AUTONOMOUS STRUCTURAL HEALTH MONITORING—PART I: MODAL PARAMETER ESTIMATION AND TRACKING

2002 ◽  
Vol 16 (4) ◽  
pp. 637-657 ◽  
Author(s):  
P. VERBOVEN ◽  
E. PARLOO ◽  
P. GUILLAUME ◽  
M. VAN OVERMEIRE
Keyword(s):  
Parameter Estimation ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Modal Parameter ◽  
Structural Health ◽  
Modal Parameter Estimation

scholarly journals The role of dynamic response parameters in damage prediction

2019 ◽  
Vol 233 (13) ◽  
pp. 4620-4636 ◽  
Author(s):  
Behzad Ahmed Zai ◽  
MA Khan ◽  
Kamran A Khan ◽  
Asif Mansoor ◽  
Aqueel Shah ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Dynamic Response ◽  
Health Monitoring ◽  
Structural Damage ◽  
Mode Shapes ◽  
Future Research ◽  
Modal Parameter ◽  
Structural Health ◽  
Structural Applications

This article presents a literature review of published methods for damage identification and prediction in mechanical structures. It discusses ways which can identify and predict structural damage from dynamic response parameters such as natural frequencies, mode shapes, and vibration amplitudes. There are many structural applications in which dynamic loads are coupled with thermal loads. Hence, a review on those methods, which have discussed structural damage under coupled loads, is also presented. Structural health monitoring with other techniques such as elastic wave propagation, wavelet transform, modal parameter, and artificial intelligence are also discussed. The published research is critically analyzed and the role of dynamic response parameters in structural health monitoring is discussed. The conclusion highlights the research gaps and future research direction.

scholarly journals Structural Health Monitoring Applications in Tall Buildings

2020 ◽  
Vol 198 ◽  
pp. 02020
Author(s):  
Yifan Zhao
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Tall Buildings ◽  
Modal Parameter ◽  
Index Method ◽  
Structural Dynamic ◽  
Modal Parameter Identification ◽  
Structural Health ◽  
Whole Process ◽  
Neural Network Algorithm

Since there is not much research on structural health monitoring (SHM) applications in tall buildings nowadays, this paper gives a proposal of how it can be applied on skyscrapers. Covering the whole process of SHM, this paper focuses more on the diagnostic algorithms, including Structural dynamic index method, Modal parameter identification method Neural network algorithm and Genetic algorithm and how these algorithms can be used in SHM. After introducing the basic process of SHM, an example is given to show how these principles can be applied in this over 400m building. And after all these introductions, a conclusion can be drawn that the structural health monitoring system can be applied properly in tall buildings following the way proposed in this paper.

scholarly journals Online Structural Health Monitoring and Parameter Estimation for Vibrating Active Cantilever Beams Using Low-Priced Microcontrollers

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Gergely Takács ◽  
Ján Vachálek ◽  
Boris Rohal’-Ilkiv
Keyword(s):  
Parameter Estimation ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Code Generation ◽  
Low Cost ◽  
Flexible Structures ◽  
Cantilever Beams ◽  
Embedded Computing ◽  
Structural Health ◽  
Estimation System

This paper presents a structural health monitoring and parameter estimation system for vibrating active cantilever beams using low-cost embedded computing hardware. The actuator input and the measured position are used in an augmented nonlinear model to observe the dynamic states and parameters of the beam by the continuous-discrete extended Kalman filter (EKF). The presence of undesirable structural change is detected by variations of the first resonance estimate computed from the observed equivalent mass, stiffness, damping, and voltage-force conversion coefficients. A fault signal is generated upon its departure from a predetermined nominal tolerance band. The algorithm is implemented using automatically generated and deployed machine code on an electronics prototyping platform, featuring an economically feasible 8-bit microcontroller unit (MCU). The validation experiments demonstrate the viability of the proposed system to detect sudden or gradual mechanical changes in real-time, while the functionality on low-cost miniaturized hardware suggests a strong potential for mass-production and structural integration. The modest computing power of the microcontroller and automated code generation designates the proposed system only for very flexible structures, with a first dominant resonant frequency under 4 Hz; however, a code-optimized version certainly allows much stiffer structures or more complicated models on the same hardware.

Predicting the variability of natural frequencies and its causes by Second-Order Blind Identification

2018 ◽  
Vol 18 (2) ◽  
pp. 486-507 ◽  
Author(s):  
Carlo Rainieri ◽  
Filipe Magalhaes ◽  
Danilo Gargaro ◽  
Giovanni Fabbrocino ◽  
Alvaro Cunha
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Second Order ◽  
Parameter Estimates ◽  
Blind Identification ◽  
Modal Parameter ◽  
Civil Structures ◽  
Structural Health ◽  
Operational Variables

Structural aging, degradation phenomena, and damage due to hazardous events are common causes of failure in civil structures and infrastructures. The increasing need of extending the structure lifespan for sustainability and economic reasons motivated the rapid development of remote, fully automated structural health monitoring systems. Different approaches have been developed for damage detection based on the incoming data. Modal-based damage detection is probably one of the most popular procedures for structural health monitoring of civil structures, also thanks to the development of robust automated operational modal analysis algorithms in the last decade. However, the sensitivity of modal parameter estimates and the associated damage features to environmental and operational factors represents a significant drawback to the extensive application of this technology. Thus, effective damage detection cannot skip the preliminary compensation of the effect of those variables on modal properties. Different approaches to compensate the environmental influence on modal property estimates are reported in the literature. In this article, the use of Second-Order Blind Identification is proposed. It is applied to a number of case studies in order to validate its effectiveness in the presence of one or more environmental or operational variables. Results demonstrate that it can model the variability of natural frequency estimates in operational conditions and, above all, it can give a fundamental insight in determining the causes of such variability.

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