scholarly journals Sequential Monte Carlo based parameter estimation for structural health monitoring with an Intel Xeon Phi optimized ultrasound kernel

2019 ◽  
Author(s):  
William C. Schneck ◽  
Heather Reed ◽  
Elizabeth D. Gregory ◽  
Cara A. C. Leckey
Keyword(s):  
Monte Carlo ◽  
Parameter Estimation ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Sequential Monte Carlo ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Structural Health ◽  
Intel Xeon

scholarly journals Parameter identification for structural health monitoring based on Monte Carlo method and likelihood estimate

2018 ◽  
Vol 14 (7) ◽  
pp. 155014771878688 ◽  
Author(s):  
Songtao Xue ◽  
Bo Wen ◽  
Rui Huang ◽  
Liyuan Huang ◽  
Tadanobu Sato ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Structural Health Monitoring ◽  
Parameter Identification ◽  
Health Monitoring ◽  
Gaussian Noise ◽  
Damage Identification ◽  
Structural Parameters ◽  
Likelihood Estimate ◽  
Structural Health

Structural parameters are the most important factors reflecting structural performance and conditions. As a result, their identification becomes the most essential aspect of the structural assessment and damage identification for the structural health monitoring. In this article, a structural parameter identification method based on Monte Carlo method and likelihood estimate is proposed. With which, parameters such as stiffness and damping are identified and studied. Identification effects subjected to three different conditions with no noise, with Gaussian noise, and with non-Gaussian noise are studied and compared. Considering the existence of damage, damage identification is also realized by the identification of the structural parameters. Both simulations and experiments are conducted to verify the proposed method. Results show that structural parameters, as well as the damages, can be well identified. Moreover, the proposed method is much robust to the noises. The proposed method may be prospective for the application of real structural health monitoring.

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.

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