Identifying dynamic characteristics of structures under ambient condition is very important for its heath monitoring and damage assessment. Nowadays, it has become a common industry standard to arrange the sensors to monitor the dynamic characteristics of some major structures so that preventive actions can be taken in advance. Comparing to some traditional wired/wireless sensing units, current smartphones are low-priced and equipped with a large amount of memory, state-of-the-art high-power CPU, and various wireless communication options such as Wi-Fi, Bluetooth and 4G. Moreover, smartphones can be integrated with Arduino boards which can accommodates some high performance sensors. This research aims to develop a wireless sensing unit incorporated with smartphone as the centra...[ Read more ]

Identifying dynamic characteristics of structures under ambient condition is very important for its heath monitoring and damage assessment. Nowadays, it has become a common industry standard to arrange the sensors to monitor the dynamic characteristics of some major structures so that preventive actions can be taken in advance. Comparing to some traditional wired/wireless sensing units, current smartphones are low-priced and equipped with a large amount of memory, state-of-the-art high-power CPU, and various wireless communication options such as Wi-Fi, Bluetooth and 4G. Moreover, smartphones can be integrated with Arduino boards which can accommodates some high performance sensors. This research aims to develop a wireless sensing unit incorporated with smartphone as the centralized data processing platform to track dynamic properties of a linear structure, including natural frequency, damping ratio and mode shape. The performance of both the embedded sensors in the smartphones and the external sensors working together with Arduino boards are studies. To realize time synchronization, two kinds of time systems, Network Time Protocol (NTP) and Global Position System (GPS), are applied for the embedded sensors module and external sensor module, respectively. To analyzing the acquired data, subspace identification techniques that can simultaneously process a large quantity of data and potentially extract the most information from the measurement are studied. This research first propose an input-output recursive combined subspace identification (RCSI) technique for tacking modal parameters of a time-varying structure under non-stationary earthquake excitation. The technique incorporates an orthogonal projection and an instrumental variable approach to eliminate the effect of earthquake input and measurement noise, respectively. A bi-iteration subspace tracker is then applied to extract step-by-step the structural modal parameters. Tracking modal parameters of a time-varying structure under unknown and unmeasured non-stationary input is next investigated. To speed up the data processing procedure in smartphone, a moving window combine subspace identification (MCSI) algorithm is developed in the application of smartphone. Some numerical examples and experimental tests are used to illustrate the proposed design and data processing technique. Both numerical and experimental results show that the proposed technique can track structural modal parameters under non-stationary earthquake excitation quite well.