Wave packet separation based corrosion damage detection for aircraft structures

2020 ◽  
Vol 64 (1-4) ◽  
pp. 1029-1038
Author(s):  
Chao Zhang ◽  
Taifeng Zhang ◽  
Yu Guo ◽  
Hongli Ji ◽  
Jinhao Qiu ◽  
...  
Keyword(s):  
Wave Packet ◽  
Damage Detection ◽  
Lamb Wave ◽  
Latent Variable ◽  
Damage Index ◽  
Corrosion Damage ◽  
Variable Model ◽  
Aircraft Structures ◽  
Damage Indices ◽  
Safety And Reliability

To guarantee the safety and reliability of aircraft structures, Lamb wave based structural health monitoring has been widely used in recent years. However, there are several factors that severely restrict its practical application, such as dispersion effect and complex boundary reflection. The overlap and deformation in wave packets make it difficult to extract the damage characteristics from the complex Lamb wave signals. To tackle this problem, a latent variable model based wave packet separation method is developed in this paper. Aimed at corrosion damage detection, several damage indices are investigated experimentally. By choosing the most sensitive damage index, the validity and the accuracy of the proposed method in corrosion damage detection are demonstrated through the corrosion experiments.

scholarly journals Lamb Wave Scattering Analysis for Interface Damage Detection between a Surface-Mounted Block and Elastic Plate

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 860
Author(s):  
Mikhail V. Golub ◽  
Alisa N. Shpak ◽  
Inka Mueller ◽  
Sergey I. Fomenko ◽  
Claus-Peter Fritzen
Keyword(s):  
Damage Detection ◽  
Elastic Plate ◽  
Lamb Wave ◽  
Wave Scattering ◽  
Hybrid Approach ◽  
Guided Wave ◽  
Open Crack ◽  
Damage Indices ◽  
Impulse Function ◽  
Thin Walled

Since stringers are often applied in engineering constructions to improve thin-walled structures’ strength, methods for damage detection at the joints between the stringer and the thin-walled structure are necessary. A 2D mathematical model was employed to simulate Lamb wave excitation and sensing via rectangular piezoelectric-wafer active transducers mounted on the surface of an elastic plate with rectangular surface-bonded obstacles (stiffeners) with interface defects. The results of a 2D simulation using the finite element method and the semi-analytical hybrid approach were validated experimentally using laser Doppler vibrometry for fully bonded and semi-debonded rectangular obstacles. A numerical analysis of fundamental Lamb wave scattering via rectangular stiffeners in different bonding states is presented. Two kinds of interfacial defects between the stiffener and the plate are considered: the partial degradation of the adhesive at the interface and an open crack. Damage indices calculated using the data obtained from a sensor are analyzed numerically. The choice of an input impulse function applied at the piezoelectric actuator is discussed from the perspective of the development of guided-wave-based structural health monitoring techniques for damage detection.

Application of artificial neural networks for compounding multiple damage indices in Lamb-wave-based damage detection

2014 ◽  
Vol 22 (1) ◽  
pp. 50-61 ◽  
Author(s):  
Ziemowit Dworakowski ◽  
Lukasz Ambrozinski ◽  
Pawel Packo ◽  
Krzysztof Dragan ◽  
Tadeusz Stepinski
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Damage Detection ◽  
Lamb Wave ◽  
Damage Indices ◽  
Artificial Neural

A New Damage Index Using FRF Data, 2D-PCA Method and Pattern Recognition Techniques

2017 ◽  
Vol 17 (08) ◽  
pp. 1750090 ◽  
Author(s):  
F. Khoshnoudian ◽  
S. Talaei
Keyword(s):  
Pattern Recognition ◽  
Damage Detection ◽  
Damage Identification ◽  
Damage Index ◽  
Principal Component ◽  
Frame Structure ◽  
Damage Scenarios ◽  
Pattern Recognition Techniques ◽  
Damage Indices ◽  
Truss Bridge

A pattern recognition-based damage detection method using a brand-new damage index (DI) obtained from the frequency response function (FRF) data is proposed in this paper. One major issue of using the FRF data is the large size of input variables. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices by applying a data reduction technique called the two-dimensional principal component analysis (2D-PCA). The proposed damage indices can be used as the unique patterns. After introducing the damage indices, a dataset of damage scenarios and related patterns is composed. Pattern recognition techniques such as the artificial neural networks and look-up-table (LUT) method are employed to find the most similar known DI to the unknown DI obtained for the damaged structure. As the result of this procedure, the actual damage location and severity can be determined. In this paper, the 2D-PCA and LUT method for damage detection is introduced for the first time. The damage identification of a truss bridge and a two-story frame structure is performed for verification of the proposed method, considering all single damage cases as well as many multiple damage scenarios. In addition, the robustness of the proposed algorithm to measurement noise was investigated by polluting the FRF data with 5%, 10%, 15% and 20% noises.

scholarly journals Damage Detection Method Based on Continuous Wavelet Transformation of Lamb Wave Signals

2020 ◽  
Vol 10 (23) ◽  
pp. 8610
Author(s):  
M. Saqib Hameed ◽  
Zheng Li ◽  
Kaihong Zheng
Keyword(s):  
Lead Zirconate Titanate ◽  
Lamb Wave ◽  
Wavelet Transformation ◽  
Damage Index ◽  
Inspection Time ◽  
Additional Parameter ◽  
Continuous Wavelet ◽  
Continuous Wavelet Transformation ◽  
Damage Indices ◽  
Pulse Echo

A damage estimation method based on continuous wavelet transformation (CWT) of the normalized Lamb wave signals is proposed here. Lamb waves are actuated and sensed using piezoelectric (lead zirconate titanate, PZT) transducers arranged in the form of square detection cells on a plate-like structure. Excitation sequences based on pitch–catch and pulse–echo configurations are tested for the same arrangement of the transducers. The possibilities of the existence of damage for each actuator–senor pair are formed by using the normalized coefficient of CWT. The size of the possible damage region is directly controlled through envelopes defined by the coefficients of CWT, and no additional parameter is required to define its size. The aggregate damage image is constructed by the fusion of damage possibilities from all actuator–sensor pairs using damage indices based on conjunctive and compromised fusion schemes. The results indicate that the proposed method can estimate the location and severity of multiple damage with signals directly from the damaged plate, without the need of baseline signals from the undamaged plate, and the time-compensated signals provide better damage imaging than the raw signals. The most accurate and computationally inexpensive combination is the pulse–echo configuration with damage index based on conjunctive image fusion scheme. The method is computationally inexpensive and can be applied for multiple damage estimations in large structures to reduce the evaluation cost and inspection time during on-line structural health monitoring.

scholarly journals Hole-Edge Corrosion Expansion Monitoring Based on Lamb Wave

Metals ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1469
Author(s):  
Xiangyu Wang ◽  
Wei Dai ◽  
Duo Xu ◽  
Weifang Zhang ◽  
Yunmeng Ran ◽  
...  
Keyword(s):  
Aluminum Alloy ◽  
Stress Concentration ◽  
Lamb Wave ◽  
Damage Index ◽  
Corrosion Damage ◽  
Critical Issue ◽  
Alloy Structure ◽  
Imaging Algorithm ◽  
Hole Edge ◽  
Hole Structure

Corrosion is a critical issue for engineered metallic components in mechanical and aerospace industries. Due to the complexity of aerospace aluminum alloy structure, corrosion is particularly tend to occur and expand in stress concentration areas, such as the edge of a hole, which causes the overall structure to be more likely to fail. In this paper, a Lamb wave-based active sensing method with improved sensors network was used to detect the hole-edge corrosion expansion. A0 wave packet of Lamb wave is extracted from signals, and two damage factors are used as characteristics of the signals. Probabilistic imaging algorithm is used to imaging and quantify the hole-edge corrosion area. Five corrosion extension tests show that the proposed method can effectively locate and quantify the hole-edge corrosion damage expansion of a single-hole structure; furthermore, the normalized amplitude damage index and phase change damage index can be used to predict hole-edge corrosion expansion effectively.

scholarly journals Structural Damage Localization and Quantification Based on a CEEMDAN Hilbert Transform Neural Network Approach: A Model Steel Truss Bridge Case Study

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1271 ◽  
Author(s):  
Asma Alsadat Mousavi ◽  
Chunwei Zhang ◽  
Sami F. Masri ◽  
Gholamreza Gholipour
Keyword(s):  
Neural Network ◽  
Damage Detection ◽  
Structural Damage ◽  
Damage Index ◽  
Steel Truss Bridge ◽  
Damage Indices ◽  
Bridge Model ◽  
Steel Truss ◽  
Truss Bridge

Vibrations of complex structures such as bridges mostly present nonlinear and non-stationary behaviors. Recently, one of the most common techniques to analyze the nonlinear and non-stationary structural response is Hilbert–Huang Transform (HHT). This paper aims to evaluate the performance of HHT based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) technique using an Artificial Neural Network (ANN) as a proposed damage detection methodology. The performance of the proposed method is investigated for damage detection of a scaled steel-truss bridge model which was experimentally established as the case study subjected to white noise excitations. To this end, four key features of the intrinsic mode function (IMF), including energy, instantaneous amplitude (IA), unwrapped phase, and instantaneous frequency (IF), are extracted to assess the presence, severity, and location of the damage. By analyzing the experimental results through different damage indices defined based on the extracted features, the capabilities of the CEEMDAN-HT-ANN model in detecting, addressing the location and classifying the severity of damage are efficiently concluded. In addition, the energy-based damage index demonstrates a more effective approach in detecting the damage compared to those based on IA and unwrapped phase parameters.

Integrated impedance and Lamb wave–based structural health monitoring strategy for long-term cycle-loaded composite structure

2017 ◽  
Vol 17 (4) ◽  
pp. 763-776 ◽  
Author(s):  
Dongyue Gao ◽  
Zhanjun Wu ◽  
Lei Yang ◽  
Yuebin Zheng
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Sensor Network ◽  
Health Monitoring ◽  
Lamb Wave ◽  
Structural Damage ◽  
Damage Index ◽  
Health Condition ◽  
Monitoring Strategy ◽  
Structural Health

Impedance of a sensor is sensitivity to small structural damage which surrounds the sensor. Lamb wave propagation provides higher damage detection efficiency in the range of large area. Both methods have been widely developed for structural health monitoring. This article presents integrated impedance and Lamb wave–based structural health monitoring strategy for composite pressure vessels. The output of the presented structural health monitoring strategy includes distribution and classification of damage and health condition of sensor network under varying internal pressure loading environments. In the strategy, a novel damage index adjusting method for Lamb wave damage detection is developed based on the signal features of real and imaginary parts of the sensor impedance. First, the potential structural damage is pre-warned by monitoring the impedance variation of the piezoelectric transducer sensor network. Then, the health condition of sensor network under the working condition is assessed by impedance-based self-diagnosis method; subsequently, the Lamb wave damage index is adjusted based on the result of sensor self-diagnosis. Finally, on the basis of sensor self-diagnosis and damage index adjustment result, damage identification and classification are performed. Practical efficacy of the structural health monitoring approach is tested by the damage monitoring experiment on loaded composite structure.

A diversified shared latent variable model for efficient image characteristics extraction and modelling

2021 ◽  
Vol 421 ◽  
pp. 244-259
Author(s):  
Hao Xiong ◽  
Yuan Yan Tang ◽  
Fionn Murtagh ◽  
Leszek Rutkowski ◽  
Shlomo Berkovsky
Keyword(s):  
Latent Variable ◽  
Latent Variable Model ◽  
Variable Model ◽  
Image Characteristics
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