A Development of Real-time Vibration Monitoring and Analysis System Linked to the Integrated Management System of Ministry of Public Safety and Security

임지훈,; 정진우,; 문대중,; 최동호,

doi:10.11112/jksmi.2016.20.3.130

Journal of the Korea institute for structural maintenance and i

2016

DOI: 10.11112/jksmi.2016.20.3.130

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A Development of Real-time Vibration Monitoring and Analysis System Linked to the Integrated Management System of Ministry of Public Safety and Security

임지훈 임지훈¹,

정진우 정진우²,

문대중 문대중³

et al.

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2020

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Selection of the Number and Location of Monitoring Sensors using Artificial Neural Network based on Building Structure-System Identification

Kim¹

2020

jcoseik

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In this study, a method for selection of the location and number of monitoring sensors in a building structure using artificial neural networks is proposed. The acceleration-history values obtained from the installed accelerometers are defined as the input values, and the mass and stiffness values of each story in a building structure are defined as the output values. To select the installation location and number of accelerometers, several installation scenarios are assumed, artificial neural networks are obtained, and the prediction performance is compared. The installation location and number of sensors are selected based on the prediction accuracy obtained in this study. The proposed method is verified by applying it to 6-and 10-story structure examples.

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Selection of the Number and Location of Monitoring Sensors using Artificial Neural Network based on Building Structure-System Identification

Kim¹

2020

jcoseik

View full text Add to dashboard Cite

show abstract

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A Development of Real-time Vibration Monitoring and Analysis System Linked to the Integrated Management System of Ministry of Public Safety and Security

Cited by 1 publication

References 7 publications

Selection of the Number and Location of Monitoring Sensors using Artificial Neural Network based on Building Structure-System Identification

Selection of the Number and Location of Monitoring Sensors using Artificial Neural Network based on Building Structure-System Identification

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