scholarly journals Transducer placement optimisation scheme for a delay and sum damage detection algorithm

2016 ◽  
Vol 24 (4) ◽  
pp. e1898 ◽  
Author(s):  
M. S. Salmanpour ◽  
Z. Sharif Khodaei ◽  
M. H. Aliabadi
Keyword(s):  
Damage Detection ◽  
Detection Algorithm ◽  
Transducer Placement

Investigation of Sensor Placement in Lamb Wave-Based SHM Method

2012 ◽  
Vol 518 ◽  
pp. 174-183 ◽  
Author(s):  
Pawel Malinowski ◽  
Tomasz Wandowski ◽  
Wiesław M. Ostachowicz
Keyword(s):  
Wave Propagation ◽  
Damage Detection ◽  
Guided Waves ◽  
Sensor Placement ◽  
Detection Algorithm ◽  
Piezoelectric Sensors ◽  
Optimal Placement ◽  
Laser Vibrometer ◽  
Contact Method ◽  
Monitoring Method

In this paper the investigation of a structural health monitoring method for thin-walled parts of structures is presented. The concept is based on the guided elastic wave propagation phenomena. This type of waves can be used in order to obtain information about structure condition and possibly damaged areas. Guided elastic waves can travel in the medium with relatively low attenuation, therefore they enable monitoring of extensive parts of structures. In this way it is possible to detect small defects in their early stage of growth. It is essential because undetected damage can endanger integrity of a structure. In reported investigation piezoelectric transducer was used to excite guided waves in chosen specimens. Dispersion of guided waves results in changes of velocity with the wave frequency, therefore a narrowband signal was used. Measurement of the wave field was realized using laser scanning vibrometer that registered the velocity responses at points belonging to a defined mesh. An artificial discontinuity was introduced to the specimen. The goals of the investigation was to detect it and find optimal sensor placement for this task. Determination of the optimal placement of sensors is a very challenging mission. In conducted investigation laser vibrometer was used to facilitate the task. The chosen mesh of measuring points was the basis for the investigation. The purpose was to consider various configuration of piezoelectric sensors. Instead of using vast amount of piezoelectric sensors the earlier mentioned laser vibrometer was used to gather the necessary data from wave propagation. The signals gather by this non-contact method for the considered network were input to the damage detection algorithm. Damage detection algorithm was based on a procedure that seeks in the signals the damage-reflected waves. Knowing the wave velocity in considered material the damage position can be estimated.

Field Validation of a Statistical-Based Bridge Damage-Detection Algorithm

2013 ◽  
Vol 18 (11) ◽  
pp. 1227-1238 ◽  
Author(s):  
Brent Phares ◽  
Ping Lu ◽  
Terry Wipf ◽  
Lowell Greimann ◽  
Junwon Seo
Keyword(s):  
Damage Detection ◽  
Detection Algorithm ◽  
Field Validation ◽  
Bridge Damage

scholarly journals Modal-based vibrothermography using feature extraction with application to composite materials

2019 ◽  
Vol 19 (4) ◽  
pp. 967-986 ◽  
Author(s):  
Xintian Chi ◽  
Dario Di Maio ◽  
Nicholas AJ Lieven
Keyword(s):  
Feature Extraction ◽  
Composite Materials ◽  
Damage Detection ◽  
Infrared Camera ◽  
Experimental Tests ◽  
Detection Algorithm ◽  
Modal Testing ◽  
Theoretical Development ◽  
Operational Environment ◽  
Practical Applications

This research focuses on the development of a damage detection algorithm based on modal testing, vibrothermography, and feature extraction. The theoretical development of mathematical models is presented to illustrate the principles supporting the associated algorithms, through which the importance of the three components contributing to this approach is demonstrated. Experimental tests and analytical simulations have been performed in laboratory conditions to show that the proposed damage detection algorithm is able to detect, locate, and extract the features generated due to the presence of sub-surface damage in aerospace grade composite materials captured by an infrared camera. Through tests and analyses, the reliability and repeatability of this damage detection algorithm are verified. In the concluding observations of this article, suggestions are proposed for this algorithm’s practical applications in an operational environment.

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.

Evolution of a Bridge Damage-Detection Algorithm

2013 ◽  
Vol 2331 (1) ◽  
pp. 71-80 ◽  
Author(s):  
Brent Phares ◽  
Ping Lu ◽  
Terry Wipf ◽  
Lowell Greimann ◽  
Junwon Seo
Keyword(s):  
Damage Detection ◽  
Detection Algorithm ◽  
Bridge Damage

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.

Lamb-Wave Based Damage Detection in Anisotropic Composite Plates

2014 ◽  
Vol 627 ◽  
pp. 1-4 ◽  
Author(s):  
Z. Sharif-Khodaei ◽  
M.H. Aliabadi
Keyword(s):  
Damage Detection ◽  
Lamb Wave ◽  
Lamb Waves ◽  
Composite Plates ◽  
Detection Algorithm ◽  
Damage State ◽  
Anisotropic Composite ◽  
Cfrp Composite ◽  
The Difference ◽  
Imaging Algorithms

Damage detection in anisotropic composite plates based on Lamb wave technique has been investigated. A network of transducers is used to detect barely visible damage caused by impact. A CFRP composite plate has been impacted and tested to verify the proposed damage detection algorithms. The difference in the propagational properties of Lamb waves in the pristine state and the damage state is used through data fusion and imaging algorithms to detect, locate and characterise the damage. The influence of directionality of the velocity on the validity of the detection algorithm is examined and some results are presented.

scholarly journals ON THE CLASSIFIER PERFORMANCE FOR SIMULATION BASED DEBRIS DETECTION IN SAR IMAGERY

2021 ◽  
Vol XLIII-B1-2021 ◽  
pp. 45-50
Author(s):  
S. Kuny ◽  
H. Hammer ◽  
K. Schulz
Keyword(s):  
Random Forest ◽  
Damage Detection ◽  
Urban Areas ◽  
Detection Algorithm ◽  
Performance Comparison ◽  
Random Forest Classifier ◽  
Training Data ◽  
Support Vector ◽  
Effective Performance ◽  
Sar Imagery

Abstract. Urban areas struck by disasters such as earthquakes are in need of a fast damage detection assessment. A post-event SAR image often is the first available image, most likely with no matching pre-event image to perform change detection. In previous work we have introduced a debris detection algorithm for this scenario that is trained exclusively with synthetically generated training data. A classification step is employed to separate debris from similar textures such as vegetation. In order to verify the use of a random forest classifier for this context, we conduct a performance comparison with two alternative popular classifiers, a support vector machine and a convolutional neural network. With the direct comparison revealing the random forest classifier to be best suited, the effective performance on the prospect of debris detection is investigated for the post-earthquake Christchurch scene. Results show a good separation of debris from vegetation and gravel, thus reducing the false alarm rate in the damage detection operation considerably.

Sign in / Sign up

Export Citation Format

Share Document