Passive structural health monitoring using cross correlation of ambient vibrations in an aluminum plate

2016 ◽  
Vol 140 (4) ◽  
pp. 2959-2959
Author(s):  
Sun Ah Jung ◽  
Keunhwa Lee ◽  
Woojae Seong
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Cross Correlation ◽  
Aluminum Plate ◽  
Ambient Vibrations ◽  
Structural Health

scholarly journals Temperature Effects on Electromechanical Response of Deposited Piezoelectric Sensors Used in Structural Health Monitoring of Aerospace Structures

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2805 ◽  
Author(s):  
Hamidreza Hoshyarmanesh ◽  
Mojtaba Ghodsi ◽  
Minjae Kim ◽  
Hyung Hee Cho ◽  
Hyung-Ho Park
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Mechanical Impedance ◽  
Peak Shift ◽  
Aluminum Plate ◽  
Distinct Advantage ◽  
Compressor Blades ◽  
Turbine Engine ◽  
Electromechanical Impedance ◽  
Structural Health

Turbomachine components used in aerospace and power plant applications preferably require continuous structural health monitoring at various temperatures. The structural health of pristine and damaged superalloy compressor blades of a gas turbine engine was monitored using real electro-mechanical impedance of deposited thick film piezoelectric transducers at 20 and 200 °C. IVIUM impedance analyzer was implemented in laboratory conditions for damage detection in superalloy blades, while a custom-architected frequency-domain transceiver circuit was used for semi-field circumstances. Recorded electromechanical impedance signals at 20 and 200 °C acquired from two piezoelectric wafer active sensors bonded to an aluminum plate, near and far from the damage, were initially utilized for accuracy and reliability verification of the transceiver at temperatures >20 °C. Damage formation in both the aluminum plate and blades showed a peak shift in the swept frequency along with an increase in the amplitude and number of impedance peaks. The thermal energy at 200 °C, on the other hand, enforces a further subsequent peak shift in the impedance signal to pristine and damaged parts such that the anti-resonance frequency keeps reducing as the temperature increases. The results obtained from the impedance signals of both piezoelectric wafers and piezo-films, revealed that increasing the temperature somewhat decreased the real impedance amplitude and the number of anti-resonance peaks, which is due to an increase in permittivity and capacitance of piezo-sensors. A trend is also presented for artificial intelligence training purposes to distinguish the effect of the temperature versus damage formation in sample turbine compressor blades. Implementation of such a monitoring system provides a distinct advantage to enhance the safety and functionality of critical aerospace components working at high temperatures subjected to crack, wear, hot-corrosion and erosion.

scholarly journals Integration of Refined Composite Multiscale Cross-Sample Entropy and Backpropagation Neural Networks for Structural Health Monitoring

2020 ◽  
Vol 10 (3) ◽  
pp. 839 ◽  
Author(s):  
Tzu-Kang Lin ◽  
Yu-Ching Chen
Keyword(s):  
Neural Network ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Confusion Matrix ◽  
Sample Entropy ◽  
Ambient Vibrations ◽  
Analysis Software ◽  
Element Analysis ◽  
Structural Health ◽  
Training Samples

This study developed a structural health monitoring (SHM) system based on refined composite multiscale cross-sample entropy (RCMCSE) and an artificial neural network for monitoring structures under ambient vibrations. RCMCSE was applied to enhance the reliability of entropy estimations. First, RCMCSE was implemented to extract damage features, and finite element analysis software was then used to generate training samples, which included stiffness reductions to achieve various damage patterns. A neural network model was constructed and trained using entropy values for these damage patterns. An experiment was conducted on a seven-story steel benchmark structure to validate the performance of the proposed system. Additionally, a confusion matrix was established to evaluate the performance of the proposed system. The results obtained for a scaled-down benchmark structure indicated that 89.8% of the floors were accurately classified, and 90% of the practical damaged floors were correctly diagnosed. The performance evaluation demonstrated that the proposed SHM system exhibited increased damage location accuracy.

Structural health monitoring of hollow cylinder using cross-correlation of ambient noise field

2019 ◽  
Vol 101 ◽  
pp. 87-93
Author(s):  
Sonia Djili ◽  
Emmanuel Moulin ◽  
Jamal Assaad ◽  
Malika Toubal ◽  
Farouk Benmeddour
Keyword(s):  
Structural Health Monitoring ◽  
Hollow Cylinder ◽  
Health Monitoring ◽  
Ambient Noise ◽  
Cross Correlation ◽  
Structural Health ◽  
Noise Field

Reusable piezoelectric transducer for structural health monitoring using both Lamb wave and electromechanical impedance modes

2020 ◽  
Vol 31 (16) ◽  
pp. 1898-1909
Author(s):  
Qijian Liu ◽  
Yuan Chai ◽  
Xinlin Qing
Keyword(s):  
Structural Health Monitoring ◽  
Lead Zirconate Titanate ◽  
Health Monitoring ◽  
Lamb Wave ◽  
Lead Zirconate ◽  
Aluminum Plate ◽  
Electromechanical Impedance ◽  
Structural Health ◽  
Zirconate Titanate ◽  
Piezoelectric Lead Zirconate Titanate

A variety of structural health monitoring techniques have been developed to support the efficient online monitoring of structural integrity. Moreover, Lamb wave and electromechanical impedance methods are increasingly used for structural health monitoring applications due to their high sensitivity and effectiveness in detecting damage. However, these techniques require transducers to be permanently attached to structures because of the usage of baselines recorded under the condition without damage. In this study, a reusable piezoelectric lead zirconate titanate transducer for monitoring corrosion damage on the aluminum plate is introduced, which can be removed from the test specimen and reused with the repeatability of signals. The reusable piezoelectric lead zirconate titanate transducer is bonded on the aluminum plate using the ethylene-acrylic acid copolymer with an aluminum enclosure. A series of experiments are conducted on an aluminum plate, including the investigation for repeatability of signals and the capability of corrosion detection of the designed piezoelectric lead zirconate titanate transducer through the Lamb wave and electromechanical impedance methods. The simulated corrosion defect with the area of 15 × 15 mm2 is detected during experiments. The experimental results confirm that the reusable piezoelectric lead zirconate titanate transducer can effectively evaluate the corrosion damage to plate structure and can be reused many times.

Research on Data Correlation in Structural Health Monitoring System

2013 ◽  
Vol 671-674 ◽  
pp. 2044-2048
Author(s):  
Qiang Li ◽  
Chun Xiao ◽  
Wei Li ◽  
Li Qiao Li ◽  
Hui Liu
Keyword(s):  
Structural Health Monitoring ◽  
Correlation Analysis ◽  
Monitoring System ◽  
Health Monitoring ◽  
Cross Correlation ◽  
Sampled Data ◽  
Health Monitoring System ◽  
Structural Health ◽  
Structural Health Monitoring System ◽  
The Cross

In structural health monitoring system, data analysis is one of the most important parts. It is mainly for processing and analysis of the collected data, among of which, the correlation analysis of the collected data can be used to verify the feasibility of the system. This paper applies the method of wavelet de-noising analysis to reduce signal noise and utilizes MATLAB and LabVIEW to calculate the cross-correlation coefficient in simulation statistics independently. To verify the feasibility of correlation analysis method and the data processing, simulation study is finished based on sampled data, which are the information of measuring points of strain and temperature from the Baishazhou Bridge. The cross-correlation coefficients between various signals can provide the reference to the whole health status of the civil engineering structure, and then enhance the accuracy of structural health assessment.

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