During a revisit to modal identification in the past three decades, an overview of the major developments and issues in modal identification is motivated. A brief review on the progress from Single-Input/Single-Output (SISO), Single-Input/Multi-Output (SIMO) to Multi-Input/Multi-Output (MIMO) identification in frequency, time and spatial domain, is presented. The latest developments and issues ...

In this study, we propose a machine-learning-based approach to identify the modal parameters of output-only data for structural health monitoring (SHM) that makes full use characteristic independence responses and principle machine learning. By taking advantage independent feature each mode, unsupervised learning, turning training process neural network into separation. A self-coding is designe...

The ambient vibration measurement is a kind of output data-only dynamic testing where the traffics and winds are used as agents responsible for natural or environmental excitation. Therefore an experimental modal analysis procedure for ambient vibration testing will need to base itself on output-only data. The modal analysis involving output-only measurements present a challenge that requires t...

The conventional eigensystem realization algorithm with data correlation (ERA/DC) combines the impulse response or free of a structural system concept function to identify modal parameter system. Previous studies have shown that parameters systems subjected stationary white noise excitation can be estimated by ERA/DC from ambient without data. This is extended in this paper for output-only iden...

Sensor network technology entails the deployment of small, low-power sensor nodes that can communicate with one another. Since sensor networks can be used to monitor the condition of many types of architectural spaces, the technology has recently received significant academic and industrial attention. Amongst the potential applications, structural monitoring of large-scale civil structures is o...