Research on Pedestal Looseness Faults of Rotating System Based on Wavelet Analysis

2007 ◽  
Author(s):  
Zhaohui Ren ◽  
Hui Ma ◽  
Naihui Song ◽  
Feng Wen ◽  
Bang Chun Wen
Keyword(s):  
Critical Speed ◽  
Low Frequency ◽  
Vertical Direction ◽  
Elastic Stiffness ◽  
Nonlinear Phenomena ◽  
Test Rig ◽  
Rotating System ◽  
Vibration Signals ◽  
Frequency Components ◽  
Set Up

A model test rig of single-span rotor system is set up. By loosing tap bolts at one side of bearing housing to weaken elastic stiffness of supporting structure, the pedestal looseness faults existing in rotating machinery are simulated. The collected vibration signals with looseness faults at vertical direction are analyzed by the 3D waterfall spectra, wavelet scalogram and trajectory. The analytical results show that the chaotic low frequency components occur near the first critical speed and the complicated nonlinear phenomena appear, such as quasiperiodic motions and bifurcations etc. When the rotational speed exceeds double critical speed, the low frequency components tend towards stability.

Research on Coupling Faults With Oil-Film Instability and Bearing Rub-Impact Based on Reassigned Wavelet Scalogram

2007 ◽  
Author(s):  
Xiaopeng Li ◽  
Hui Ma ◽  
Guiqiu Song ◽  
Bangchun Wen
Keyword(s):  
Low Frequency ◽  
Decisive Role ◽  
Frequency Resolution ◽  
Vibration Signals ◽  
Oil Film ◽  
Rotor Systems ◽  
Time Frequency ◽  
Coupling Faults ◽  
Film Instability ◽  
Frequency Components

An experiment rig was set up to simulate coupling faults with oil-film instability and local rub-impact. The collected vibration signals were roughly analyzed by 3-D waterfall spectra. In complicated frequency components domain, the vibration signals were analyzed with wavelet scalogram and reassigned wavelet scalogram. Results show that reassigned wavelet scalogram has higher time-frequency resolution than wavelet scalogram and can well identify such close low-frequency components. The analysis results also indicated rub-impact faults induced by oil-film instability can produce some low-frequency components with small amplitude and oil whip can produce half frequency component; rub-impact with a common extent exerts a light influence on rotor systems and nonlinear oil-film force plays a decisive role in rotor systems.

An Analytical and Experimental Study of Automobile Dynamics With Random Roadway Inputs

1977 ◽  
Vol 99 (4) ◽  
pp. 284-292 ◽  
Author(s):  
A. J. Healey ◽  
E. Nathman ◽  
C. C. Smith
Keyword(s):  
Experimental Study ◽  
Degrees Of Freedom ◽  
Low Frequency ◽  
Vertical Direction ◽  
Degree Of Freedom ◽  
Vehicle Body ◽  
Acceleration Response ◽  
Wide Range ◽  
Frequency Components ◽  
The Common

This paper presents the results of an analytical and experimental study of ride vibrations in an automobile over roads of various degrees of roughness. Roadway roughness inputs were measured. Three different linear mathematical models were employed to predict the acceleration response of the vehicle body. The models used included two, four, and seven degrees of freedom, primarily for vertical direction motion. The results show that the prime source of errors in predicting responses of this type lies in the common assumptions made for roadway roughness spectra. With adequate description of the roadway inputs, the results showed that the seven degree of freedom model accurately predicted the low frequency response (up to 10 Hz). Using the seven degree of freedom model, predicted accelerations compare well with measured data for a wide range of roadways in the low frequency range. Higher frequency components in the measured acceleration response are significant and are illustrated here.

scholarly journals Fault Detection Enhancement in Rolling Element Bearings via Peak-Based Multiscale Decomposition and Envelope Demodulation

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Hua-Qing Wang ◽  
Wei Hou ◽  
Gang Tang ◽  
Hong-Fang Yuan ◽  
Qing-Liang Zhao ◽  
...  
Keyword(s):  
Fault Detection ◽  
Low Frequency ◽  
Frequency Noise ◽  
Rolling Element Bearings ◽  
Wavelet Domain ◽  
Vibration Signals ◽  
Multiscale Decomposition ◽  
Rolling Element ◽  
Frequency Components ◽  
Noise Threshold

Vibration signals of rolling element bearings faults are usually immersed in background noise, which makes it difficult to detect the faults. Wavelet-based methods being used commonly can reduce some types of noise, but there is still plenty of room for improvement due to the insufficient sparseness of vibration signals in wavelet domain. In this work, in order to eliminate noise and enhance the weak fault detection, a new kind of peak-based approach combined with multiscale decomposition and envelope demodulation is developed. First, to preserve effective middle-low frequency signals while making high frequency noise more significant, a peak-based piecewise recombination is utilized to convert middle frequency components into low frequency ones. The newly generated signal becomes so smoother that it will have a sparser representation in wavelet domain. Then a noise threshold is applied after wavelet multiscale decomposition, followed by inverse wavelet transform and backward peak-based piecewise transform. Finally, the amplitude of fault characteristic frequency is enhanced by means of envelope demodulation. The effectiveness of the proposed method is validated by rolling bearings faults experiments. Compared with traditional wavelet-based analysis, experimental results show that fault features can be enhanced significantly and detected easily by the proposed method.

Characteristics Identification of Overlapping Vibration Signals on Mallat

2010 ◽  
Vol 97-101 ◽  
pp. 4375-4378
Author(s):  
Huer Sun ◽  
Zhao Jian Yang ◽  
Qun Long Liang ◽  
Xin Yu Pang
Keyword(s):  
Vibration Source ◽  
Test Rig ◽  
Vibration Signals ◽  
Reconstructed Signal ◽  
Rotor Bearing ◽  
Set Up ◽  
Source Signals ◽  
Bearing System

In rotor-bearing system running, vibration signals measured were an kind of Multi-vibration source signals which is overlapping each other. These overlapping signals were difficult to be separated by the ordinary methods, which is adverse to precisely estimate faults of rotor-bearing system in running. In this paper, a test rig was set up to simulate mis-alignment faults; collected vibration signals of bearings were decomposed and reconstructed by algorithm of Mallat. Reconstructed signal can reflect detail character s of bearings vibration. And vibration signals characteristics of fault rotor were effectively identified.

Simulations of high-resolution images of amorphous silicon films

1986 ◽  
Vol 44 ◽  
pp. 544-545
Author(s):  
G. Y. Fan ◽  
J. M. Cowley
Keyword(s):  
Electron Microscope ◽  
High Frequency ◽  
Fourier Transformation ◽  
Amorphous Materials ◽  
Low Frequency ◽  
Chromatic Aberration ◽  
Structure Information ◽  
Frequency Components ◽  
High Resolution Images ◽  
Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

ANALYSIS OF STAND RESEARCH RESULTS OF AXIAL DYNAMIC FORCE IN DRILLING BY THREE ROLLER CONE BIT

2019 ◽  
pp. 81-93
Author(s):  
В. М. Мойсишин ◽  
M. V. Lyskanych ◽  
R. A. Zhovniruk ◽  
Ye. P. Majkovych
Keyword(s):  
Low Frequency ◽  
Maximum Energy ◽  
Dynamic Force ◽  
Low Frequency Oscillation ◽  
Drilling Tool ◽  
Rock Destruction ◽  
Frequency Components ◽  
Harmonic Components ◽  
Experimental Values ◽  
Harmful Effects

The purpose of the proposed article is to establish the causes of oscillations of drilling tool and the basic laws of the distribution of the total energy of the process of changing the axial dynamic force over frequencies of spectrum. Variable factors during experiments on the classical plan were the rigidity of drilling tool and the hardness of the rock. According to the results of research, the main power of the process of change of axial dynamic force during drilling of three roller cone bits is in the frequency range 0-32 Hz in which three harmonic frequency components are allocated which correspond to the theoretical values of low-frequency and gear oscillations of the chisel and proper oscillations of the bit. The experimental values of frequencies of harmonic components of energy and normalized spectrum as well as the magnitude of the dispersion of the axial dynamic force and its normalized values at these frequencies are presented. It has been found that with decreasing rigidity of the drilling tool maximum energy of axial dynamic force moves from the low-frequency oscillation region to the tooth oscillation area, intensifying the process of rock destruction and, at the same time, protecting the tool from the harmful effects of the vibrations of the bit. Reducing the rigidity of the drilling tool protects the bit from the harmful effects of the vibrations generated by the stand. The energy reductions in these fluctuations range from 47 to 77%.

A Novel Adaptive PET/CT Image Fusion Algorithm

2019 ◽  
Vol 14 (7) ◽  
pp. 658-666
Author(s):  
Kai-jian Xia ◽  
Jian-qiang Wang ◽  
Jian Cai
Keyword(s):  
Lung Cancer ◽  
Image Fusion ◽  
High Frequency ◽  
Malignant Tumors ◽  
Low Frequency ◽  
Combination Method ◽  
Ct Image ◽  
Fusion Algorithm ◽  
Pet Ct ◽  
Frequency Components

Background: Lung cancer is one of the common malignant tumors. The successful diagnosis of lung cancer depends on the accuracy of the image obtained from medical imaging modalities. Objective: The fusion of CT and PET is combining the complimentary and redundant information both images and can increase the ease of perception. Since the existing fusion method sare not perfect enough, and the fusion effect remains to be improved, the paper proposes a novel method called adaptive PET/CT fusion for lung cancer in Piella framework. Methods: This algorithm firstly adopted the DTCWT to decompose the PET and CT images into different components, respectively. In accordance with the characteristics of low-frequency and high-frequency components and the features of PET and CT image, 5 membership functions are used as a combination method so as to determine the fusion weight for low-frequency components. In order to fuse different high-frequency components, we select the energy difference of decomposition coefficients as the match measure, and the local energy as the activity measure; in addition, the decision factor is also determined for the high-frequency components. Results: The proposed method is compared with some of the pixel-level spatial domain image fusion algorithms. The experimental results show that our proposed algorithm is feasible and effective. Conclusion: Our proposed algorithm can better retain and protrude the lesions edge information and the texture information of lesions in the image fusion.

Underwater Image Enhancement Method Combining color and Luminance

2020 ◽  
Vol 13 ◽  
Author(s):  
ZHAO Baiting ◽  
WANG Feng ◽  
JIA Xiaofen ◽  
GUO Yongcun ◽  
WANG Chengjun
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Low Frequency ◽  
Brightness Enhancement ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method ◽  
Frequency Components ◽  
Image Contour ◽  
Objective Indicators

Background:: Aiming at the problems of color distortion, low clarity and poor visibility of underwater image caused by complex underwater environment, a wavelet fusion method UIPWF for underwater image enhancement is proposed. Methods:: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels, and balance the color of R, G and B channels by affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour. Results:: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information. Conclusion:: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

Despeckling of Sar Images Using Shrinkage of Two-Dimensional Discrete Orthonormal S-Transform

2020 ◽  
pp. 2150023
Author(s):  
Priya R. Kamath ◽  
Kedarnath Senapati ◽  
P. Jidesh
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Relevant Information ◽  
Detection Algorithm ◽  
Two Dimensional ◽  
Sar Images ◽  
S Transform ◽  
Processing Step ◽  
Frequency Components ◽  
Shock Filter

Speckles are inherent to SAR. They hide and undermine several relevant information contained in the SAR images. In this paper, a despeckling algorithm using the shrinkage of two-dimensional discrete orthonormal S-transform (2D-DOST) coefficients in the transform domain along with shock filter is proposed. Also, an attempt has been made as a post-processing step to preserve the edges and other details while removing the speckle. The proposed strategy involves decomposing the SAR image into low and high-frequency components and processing them separately. A shock filter is used to smooth out the small variations in low-frequency components, and the high-frequency components are treated with a shrinkage of 2D-DOST coefficients. The edges, for enhancement, are detected using a ratio-based edge detection algorithm. The proposed method is tested, verified, and compared with some well-known models on C-band and X-band SAR images. A detailed experimental analysis is illustrated.

scholarly journals Multi-scale time-frequency domain full waveform inversion with a weighted local correlation-phase misfit function

2019 ◽  
Vol 16 (6) ◽  
pp. 1017-1031 ◽  
Author(s):  
Yong Hu ◽  
Liguo Han ◽  
Rushan Wu ◽  
Yongzhong Xu
Keyword(s):  
Frequency Domain ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Local Correlation ◽  
Time Frequency ◽  
Model Dependence ◽  
Full Waveform ◽  
Frequency Components

Abstract Full Waveform Inversion (FWI) is based on the least squares algorithm to minimize the difference between the synthetic and observed data, which is a promising technique for high-resolution velocity inversion. However, the FWI method is characterized by strong model dependence, because the ultra-low-frequency components in the field seismic data are usually not available. In this work, to reduce the model dependence of the FWI method, we introduce a Weighted Local Correlation-phase based FWI method (WLCFWI), which emphasizes the correlation phase between the synthetic and observed data in the time-frequency domain. The local correlation-phase misfit function combines the advantages of phase and normalized correlation function, and has an enormous potential for reducing the model dependence and improving FWI results. Besides, in the correlation-phase misfit function, the amplitude information is treated as a weighting factor, which emphasizes the phase similarity between synthetic and observed data. Numerical examples and the analysis of the misfit function show that the WLCFWI method has a strong ability to reduce model dependence, even if the seismic data are devoid of low-frequency components and contain strong Gaussian noise.

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