore the system is theoretically insensitive to environmental changes as temperature or humidity variation (global structural changes do not cause a drop of modal filtration accuracy). In the paper the practical implementation of the presented technique is shown. The developed structural health monitoring (SHM) system is described as well as results of its extensive simulation and laboratory testing. Finally the application of the system for the structural changes detection on the airplane parts is presented..

Damage Detectability Model of Pitch-Catch Configuration in Composite Plates

2017 ◽  
Vol 754 ◽  
pp. 387-390 ◽  
Author(s):  
Nan Yue ◽  
Zahra Sharif Khodaei ◽  
Ferri M.H. Aliabadi
Keyword(s):  
Wave Propagation ◽  
Damage Detection ◽  
Health Monitoring ◽  
Lamb Waves ◽  
Composite Plates ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Operational Conditions ◽  
Proposed Model ◽  
Lamb Wave Propagation

Detectability of damage using Lamb waves depends on many factors such as size and severity of damage, attenuation of the wave and distance to the transducers. This paper presents a detectability model for pitch-catch sensors configuration for structural health monitoring (SHM) applications. The proposed model considers the physical properties of lamb wave propagation and is independent of damage detection algorithm, which provides a generic solution for probability of detection. The applicability of the model in different environmental and operational conditions is also discussed.

Effects of environmental and operational variability on structural health monitoring

2006 ◽  
Vol 365 (1851) ◽  
pp. 539-560 ◽  
Author(s):  
Hoon Sohn
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Changes ◽  
Vibration Signal ◽  
Data Normalization ◽  
Operational Conditions ◽  
Structural Health ◽  
Structural Deterioration ◽  
Damage Data ◽  
Environmental Variations

Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based on measured dynamic or static characteristics of a system to be monitored. In reality, structures are subject to changing environmental and operational conditions that affect measured signals, and these ambient variations of the system can often mask subtle changes in the system's vibration signal caused by damage. Data normalization is a procedure to normalize datasets, so that signal changes caused by operational and environmental variations of the system can be separated from structural changes of interest, such as structural deterioration or degradation. This paper first reviews the effects of environmental and operational variations on real structures as reported in the literature. Then, this paper presents research progresses that have been made in the area of data normalization.

scholarly journals A Bioinspired Methodology Based on an Artificial Immune System for Damage Detection in Structural Health Monitoring

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Maribel Anaya ◽  
Diego A. Tibaduiza ◽  
Francesc Pozo
Keyword(s):  
Immune System ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Artificial Immune System ◽  
Structural Changes ◽  
Sensor Data ◽  
Artificial Immune ◽  
Structural Health ◽  
Industrial Sectors

Among all the aspects that are linked to a structural health monitoring (SHM) system, algorithms, strategies, or methods for damage detection are currently playing an important role in improving the operational reliability of critical structures in several industrial sectors. This paper introduces a bioinspired strategy for the detection of structural changes using an artificial immune system (AIS) and a statistical data-driven modeling approach by means of a distributed piezoelectric active sensor network at different actuation phases. Damage detection and classification of structural changes using ultrasonic signals are traditionally performed using methods based on the time of flight. The approach followed in this paper is a data-based approach based on AIS, where sensor data fusion, feature extraction, and pattern recognition are evaluated. One of the key advantages of the proposed methodology is that the need to develop and validate a mathematical model is eliminated. The proposed methodology is applied, tested, and validated with data collected from two sections of an aircraft skin panel. The results show that the presented methodology is able to accurately detect damage.

Design of a PZT Sensor Network Based on Guided Lamb Waves for Structural Health Monitoring of Metallic Structures

2010 ◽  
Author(s):  
Bruno Rocha ◽  
Carlos Silva ◽  
Afzal Suleman
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Lamb Waves ◽  
Detection Algorithm ◽  
Probability Of Detection ◽  
Design Development ◽  
Metallic Structures ◽  
Structural Health ◽  
Selection Of

A Structural Health Monitoring (SHM) system of metallic structures based on guided Lamb waves is presented. Lamb waves are reflected on discontinuities in material properties and geometries such as damage. Lamb waves present advantages when applied on thin structures due to their low amplitude damping which enables them to travel longer distances. The selection of transducers, their size and selected locations in the structure are described. Additionally, the design, development and implementation of a new signal generation and data acquisition systems is presented in detail. The requirements leading to the development and selection of these systems are explained and particularly the selection of the actuation signal is discussed. A damage detection algorithm based on the comparison between the damaged structural state and a healthy reference state is used to detect damage based on reflected Lamb waves. Subsequently, the detection algorithm based on discrete signals correlation was further improved by incorporating statistical methods. Tests performed on a plate with multiple surface cuts, through the thickness cuts, loosened rivets and cuts originating from rivets resulted in repeatable detections of 1 mm damages with a probability of detection greater that 95%. New tests are currently being performed on composite panels with embedded Fiber Bragg Grating (FBG) optical sensor network to detect the fast propagating Lamb waves.

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