Novelty Detection in a Changing Environment: Regression and Interpolation Approaches

Worden, Keith; Sohn, Hoon; Farrar, C.R.

doi:10.1006/jsvi.2002.5148

Cited by 159 publications

(114 citation statements)

References 6 publications

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“…Separating the effect of damage from the effect of the environment requires the use of statistical models, such as the multiple data regression (MDR) and the Principal Component Analysis (PCA) [16][17][18][19], and other suitable compensation techniques [16,20,21]. Among the various environmental factors, temperature is especially important: numerous case studies reported in the literature show that natural temperature variations could produce changes in the modal properties much bigger than those induced by a typical structural damage [22] or the normal operational loads [23].…”

Section: Introductionmentioning

confidence: 99%

Effect of Environmental Conditions on the Modal Response of a 10‐Story Reinforced Concrete Tower

Regni

Arezzo

Carbonari

et al. 2018

Shock and Vibration

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We analyse the effect of temperature and wind velocity on the natural frequencies and modal damping ratios of the Faculty of Engineering Tower at the Università Politecnica delle Marche, a 10-story reinforced concrete frame building, permanently monitored with low-noise accelerometers. The data recorded over the first 5 months of monitoring demonstrate that temperature variations and wind intensity have a clear effect on the first three natural frequencies and the corresponding damping ratios. Temperature is positively correlated to the first and second frequencies, corresponding to shear displacement modes and negatively correlated to the third frequency, corresponding to a torsional mode. All frequencies are positively correlated to wind velocity and changes in damping ratios are inversely correlated to any change in frequency. A mechanical explanation of these phenomena is offered, based on a critical review of literature case studies. These results suggest that using changes in modal parameters for damage detection always requires accurate knowledge of the correlation between modal parameters and environmental quantities (temperature, humidity, and wind velocity), an information which is only available through long-term continuous monitoring of the structural response.

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Section: Introductionmentioning

confidence: 99%

Effect of Environmental Conditions on the Modal Response of a 10‐Story Reinforced Concrete Tower

Regni

Arezzo

Carbonari

et al. 2018

Shock and Vibration

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“…The effect of environmental conditions has been investigated [49] and various methods are adopted to remove this effect, such as principal component analysis (PCA) [50,51], factor analysis [52], nonlinear PCA based on unsupervised support vector machine [53], the Cointegration concept for non-stationary time series [54], PCA method in time-varying systems [55], etc. Moreover, the novelty detection and outlier analysis are used to perform the lowest level of damage identification in operational conditions [56,57], and the multivariate statistical analysis method becomes popular for automatically revealing the damage existence using vibration data under changing environmental and operational conditions [58][59][60].…”

Section: Methods For Changing Environmental Conditionsmentioning

confidence: 99%

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

2017

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Abstract:Research on detecting structural damage at the earliest possible stage has been an interesting topic for decades. Among them, the vibration-based damage detection method as a global technique is especially pervasive. The present study reviewed the state-of-the-art on the framework of vibration-based damage identification in different levels including the prediction of the remaining useful life of structures and the decision making for proper actions. This framework consists of several major parts including the detection of damage occurrence using response-based methods, building reasonable structural models, selecting damage parameters and constructing objective functions with sensitivity analysis, adopting optimization techniques to solve the problem, predicting the remaining useful life of structures, and making decisions for the next actions. For each part, the commonly used methods were reviewed and the merits and drawbacks were summarized to give recommendations. This framework is aimed to guide the researchers and engineers to implement step by step the structure damage identification using vibration measurements. Finally, the future research work in this field is recommended.

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“…Typically, such a deterministic functional relationship is captured via a functional series expansion. Methods falling into this class include the regression/interpolation methods discussed in Worden et al (2002) and Sohn (2007), as well as the Functionally Pooled (FP) time-series models explained in Kopsaftopoulos et al (2018) and Sakellariou and Fassois (2016). These methods are particularly effective when a direct relationship exists between measurable input EOPs and the characteristic quantities of the time-series models.…”

Section: Introductionmentioning

confidence: 99%

Gaussian Process Time-Series Models for Structures under Operational Variability

Avendaño-Valencia

Chatzi

Koo

et al. 2017

Front. Built Environ.

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A wide range of vibrating structures are characterized by variable structural dynamics resulting from changes in environmental and operational conditions, posing challenges in their identification and associated condition assessment. To tackle this issue, the present contribution introduces a stochastic modeling methodology via Gaussian Process (GP) time-series models. In the presently introduced approach, the vibration response is represented by means of a random coefficient time-series model, whose coefficients comply with a GP regression on the environmental and operational parameters. The approach may be implemented in conjunction to any type of linear-in-the-parameters time-series model, ranging from simple AR models to more complex non-linear or nonstationary time-series models. The obtained GP time-series modeling approach provides an effective and compact global representation of the vibrational response of a structure under a wide span of environmental and operational conditions. The effectiveness of the postulated GP time-series models is demonstrated through two case studies: the first involves the identification of the vertical vibration response of the Humber bridge, evaluated over a period of three years; the second considers the long-term simulated vibration response of a wind turbine featuring non-stationary dynamics stemming from the rotor speed. In both cases, the variation of the average wind speed is the main driver of uncertainty, while, through application of the proposed GP time-series models, it is possible to track the resulting variation in modal quantities.

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Novelty Detection in a Changing Environment: Regression and Interpolation Approaches

Cited by 159 publications

References 6 publications

Effect of Environmental Conditions on the Modal Response of a 10‐Story Reinforced Concrete Tower

Effect of Environmental Conditions on the Modal Response of a 10‐Story Reinforced Concrete Tower

The State-of-the-Art on Framework of Vibration-Based Structural Damage Identification for Decision Making

Gaussian Process Time-Series Models for Structures under Operational Variability

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