Damping Estimation by 2D dr_APES and its Application to a Real Cable-Stayed Bridge

2016 ◽  
Vol 16 (05) ◽  
pp. 1550002 ◽  
Author(s):  
Dan-Hui Dan ◽  
Jiong-Xin Gong ◽  
Li-Min Sun ◽  
Wei Cheng
Keyword(s):  
Amplitude Spectrum ◽  
Flexible Structures ◽  
Three Dimensional ◽  
Dynamic Test ◽  
Vibration Signal ◽  
Damping Factor ◽  
Engineering Structures ◽  
Vibration Signals ◽  
Cable Stayed Bridge ◽  
Identification Approach

Introduced herein is a new structural damping identification approach based on a two-dimensional (2D) amplitude and phase estimation (APES) method. The original APES method is suitable for application to an undamped and complex harmonic vibration signal. Hence, it has to be modified for application to real damped vibration signals such as the vibration test signals in engineering structures. This modified approach will be named as dr_APES. It can transform one-dimensional (1D) signals in time domain into their corresponding signals in the 2D domain of frequency and damping factor. By applying this dr_APES approach, the three-dimensional (3D) amplitude spectrum, with peaks corresponding to the vibration modes, can be obtained for any given vibration signals. By accurately locating the coordinates of the peaks, modal frequencies and damping factors can be identified. Owing to the high-resolution of the location of 2D ordinates of the spectral line and the value of spectrum, the accurate location of peaks can be estimated, and therefore, the modal frequencies and damping factor can be accurately determined. This is demonstrated by a numerical case study. Moreover, by applying the proposed approach to a real onsite dynamic test on two cables in a cable-stayed bridge, the inherent damping of the two cables was identified accurately, thereby verifying the ability of proposed damping identification approach in meeting the requirement of weak damping characteristics identification in flexible structures such as naked cables.

Fault Detection of Broken Rotor Bar Using an Improved form of Hilbert–Huang Transform

2018 ◽  
Vol 17 (02) ◽  
pp. 1850012 ◽  
Author(s):  
F. Sabbaghian-Bidgoli ◽  
J. Poshtan
Keyword(s):  
Signal Processing ◽  
Fault Detection ◽  
Hilbert Transform ◽  
Wavelet Packet ◽  
Amplitude Spectrum ◽  
Vibration Signal ◽  
External Noise ◽  
Vibration Signals ◽  
Broken Rotor Bar ◽  
Hilbert Huang Transform

Signal processing is an integral part in signal-based fault diagnosis of rotary machinery. Signal processing converts the raw data into useful features to make the diagnostic operations. These features should be independent from the normal working conditions of the machine and the external noise. The extracted features should be sensitive only to faults in the machine. Therefore, applying more efficient processing techniques in order to achieve more useful features that bring faster and more accurate fault detection procedure has attracted the attention of researchers. This paper attempts to improve Hilbert–Huang transform (HHT) using wavelet packet transform (WPT) as a preprocessor instead of ensemble empirical mode decomposition (EEMD) to decompose the signal into narrow frequency bands and extract instantaneous frequency and compares the efficiency of the proposed method named “wavelet packet-based Hilbert transform (WPHT)” with the HHT in the extraction of broken rotor bar frequency components from vibration signals. These methods are tested on vibration signals of an electro-pump experimental setup. Moreover, this project applies wavelet packet de-noising to remove the noise of vibration signal before applying both methods mentioned and thereby achieves more useful features from vibration signals for the next stages of diagnosis procedure. The comparison of Hilbert transform amplitude spectrum and the values and numbers of detected instantaneous frequencies using HHT and WPHT techniques indicates the superiority of the WPHT technique to detect fault-related frequencies as an improved form of HHT.

scholarly journals Damped CAPES 2D Spectral Estimation for Real-Valued Vibration Signals

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Danhui Dan ◽  
Jiongxin Gong ◽  
Yiming Zhao
Keyword(s):  
Spectral Estimation ◽  
Amplitude Spectrum ◽  
Vibration Signal ◽  
Angular Frequency ◽  
Frequency Resolution ◽  
Spectrum Estimation ◽  
Vibration Signals ◽  
Vibration Data ◽  
Decay Factor ◽  
Sine Term

We propose a 2D representation in the frequency-decay factor plane of an arbitrary real-world vibration signal. The signal is expressed as the sum of a decayed-attenuation sine term modulated by an amplitude function and a noise residue. We extend the combined approach of Capon estimation and amplitude and phase estimation (CAPES) to damped real vibration signals (DR-CAPES). In the proposed DR-CAPES method, the high-resolution amplitude and phase are estimated simultaneously for both angular frequency and decay factor grids. The performance of the proposed approach is tested numerically with noisy vibration data. Results show that the DR-CAPES method has an excellent frequency resolution, which helps to overcome difficulties in spectrum estimation when vibration modes are very close, and a small bias, which makes it suitable for obtaining accurate amplitude spectrums. The results also indicate that the proposed method can accurately estimate the amplitude spectrum with the use of averaging and denoising processes.

Effect of Pile-Soil-Structure Interaction on the Cable-Stayed Bridge in Response to the Earthquake

2014 ◽  
Vol 539 ◽  
pp. 731-735 ◽  
Author(s):  
Yu Chen
Keyword(s):  
Finite Element ◽  
Seismic Response ◽  
Soil Structure ◽  
Response Spectrum ◽  
Three Dimensional ◽  
Soil Structure Interaction ◽  
Structure Interaction ◽  
Finite Element Software ◽  
Cable Stayed Bridge ◽  
Three Dimensional Finite Element

In this thesis, based on the design of a 140+90m span unusual single tower and single cable plane cable-stayed bridge, free vibration characteristics and seismic response are investigated; three dimensional finite element models of a single tower cable-stayed bridge with and without the pile-soil-structure interaction are established respectively by utilizing finite element software MIDAS/CIVIL, seismic response of Response spectrum and Earthquake schedule are analyzed respectively and compared. By the comparison of the data analysis, for small stiffness span cable-stayed bridge, the pile-soil-structure interaction can not be ignored with calculation and analysis of seismic response.

Experimental Study on the Continuous Type Three-Dimensional Control of the Cable-Stayed Bridge

2011 ◽  
Vol 71-78 ◽  
pp. 1933-1937
Author(s):  
Jia Yun Xu ◽  
Ji Chen ◽  
Xian Wei Qu ◽  
Wen Kai Gong
Keyword(s):  
Angular Displacement ◽  
Three Dimensional ◽  
Wind Tunnel Test ◽  
Highway Bridge ◽  
Changjiang River ◽  
Continuous Type ◽  
Torsional Response ◽  
Cable Stayed Bridge ◽  
Bridge Model ◽  
Wind Induced Vibration

This paper takes a Chinese Changjiang River highway bridge as engineering background, and a kind of continuous three-dimensional (vertical, lateral and torsion)controllers which can apply in the large span cable-stayed bridge is presented. The controllers can control vertical, lateral and torsional response of bridge wind-induced vibration at the same time. Through comparative wind tunnel test of the bridge model with and without controllers, some important conclusions are made as follows: when the continuous three-dimensional controllers are installed on the bridge model, its flutter critical wind speed increases significantly (mostly increases 33.36%); Meanwhile, there is a certain degree of reduction in its RMS values of vertical, lateral and torsional angular displacement response.

scholarly journals Learning to See the Vibration: A Neural Network for Vibration Frequency Prediction

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2530 ◽  
Author(s):  
Jiantao Liu ◽  
Xiaoxiang Yang
Keyword(s):  
Neural Network ◽  
Vibration Frequency ◽  
Frequency Estimation ◽  
Vibration Signal ◽  
Frequency Measurement ◽  
Optical Methods ◽  
Vibration Measurement ◽  
Vibration Signals ◽  
Engineering Practices ◽  
To Receive

Vibration measurement serves as the basis for various engineering practices such as natural frequency or resonant frequency estimation. As image acquisition devices become cheaper and faster, vibration measurement and frequency estimation through image sequence analysis continue to receive increasing attention. In the conventional photogrammetry and optical methods of frequency measurement, vibration signals are first extracted before implementing the vibration frequency analysis algorithm. In this work, we demonstrate that frequency prediction can be achieved using a single feed-forward convolutional neural network. The proposed method is verified using a vibration signal generator and excitation system, and the result compared with that of an industrial contact vibrometer in a real application. Our experimental results demonstrate that the proposed method can achieve acceptable prediction accuracy even in unfavorable field conditions.

scholarly journals Compressive sensing-based vibration signal reconstruction using sparsity adaptive subspace pursuit

2018 ◽  
Vol 10 (8) ◽  
pp. 168781401879087 ◽  
Author(s):  
Lin Zhou ◽  
Qianxiang Yu ◽  
Daozhi Liu ◽  
Ming Li ◽  
Shukai Chi ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
Data Storage ◽  
Wireless Sensors ◽  
Signal Reconstruction ◽  
Estimation Method ◽  
Vibration Signal ◽  
Estimation Accuracy ◽  
Offshore Structure ◽  
Vibration Signals ◽  
Reconstructed Signal

Wireless sensors produce large amounts of data in long-term online monitoring following the Shannon–Nyquist theorem, leading to a heavy burden on wireless communications and data storage. To address this problem, compressive sensing which allows wireless sensors to sample at a much lower rate than the Nyquist frequency has been considered. However, the lower rate sacrifices the integrity of the signal. Therefore, reconstruction from low-dimension measurement samples is necessary. Generally, the reconstruction needs the information of signal sparsity in advance, whereas it is usually unknown in practical applications. To address this issue, a sparsity adaptive subspace pursuit compressive sensing algorithm is deployed in this article. In order to balance the computational speed and estimation accuracy, a half-fold sparsity estimation method is proposed. To verify the effectiveness of this algorithm, several simulation tests were performed. First, the feasibility of subspace pursuit algorithm is verified using random sparse signals with five different sparsities. Second, the synthesized vibration signals for four different compression rates are reconstructed. The corresponding reconstruction correlation coefficient and root mean square error are demonstrated. The high correlation and low error result mean that the proposed algorithm can be applied in the vibration signal process. Third, implementation of the proposed approach for a practical vibration signal from an offshore structure is carried out. To reduce the effect of signal noise, the wavelet de-noising technique is used. Considering the randomness of the sampling, many reconstruction tests were carried out. Finally, to validate the reliability of the reconstructed signal, the structure modal parameters are calculated by the Eigensystem realization algorithm, and the result is only slightly different between original and reconstructed signal, which means that the proposed method can successfully save the modal information of vibration signals.

scholarly journals In-Depth Verification of a Numerical Model for an Axisymmetric RC Dome

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2152
Author(s):  
Przemysław Czumaj ◽  
Sławomir Dudziak ◽  
Zbigniew Kacprzyk
Keyword(s):  
Three Dimensional ◽  
Spatial Models ◽  
Detailed Comparison ◽  
The Finite Element Method ◽  
Robot System ◽  
Engineering Structures ◽  
Computational Analyses ◽  
Computational Systems ◽  
Good Agreement ◽  
Made In

The designers of civil engineering structures often have to face the problem of the reliability of complex computational analyses performed most often with the Finite Element Method (FEM). Any assessment of reliability of such analyses is difficult and can only be approximate. The present paper puts forward a new method of verification and validation of the structural analyses upon an illustrative example of a dome strengthened by circumferential ribs along the upper and lower edges. Four computational systems were used, namely Abaqus, Autodesk Robot, Dlubal RFEM, and FEAS. Different models were also analyzed—two-dimensional (2D) and three-dimensional (3D) ones using continuum, bar, and shell finite elements. The results of the static (with two kinds of load—self-weight and load distributed along the upper ring) and modal analyses are presented. A detailed comparison between the systems’ and models’ predictions was made. In general, the spatial models predicted a less stiff behavior of the analyzed dome than the planar models. The good agreement between different models and systems was obtained for the first natural frequency with axisymmetric eigenmodes (except from the Autodesk Robot system). The presented approach to the verification of complex shell–bar models can be effectively applied by structural designers.

scholarly journals Engine Fault Detection Approach Based on Angle Domain Signal Model

2021 ◽  
Vol 2068 (1) ◽  
pp. 012034
Author(s):  
Hai Zeng ◽  
Ning Zeng ◽  
Jin Han ◽  
Yan Ding
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Failure Detection ◽  
Vibration Signal ◽  
Bench Test ◽  
Signal Model ◽  
Vibration Signals ◽  
Engine Vibration ◽  
Detection Approach ◽  
Diagnosis Approach

Abstract Engine vibration signals include strong noise and non-stationary signals. By the time domain signal processing approach, it is hard to extract the failure features of engine vibration signals, so it is hard to identify engine failures. For improving the success rate of engine failure detection, an engine angle domain vibration signal model is established and an engine fault detection approach based on the signal model is proposed. The angle domain signal model reveals the modulation feature of the engine angular signal. The engine fault diagnosis approach based on the angle domain signal model involves equal angle sampling and envelope analysis of engine vibration signals. The engine bench test verifies the effectiveness of the engine fault diagnosis approach based on the angle domain signal model. In addition, this approach indicates a new path of engine fault diagnosis and detection.

Mine Ventilator Fault Diagnosis Based on Harmonic Wavelet Analysis

2011 ◽  
Vol 143-144 ◽  
pp. 613-617
Author(s):  
Shuang Xi Jing ◽  
Yong Chang ◽  
Jun Fa Leng
Keyword(s):  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Frequency Domain ◽  
Vibration Signal ◽  
Wavelet Function ◽  
Frequency Region ◽  
Analysis Method ◽  
Vibration Signals ◽  
Harmonic Wavelet ◽  
Frequency Components

Harmonic wavelet function, with the strict box-shaped characteristic of spectrum, has strong ability of identifying signal in frequency domain, and can extract weak components form vibration signals in frequency domain. Using harmonic wavelet analysis method, the selected frequency region and other frequency components of vibration signal of mine ventilator were decomposed into independent frequency bands without any over-lapping or leaking. Simulation and diagnosis example show that this method has good fault diagnosis effect, and the ventilator fault is diagnosed successfully.

A fractal-dimension-based envelope demodulation for rolling element bearing fault feature extraction from vibration signals

2016 ◽  
Vol 230 (18) ◽  
pp. 3194-3211 ◽  
Author(s):  
Juanjuan Shi ◽  
Ming Liang
Keyword(s):  
Feature Extraction ◽  
Fractal Dimension ◽  
Search Algorithm ◽  
Vibration Signal ◽  
Rolling Element Bearing ◽  
Vibration Signals ◽  
Bearing Fault ◽  
Bearing Condition Monitoring ◽  
Interference Frequency ◽  
Fault Feature Extraction

Vibration analysis has been extensively used as an effective tool for bearing condition monitoring. The vibration signal collected from a defective bearing is, however, a mixture of several signal components including the fault feature (i.e. fault-induced impulses), periodic interferences from other mechanical/electrical components, and background noise. The incipient impulses which excite as well as modulate the resonance frequency of the system are easily masked by compounded effects of periodic interferences and noise, making it challenging to do a reliable fault diagnosis. As such, this paper proposes an envelope demodulation method termed short time fractal dimension (STFD) transform for fault feature extraction from such vibration signal mixture. STFD transform calculation related issues are first addressed. Then, by STFD, the original signal can be quickly transformed into a STFD representation, where the envelope of fault-induced impulses becomes more pronounced whereas interferences are partly weakened due to their morphological appearance differences. It has been found that the lower the interference frequency, the less effect the interference has on STFD representations. When interference frequency keeps increasing, more effects on STFD representations will be resulted. Such effects can be reduced by the proposed kurtosis-based peak search algorithm (KPSA). Therefore, bearing fault signature is kept and interferences are further weakened in the STFD-KPSA representation. The proposed method has been favourably compared with two widely used enveloping methods, i.e. multi-morphological analysis and energy operator, in terms of extracting impulse envelopes from vibration signals obscured by multiple interferences. Its performance has also been examined using both simulated and experimental data.

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