Effect of image acquisition and processing parameters on the estimation of crowd-induced dynamic loading on stadium grandstands

Turrisi, Simone; Zappa, Emanuele; Cigada, Alfredo; Vivanco, Miguel Ruiz; Avin, Nerea Carrera

doi:10.1109/i2mtc50364.2021.9460021

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…As anticipated in the introduction, many researches successfully applied Digital Image Correlation to estimate the crowd motion. In a recent work [15], the same authors of this paper investigate the effect that the main image acquisition and DIC parameters have on the estimation of crowd loading. They found that the measurement uncertainty is minimized when the subset size lies between 200 mm x 200 mm and 500 mm x 500 mm and when the conversion factor is 30 mm/px or lower.…”

Section: Correlationmentioning

confidence: 99%

Experimental Validation of a Vision-Based Technique to Estimate the Crowd Loading on Stadium Grandstands

Turrisi

Zappa

Cigada

2022

IEEE Open J. Instrum. Meas.

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Stadium grandstands may experience high vibration levels due to the crowd action. Existing codes and guidelines used for the design and the assessment of grandstands highlight the need of an already ongoing revision, since there is a lack of information about the real nature of the crowd excitation and its accurate evaluation. This paper describes a highly improved computer vision method, based on the use of Digital Image Correlation (DIC), able to provide reliable estimates of the crowd induced loads on stadium grandstands. The effectiveness and the applicability of DIC is validated through a series of experimental tests held at the G. Meazza stadium in Milan. A first study with 27 jumping volunteers is carried out to assess the performance of DIC in a real environment. Then, the procedure is extended to the case of a larger crowd made of 108 individuals. In both cases, the forces estimated through image processing have been used in conjunction with the impulse response function of the stand to determine the resulting structural vibrations. The comparison between measured and computed vibrations provides a good agreement both in the time and the frequency domain.

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Section: Correlationmentioning

confidence: 99%

Experimental Validation of a Vision-Based Technique to Estimate the Crowd Loading on Stadium Grandstands

Turrisi

Zappa

Cigada

2022

IEEE Open J. Instrum. Meas.

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“…Within a SHM context, a potential issue is represented by the influence that environmental and operational variations (EOVs) have a structure features. This effect is particularly evident for civil infrastructures such as bridges, whose measured responses are constantly subjected to important variations induced by wind, humidity, traffic, human loading [ 8 ] and, above all, temperature [ 9 , 10 , 11 , 12 ]. Since changes due to these benign reasons typically manifest with the same order of magnitude of those due to structure degradations, they could appear as outliers in the data masking any potential indication of ongoing structural damage.…”

Section: Introductionmentioning

confidence: 99%

Combined Use of Cointegration Analysis and Robust Outlier Statistics to Improve Damage Detection in Real-World Structures

Turrisi

Zappa

Cigada

2022

Sensors

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Due to the need for controlling many ageing and complex structures, structural health monitoring (SHM) has become increasingly common over the past few decades. However, one of the main limitations for the implementation of continuous monitoring systems in real-world structures is the effect that benign influences, such as environmental and operational variations (EOVs), have on damage sensitive features. These fluctuations may mask malign changes caused by structural damages, resulting in false structural condition assessment. When damage identification is implemented as novelty detection due to the lack of known damage states, outliers may be part of the data set as the result of the benign and malign factors mentioned above. Thanks to the developments in the field of robust outlier detection, the current paper presents a new data fusion method based on the use of cointegration and minimum covariance determinant estimator (MCD), which allows us to visualize and to classify outliers in SHM data, depending on their origin. To validate the effectiveness of this technique, the recent case study of the KW51 bridge has been considered, whose natural frequencies are subjected to variations due to both EOVs and a real structural change.

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Assessment of a Vision-Based Technique to Estimate the Synchronization of Jumping Crowds in Civil Structures

Turrisi,

Zappa,

Cigada

2023

Conference Proceedings of the Society for Experimental Mechanics Series

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Effect of image acquisition and processing parameters on the estimation of crowd-induced dynamic loading on stadium grandstands

Cited by 4 publications

References 7 publications

Experimental Validation of a Vision-Based Technique to Estimate the Crowd Loading on Stadium Grandstands

Experimental Validation of a Vision-Based Technique to Estimate the Crowd Loading on Stadium Grandstands

Combined Use of Cointegration Analysis and Robust Outlier Statistics to Improve Damage Detection in Real-World Structures

Assessment of a Vision-Based Technique to Estimate the Synchronization of Jumping Crowds in Civil Structures

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