scholarly journals Analysis of Vibration Response Law of Multistory Building under Tunnel Blasting Loads

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Runke Huo ◽  
Shuguang Li ◽  
Zhanping Song ◽  
Yoshiaki Fujii ◽  
Shan Lei ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Particle Velocity ◽  
High Frequency ◽  
Wavelet Packet ◽  
Low Frequency ◽  
Dominant Frequency ◽  
Vibration Response ◽  
Mountainous Area ◽  
Masonry Building ◽  
Tunnel Blasting

This paper takes the Dizong tunnel engineering as its background. Combined with the on-site monitoring data, the wavelet packet program based on MATLAB was compiled to study the vibration response of the four-story masonry building in a typical southwestern mountainous area of China under the blasting load. The results showed that the maximum particle velocity increased to the 3rd floor and attenuation occurred on the 4th floor. The particle velocity in the z-direction was the largest and should be paid attention. The dominant frequency of the building showed a trend from high frequency to low frequency, the duration became short, and the acceleration decreased to the 4th floor. With the increase of the building floor, the main frequency domain of the building decreased and then gradually tended to the low-frequency domain. The high-frequency particle velocity gradually decreased, gathered to the low frequency, and developed from the dispersed multiband to the concentrated low-frequency band. The total energy value of vibration increased to the 3rd floor and then decreased to the 4th floor. The energy of the building was between 0 and 171.6 Hz. The higher the floor was, the more concentrated the energy was in the low-frequency domain.

scholarly journals An Investigation into Error Source Identification of Machine Tools Based on Time-Frequency Feature Extraction

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Dongju Chen ◽  
Shuai Zhou ◽  
Lihua Dong ◽  
Jinwei Fan
Keyword(s):  
Machine Tool ◽  
Frequency Domain ◽  
Surface Topography ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Time Frequency ◽  
Cross Correlation Analysis ◽  
Correlation Analysis Method

This paper presents a new identification method to identify the main errors of the machine tool in time-frequency domain. The low- and high-frequency signals of the workpiece surface are decomposed based on the Daubechies wavelet transform. With power spectral density analysis, the main features of the high-frequency signal corresponding to the imbalance of the spindle system are extracted from the surface topography of the workpiece in the frequency domain. With the cross-correlation analysis method, the relationship between the guideway error of the machine tool and the low-frequency signal of the surface topography is calculated in the time domain.

scholarly journals Time–Frequency Domain Characteristics of Acoustic Emission Signals and Critical Fracture Precursor Signals in the Deep Granite Deformation Process

2021 ◽  
Vol 11 (17) ◽  
pp. 8236
Author(s):  
Le Zhang ◽  
Hongguang Ji ◽  
Liyuan Liu ◽  
Jiwei Zhao
Keyword(s):  
Acoustic Emission ◽  
Frequency Domain ◽  
High Frequency ◽  
Wavelet Packet ◽  
Confining Pressure ◽  
Wavelet Packet Decomposition ◽  
Evolution Law ◽  
Time Frequency ◽  
Characteristic Signal ◽  
Failure Precursor

To study the crack evolution law and failure precursory characteristics of deep granite rocks in the process of deformation and failure under high confining pressure, granite samples obtained from a depth of 1150 m are tested using a TAW-2000 triaxial hydraulic servo testing machine and a PCI-II acoustic emission monitoring system. Based on the stress–strain curve and IET function, the loading process of the sample is divided into five stages: crack closure, linear elastic deformation, microcrack generation and development, macroscopic fracture generation and energy surge, and post-peak failure. The evolution trend and fracture evolution law of the acoustic emission signal event interval function in different stages are analyzed. In particular, the signals with an amplitude greater than 85 dB, a peak frequency greater than 350 kHz, and a frequency centroid greater than 275 kHz are defined as the failure precursor signals before the rock reaches the peak stress. The defined precursor signal conditions agree well with the experimental results. The time–frequency analysis and wavelet packet decomposition of the precursor signal are performed on the extracted characteristic signal of the failure precursor. The results show that the time-domain signal is in the form of a continuous waveform, and the frequency-domain waveform has multi-peak coexistence that is mainly concentrated in the high-frequency region. The energy distribution obtained by the wavelet packet decomposition of the characteristic signal is verified with the frequency-domain waveform. The energy distribution of the signal is mainly concentrated in the 343.75–375 kHz frequency band, followed by the 281.25–312.5 kHz frequency band. The energy proportion of the high-frequency signal increases with the confining pressure.

scholarly journals Fast Texture Synthesis in Adaptive Wavelet Packet Trees

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Ying-Shen Juang ◽  
Hsi-Chin Hsin ◽  
Tze-Yun Sung ◽  
Carlo Cattani
Keyword(s):  
High Frequency ◽  
Texture Synthesis ◽  
Wavelet Packet ◽  
Low Frequency ◽  
Computation Time ◽  
Wavelet Packet Transform ◽  
Synthesis Process ◽  
Adaptive Wavelet ◽  
Hierarchical Trees ◽  
Speed Up

Wavelet packet transform known as a substantial extension of wavelet transform has drawn a lot of attention to visual applications. In this paper, we advocate using adaptive wavelet packet transform for texture synthesis. The adaptive wavelet packet coefficients of an image are organized into hierarchical trees called adaptive wavelet packet trees, based on which an efficient algorithm has been proposed to speed up the synthesis process, from the low-frequency tree nodes representing the global characteristics of textures to the high-frequency tree nodes representing the local details. Experimental results show that the texture synthesis in the adaptive wavelet packet trees (TSIAWPT) algorithm is suitable for a variety of textures and is preferable in terms of computation time.

scholarly journals Mechanistic Characteristics of Double Dominant Frequencies of Acoustic Emission Signals in the Entire Fracture Process of Fine Sandstone

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3959 ◽  
Author(s):  
Chuangye Wang ◽  
Xinke Chang ◽  
Yilin Liu ◽  
Shijiang Chen
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Fracture Process ◽  
Low Frequency ◽  
High Amplitude ◽  
Dominant Frequency ◽  
Band Energy ◽  
Ae Signal ◽  
Low Amplitude ◽  
Frequency Band Energy

To determine the intrinsic relationship between the acoustic emission (AE) phenomenon and the fracture pattern pertaining to the entire fracture process of rock, the present paper proposed a multi-dimensional spectral analysis of the AE signal released during the entire process. Some uniaxial compression AE tests were carried out on the fine sandstone specimens, and the axial compression stress–strain curves and AE signal released during the entire fracture process were obtained. In order to deal with tens of thousands of AE data efficiently, a subroutine was programmed in MATLAB. All AE waveforms of the tests were denoised by wavelet threshold firstly. The fast Fourier transform (FFT) and wavelet packet transform (WPT) were applied to the denoised waveforms to obtain the dominant frequency, amplitude, fractal, and frequency band energy ratio distribution. The results showed that the AE signal in the entire fracture process of fine sandstone had a double dominant frequency band of the low and high-frequency bands, which can be subdivided into low-frequency low-amplitude, high-frequency low-amplitude, high-frequency high-amplitude, and low-frequency high-amplitude signals, according to the magnitude. The low-frequency amplitude relevant fractal dimension and the high-frequency amplitude relevant fractal dimension each had turning points that corresponded to significant decreases in the middle and end stages of loading, respectively. The frequency band energy was mainly concentrated in the range of 0–187.5 kHz, and the energy ratios of some bands had different turning points, which appeared before the complete failure of the rock. It is suggested that the multi-dimensional spectral analysis may understand the failure mechanism of rock better.

Evaluation of Surface Vibrations in the Low and High Frequency Domain

1995 ◽  
Author(s):  
Peter Fischer ◽  
Helmut J. Pradlwarter ◽  
Gerhart I. Schuëller
Keyword(s):  
Frequency Domain ◽  
High Frequency ◽  
Flow Characteristics ◽  
Low Frequency ◽  
Structural Response ◽  
Short Wave ◽  
Fe Model ◽  
Special Cases ◽  
Wide Range ◽  
Surface Vibrations

Abstract The frequency domain of many problems in structural dynamics encompasses a wide range, covering nearly static behavior up to vibration flow characteristics similar to heat transfer. This work presents an uniform approach for low and high frequency vibration analysis, which is based on Finite Element modeling of the structure. Vibrations in the low frequency range are determined by an efficient superposition technique of complex modes, which accounts accurately for any linear damping effect. The modal method is extended to the high frequency domain by applying different levels of averaging to the response and eigenfrequencies and by the introduction of random properties of modeshapes. The high frequency domain is defined by the size of the Finite Elements, i.e. short wave lengths of high frequency modeshapes cannot be represented by the FE-model. The response computation of isolated structures is extended to substructures of complex systems by prescribing stochastic multi-support base excitation at the substructure boundaries. It may be noted, that the presented approach of stochastic high frequency dynamics contains, as special cases, the expressions of the structural response of Statistical Energy Analysis, Bolotin’s integral method and the results of Asymptotic Modal Analysis.

The Pattern of Sympathovagal Balance Explored in the Frequency Domain

Physiology ◽  
1999 ◽  
Vol 14 (3) ◽  
pp. 111-117 ◽  
Author(s):  
Alberto Malliani
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Frequency Domain ◽  
High Frequency ◽  
Low Frequency ◽  
Sympathovagal Balance ◽  
Heart Period ◽  
Reciprocal Regulation ◽  
Physiological Conditions

In most physiological conditions, sympathetic and vagal activities modulating heart period undergo a reciprocal regulation, leading to the concept of sympathovagal balance. This pattern can be indirectly quantified by computing the spectral powers of the oscillatory components corresponding to respiratory acts (high frequency) and to vasomotor waves (low frequency) present in heart rate variability.

An Automaton Fault Diagnosis Based on Shock Response Analysis

2012 ◽  
Vol 226-228 ◽  
pp. 745-748
Author(s):  
Hong Xia Pan ◽  
Ming Zhi Pan ◽  
Run Peng Zhao ◽  
Hai Feng Ren
Keyword(s):  
Frequency Domain ◽  
High Speed ◽  
Energy Analysis ◽  
Signal To Noise Ratio ◽  
Wavelet Packet ◽  
Rapid Identification ◽  
Vibration Response ◽  
Response Analysis ◽  
Machine Vibration ◽  
Diagnosis Method

Shock and vibration response is a particularly important signal to characterize the system state. This paper analyzes the reason of fault generated high speed machine, vibration response mechanism and its frequency characteristic. According to the measured vibration signals, done time and frequency domain features analysis, wavelet packet analysis and frequency domain energy analysis, put forward a kind of fault comprehensive diagnosis method with accurate and rapid identification characteristics, can adapt to the complex vibration response signal with interference and low signal to noise ratio.

A Comparison of Methods for the Coupled Analysis of Floating Structures

2007 ◽  
Author(s):  
Ying Min Low ◽  
Robin S. Langley
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
High Frequency ◽  
Geometric Nonlinearity ◽  
Low Frequency ◽  
Alternative Methods ◽  
Coupled Analysis ◽  
Intermediate Water ◽  
Low Frequency Motion ◽  
Frequency Domain Approach

The dynamic analysis of a deepwater floating platform and the associated mooring/riser system should ideally be fully coupled to ensure a reliable response prediction. It is generally held that a time domain analysis is the only means of capturing the various coupling and nonlinear effects accurately. However, in recent work it has been found that for an ultra-deepwater floating system (2000m water depth), the highly efficient frequency domain approach can provide highly accurate response predictions. One reason for this is the accuracy of the drag linearization procedure over both first and second order motions, another reason is the minimal geometric nonlinearity displayed by the mooring lines in deepwater. In this paper, the aim is to develop an efficient analysis method for intermediate water depths, where both mooring/vessel coupling and geometric nonlinearity are of importance. It is found that the standard frequency domain approach is not so accurate for this case and two alternative methods are investigated. In the first, an enhanced frequency domain approach is adopted, in which line nonlinearities are linearized in a systematic way. In the second, a hybrid approach is adopted in which the low frequency motion is solved in the time domain while the high frequency motion is solved in the frequency domain; the two analyses are coupled by the fact that (i) the low frequency motion affects the mooring line geometry for the high frequency motion, and (ii) the high frequency motion affects the drag forces which damp the low frequency motion. The accuracy and efficiency of each of the methods are systematically compared.

A New Adaptive Image Denoising Method Based on Wavelet Packet Transform and Neighbor Dependency

2013 ◽  
Vol 433-435 ◽  
pp. 301-305
Author(s):  
Bin Wen Huang ◽  
Yuan Jiao
Keyword(s):  
High Frequency ◽  
Wavelet Packet ◽  
Estimation Method ◽  
Low Frequency ◽  
Adaptive Threshold ◽  
Difficult Problem ◽  
Wavelet Packet Transform ◽  
Denoising Method ◽  
Image Edges ◽  
Orthogonal Wavelet Transform

In image processing, removal of noise without blurring the image edges is a difficult problem. Aiming at orthogonal wavelet transform and traditional thresholds shortage, a new adaptive threshold image de-noising method which is based on wavelet packet transform and neighbor dependency is proposed. Low frequency part and high frequency part can be decomposed at the same time in wavelet packet transform and the information contained in wavelet coefficients is redundant. Using this kind of relativity in wavelet packet coefficients, we use a new variance neighbor estimation method and then neighbor dependency adaptive threshold is produced. From the experiment result, we see that compared with traditional methods, this method can not only effectively eliminate noise, but can also well keep original images information and the quality after image de-noising is very well.

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