Statistical damage identification method based on dynamic response sensitivity

Mao, Ling; Weng, Shun; Li, Shujin; Zhu, Hongping; Sun, Yanjing

doi:10.1177/1461348418784828

Cited by 10 publications

(7 citation statements)

References 24 publications

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“…where [f i , φ i ] and [f k i , φ k i ] mean the i-th noise-free and contaminated natural frequencies and modal shapes, respectively; σ stands for the noise pollution level [38][39][40]; and rand is a random number that ranges from −1 to 1.…”

Section: Example Studiesmentioning

confidence: 99%

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

Lei

Zhou

et al. 2021

Shock and Vibration

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The bearing of a bridge, as a critical component, is important in the force transformation of the superstructure; however, due to the service condition and repeated impact load, the bearing is prone to be damaged but difficult to detect the damage; the present research has few studies that focused on the damage detection of the structural bearing. Meanwhile, practical engineering is always surrounded by variational environmental conditions, and sometimes, the element and bearing damage both exist in the structure. Thus, these uncertain conditions all cause inaccurate damage identification results using the vibration-based damage detection method. In order to detect the damage of the structural bearing and improve the precision, firstly, the structural dynamic characteristic equation considering uncertain conditions has been deduced; then, a damage detection framework constructed by the Bayesian theory and perturbation method has been developed in this article; a numerical example of an 8-span concrete continuous beam and a practical example of I-40 steel-concrete composite bridge are utilized to validate the feasibility of the proposed method, and single type and two types of damage cases are studied. The outcomes demonstrate that the damage of structural elements and bearings can be detected with high accuracy. The proposed method is of great applicability and good potential.

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Section: Example Studiesmentioning

confidence: 99%

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

Lei

Zhou

et al. 2021

Shock and Vibration

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“…The traditional moving-load-driven methods have good interpretability, as these methods are based on the accurate vehicle–bridge interaction model [ 20 ]. These methods are suitable for controlled environmental conditions, but it is laborious and time consuming to ensure their performances due to their limited anti-noise ability [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

Moving-Principal-Component-Analysis-Based Structural Damage Detection for Highway Bridges in Operational Environments

Yuan,

Zhu,

2024

Sensors

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With the deterioration of bridge performance and ever-increasing amounts of traffic, bridge safety is becoming a concern for the engineering community. A method that can assess a bridge’s condition in real time is urgently needed. The main factors that hinder bridge condition assessment are the uncertain operational environments. A new moving principal component analysis (MPCA)-based method is developed for structural damage detection in bridges in operational environments in this paper. Two main operational environmental factors, the environmental temperature and traffic loads, are studied in the assessment process to verify the robustness and practicality of the proposed method. The numerical and experimental results show that the proposed method is effective and accurate in assessing the bridge’s condition in operational environments.

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“…An ARMA model was applied to time signal, and the first three AR components were used as the damage-sensitive feature (Nair et al, 2006). A model-based statistical SHM method was proposed by Mao et al (2018) based on dynamic response sensitivity in state-space domain. The probability of damage existence for each structural element is estimated using the statistical characteristic of the identified structural parameters.…”

Section: Introductionmentioning

confidence: 99%

A statistical and reliability approach to vibration-based health monitoring in composite structures

Nobari

Aliabadi

2023

Journal of Vibration and Control

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In this paper, a novel statistical vibration-based damage detection method is developed considering uncertainties in measured resonance frequencies. The proposed method is based on the application of resonance frequencies as the most accurate and easiest measurable vibration feature. For proof of efficiency of the proposed method, case studies were undertaken using two identical composite plates, one delaminated and the other pristine. In this respect, the frequency response functions (FRFs) were measured and used as the main input to the Resonance Detection Algorithm as the proposed method. Applying these FRFs to a Resonance Detector Function can determine the resonant frequencies and their statistical distribution. Through the statistical distributions of the corresponding resonant frequencies, their reliability of detecting damage has been obtained via the beta distribution. By observing the damage detection reliability of the two sets of corresponding resonant frequencies, it has been determined that the changes in natural frequencies are due to structural changes and not random errors through measurement.

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Statistical damage identification method based on dynamic response sensitivity

Cited by 10 publications

References 24 publications

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

Bearing Damage Detection of a Bridge under the Uncertain Conditions Based on the Bayesian Framework and Matrix Perturbation Method

Moving-Principal-Component-Analysis-Based Structural Damage Detection for Highway Bridges in Operational Environments

A statistical and reliability approach to vibration-based health monitoring in composite structures

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