scholarly journals Sensor Placement Strategies for the Seismic Monitoring of Complex Vaulted Structures of the Modern Architectural Heritage

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Erica Lenticchia ◽  
Rosario Ceravolo ◽  
Paola Antonaci
Keyword(s):  
Sensor Placement ◽  
Seismic Damage ◽  
Operating Conditions ◽  
Ambient Vibration ◽  
Health State ◽  
Architectural Heritage ◽  
Optimal Sensor Placement ◽  
Damage Scenario ◽  
Restoration Planning ◽  
Ambient Vibration Testing

Effective diagnostic and monitoring systems are highly needed in the building and infrastructure sector, to provide a comprehensive assessment of the structural health state and improve the maintenance and restoration planning. Vibration-based techniques, and especially ambient vibration testing, have proved to be particularly suitable for both periodic and continuous monitoring of existing structures. As a general requirement, permanent systems must include a sensing network able to run a continuous surveillance and provide reliable analyses based on different information sources. The variability in the environmental and operating conditions needs to be accounted for in designing such a sensor network, but it is mainly the structural typology that governs the optimal sensor placement strategy. Architectural heritage consists of a great variety of buildings and monuments that significantly differ from each other in terms of typology, historic period, construction techniques, and materials. In this paper, the main issues regarding seismic protection and analysis of the modern architectural heritage are introduced and applied to one of the vaulted structures built by Pier Luigi Nervi in the Turin Exhibition Centre. The importance of attaining an adequate level of knowledge in historic structures is also highlighted. After an overview of the Turin Exhibition Centre and its construction innovations, this paper focuses on Hall B, describing the structural design conceived by Pier Luigi Nervi. A seismic assessment of the structures of Hall B is then presented, considering the potential seismic damage to nonstructural elements. Subsequently, the application of an optimal sensor placement strategy is described with reference to two different scenarios: the first one corresponding to the undamaged structure and the second one that considers a possible damage to the infill walls. Finally, a novel damage-scenario-driven sensor placement strategy based on a combination of the two above mentioned is proposed and discussed. One of the major conclusions drawn from the analyses performed is that nonstructural elements undergoing seismic damage or degradation may significantly affect the global dynamic response and consequently the optimal sensing configurations.

scholarly journals Structural health assessment of Puente del Inca natural monument using the integration of instruments and technologies

2020 ◽  
Vol 46 (2) ◽  
pp. 447-476
Author(s):  
E. Lannutti ◽  
M.G. Lenzano ◽  
J. Barón ◽  
S. Moragues ◽  
L. Lenzano
Keyword(s):  
Thermal Water ◽  
Dynamic Balance ◽  
Health Assessment ◽  
Satellite System ◽  
Ambient Vibration ◽  
Health State ◽  
Structural Deterioration ◽  
Ambient Vibration Testing ◽  
Geological Formation ◽  
Natural Monument

Puente del Inca is a natural monument standing over the Cuevas river in Mendoza, Argentina. The bridge currently exhibits structural deterioration due to natural and anthropic factors. This article seeks to offer a contribution to the conservation and restoration works of Puente del Inca by integrating instruments and technologies that allow the assessment of the health state of the natural bridge. The study relied on visual inspection, accretion-erosion rate measurements, hydrothermal flow characterization, ground-penetrating radar, soil dielectric sensor, Global Navigation Satellite System, laboratory testing, Structure from Motion, the Finite Element Method and ambient vibration testing. The results show that the morphology and health of the natural bridge depend on the dynamic balance between the erosion and the geobiological system intervening in the formation of the travertine constituting the natural bridge. The computational structural modeling demonstrates that there is a controversy between the benefit of irrigating the geological formation with thermal water and the loss of stability of the bridge under saturation conditions. Nevertheless, a continuous monitoring and an efficient administration of thermal water may ensure the deceleration of most of the erosive processes as well as the improvement of the geobiological system health.

Optimal Sensor Placement Algorithm for Structural Damage Identification

2020 ◽  
Vol 14 (1) ◽  
pp. 69-81
Author(s):  
C.H. Li ◽  
Q.W. Yang
Keyword(s):  
Structural Damage ◽  
Damage Identification ◽  
Sensor Placement ◽  
Optimization Procedure ◽  
Frame Structure ◽  
Truss Structures ◽  
Optimal Sensor Placement ◽  
Structural Damage Identification ◽  
Placement Algorithm ◽  
Sensor Locations

Background: Structural damage identification is a very important subject in the field of civil, mechanical and aerospace engineering according to recent patents. Optimal sensor placement is one of the key problems to be solved in structural damage identification. Methods: This paper presents a simple and convenient algorithm for optimizing sensor locations for structural damage identification. Unlike other algorithms found in the published papers, the optimization procedure of sensor placement is divided into two stages. The first stage is to determine the key parts in the whole structure by their contribution to the global flexibility perturbation. The second stage is to place sensors on the nodes associated with those key parts for monitoring possible damage more efficiently. With the sensor locations determined by the proposed optimization process, structural damage can be readily identified by using the incomplete modes yielded from these optimized sensor measurements. In addition, an Improved Ridge Estimate (IRE) technique is proposed in this study to effectively resist the data errors due to modal truncation and measurement noise. Two truss structures and a frame structure are used as examples to demonstrate the feasibility and efficiency of the presented algorithm. Results: From the numerical results, structural damages can be successfully detected by the proposed method using the partial modes yielded by the optimal measurement with 5% noise level. Conclusion: It has been shown that the proposed method is simple to implement and effective for structural damage identification.

scholarly journals A Data Driven Method for Optimal Sensor Placement in Multi-Zone Buildings

2021 ◽  
pp. 110956
Author(s):  
Gowri Suryanarayana ◽  
Javier Arroyo ◽  
Lieve Helsen ◽  
Jesus Lago
Keyword(s):  
Sensor Placement ◽  
Data Driven ◽  
Optimal Sensor Placement

scholarly journals Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information Theory

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3400
Author(s):  
Tulay Ercan ◽  
Costas Papadimitriou
Keyword(s):  
Utility Function ◽  
Measurement Errors ◽  
Structural Model ◽  
Information Gain ◽  
Sensor Placement ◽  
Optimal Sensor Placement ◽  
Modal Expansion ◽  
Expected Information ◽  
Virtual Sensing ◽  
Multidimensional Integral

A framework for optimal sensor placement (OSP) for virtual sensing using the modal expansion technique and taking into account uncertainties is presented based on information and utility theory. The framework is developed to handle virtual sensing under output-only vibration measurements. The OSP maximizes a utility function that quantifies the expected information gained from the data for reducing the uncertainty of quantities of interest (QoI) predicted at the virtual sensing locations. The utility function is extended to make the OSP design robust to uncertainties in structural model and modeling error parameters, resulting in a multidimensional integral of the expected information gain over all possible values of the uncertain parameters and weighted by their assigned probability distributions. Approximate methods are used to compute the multidimensional integral and solve the optimization problem that arises. The Gaussian nature of the response QoI is exploited to derive useful and informative analytical expressions for the utility function. A thorough study of the effect of model, prediction and measurement errors and their uncertainties, as well as the prior uncertainties in the modal coordinates on the selection of the optimal sensor configuration is presented, highlighting the importance of accounting for robustness to errors and other uncertainties.

Sign in / Sign up

Export Citation Format

Share Document