scholarly journals A Study on Instantaneous Time-Frequency Methods for Damage Detection of Nonlinear Moment-Resisting Frames

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Ehsan Darvishan ◽  
Gholamreza Ghodrati Amiri ◽  
Pedram Ghaderi
Keyword(s):  
Damage Detection ◽  
Structural Characteristics ◽  
Probabilistic Approach ◽  
Energy Operator ◽  
Seismic Excitation ◽  
Moment Frames ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Nonlinear Hysteresis ◽  
Ground Motion Records

Most of the civil structures exhibit nonlinear hysteresis behavior during earthquakes. However, detection of damage in these structures is a challenging issue due to successive change in structural characteristics during a seismic excitation. The current paper presents a promising approach for damage detection of nonlinear moment frames. First, several instantaneous time-frequency methods including Hilbert-Huang transform, direct quadrature, Teager energy operator, and higher-order energy operator are investigated as signal processing tools and the most appropriate method is selected using an outlier analysis. Next, a procedure is proposed based on time-frequency analysis in conjunction with clustering to find damage extension in moment frames under a seismic excitation using frequency, amplitude, and energy damage measures. A probabilistic approach is implemented to investigate capability of the procedure for different ground motion records using incremental dynamic analysis. Results show that frequency is not an appropriate feature to detect damage in nonlinear structures.

Rotor Local Rubbing Fault Feature Analysis Based on Teager-Huang Transform

2014 ◽  
Vol 989-994 ◽  
pp. 3244-3247 ◽  
Author(s):  
Shang Kun Liu ◽  
Gui Ji Tang ◽  
Bin Pang
Keyword(s):  
Energy Operator ◽  
Vibration Signal ◽  
Analysis Method ◽  
Test Rig ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Teager Energy Operator ◽  
Mode Function ◽  
Mode Decomposition ◽  
Teager Energy

An analysis method based on Teager-Huang transform for rotor local rubbing fault diagnosis is introduced. Firstly, the original vibration signal is decomposed into some Intrinsic Mode Function (IMF) components by using Empirical Mode Decomposition (EMD) approach, secondly, Teager energy operator is applied to estimate the instantaneous amplitude and instantaneous frequency of each IMF component, so the time-frequency distribution of the signal is obtained. The rotor local rubbing fault is simulated on a rotor test rig. The analysis results show that this method compared with Hilbert-Huang transform (HHT) can track the occurrence of rotor local rubbing fault better and can extract the characteristics of rotor local rubbing fault effectively. It provides a reliable method for timely and accurate diagnostic to the rotor local rubbing fault.

scholarly journals Dynamic deformation monitoring of an offshore platform structure with accelerometers

2021 ◽  
Author(s):  
Wen Li ◽  
Craig Hancock ◽  
Yusong Yang ◽  
Jian Wang ◽  
Xiaolin Meng
Keyword(s):  
High Frequency ◽  
Structural Characteristics ◽  
Three Dimensional ◽  
Deformation Monitoring ◽  
Offshore Platforms ◽  
Dynamic Displacement ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Average Value ◽  
The North

AbstractIn this paper, structural characteristics are evaluated by displacement and frequency indicators that indicate the real-time health status of offshore platforms. This paper uses an accelerometer to collect the dynamic response of the platform in the event of a ship collision. The main contributions of this research are reflected in three aspects. Firstly, based on Empirical Mode Decomposition (EMD) multiscale decomposition, the noise range is determined according to the scale and the average value of the standardized accumulation mode, and the original acceleration sequence is denoised. Secondly, two impact tests were carried out to understand the platform's structural characteristics under an external load. Combined with the FFT algorithm and Hilbert Huang transform, the three-dimensional information of the time, frequency, and energy is analyzed. Finally, a method of high-frequency dynamic displacement reconstruction is proposed. According to the extracted vibration frequency information, the parameters for the filter are reasonably set, and the denoised acceleration time sequence is processed with bandpass filtering and quadratic integration to obtain the high-frequency dynamic displacement of the structure. The results show that the high-frequency dynamic displacement of the accelerometer reconstruction is 1.5 mm. Two collision event frequencies, 1.477 Hz and 1.483 Hz, were successfully extracted from the north direction.

scholarly journals Simulation of non-stationary stochastic ground motions based on recent Italian earthquakes

2021 ◽  
Author(s):  
Fabio Sabetta ◽  
Antonio Pugliese ◽  
Gabriele Fiorentino ◽  
Giovanni Lanzano ◽  
Lucia Luzi
Keyword(s):  
Ground Motion ◽  
Ground Motions ◽  
Strong Motion ◽  
Stochastic Simulations ◽  
Model Parameters ◽  
Motion Model ◽  
Arias Intensity ◽  
Time Frequency ◽  
Ground Motion Model ◽  
Ground Motion Records

AbstractThis work presents an up-to-date model for the simulation of non-stationary ground motions, including several novelties compared to the original study of Sabetta and Pugliese (Bull Seism Soc Am 86:337–352, 1996). The selection of the input motion in the framework of earthquake engineering has become progressively more important with the growing use of nonlinear dynamic analyses. Regardless of the increasing availability of large strong motion databases, ground motion records are not always available for a given earthquake scenario and site condition, requiring the adoption of simulated time series. Among the different techniques for the generation of ground motion records, we focused on the methods based on stochastic simulations, considering the time- frequency decomposition of the seismic ground motion. We updated the non-stationary stochastic model initially developed in Sabetta and Pugliese (Bull Seism Soc Am 86:337–352, 1996) and later modified by Pousse et al. (Bull Seism Soc Am 96:2103–2117, 2006) and Laurendeau et al. (Nonstationary stochastic simulation of strong ground-motion time histories: application to the Japanese database. 15 WCEE Lisbon, 2012). The model is based on the S-transform that implicitly considers both the amplitude and frequency modulation. The four model parameters required for the simulation are: Arias intensity, significant duration, central frequency, and frequency bandwidth. They were obtained from an empirical ground motion model calibrated using the accelerometric records included in the updated Italian strong-motion database ITACA. The simulated accelerograms show a good match with the ground motion model prediction of several amplitude and frequency measures, such as Arias intensity, peak acceleration, peak velocity, Fourier spectra, and response spectra.

Time–frequency and time–scale analyses for structural health monitoring

2006 ◽  
Vol 365 (1851) ◽  
pp. 449-477 ◽  
Author(s):  
Wiesław J Staszewski ◽  
Amy N Robertson
Keyword(s):  
Signal Processing ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Time Scale ◽  
Time Frequency ◽  
Structural Health ◽  
Variant Analysis

Signal processing is one of the most important elements of structural health monitoring. This paper documents applications of time-variant analysis for damage detection. Two main approaches, the time–frequency and the time–scale analyses are discussed. The discussion is illustrated by application examples relevant to damage detection.

Characterization of Cavitation During Pump Operation Based on Hilbert-Huang Transform

2018 ◽  
Author(s):  
Hui Sun ◽  
Shouqi Yuan ◽  
Yin Luo ◽  
Bo Gong
Keyword(s):  
Centrifugal Pump ◽  
Longitudinal Vibration ◽  
Process Time ◽  
Current Signal ◽  
Vibration Signals ◽  
Pump Operation ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Cavitation Process ◽  
Non Stationary Signal

Cavitation has negative influence on pump operation. In order to detect incipient cavitation effectively, experimental investigation was conducted to through acquisition of current and vibration signals during cavitation process. In this research, a centrifugal pump was modeled for research. The data was analyzed by HHT method. The results show that Torque oscillation resulted from unsteady flow during cavitation process could result in energy variation. Variation regulation of RMS of IMF in current signal is similar to that in axial vibration signal. But RMS of IMF in current signal is more sensitive to cavitation generation. It could be regarded as the indicator of incipient cavitation. RMS variation of IMF in base, radial, longitudinal vibration signals experiences an obvious increasing when cavitation gets severe. Such single variation regulation could be selected as the indicator of cavitation stage recognition. Hilbert-Huang transform is suitable for transient and non-stationary signal process. Time-frequency characteristics could be extracted from results of HHT process to reveal pump operation condition. The contents of current work could provide valuable references for further research on centrifugal pump operation detection.

Damage detection in composite structures using Lamb wave analysis and time-frequency approach

2011 ◽  
Author(s):  
Yingtao Liu ◽  
Masoud Yekani Fard ◽  
Seung B. Kim ◽  
Aditi Chattopadhyay ◽  
Derek Doyle
Keyword(s):  
Damage Detection ◽  
Lamb Wave ◽  
Composite Structures ◽  
Wave Analysis ◽  
Time Frequency

Vibration Fatigue Test Based on Fiber Bragg Grating Sensors and HHT

2013 ◽  
Vol 328 ◽  
pp. 193-197
Author(s):  
Si Jin Xin ◽  
Zhen Tong
Keyword(s):  
Titanium Alloy ◽  
Fiber Bragg Grating ◽  
Fatigue Test ◽  
Alloy Sheet ◽  
Bragg Grating ◽  
Metal Fatigue ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Vibration Fatigue ◽  
Fbg Sensors

The metal fatigue is an important factor to cause an accident in machine operation, so metal fatigue test is a significant procedure in manufacturing. Fiber Bragg Grating (FBG), as an innovative sensor, has been applied to the measurement of various rotating machines. In this paper, the time-frequency analysis is used to detect the fatigue feature of a titanium alloy measured by FBG sensors. Furthermore, the Hilbert-Huang transform (HHT) is more effective to observe the fatigue limit of the titanium alloy sheet, compared to the Wavelet transform (WT).

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