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Author:

Ni, Ping-He (Ni, Ping-He.) | Ye, Xiao-Wei (Ye, Xiao-Wei.) | Ding, Yang (Ding, Yang.)

Indexed by:

EI Scopus SCIE

Abstract:

The interesting to assess the condition of a structure with structural health monitoring data has gained many attentions. Most of the existing methods require the measurement at the force location. This paper presents a novel output-only condition assessment method that does not require measurement at the force location. The unknown structural damage indices and input force can be identified with the stochastic gradient descent method. The dynamic acceleration response sensitivities with respect to the unknown structural damage indices and input force are derived analytically. Both unknown damage indices and unknown input force can be identified by minimizing the discrepancy between the measured and calculated vibration data. Numerical studies on a two-dimensional truss and seven-floor frame and experimental studies on a steel frame structure are presented to verify the accuracy and efficiency of the proposed method. Results demonstrate that the damage severity, location, and unknown input force can be identified. Also, the measurement at the force location is not required. Furthermore, when 20% measurement noise is considered, the identified error is less than 5%.

Keyword:

inverse problem condition assessment structural health monitoring output-only stochastic gradient descent method

Author Community:

  • [ 1 ] [Ni, Ping-He]Beijing Univ Technol, Minist Educ, Key Lab Urban Secur & Disaster Engn, Beijing, Peoples R China
  • [ 2 ] [Ye, Xiao-Wei]Zhejiang Univ, Dept Civil Engn, Hangzhou 310058, Peoples R China
  • [ 3 ] [Ding, Yang]Zhejiang Univ, Dept Civil Engn, Hangzhou 310058, Peoples R China

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Source :

STRUCTURAL CONTROL & HEALTH MONITORING

ISSN: 1545-2255

Year: 2022

Issue: 12

Volume: 29

5 . 4

JCR@2022

5 . 4 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:49

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 12

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