Damage scenario-driven strategies for the seismic monitoring of XX century spatial structures with application to Pier Luigi Nervi’s Turin Exhibition Centre

Lenticchia, Erica; Ceravolo, Rosario; Chiorino, Cristiana

doi:10.1016/j.engstruct.2017.01.067

Cited by 21 publications

(12 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, this will return different results, as will be shown later. Two works closely related to this investigation can be found in Lenticchia, Ceravolo, and Chiorino (2017) and Lenticchia, Ceravolo, and Antonaci (2018). In those cases, SO optimization was performed, but using a compounded OF.…”

Section: Metaheuristic Algorithms In Optimal Sensor Placementmentioning

confidence: 93%

A multi‐objective genetic algorithm strategy for robust optimal sensor placement

Civera

Pecorelli

Ceravolo

et al. 2021

Computer aided Civil Eng

Self Cite

View full text Add to dashboard Cite

The performance of a monitoring system for civil buildings and infrastructures or mechanical systems depends mainly on the position of the deployed sensors. At the current state, this arrangement is chosen through optimal sensor placement (OSP) techniques that consider only the initial conditions of the structure. The effects of the potential damage are usually completely neglected during its design. Consequently, this sensor pattern is not guaranteed to remain optimal during the whole lifetime of the structure, especially for complex masonry buildings in high seismic hazard zones. In this paper, a novel approach based on multi‐objective optimization (MO) and genetic algorithms (GAs) is proposed for a damage scenario driven OSP strategy. The aim is to improve the robustness of the sensor configuration for damage detection after a potentially catastrophic event. The performance of this strategy is tested on the case study of the bell tower of the Santa Maria and San Giovenale Cathedral in Fossano (Italy) and compared to other classic OSP strategies and a standard GA approach with a single objective function.

show abstract

Section: Metaheuristic Algorithms In Optimal Sensor Placementmentioning

confidence: 93%

A multi‐objective genetic algorithm strategy for robust optimal sensor placement

Civera

Pecorelli

Ceravolo

et al. 2021

Computer aided Civil Eng

Self Cite

View full text Add to dashboard Cite

show abstract

“…On the other hand, regarding buildings evaluation, in [31], is proposed a project for monitoring the Pier Luigi Nervi Exhibition Centre (Turin-Italy), affected by the seismicity of the region. In particular, the main goal consists in determining the proper location for sensors considering the complex building architecture.…”

Section: Related Workmentioning

confidence: 99%

Reliable Data Acquisition System for a Low-Cost Accelerograph Applied to Structural Health Monitoring

Muñoz

Guevara

González

et al. 2021

J. Appl. Sci. Eng. Technol. Educ.

View full text Add to dashboard Cite

This paper presents and evaluates a continuous recording system designed for a low-cost seismic station. The architecture has three main blocks. An accelerometer sensor based on MEMS technology (Microelectromechanical Systems), an SBC platform (Single Board Computer) with embedded Linux and a microcontroller device. In particular, the microcontroller represents the central component which operates as an intermediate agent to manage the communication between the accelerometer and the SBC block. This strategy allows the system for data acquisition in real time. On the other hand, the SBC platform is used for storing and processing data as well as in order to configure the remote communication with the station. This proposal is intended as a robust solution for structural health monitoring (i.e. in order to characterize the response of an infrastructure before, during and after a seismic event). The paper details the communication scheme between the system components, which has been minutely designed to ensure the samples are collected without information loss. Furthermore, for the experimental evaluation the station was located in the facilities on a relevant infrastructure, specifically a hydroelectric dam. The system operation was compared and verified with respect to a certified accelerograph station. Results prove that the continuous recording system operates successfully and allows for detecting seismic events according to requirements of structural health applications (i.e. detects events with a frequency of vibration less than 100 Hz). Specifically, through the system implemented it was possible to characterize the effect of a seismic event of 4 MD reported by the regional seismology network and with epicenter located about 30 Km of the hydroelectric dam. Particularly, the vibration frequencies detected on the infrastructure are in the range of 13 Hz and 29 Hz. Regarding the station performance, results from experiments reveals an average CPU load of 51%, consequently the processes configured on the SBC platform do not involve an overload. Finally, the average energy consumption of the station is close to 2.4 W, therefore autonomy provided by the backup system is aroud of 10 hours.

show abstract

“…Optimal sensor placement methods have been widely employed in civil engineering structures such as bridges, whereas the number of applications in historical structures is scarce. Only a few experiences can be found in the literature [26][27][28]. In addition, most works on the application of OSP techniques are based upon simple benchmark case studies and/or consider deterministic definitions of the material properties of the monitored structure.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of optimal sensor placement algorithms for the Structural Health Monitoring of architectural heritage. Application to the Monastery of San Jerónimo de Buenavista (Seville, Spain)

Pachón

Infantes

Cámara

et al. 2020

Engineering Structures

View full text Add to dashboard Cite

In recent years, Structural Health Monitoring (SHM) based on Operational Modal Analysis (OMA) and damage detection tools has become a popular non-destructive solution to assess the real-time integrity of any kind of structure. This technique is especially well-suited for the condition-based conservation of historical structures, where minimal invasiveness must be ensured owing to their high cultural and architectural value. Optimal Sensor Placement (OSP) techniques represent a valuable tool for efficiently designing the sensor layout in a SHM system in order to achieve an effective modal identification with a reduced number of sensors and, consequently, an improved cost efficiency. In this light, this paper proposes a design methodology of sensor networks based on OSP techniques suitable for historical structures. To do so, a preliminary extensive OMA campaign is conducted in order to construct a reliable finite element (FE) model by fitting the identified modal properties. Afterwards, an optimal sensor arrangement with a limited number of sensors is obtained by applying different model-based OSP techniques. In order to improve the robustness of the solution, material uncertainties are included in the model and the optimal sensor placement is conducted within a statistical framework. This methodology is presented and evaluated with a case study of a Spanish secular building: the Monastery of San Jerónimo de Buenavista in Seville (Spain). In particular, this paper presents the results of the preliminary ambient vibration test and the modal identification of the monastery, the updating process of the FE model, as well as a critical review of the different OSP techniques within a framework of material parameter uncertainty. The presented analysis demonstrate that OSP techniques based on the rank optimization of the kinetic energy matrix of the structure yield robust sensor layout.

show abstract

Damage scenario-driven strategies for the seismic monitoring of XX century spatial structures with application to Pier Luigi Nervi’s Turin Exhibition Centre

Cited by 21 publications

References 18 publications

A multi‐objective genetic algorithm strategy for robust optimal sensor placement

A multi‐objective genetic algorithm strategy for robust optimal sensor placement

Reliable Data Acquisition System for a Low-Cost Accelerograph Applied to Structural Health Monitoring

Evaluation of optimal sensor placement algorithms for the Structural Health Monitoring of architectural heritage. Application to the Monastery of San Jerónimo de Buenavista (Seville, Spain)

Contact Info

Product

Resources

About