Structural Health Monitoring of Thin Aluminum Plate Using Acoustic Sensors

2012 ◽  
Vol 622-623 ◽  
pp. 1389-1395
Author(s):  
R. Nishanth ◽  
K. Lingadurai ◽  
V. Malolan ◽  
Gowrishankar Wuriti ◽  
M.R.M. Babu
Keyword(s):  
Lamb Wave ◽  
Damage Identification ◽  
Lamb Waves ◽  
Time Domain Analysis ◽  
Ultrasonic Waves ◽  
Aluminum Plate ◽  
Identification System ◽  
Time Frequency ◽  
Thin Aluminum ◽  
Aluminum Plates

SHM is defined as “an emerging technology that can be defined as continuous, autonomous, real time, in-service monitoring of the physical condition of a structure by means of embedded or attached sensors with minimum manual intervention” .SHM provides the ability of a system to detect adverse changes within a system’s structure to enhance reliability and reduce maintenance costs. There are different Non-Destructive techniques like acoustic emission, ultrasonic, acousto-ultrasonic, guided ultrasonic waves or Lamb waves which are nowadays investigated for the development of an efficient and user-friendly damage identification system. This paper deals with the latter which is based on Lamb wave propagation. It has been developed especially for distinguishing different kinds of damages. The Lamb wave-based active SHM method uses piezoelectric (PZT) sensors to transmit and receive Lamb waves in a thin Aluminum plate. The Lamb wave modes (AO &SO) travel into the structure and are reflected by the structural boundaries, discontinuities, and damage. By studying their propagation and reflection, the presence of defect in the structure is determined. Laboratory level experiments have been carried out on thin Aluminum plates with angular, horizontal and vertical defect. The obtained waveform is filtered to avoid unwanted noise & disturbances using Savitzky-Golay filtering. The filtered waveforms are compared to differentiate the defects. Short Time Fourier Transform has been carried out on the acquired waveform. This study provides significant insight into the problem of identifying localized damages in the structure using PZT and dispersion of signal after they interact with different types of damage. Those small defects like the horizontal one that may be nearly missed in time domain analysis can also be clearly identified in the STFT analysis. Moreover the occurrence of So mode is also clearly seen. Thus, Lamb waves generated by PZT sensors and time-frequency analysis techniques could be used effectively for damage detection in aluminum plate. This study has given a complete idea of the working and the basic requirements of SHM system.

scholarly journals Damage Identification of Large Generator Stator Insulation Based on PZT Sensor Systems and Hybrid Features of Lamb Waves

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2745 ◽  
Author(s):  
Ruihua Li ◽  
Hao Li ◽  
Bo Hu
Keyword(s):  
Power Systems ◽  
Lamb Wave ◽  
Damage Identification ◽  
Lamb Waves ◽  
Fem Simulation ◽  
Correlation Coefficients ◽  
Hybrid Features ◽  
Material Inhomogeneity ◽  
Time Frequency ◽  
Damage Imaging

Large generators are the principal pieces of equipment in power systems, and their operation reliability critically depends on the stator insulation. Damages in stator insulation will gradually lead to the failure and breakdown of generator. Due to the advantages of Lamb waves in Structural health monitoring (SHM), in this study, a distributed piezoelectric (PZT) sensor system and hybrid features of the Lamb waves are introduced to identify stator insulation damage of large generator. A hierarchical probability damage-imaging (PDI) algorithm is proposed to tackle the material inhomogeneity and anisotropy of the stator insulation. The proposed method includes three steps: global detection using correlation coefficients, local detection using Time of flight (ToF) along with the amplitude of damage-scattered Lamb wave, and final images fusion. Wavelet Transform was used to extract the ToF of Lamb wave in terms of the time-frequency domain. Finite Element Modeling (FEM) simulation and experimental work were carried out to identify four typical stator insulation damages for validation, including inner void, inner delamination, puncture, and crack. Results show that the proposed method can precisely identify the location of stator insulation damage, and the reconstruction image can be used to identify the size of stator insulation damage.

scholarly journals A Novel Complementary Method for the Point-Scan Nondestructive Tests Based on Lamb Waves

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Rahim Gorgin ◽  
Zhanjun Wu ◽  
Yuebin Zheng
Keyword(s):  
Lamb Wave ◽  
Test Piece ◽  
Damage Identification ◽  
Lamb Waves ◽  
Complementary Method ◽  
Nondestructive Tests ◽  
Damage Probability ◽  
Scan Test ◽  
Aluminum Plates ◽  
Probability Index

This study presents a novel area-scan damage identification method based on Lamb waves which can be used as a complementary method for point-scan nondestructive techniques. The proposed technique is able to identify the most probable locations of damages prior to point-scan test which lead to decreasing the time and cost of inspection. The test-piece surface was partitioned with some smaller areas and the damage probability presence of each area was evaluated.A0mode of Lamb wave was generated and collected using a mobile handmade transducer set at each area. Subsequently, a damage presence probability index (DPPI) based on the energy of captured responses was defined for each area. The area with the highest DPPI value highlights the most probable locations of damages in test-piece. Point-scan nondestructive methods can then be used once these areas are found to identify the damage in detail. The approach was validated by predicting the most probable locations of representative damages including through-thickness hole and crack in aluminum plates. The obtained experimental results demonstrated the high potential of developed method in defining the most probable locations of damages in structures.

Simulation Study of Damage Identification Method Based on Lamb Wave Scattering in Aluminium Plate

2012 ◽  
Vol 433-440 ◽  
pp. 2611-2618
Author(s):  
Zhen Hua Tian ◽  
Hong Yuan Li ◽  
Hong Xu
Keyword(s):  
Energy Distribution ◽  
Lamb Wave ◽  
Damage Identification ◽  
Optimization Method ◽  
Propagation Path ◽  
Transient Dynamic Analysis ◽  
Time Frequency ◽  
Damage Location ◽  
Identification Method ◽  
Short Time

The propagation of scattering Lamb wave in plate was simulated using transient dynamic analysis in ANSYS. In order to extract the characteristic information of received signal for damage identification, the short time Fourier transform based on time-frequency analysis was utilized, and then the energy distribution and envelop of received signal were obtained. Based on the displacement contour of simulation and energy distribution, the propagation of scattering wave in plate with a through hole was examined. Also, a mathematic relationship between damage location and scattering signal was developed, with the help of wave propagation path through actuator, damage and sensor. A nonlinear optimization method was applied on the mathematic relationship to obtain the damage location. The damage identification method using scattering Lamb wave was therefore established.

scholarly journals Improvement of Accuracy in Damage Localization Using Frequency Slice Wavelet Transform

2012 ◽  
Vol 19 (4) ◽  
pp. 585-596 ◽  
Author(s):  
Xinglong Liu ◽  
Zhongwei Jiang ◽  
Zhonghong Yan
Keyword(s):  
Wavelet Transform ◽  
Damage Identification ◽  
Lamb Waves ◽  
Group Velocity Dispersion ◽  
Propagation Distance ◽  
Primary Objective ◽  
Frequency Resolution ◽  
Damage Localization ◽  
Arrival Times ◽  
Time Frequency

Damage localization is a primary objective of damage identification. This paper presents damage localization in beam structure using impact-induced Lamb wave and Frequency Slice Wavelet Transform (FSWT). FSWT is a new time-frequency analysis method and has the adaptive resolution feature. The time-frequency resolution is a vital factor affecting the accuracy of damage localization. In FSWT there is a unique parameter controlling the time-frequency resolution. To improve the accuracy of damage localization, a generalized criterion is proposed to determine the parameter value for achieving a suitable time-frequency resolution. For damage localization, the group velocity dispersion curve (GVDC) of A0Lamb waves in beam is first accurately estimated using FSWT, and then the arrival times of reflection wave from the crack for some individual frequency components are determined. An average operation on the calculated propagation distance is then performed to further improve the accuracy of damage localization.

scholarly journals Machine Learning-Enriched Lamb Wave Approaches for Automated Damage Detection

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1790
Author(s):  
Zi Zhang ◽  
Hong Pan ◽  
Xingyu Wang ◽  
Zhibin Lin
Keyword(s):  
Machine Learning ◽  
Feature Extraction ◽  
Feature Selection ◽  
Damage Detection ◽  
Lamb Wave ◽  
Lamb Waves ◽  
Feature Selection Method ◽  
Support Vector ◽  
Time Frequency ◽  
Damage States

Lamb wave approaches have been accepted as efficiently non-destructive evaluations in structural health monitoring for identifying damage in different states. Despite significant efforts in signal process of Lamb waves, physics-based prediction is still a big challenge due to complexity nature of the Lamb wave when it propagates, scatters and disperses. Machine learning in recent years has created transformative opportunities for accelerating knowledge discovery and accurately disseminating information where conventional Lamb wave approaches cannot work. Therefore, the learning framework was proposed with a workflow from dataset generation, to sensitive feature extraction, to prediction model for lamb-wave-based damage detection. A total of 17 damage states in terms of different damage type, sizes and orientations were designed to train the feature extraction and sensitive feature selection. A machine learning method, support vector machine (SVM), was employed for the learning model. A grid searching (GS) technique was adopted to optimize the parameters of the SVM model. The results show that the machine learning-enriched Lamb wave-based damage detection method is an efficient and accuracy wave to identify the damage severity and orientation. Results demonstrated that different features generated from different domains had certain levels of sensitivity to damage, while the feature selection method revealed that time-frequency features and wavelet coefficients exhibited the highest damage-sensitivity. These features were also much more robust to noise. With increase of noise, the accuracy of the classification dramatically dropped.

Lamb-Wave-Based Damage Identification in Laminated Composite Plates

2014 ◽  
Vol 1014 ◽  
pp. 3-8
Author(s):  
Zai Lin Yang ◽  
Hamada M. Elgamal ◽  
Jian Wei Zhang
Keyword(s):  
Lamb Wave ◽  
Structural Damage ◽  
Damage Identification ◽  
Lamb Waves ◽  
Laminated Composite ◽  
Composite Plates ◽  
High Sensitivity ◽  
Scattered Wave ◽  
Propagation Path ◽  
Laminated Composite Plates

With advantages including capability of propagation over a significant distance and high sensitivity to abnormalities and inhomogeneity near the wave propagation path, Lamb waves can be energised to disseminate in a structure and any changes in material properties or structural geometry created by a discontinuity, boundary or structural damage can be identified by examining the scattered wave signals. This paper presents an overview of the Lamb-wave-based damage identification in laminated composite plates including the formulation of lamb waves in an isotropic plate.

Lamb Wave Based Damage Identification in Structures With Complex Geometry

2008 ◽  
Author(s):  
Xi Lu ◽  
Fucai Li ◽  
Guang Meng ◽  
Lin Ye ◽  
Ye Lu
Keyword(s):  
Finite Element ◽  
Lamb Wave ◽  
Damage Identification ◽  
Complex Geometry ◽  
Lamb Waves ◽  
Three Dimensional ◽  
Quantitative Relationship ◽  
Element Model ◽  
Crack Location ◽  
Propagation Behavior

Structural health monitoring (SHM) plays a significant role in terms of fatigue life and damage accumulation prognostics. SHM for structures with complex geometry are much more practical in engineering applications. In this paper, complex aluminium alloy structures with “U” shape section were evaluated in terms of both finite element method (FEM)- and experiment-based Lamb wave analysis for the purpose of damage detection and identification. In the FEM-based analysis, three-dimensional finite element model was established to simulate the propagation behavior of Lamb wave in the structures. On the other hand, in the experiments, piezoelectric (PZT) wafers, functioning as both actuator and sensor, were used to generate Lamb waves propagating in the structures and collect the Lamb wave signals from the complex structures. Quantitative relationship between crack location and the reflection coefficient was constructed by taking advantage of continuous wavelet transform (CWT) and Hilbert transform (HT), which are based on the collected Lamb wave signals. Furthermore, the differences between simulated and experimental results in respect of crack severity evaluation and the reasons were discussed.

Impact of Changing Temperature on Lamb Wave Propagation for Damage Detection

2013 ◽  
Vol 588 ◽  
pp. 140-148 ◽  
Author(s):  
Rafal Radecki ◽  
Wieslaw Jerzy Staszewski ◽  
Tadeusz Uhl
Keyword(s):  
Wave Propagation ◽  
Damage Detection ◽  
Lamb Wave ◽  
Structural Damage ◽  
Clustering Algorithm ◽  
Lamb Waves ◽  
Ultrasonic Waves ◽  
Effect Of Temperature ◽  
Propagation Parameters ◽  
Lamb Wave Propagation

Lamb waves are the most widely used guided ultrasonic waves for structural damage detection. One of the major problems associate with Lamb wave propagation is the effect of temperature on wave propagation parameters. It is important that these parameters are more sensitive to damage than to varying temperature. The paper demonstrates how amplitude and arrival time of Lamb waves are affected by temperature. The analysis is performed for the experimental data gathered from Lamb wave propagation in a damaged aluminium plate. A simple clustering algorithm is used to distinguish between "undamaged" and "damaged" conditions in the presence of changing temperature.

scholarly journals Wave Frequency Effects on Damage Imaging in Adhesive Joints Using Lamb Waves and RMS

Materials ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 1842 ◽  
Author(s):  
Erwin Wojtczak ◽  
Magdalena Rucka
Keyword(s):  
Damage Identification ◽  
Lamb Waves ◽  
Excitation Frequency ◽  
Visual Assessment ◽  
Adhesive Joints ◽  
Ultrasonic Waves ◽  
Steel Plates ◽  
Wave Frequency ◽  
Destructive Testing ◽  
Wide Range

Structural adhesive joints have numerous applications in many fields of industry. The gradual deterioration of adhesive material over time causes a possibility of unexpected failure and the need for non-destructive testing of existing joints. The Lamb wave propagation method is one of the most promising techniques for the damage identification of such connections. The aim of this study was experimental and numerical research on the effects of the wave frequency on damage identification in a single-lap adhesive joint of steel plates. The ultrasonic waves were excited at one point of an analyzed specimen and then measured in a certain area of the joint. The recorded wave velocity signals were processed by the way of a root mean square (RMS) calculation, giving the actual position and geometry of defects. In addition to the visual assessment of damage maps, a statistical analysis was conducted. The influence of an excitation frequency value on the obtained visualizations was considered experimentally and numerically in the wide range for a single defect. Supplementary finite element method (FEM) calculations were performed for three additional damage variants. The results revealed some limitations of the proposed method. The main conclusion was that the effectiveness of measurements strongly depends on the chosen wave frequency value.

Sign in / Sign up

Export Citation Format

Share Document