scholarly journals Real-Time System Identification of a Nonlinear Four-Story Steel Frame Structure—Application to Structural Health Monitoring

2009 ◽  
Vol 9 (11) ◽  
pp. 1339-1346 ◽  
Author(s):  
C.E. Hann ◽  
I. Singh-Levett ◽  
B.L. Deam ◽  
J.B. Mander ◽  
J.G. Chase
Keyword(s):  
System Identification ◽  
Structural Health Monitoring ◽  
Real Time ◽  
Health Monitoring ◽  
Steel Frame ◽  
Frame Structure ◽  
Time System ◽  
Real Time System ◽  
Structural Health ◽  
Steel Frame Structure

A Variation Model Method for Real Time System Identification in Bridge Health Monitoring

2018 ◽  
Author(s):  
Ngoc Trung ◽  
Luu ◽  
Al‐Hakam Hamdan ◽  
Michael Polter ◽  
Tobias Mansperger
Keyword(s):  
System Identification ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Model ◽  
Real Time System ◽  
Structural Health ◽  
Multi Stage ◽  
Bridge Structures ◽  
Damage Data ◽  
Variation Model

The Structural Health Monitoring of bridge structures is becoming increasingly important. Due to new developments in the field of sensor and data processing technology, a new method will be introduced, which enables prognosis of the bridge lifespan through system identification based on the monitoring process. Therefore, the damages of the bridge, which are modelled in an appropriate damage model, will be linked with its BIM Model. The damage data will then be variated by using a separate Variation Model. Using this method results in the automatized creation of numerous input models for mass simulation. This forms the basis for a multi‐stage procedure, which identifies the structural bridge state by using the simulation results for a numerical best‐fit method. Thereby engineers can utilize the evaluated models to make more precise decisions and improve the Structural Health Monitoring of bridge structures.

scholarly journals Infrared Thermography Measurement for Vibration-Based Structural Health Monitoring in Low-Visibility Harsh Environments

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7067
Author(s):  
Jia-Hao He ◽  
Ding-Peng Liu ◽  
Cheng-Hsien Chung ◽  
Hsin-Haou Huang
Keyword(s):  
Structural Health Monitoring ◽  
Infrared Thermography ◽  
Mode Shape ◽  
Health Monitoring ◽  
Large Scale ◽  
Frame Structure ◽  
Harsh Environments ◽  
Thermal Imager ◽  
Heat Sources ◽  
Structural Health

In this study, infrared thermography is used for vibration-based structural health monitoring (SHM). Heat sources are employed as sensors. An acrylic frame structure was experimentally investigated using the heat sources as structural marker points to record the vibration response. The effectiveness of the infrared thermography measurement system was verified by comparing the results obtained using an infrared thermal imager with those obtained using accelerometers. The average error in natural frequency was between only 0.64% and 3.84%. To guarantee the applicability of the system, this study employed the mode shape curvature method to locate damage on a structure under harsh environments, for instance, in dark, hindered, and hazy conditions. Moreover, we propose the mode shape recombination method (MSRM) to realize large-scale structural measurement. The partial mode shapes of the 3D frame structure are combined using the MSRM to obtain the entire mode shape with a satisfactory model assurance criterion. Experimental results confirmed the feasibility of using heat sources as sensors and indicated that the proposed methods are suitable for overcoming the numerous inherent limitations associated with SHM in harsh or remote environments as well as the limitations associated with the SHM of large-scale structures.

scholarly journals Arrays of Conformable Ultrasonic Lamb Wave Transducers for Structural Health Monitoring with Real-time Electronics

2014 ◽  
Vol 87 ◽  
pp. 1266-1269 ◽  
Author(s):  
L. Capineri ◽  
A. Bulletti ◽  
M. Calzolai ◽  
P. Giannelli ◽  
D. Francesconi
Keyword(s):  
Structural Health Monitoring ◽  
Real Time ◽  
Health Monitoring ◽  
Lamb Wave ◽  
Structural Health

scholarly journals A Multiobjective Perspective to Optimal Sensor Placement by Using a Decomposition-Based Evolutionary Algorithm in Structural Health Monitoring

2020 ◽  
Vol 10 (21) ◽  
pp. 7710
Author(s):  
Tsung-Yueh Lin ◽  
Jin Tao ◽  
Hsin-Haou Huang
Keyword(s):  
Structural Health Monitoring ◽  
Evolutionary Algorithm ◽  
Health Monitoring ◽  
Sensor Placement ◽  
Frame Structure ◽  
Mode Shapes ◽  
Beam Model ◽  
Optimal Sensor Placement ◽  
Modal Assurance Criterion ◽  
Structural Health

The objective of optimal sensor placement in a dynamic system is to obtain a sensor layout that provides as much information as possible for structural health monitoring (SHM). Whereas most studies use only one modal assurance criterion for SHM, this work considers two additional metrics, signal redundancy and noise ratio, combining into three optimization objectives: Linear independence of mode shapes, dynamic information redundancy, and vibration response signal strength. A modified multiobjective evolutionary algorithm was combined with particle swarm optimization to explore the optimal solution sets. In the final determination, a multiobjective decision-making (MODM) strategy based on distance measurement was used to optimize the aforementioned objectives. We applied it to a reduced finite-element beam model of a reference building and compared it with other selection methods. The results indicated that MODM suitably balanced the objective functions and outperformed the compared methods. We further constructed a three-story frame structure for experimentally validating the effectiveness of the proposed algorithm. The results indicated that complete structural modal information can be effectively obtained by applying the MODM approach to identify sensor locations.

Safety 4.0 for the Most Dangerous Industrial Objects

2021 ◽  
Author(s):  
Igor Razuvaev
Keyword(s):  
Decision Making ◽  
Structural Health Monitoring ◽  
Real Time ◽  
Health Monitoring ◽  
Low Temperatures ◽  
Storage Tanks ◽  
Data Verification ◽  
Structural Health

Abstract Isothermal Storage Tanks (IST) contains tens thousands tons of the liquefied gases (propane, ethane, ethylene, etc.) at very low temperatures. These are the most dangerous industrial objects. In the report the Integrated Structural Health Monitoring (ISHM) Systems for the management of the integrity of these tanks in real time is considered. The structure of the ISHM Systems, NDT methods, technical characteristics, data verification procedures, a decision-making algorithm and practical results are described.

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