SSA-based stochastic subspace identification of structures from output-only vibration measurements

Loh, Chin-Hsiung,Liu, Yi-Cheng,Ni, Yi-Qing Techno-Press 2012 Smart Structures and Systems, An International Jou Vol.10 No.4

In this study an output-only system identification technique for civil structures under ambient vibrations is carried out, mainly focused on using the Stochastic Subspace Identification (SSI) based algorithms. A newly developed signal processing technique, called Singular Spectrum Analysis (SSA), capable to smooth a noisy signal, is adopted for preprocessing the measurement data. An SSA-based SSI algorithm with the aim of finding accurate and true modal parameters is developed through stabilization diagram which is constructed by plotting the identified system poles with increasing the size of data matrix. First, comparative study between different approaches, with and without using SSA to pre-process the data, on determining the model order and selecting the true system poles is examined in this study through numerical simulation. Finally, application of the proposed system identification task to the real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures, using SSA-based SSI algorithm is carried out to extract the dynamic characteristics of the tower from output-only measurements.

Application of recursive SSA as data pre-processing filter for stochastic subspace identification

Loh, Chin-Hsiung,Liu, Yi-Cheng Techno-Press 2013 Smart Structures and Systems, An International Jou Vol.11 No.1

The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.

Vibration-based identification of rotating blades using Rodrigues’ rotation formula from a 3-D measurement

Chin-Hsiung Loh,Yu-Ting Huang,Wan-Ying Hsiung,Yuan-Sen Yang,Kenneth J. Loh 한국풍공학회 2015 Wind and Structures, An International Journal (WAS Vol.21 No.6

In this study, the geometrical setup of a turbine blade is tracked. A research-scale rotating turbine blade system is setup with a single 3-axes accelerometer mounted on one of the blades. The turbine system is rotated by a controlled motor. The tilt and rolling angles of the rotating blade under operating conditions are determined from the response measurement of the single accelerometer. Data acquisition is achieved using a prototype wireless sensing system. First, the Rodrigues' rotation formula and an optimization algorithm are used to track the blade rolling angle and pitching angles of the turbine blade system. In addition, the blade flapwise natural frequency is identified by removing the rotation-related response induced by gravity and centrifuge force. To verify the result of calculations, a covariance-driven stochastic subspace identification method (SSI-COV) is applied to the vibration measurements of the blades to determine the system natural frequencies. It is thus proven that by using a single sensor and through a series of coordinate transformations and the Rodrigues' rotation formula, the geometrical setup of the blade can be tracked and the blade flapwise vibration frequency can be determined successfully.

Researches Related to Seismic Hazard Mitigation in Taiwan

Loh Chin Hsiung,Yeh Chin Hsun 한국지진공학회 1998 한국지진공학회논문집 Vol.2 No.3

In view of the rapid development of economics and technology, perilous meteorological and geological conditions often cause natural disasters and result in severe loss of lives and properties in Taiwan. To promote multi-hazard mitigation strategies in an integrated a, pp.oach, the National Science Council established a National Science and Technology Program for Disaster Mitigation in January 1998. This program emphasizes on the implementation of research results in the National Disaster Management System. This paper describes the earthquake loss estimation methodology that is currently developed in Taiwan. Topics of potential earth science hazards (PESH) and building vulnerability analysis are described in detail.

Vibration-based identification of rotating blades using Rodrigues' rotation formula from a 3-D measurement

Loh, Chin-Hsiung,Huang, Yu-Ting,Hsiung, Wan-Ying,Yang, Yuan-Sen,Loh, Kenneth J. Techno-Press 2015 Wind and Structures, An International Journal (WAS Vol.21 No.6

In this study, the geometrical setup of a turbine blade is tracked. A research-scale rotating turbine blade system is setup with a single 3-axes accelerometer mounted on one of the blades. The turbine system is rotated by a controlled motor. The tilt and rolling angles of the rotating blade under operating conditions are determined from the response measurement of the single accelerometer. Data acquisition is achieved using a prototype wireless sensing system. First, the Rodrigues' rotation formula and an optimization algorithm are used to track the blade rolling angle and pitching angles of the turbine blade system. In addition, the blade flapwise natural frequency is identified by removing the rotation-related response induced by gravity and centrifuge force. To verify the result of calculations, a covariance-driven stochastic subspace identification method (SSI-COV) is applied to the vibration measurements of the blades to determine the system natural frequencies. It is thus proven that by using a single sensor and through a series of coordinate transformations and the Rodrigues' rotation formula, the geometrical setup of the blade can be tracked and the blade flapwise vibration frequency can be determined successfully.

Application of recursive SSA as data pre-processing filter for stochastic subspace identification

Chin-Hsiung Loh,Yi-Cheng Liu 국제구조공학회 2013 Smart Structures and Systems, An International Jou Vol.11 No.1

The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified 1st mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of 2nd mode slope ratio could be used as another feature to indicate imminent pier settlement.

SSA-based stochastic subspace identification of structures from output-only vibration measurements

Chin-Hsiung Loh,Yi-Cheng Liu,Yi-Qing Ni 국제구조공학회 2012 Smart Structures and Systems, An International Jou Vol.10 No.4

In this study an output-only system identification technique for civil structures under ambient vibrations is carried out, mainly focused on using the Stochastic Subspace Identification (SSI) based algorithms. A newly developed signal processing technique, called Singular Spectrum Analysis (SSA), capable to smooth a noisy signal, is adopted for preprocessing the measurement data. An SSA-based SSI algorithm with the aim of finding accurate and true modal parameters is developed through stabilization diagram which is constructed by plotting the identified system poles with increasing the size of data matrix. First, comparative study between different approaches, with and without using SSA to pre-process the data, on determining the model order and selecting the true system poles is examined in this study through numerical simulation. Finally, application of the proposed system identification task to the real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures, using SSA-based SSI algorithm is carried out to extract the dynamic characteristics of the tower from output-only measurements.

Real-time structural damage detection using wireless sensing and monitoring system

Lu, Kung-Chun,Loh, Chin-Hsiung,Yang, Yuan-Sen,Lynch, Jerome P.,Law, K.H. Techno-Press 2008 Smart Structures and Systems, An International Jou Vol.4 No.6

A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

Application of subspace identification on the recorded seismic response data of Pacoima Dam

Yu, I-No,Huang, Shieh-Kung,Loh, Kenneth J.,Loh, Chin-Hsiung Techno-Press 2019 Structural monitoring and maintenance Vol.6 No.4

Two seismic response data from the CSMIP strong motion instrumentation of Pacoima dam are selected: San Fernando earthquake (Jan 13, 2001; ML=4.3) and Newhall earthquake (Sept. 1, 2011; ML=4.2), for the identification of the dam system. To consider the spatially nonuniform input ground motion along the dam abutment, the subspace identification technique with multiple-input and multiple-output is used to extract the dynamic behavior of the dam-reservoir interaction system. It is observed that the dam-reservoir interaction is significant from the identification of San Fernando earthquake data. The influence of added mass (from the reservoir) during strong ground motion will create a tuned-mass damper phenomenon on the dam body. The fundamental frequency of the dam will be tuned to two different frequencies but with the same mode shapes. As for the small earthquake event, the dam-reservoir interaction is insignificant.

Damage evaluation of seismic response of structure through time-frequency analysis technique

Chen, Wen-Hui,Hseuh, Wen,Loh, Kenneth J.,Loh, Chin-Hsiung Techno-Press 2022 Structural monitoring and maintenance Vol.9 No.2

Structural health monitoring (SHM) has been related to damage identification with either operational loads or other environmental loading playing a significant complimentary role in terms of structural safety. In this study, a non-parametric method of time frequency analysis on the measurement is used to address the time-frequency representation for modal parameter estimation and system damage identification of structure. The method employs the wavelet decomposition of dynamic data by using the modified complex Morlet wavelet with variable central frequency (MCMW+VCF). Through detail discussion on the selection of model parameter in wavelet analysis, the method is applied to study the dynamic response of both steel structure and reinforced concrete frame under white noise excitation as well as earthquake excitation from shaking table test. Application of the method to building earthquake response measurement is also examined. It is shown that by using the spectrogram generated from MCMW+VCF method, with suitable selected model parameter, one can clearly identify the time-varying modal frequency of the reinforced concrete structure under earthquake excitation. Discussions on the advantages and disadvantages of the method through field experiments are also presented.