Scaled Acoustics Experiments and Vibration Prediction Based Structural Health Monitoring

2008 ◽  
Author(s):  
Nesrin Sarigul-Klijn ◽  
Israel Lopez ◽  
Seung-Il Baek
Keyword(s):  
Health Monitoring ◽  
Dimensional Reduction ◽  
Structural Damage ◽  
Numerical Study ◽  
Damage Index ◽  
Time Frequency ◽  
Structural Health ◽  
Reduction Techniques ◽  
Vibration Prediction ◽  
Dimensional Reduction Techniques

Vibration and acoustic-based health monitoring techniques are presented to monitor structural health under dynamic environment. In order to extract damage sensitive features, linear and nonlinear dimensional reduction techniques are applied and compared. First, a vibration numerical study based on the damage index method is used to provide both location and severity of impact damage. Next, controlled scaled experimental measurements are taken to investigate the aeroacoustic properties of sub-scale wings under known damage conditions. The aeroacoustic nature of the flow field in and around generic aircraft wing damage is determined to characterize the physical mechanism of noise generated by the damage and its applicability to battle damage detection. Simulated battle damage is investigated using a baseline, and two damage models introduced; namely, (1) an undamaged wing as baseline, (2) chordwise-spanwise-partial-penetration (SCPP), and (3) spanwise-chordwise-full-penetration (SCFP). Dimensional reduction techniques are employed to extract time-frequency domain features, which can be used to detect the presence of structural damage. Results are given to illustrate effectiveness of this approach.

scholarly journals Damage Indexing Method for Shear Critical Tubular Reinforced Concrete Structures based on Crack Image Analysis

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4304 ◽  
Author(s):  
Yang ◽  
Chang ◽  
Wu
Keyword(s):  
Image Analysis ◽  
Reinforced Concrete ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Measurement Method ◽  
Damage Index ◽  
Structural Health ◽  
Damage Indices ◽  
Indexing Method

Image analysis techniques have been applied to measure the displacements, strain field, and crack distribution of structures in the laboratory environment, and present strong potential for use in structural health monitoring applications. Compared with accelerometers, image analysis is good at monitoring area-based responses, such as crack patterns at critical regions of reinforced concrete (RC) structures. While the quantitative relationship between cracks and structural damage depends on many factors, cracks need to be detected and quantified in an automatic manner for further investigation into structural health monitoring. This work proposes a damage-indexing method by integrating an image-based crack measurement method and a crack quantification method. The image-based crack measurement method identifies cracks locations, opening widths, and orientations. Fractal dimension analysis gives the flexural cracks and shear cracks an overall damage index ranging between 0 and 1. According to the orientations of the cracks analyzed by image analysis, the cracks can be classified as either shear or flexural, and the overall damage index can be separated into shear and flexural damage indices. These damage indices not only quantify the damage of an RC structure, but also the contents of shear and flexural failures. While the engineering significance of the damage indices is structure dependent, when the damage indexing method is used for structural health monitoring, the damage indices safety thresholds can further be defined based on the structure type under consideration. Finally, this paper demonstrates this method by using the results of two experiments on RC tubular containment vessel structures.

Effects of Dimensional Reduction Techniques on Structural Damage Assessment Under Uncertainty

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
Israel Lopez ◽  
Nesrin Sarigul-Klijn
Keyword(s):  
Dimensional Reduction ◽  
Damage Assessment ◽  
Structural Damage ◽  
Principal Component ◽  
Index Method ◽  
Reduction Techniques ◽  
Structural Deterioration ◽  
Curvature Index ◽  
And Performance ◽  
Dimensional Reduction Techniques

In this paper, we present a study of dimensional reduction techniques for structural damage assessment of time-varying structures under uncertainty. Discrete tracking of the frequency response and the mode shape curvature index method is employed to perform damage assessment. Assessment of spontaneous damage in deteriorating structures is important as it can have potential benefits in improving their safety and performance. Most of the available damage assessment techniques incorporate the usage of system identification and classification techniques for detecting damage, location, and/or severity; however, much work is needed in the area of dimensional reduction in order to compress the ever-increasing data and facilitate decision-making in damage assessment classification. A comparison of dimensional reduction techniques is presented and evaluated in terms of separating damaged from undamaged data sets under two types of uncertainty, structural deterioration and environmental uncertainties. The use of a recursive principal component analysis for detecting and tracking structural deterioration and spontaneous damage is evaluated via computational simulations. The results of this study reveal that dimensional reduction techniques can greatly enhance structural damage assessment under uncertainties. This paper compares multiple dimensional reduction techniques by identifying their weaknesses and strengths.

scholarly journals Structural Health Monitoring Using Ultrasonic Guided-Waves and the Degree of Health Index

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 993
Author(s):  
Sergio Cantero-Chinchilla ◽  
Gerardo Aranguren ◽  
José Manuel Royo ◽  
Manuel Chiachío ◽  
Josu Etxaniz ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Pattern Matching ◽  
Health Monitoring ◽  
Structural Damage ◽  
Guided Waves ◽  
Damage Index ◽  
Guided Wave ◽  
Structural Health ◽  
Wave Measurements ◽  
Beamforming Technique

This paper proposes a new damage index named degree of health (DoH) to efficiently tackle structural damage monitoring in real-time. As a key contribution, the proposed index relies on a pattern matching methodology that measures the time-of-flight mismatch of sequential ultrasonic guided-wave measurements using fuzzy logic fundamentals. The ultrasonic signals are generated using the transmission beamforming technique with a phased-array of piezoelectric transducers. The acquisition is carried out by two phased-arrays to compare the influence of pulse-echo and pitch-catch modes in the damage assessment. The proposed monitoring approach is illustrated in a fatigue test of an aluminum sheet with an initial notch. As an additional novelty, the proposed pattern matching methodology uses the data stemming from the transmission beamforming technique for structural health monitoring. The results demonstrate the efficiency and robustness of the proposed framework in providing a qualitative and quantitative assessment for fatigue crack damage.

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.

scholarly journals An overview of 38 least squares–based frameworks for structural damage tomography

2019 ◽  
Vol 19 (1) ◽  
pp. 215-239 ◽  
Author(s):  
Danny Smyl ◽  
Sven Bossuyt ◽  
Waqas Ahmad ◽  
Anton Vavilov ◽  
Dong Liu
Keyword(s):  
Structural Health Monitoring ◽  
Least Squares ◽  
Health Monitoring ◽  
Structural Damage ◽  
Tomographic Imaging ◽  
Inverse Methods ◽  
One Dimension ◽  
Distributed Data ◽  
Structural Health ◽  
Static Elasticity

The ability to reliably detect damage and intercept deleterious processes, such as cracking, corrosion, and plasticity are central themes in structural health monitoring. The importance of detecting such processes early on lies in the realization that delays may decrease safety, increase long-term repair/retrofit costs, and degrade the overall user experience of civil infrastructure. Since real structures exist in more than one dimension, the detection of distributed damage processes also generally requires input data from more than one dimension. Often, however, interpretation of distributed data—alone—offers insufficient information. For this reason, engineers and researchers have become interested in stationary inverse methods, for example, utilizing distributed data from stationary or quasi-stationary measurements for tomographic imaging structures. Presently, however, there are barriers in implementing stationary inverse methods at the scale of built civil structures. Of these barriers, a lack of available straightforward inverse algorithms is at the forefront. To address this, we provide 38 least-squares frameworks encompassing single-state, two-state, and joint tomographic imaging of structural damage. These regimes are then applied to two emerging structural health monitoring imaging modalities: Electrical Resistance Tomography and Quasi-Static Elasticity Imaging. The feasibility of the regimes are then demonstrated using simulated and experimental data.

Time–frequency and time–scale analyses for structural health monitoring

2006 ◽  
Vol 365 (1851) ◽  
pp. 449-477 ◽  
Author(s):  
Wiesław J Staszewski ◽  
Amy N Robertson
Keyword(s):  
Signal Processing ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Time Scale ◽  
Time Frequency ◽  
Structural Health ◽  
Variant Analysis

Signal processing is one of the most important elements of structural health monitoring. This paper documents applications of time-variant analysis for damage detection. Two main approaches, the time–frequency and the time–scale analyses are discussed. The discussion is illustrated by application examples relevant to damage detection.

Review of piezoelectric impedance based structural health monitoring: Physics-based and data-driven methods

2021 ◽  
pp. 136943322110384
Author(s):  
Xingyu Fan ◽  
Jun Li ◽  
Hong Hao
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Low Frequency ◽  
Data Driven ◽  
Mode Shapes ◽  
Monitoring Methods ◽  
Destructive Testing ◽  
Electromechanical Impedance ◽  
Structural Health

Vibration based structural health monitoring methods are usually dependent on the first several orders of modal information, such as natural frequencies, mode shapes and the related derived features. These information are usually in a low frequency range. These global vibration characteristics may not be sufficiently sensitive to minor structural damage. The alternative non-destructive testing method using piezoelectric transducers, called as electromechanical impedance (EMI) technique, has been developed for more than two decades. Numerous studies on the EMI based structural health monitoring have been carried out based on representing impedance signatures in frequency domain by statistical indicators, which can be used for damage detection. On the other hand, damage quantification and localization remain a great challenge for EMI based methods. Physics-based EMI methods have been developed for quantifying the structural damage, by using the impedance responses and an accurate numerical model. This article provides a comprehensive review of the exciting researches and sorts out these approaches into two categories: data-driven based and physics-based EMI techniques. The merits and limitations of these methods are discussed. In addition, practical issues and research gaps for EMI based structural health monitoring methods are summarized.

Acceleration data quality assessment for bridge structural health monitoring via statistical and deep-learning approach

2021 ◽  
Author(s):  
Huaqiang Zhong ◽  
Limin Sun ◽  
José Turmo ◽  
Ye Xia
Keyword(s):  
Structural Health Monitoring ◽  
Data Quality ◽  
Health Monitoring ◽  
Structural Damage ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Operating Conditions ◽  
Monitoring Data ◽  
Statistical Characteristics ◽  
Structural Health

<p>In recent years, the safety and comfort problems of bridges are not uncommon, and the operating conditions of in-service bridges have received widespread attention. Many large-span key bridges have installed structural health monitoring systems and collected massive amounts of data. Monitoring data is the basis of structural damage identification and performance evaluation, and it is of great significance to analyze and evaluate its quality. This paper takes the acceleration monitoring data of the main girder and arch rib of a long-span arch bridge as the research object, analyzes and summarizes the statistical characteristics of the data, summarizes 6 abnormal data conditions, and proposes a data quality evaluation method of convolutional neural network. This paper conducts frequency statistics on the acceleration vibration amplitude of the bridge in December 2018 in hours. In order to highlight the end effect of frequency statistics, the whole is amplified and used as network input for training and data quality evaluation. The results are good. It provides another new method for structural monitoring data quality evaluation and abnormal data elimination.</p>

scholarly journals Research on the Progress of Interdigital Transducer (IDT) for Structural Damage Monitoring

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wang Ziping ◽  
Xiong Xiqiang ◽  
Qian Lei ◽  
Wang Jiatao ◽  
Fei Yue ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Large Scale ◽  
Safety Information ◽  
Health And Safety ◽  
Guided Wave ◽  
Structural Safety ◽  
Structural Health ◽  
Damage Monitoring

In the application of Structural Health Monitoring (SHM) methods and related technologies, the transducer used for electroacoustic conversion has gradually become a key component of SHM systems because of its unique function of transmitting structural safety information. By comparing and analyzing the health and safety of large-scale structures, the related theories and methods of Structural Health Monitoring (SHM) based on ultrasonic guided waves are studied. The key technologies and research status of the interdigital guided wave transducer arrays which used for structural damage detection are introduced. The application fields of interdigital transducers are summarized. The key technical and scientific problems solved by IDT for Structural Damage Monitoring (SHM) are presented. Finally, the development of IDT technology and this research project are summarised.

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