Structural health monitoring and damage assessment using a novel time series analysis methodology with sensor clustering

2011 ◽  
Vol 330 (6) ◽  
pp. 1196-1210 ◽  
Author(s):  
Mustafa Gul ◽  
F. Necati Catbas
Keyword(s):  
Time Series ◽  
Structural Health Monitoring ◽  
Time Series Analysis ◽  
Health Monitoring ◽  
Damage Assessment ◽  
Structural Health ◽  
Series Analysis ◽  
Analysis Methodology ◽  
Sensor Clustering

Structural Health Monitoring Using Statistical Pattern Recognition Techniques

2001 ◽  
Vol 123 (4) ◽  
pp. 706-711 ◽  
Author(s):  
Hoon Sohn ◽  
Charles R. Farrar ◽  
Norman F. Hunter ◽  
Keith Worden
Keyword(s):  
Time Series ◽  
Pattern Recognition ◽  
Structural Health Monitoring ◽  
Time Series Analysis ◽  
Health Monitoring ◽  
Statistical Pattern Recognition ◽  
Pattern Recognition Techniques ◽  
Series Analysis ◽  
Statistical Pattern ◽  
Auto Regressive

This paper casts structural health monitoring in the context of a statistical pattern recognition paradigm. Two pattern recognition techniques based on time series analysis are applied to fiber optic strain gauge data obtained from two different structural conditions of a surface-effect fast patrol boat. The first technique is based on a two-stage time series analysis combining Auto-Regressive (AR) and Auto-Regressive with eXogenous inputs (ARX) prediction models. The second technique employs an outlier analysis with the Mahalanobis distance measure. The main objective is to extract features and construct a statistical model that distinguishes the signals recorded under the different structural conditions of the boat. These two techniques were successfully applied to the patrol boat data clearly distinguishing data sets obtained from different structural conditions.

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 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.

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