Experimental validation of a new statistical process control feature for damage detection

Zapico-Valle, J.L.; García-Diéguez, M.; Martínez, María Placeres González; Worden, Keith

doi:10.1016/j.ymssp.2011.02.007

Cited by 13 publications

(9 citation statements)

References 11 publications

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“…Extreme value and kernel density estimation (KDE) functions have been previously used for this purpose. 50,51 The KDE is considered herein more suitable since, for some cases, the distribution of the damage indexes is found to be bimodal, as will be shown later on. Such behavior cannot be properly described by extreme value distributions.…”

Section: Discussionmentioning

confidence: 99%

Damage detection and localization from linear and nonlinear global vibration features in concrete slabs subjected to localized thermal damage

Eiras

Payan

Rakotonarivo

et al. 2020

Structural Health Monitoring

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In this study, different alternatives to detect and localize damage from linear and nonlinear vibration responses were investigated. These alternatives were compared on two concrete slabs subjected to different damage extents. Linear and nonlinear modal test configurations were considered. The variations of linear resonant frequencies, modal assurance criterion values, and nonlinear hysteretic parameters were used to detect damage. Then, the modal shapes were used to locate damage positions. The maximum principal curvatures derived from the original modal shape displacements between damaged and undamaged states made it possible to spot the damaged zones. Damage localization was further enhanced by weighting the principal modal shape curvature differences for every mode by their respective variations of the nonlinear hysteretic parameter. Finally, damage localization was achieved using different outlier identification techniques.

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Section: Discussionmentioning

confidence: 99%

Damage detection and localization from linear and nonlinear global vibration features in concrete slabs subjected to localized thermal damage

Eiras

Payan

Rakotonarivo

et al. 2020

Structural Health Monitoring

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“…In [14], it was found that a screw joint is relaxed at smaller loads than expected due to the sliding of contact area. Zapico-Valle [15] presented an experimental validation of a new statistical process control feature for damage detection. In [16,17], screw joints excited by vibrations of different frequencies were analyzed.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Different Metal Screw Joint Parameters by Using Multiple Criteria Analysis Methods

Čereška

Podviezko

Zavadskas

2018

Metals

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This study compares screw joints made of different materials, including screws of different diameters. For that purpose, 8, 10, 12, 14, 16 mm diameter steel screws and various parts made of aluminum (Al), steel (Stl), bronze (Brz), cast iron (CI), copper (Cu) and brass (Br) are considered. Multiple criteria decision making (MCDM) methods such as evaluation based on distance from average solution (EDAS), simple additive weighting (SAW), technique for order of preference by similarity to ideal solution (TOPSIS) and complex proportional assessment (COPRAS) are utilized to assess reliability of screw joints also considering cost issues. The entropy, criterion impact loss (CILOS) and integrated determination of objective criteria weights (IDOCRIW) methods are utilized to assess weights of decision criteria and find the best design alternative. Numerical results confirm the validity of the proposed approach.

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“…When the process data deviate from their normal range and trigger the control limits, the excessive variation of data indicates the presence of faults or damage in the system. SPC has been applied to many damage detection problems in the field of SHM, especially in longterm bridge-monitoring research projects (Deraemaeker et al, 2008;Fugate et al, 2001;Kullaa, 2003;Magalha˜es et al, 2012;Sohn et al, 2000;Zapico-Valle et al, 2011). The above studies all used static SPC methods, in which the control limits are fixed constant values calculated from statistical indicators of historical data.…”

Section: Introductionmentioning

confidence: 99%

An integrated real-time structural damage detection method based on extended Kalman filter and dynamic statistical process control

Jin

Jang

Sun

2016

Advances in Structural Engineering

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Real-time structural parameter identification and damage detection are of great significance for structural health monitoring systems. The extended Kalman filter has been implemented in many structural damage detection methods due to its capability to estimate structural parameters based on online measurement data. Current research assumes constant structural parameters and uses static statistical process control for damage detection. However, structural parameters are typically slow-changing due to variations such as environmental and operational effects. Hence, false alarms may easily be triggered when the data points falling outside of the static statistical process control range due to the environmental and operational effects. In order to overcome this problem, this article presents a novel real-time structural damage detection method by integrating extended Kalman filter and dynamic statistical process control. Based on historical measurements of damage-sensitive parameters in the state-space model, extended Kalman filter is used to provide real-time estimations of these parameters as well as standard derivations in each time step, which are then used to update the control limits for dynamic statistical process control to detect any abnormality in the selected parameters. The numerical validation is performed on both linear and nonlinear structures, considering different damage scenarios. The simulation results demonstrate high detection accuracy rate and light computational costs of the developed extended Kalman filter–dynamic statistical process control damage detection method and the potential for implementation in structural health monitoring systems for in-service civil structures.

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Experimental validation of a new statistical process control feature for damage detection

Cited by 13 publications

References 11 publications

Damage detection and localization from linear and nonlinear global vibration features in concrete slabs subjected to localized thermal damage

Damage detection and localization from linear and nonlinear global vibration features in concrete slabs subjected to localized thermal damage

Assessment of Different Metal Screw Joint Parameters by Using Multiple Criteria Analysis Methods

An integrated real-time structural damage detection method based on extended Kalman filter and dynamic statistical process control

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