Structural health monitoring and damage assessment Part II: Application of the damage locating vector (DLV) method to the ASCE benchmark structure experimental data

2012 ◽  
Vol 7 (9) ◽  
Author(s):  
Burcu Gunes
Keyword(s):  
Experimental Data ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Assessment ◽  
Structural Health

Damage Assessment of Structures - An Air Force Office of Scientific Research Structural Mechanics Perspective

2007 ◽  
Vol 347 ◽  
pp. 69-74 ◽  
Author(s):  
Victor Giurgiutiu
Keyword(s):  
Structural Health Monitoring ◽  
Air Force ◽  
Health Monitoring ◽  
Damage Assessment ◽  
Scientific Research ◽  
Structural Mechanics ◽  
Structural Health ◽  
Aging Aircraft ◽  
Periodic Maintenance ◽  
Implementation And Dissemination

This paper presents the perspective of the Structural Mechanics program of the Air Force Office of Scientific Research on the damage assessment of structures. It is found that damage assessment of structures plays a very important role in assuring the safety and operational readiness of Air Force fleet. The current fleet has many aging aircraft, which poses a considerable challenge for the operators and maintainers. The nondestructive evaluation technology is rather mature and able to detect damage with considerable reliability during the periodic maintenance inspections. The emerging structural health monitoring methodology has great potential, because it will use on-board damage detection sensors and systems, will be able to offer on-demand structural health bulletins. Considerable fundamental and applied research is still needed to enable the development, implementation, and dissemination of structural health monitoring technology.

scholarly journals The Teager-Kaiser Energy Cepstral Coefficients as an Effective Structural Health Monitoring Tool

2019 ◽  
Vol 9 (23) ◽  
pp. 5064 ◽  
Author(s):  
Marco Civera ◽  
Matteo Ferraris ◽  
Rosario Ceravolo ◽  
Cecilia Surace ◽  
Raimondo Betti
Keyword(s):  
Experimental Data ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Speech Processing ◽  
Speaker Recognition ◽  
Vibration Analysis ◽  
Monitoring Tool ◽  
Mel Frequency Cepstral Coefficients ◽  
Structural Health ◽  
Cepstral Coefficients

Recently, features and techniques from speech processing have started to gain increasing attention in the Structural Health Monitoring (SHM) community, in the context of vibration analysis. In particular, the Cepstral Coefficients (CCs) proved to be apt in discerning the response of a damaged structure with respect to a given undamaged baseline. Previous works relied on the Mel-Frequency Cepstral Coefficients (MFCCs). This approach, while efficient and still very common in applications, such as speech and speaker recognition, has been followed by other more advanced and competitive techniques for the same aims. The Teager-Kaiser Energy Cepstral Coefficients (TECCs) is one of these alternatives. These features are very closely related to MFCCs, but provide interesting and useful additional values, such as e.g., improved robustness with respect to noise. The goal of this paper is to introduce the use of TECCs for damage detection purposes, by highlighting their competitiveness with closely related features. Promising results from both numerical and experimental data were obtained.

scholarly journals Review of Structural Health Monitoring Methods Regarding a Multi-Sensor Approach for Damage Assessment of Metal and Composite Structures

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 826 ◽  
Author(s):  
Christoph Kralovec ◽  
Martin Schagerl
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Assessment ◽  
Composite Structures ◽  
Joint Damage ◽  
Ultrasonic Waves ◽  
Physical Models ◽  
Monitoring Methods ◽  
Structural Health ◽  
Different Levels

Structural health monitoring (SHM) is the continuous on-board monitoring of a structure’s condition during operation by integrated systems of sensors. SHM is believed to have the potential to increase the safety of the structure while reducing its deadweight and downtime. Numerous SHM methods exist that allow the observation and assessment of different damages of different kinds of structures. Recently data fusion on different levels has been getting attention for joint damage evaluation by different SHM methods to achieve increased assessment accuracy and reliability. However, little attention is given to the question of which SHM methods are promising to combine. The current article addresses this issue by demonstrating the theoretical capabilities of a number of prominent SHM methods by comparing their fundamental physical models to the actual effects of damage on metal and composite structures. Furthermore, an overview of the state-of-the-art damage assessment concepts for different levels of SHM is given. As a result, dynamic SHM methods using ultrasonic waves and vibrations appear to be very powerful but suffer from their sensitivity to environmental influences. Combining such dynamic methods with static strain-based or conductivity-based methods and with additional sensors for environmental entities might yield a robust multi-sensor SHM approach. For demonstration, a potent system of sensors is defined and a possible joint data evaluation scheme for a multi-sensor SHM approach is presented.

scholarly journals Damage Localization in a Building Structure during Seismic Excitation

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Jesús Morales-Valdez ◽  
Luis Alvarez-Icaza ◽  
José A. Escobar
Keyword(s):  
Structural Health Monitoring ◽  
Real Time ◽  
Health Monitoring ◽  
Damage Assessment ◽  
Early Stage ◽  
Detection Methods ◽  
Identification System ◽  
Building Structures ◽  
Simple Method ◽  
Structural Health

Aging of buildings during their service life has attracted the attention of researchers on structural health monitoring (SHM). This paper is related with detecting damage in building structures at the earliest possible stage during seismic activity to facilitate decision-making on evacuation before physical inspection is possible. For this, a simple method for damage assessment is introduced to identify the damage story of multistory buildings from acceleration measurements under a wave propagation approach. In this work, damage is assumed as reduction in shear wave velocities and changes in damping ratios that are directly related with stiffness loss. Most damage detection methods are off-line processes; this is not the case with this method. First, a real-time identification system is introduced to estimate the current parameters to be compared with nominal values to detect any changes in the characteristics that may indicate damage in the building. In addition, this identification system is robust to constant disturbances and measurement noise. The time needed to complete parameter identification is shorter compared to the typically wave method, and the damage assessment can keep up with the data flow in real time. Finally, using a robust threshold, postprocess of the compared signal is performed to find the location of the possible damage. The performance of the proposed method is demonstrated through experiments on a reduced-scale five-story building, showing the ability of the proposed method to improve early stage structural health monitoring.

Improving Excitations for Active Sensing in Structural Health Monitoring via Evolutionary Algorithms

2007 ◽  
Vol 129 (6) ◽  
pp. 784-802 ◽  
Author(s):  
Colin C. Olson ◽  
M. D. Todd ◽  
Keith Worden ◽  
Charles Farrar
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Damage Assessment ◽  
Structural Response ◽  
Frequency Characteristics ◽  
Mass System ◽  
Structural Health ◽  
Extraneous Noise ◽  
Ordinary Differential Equation Systems

Active excitation is an emerging area of study within the field of structural health monitoring whereby prescribed inputs are used to excite the structure so that damage-sensitive features may be extracted from the structural response. This work demonstrates that the parameters of a system of ordinary differential equations may be adjusted via an evolutionary algorithm to produce excitations that improve the sensitivity and robustness to extraneous noise of state-space based damage detection features extracted from the structural response to such excitations. A simple computational model is used to show that significant gains in damage detection and quantification may be obtained from the response of a spring-mass system to improved excitations generated by three separate representative ordinary differential equation systems. Observed differences in performance between the excitations produced by the three systems cannot be explained solely by considering the frequency characteristics of the excitations. This work demonstrates that the particular dynamic evolution of the excitation applied to the structure can be as important as the frequency characteristics of said excitation if improved damage detection is desired. In addition, the implied existence of a globally optimum excitation (in the sense of improved damage assessment) for the model system is explored.

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