scholarly journals Research on the Influence of Time-Varying Excitation on Vibration Characteristics of the Spiral Bevel Geared Transmission System with Broken Teeth

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Dalian Yang ◽  
Liman Chen ◽  
Lingli Jiang ◽  
Ping Wang ◽  
Jie Tao
Keyword(s):  
Frequency Domain ◽  
Dynamic Model ◽  
Torsional Vibration ◽  
Low Frequency ◽  
Time Varying ◽  
Crest Factor ◽  
Time Frequency ◽  
Bevel Gears ◽  
Spiral Bevel ◽  
The Time Domain

Due to heavy and alternating loads of working conditions, spiral bevel gears are prone to broken tooth failures. To solve the problem of vibration characteristic of spiral bevel geared transmission with broken tooth failures that is unknown, this study, considering time-varying mesh stiffness and friction excitation, proposed a torsional vibration dynamic model of spiral bevel geared transmission, which has more simple transmission path and the smaller signal attenuation. First, the time-varying excitations of various broken tooth failure are calculated and introduced into the torsional vibration dynamic model. The vibration response of spiral bevel geared transmission with various broken tooth failures is analysed in the time-frequency domain. Then, the sensitivity of the time-domain statistical index and the frequency domain components to different broken tooth failures are studied. Finally, the correctness of the simulation is verified by experiment. The results show that the crest factor is sensitive to minor tooth failure (10–30%), while kurtosis is sensitive to severe failure (30–60%). With the increase of degrees of broken tooth failure, the energy of the low-frequency band increases obviously.

scholarly journals Transformation Algorithm of Dielectric Response in Time-Frequency Domain

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Ji Liu ◽  
Daning Zhang ◽  
Xinlao Wei ◽  
Hamid Reza Karimi
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Dielectric Response ◽  
Low Frequency ◽  
Dissipation Factor ◽  
Depolarization Current ◽  
Ultralow Frequency ◽  
Time Frequency ◽  
Transformation Algorithm ◽  
The Time Domain

A transformation algorithm of dielectric response from time domain to frequency domain is presented. In order to shorten measuring time of low or ultralow frequency dielectric response characteristics, the transformation algorithm is used in this paper to transform the time domain relaxation current to frequency domain current for calculating the low frequency dielectric dissipation factor. In addition, it is shown from comparing the calculation results with actual test data that there is a coincidence for both results over a wide range of low frequencies. Meanwhile, the time domain test data of depolarization currents in dry and moist pressboards are converted into frequency domain results on the basis of the transformation. The frequency domain curves of complex capacitance and dielectric dissipation factor at the low frequency range are obtained. Test results of polarization and depolarization current (PDC) in pressboards are also given at the different voltage and polarization time. It is demonstrated from the experimental results that polarization and depolarization current are affected significantly by moisture contents of the test pressboards, and the transformation algorithm is effective in ultralow frequency of 10−3 Hz. Data analysis and interpretation of the test results conclude that analysis of time-frequency domain dielectric response can be used for assessing insulation system in power transformer.

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.

scholarly journals A research on fiber-optic vibration pattern recognition based on time-frequency characteristics

2018 ◽  
Vol 10 (12) ◽  
pp. 168781401881346 ◽  
Author(s):  
Tabi Fouda Bernard Marie ◽  
Dezhi Han ◽  
Bowen An ◽  
Jingyun Li
Keyword(s):  
Pattern Recognition ◽  
Frequency Domain ◽  
Time Domain ◽  
Fiber Optic ◽  
Pattern Recognition Method ◽  
Recognition Method ◽  
Time Frequency ◽  
Mode Decomposition ◽  
Vibration Pattern ◽  
The Time Domain

To detect and recognize any type of events over the perimeter security system, this article proposes a fiber-optic vibration pattern recognition method based on the combination of time-domain features and time-frequency domain features. The performance parameters (event recognition, event location, and event classification) are very important and describe the validity of this article. The pattern recognition method is precisely based on the empirical mode decomposition of time-frequency entropy and center-of-gravity frequency. It implements the function of identifying and classifying the event (intrusions or non-intrusion) over the perimeter to secure. To achieve this method, the first-level prejudgment is performed according to the time-domain features of the vibration signal, and the second-level prediction is carried out through time-frequency analysis. The time-frequency distribution of the signal is obtained by empirical mode decomposition and Hilbert transform and then the time-frequency entropy and center-of-gravity frequency are used to form the time-frequency domain features, that is, combined with the time-domain features to form feature vectors. Multiple types of probabilistic neural networks are identified to determine whether there are intrusions and the intrusion types. The experimental results demonstrate that the proposed method is effective and reliable in identifying and classifying the type of event.

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.

Numerical Study on Hydrodynamic Responses of a Two-Body System in Side-by-Side Operation

2016 ◽  
Author(s):  
Shaowu Ou ◽  
Shixiao Fu ◽  
Wei Wei ◽  
Tao Peng ◽  
Xuefeng Wang
Keyword(s):  
Numerical Study ◽  
Low Frequency ◽  
Optimal Operation ◽  
Hydrodynamic Interactions ◽  
Irregular Waves ◽  
Mooring System ◽  
Time Varying ◽  
Body System ◽  
The Time Domain ◽  
Two Bodies

Typically, in some side-by-side offshore operations, the speed of vessels is very low or even 0 and the headings are manually maneuvered. In this paper, the hydrodynamic responses of a two-body system in such operations under irregular seas are investigated. The numerical model includes two identical PSVs (Platform Supply Vessel) as well as the fenders and connection lines between them. A horizontal mooring system constraining the low frequency motions is set on one of the ships to simulate maneuver system. Accounting for the hydrodynamic interactions between two bodies, 3D potential theory is applied for the analysis of their hydrodynamic coefficients. With wind and current effects included, these coefficients are further applied in the time domain simulations in irregular waves. The relevant coefficients are estimated by experiential formulas. Time-varying loads on fenders and connection lines are analyzed. Meanwhile, the relative motions as well as the effects of the hydrodynamic interactions between ships are further discussed, and finally an optimal operation scheme in which operation can be safely performed is summarized.

scholarly journals A SFTD Algorithm for Optimizing the Performance of the Readout Strategy of Residence Time Difference Fluxgate

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3985 ◽  
Author(s):  
Siyu Chen ◽  
Yanzhang Wang ◽  
Jun Lin
Keyword(s):  
Residence Time ◽  
Time Domain ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Transformation Method ◽  
Time Difference ◽  
Single Frequency ◽  
Time Frequency ◽  
Frequency Magnetic Field ◽  
The Time Domain

Residence time difference (RTD) fluxgate sensor is a potential device to measure the DC or low-frequency magnetic field in the time domain. Nevertheless, jitter noise and magnetic noise severely affect the detection result. A novel post-processing algorithm for jitter noise reduction of RTD fluxgate output strategy based on the single-frequency time difference (SFTD) method is proposed in this study to boost the performance of the RTD system. This algorithm extracts the signal that has a fixed frequency and preserves its time-domain information via a time–frequency transformation method. Thereby, the single-frequency signal without jitter noise, which still contains the ambient field information in its time difference, is yielded. Consequently, compared with the traditional comparator RTD method (CRTD), the stability of the RTD estimation (in other words, the signal-to-noise ratio of residence time difference) has been significantly boosted with sensitivity of 4.3 μs/nT. Furthermore, the experimental results reveal that the RTD fluxgate is comparable to harmonic fluxgate sensors, in terms of noise floor.

scholarly journals Dynamic Characteristics of Gear Coupling and Rotor System in Transmission Process Considering Misalignment and Tooth Contact Analysis

Processes ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1336
Author(s):  
Wei Fan ◽  
Hong Lu ◽  
Yongquan Zhang ◽  
Xiangang Su
Keyword(s):  
Finite Element ◽  
Dynamic Model ◽  
Calculation Method ◽  
High Speed ◽  
Low Frequency ◽  
Rotor System ◽  
Integral Approach ◽  
Time Frequency ◽  
Low Frequency Vibration ◽  
Mass Eccentricity

The dynamic vibration of the gear coupling-rotor system (GCRS) caused by misalignment is an important factor of low frequency vibration and noise radiation of the naval marine. The axial misalignment of gear coupling is inevitable owing to mass eccentricity, and is unconstrained in axial direction at high-speed operation. Therefore, the dynamic model of GCRS is proposed, considering gear-coupling misalignment and contact force in this paper. The whole motion differential equation of GCRS is established based on the finite element method. Moreover, the numerical calculation method of meshing force, considering the uniform distribution load on contact surface, is presented, and the mathematical predictive time–frequency characteristics are analyzed by the Newmark stepwise integral approach. Finally, a reduced-scale application of the propulsion shaft system is utilized to validate the effectiveness of the proposed dynamic model. For the sensibility to low-frequency vibration, the natural frequencies and vibration modes of GCRS are analyzed through the processing and analysis of acceleration signal. The experimental dynamic response and main components of vibration are respectively consistent with mathematical results, which demonstrate the effectiveness of the proposed dynamic model of GCRS with misalignment. Furthermore, it also shows that the proposed finite element analysis and calculation method are suitable for complex shafting, providing a novel thought for dynamic analysis of the propeller–shaft–hull coupled system of marine.

scholarly journals Vibrations in CDFW

Entropy ◽  
2020 ◽  
Vol 22 (6) ◽  
pp. 704
Author(s):  
Daniel Soares de Alcantara ◽  
Pedro Paulo Balestrassi ◽  
José Henrique Freitas Gomes ◽  
Carlos Alberto Carvalho Castro
Keyword(s):  
Time Domain ◽  
Low Frequency ◽  
Welding Process ◽  
Statistical Characteristics ◽  
Crest Factor ◽  
Vibration Signals ◽  
Mode Decomposition ◽  
Complex Process ◽  
The Time Domain ◽  
Peak Value

Continuous drive friction welding is a solid-state welding process that has been experimentally proven to be a fast and reliable method. This is a complex process; deformations in the viscosity of a material alter the friction between the surfaces of the pieces. All these dynamics cause changes in the vibration signals; the interpretation of these signals can reveal important information. The vibration signals generated during the friction and forging stages are measured on the stationary part of the structure to determine the influence of the manipulated variables on the time domain statistical characteristics (root mean square, peak value, crest factor, and kurtosis). In the frequency domain, empirical mode decomposition is used to characterize frequencies. It was observed that it is possible to identify the effects of the manipulated variables on the calculated statistical characteristics. The results also indicate that the effect of manipulated variables is stronger on low-frequency signals.

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