A dynamic strain prediction method for malfunction of sensors in buildings subjected to seismic loads using CWT and CNN.

ABSTRACT: Structural health monitoring (SHM) is a technique used to evaluate the safety of a structure based on the structural response. In the SHM, sensors may fail to measure the structural response, or data loss can occur during the data transmission and reception. In this regard, this paper proposes a method of predicting the strain response when a sensor installed in a structural member suffers a malfunction. To this end, a convolutional neural network (CNN) is introduced to predict the strain response. Time-history strain data for seismic loads measured in adjacent structural members are set as the input layer of the CNN, and continuous wavelet transform (CWT) results are additionally set in the input layer of the CNN to reflect the dynamic structural behavior during earthquakes in the CNN pre

SUBMITTER: Park HS 

PROVIDER: S-EPMC11568183 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature