Research of the Vertical Vibrations of Tandem Mill Based on Wavelet Analysis

2015 ◽  
Vol 724 ◽  
pp. 279-282
Author(s):  
Chun Hua Ren ◽  
Xu Ma ◽  
Ze Ming Li ◽  
Yan Hong Ding
Keyword(s):  
Wavelet Analysis ◽  
Wavelet Decomposition ◽  
Vibration Signal ◽  
Vertical Vibration ◽  
Rolling Speed ◽  
Vibration Data ◽  
Signal Features ◽  
Operating Side ◽  
Vertical Vibrations ◽  
Vibration Parameters

In this paper, the defect sheet was captured coincidentally. According to the defective product’s characteristics, we suspected to be caused by the vertical vibration of the roll. When the rolling speed reached a certain value, the vibration of the fourth stand can be feel. The experiment of the vibration data collection was taken to compare the vibration parameters of rolling operating side with those of drive side by wavelet analysis. The result states that the abnormal vibration signal features can be extracted in a special frequency segment of wavelet decomposition, and the vibration frequency to the roll is confirmed which appeared product defects.

scholarly journals Vibration analysis based on the spectrum kurtosis for adjustment and monitoring of ball bearing radial clearance

2018 ◽  
Vol 211 ◽  
pp. 06006 ◽  
Author(s):  
Anthimos Georgiadis ◽  
Xiaoyun Gong ◽  
Nicolas Meier
Keyword(s):  
Signal Analysis ◽  
Vibration Signal ◽  
Radial Clearance ◽  
Spectral Kurtosis ◽  
Vibration Data ◽  
Bearing Clearance ◽  
Bearing Condition Monitoring ◽  
Bearing Vibration ◽  
Vibration Signal Analysis

Vibration signal analysis is a common tool to detect bearing condition. Effective methods of vibration signal analysis should extract useful information for bearing condition monitoring and fault diagnosis. Spectral kurtosis (SK) represents one valuable tool for these purposes. The aim of this paper is to study the relationship between bearing clearance and bearing vibration frequencies based on SK method. It also reveals the effect of the bearing clearance on the bearing vibration characteristic frequencies This enables adjustment of bearing clearance in situ, which could significantly affect the performance of the bearings. Furthermore, the application of the proposed method using SK on the measured data offers useful information for predicting bearing clearance change. Bearing vibration data recorded at various clearance settings on a floating and a fixed bearing mounted on a shaft are the basis of this study

FFT Analysis Using LabView as a Part of Vibration and Preventive Maintenance Class for Senior Level MET students

2005 ◽  
Author(s):  
Aniruddha Mitra ◽  
Sahana Sen
Keyword(s):  
Preventive Maintenance ◽  
Laboratory Experiments ◽  
Vibration Signal ◽  
Engineering Technology ◽  
Technology Program ◽  
Student Activities ◽  
Labview Software ◽  
Vibration Data ◽  
Set Up ◽  
Fft Analysis

An existing senior level elective course on vibration in Mechanical Engineering Technology program at Georgia Southern University has been modified significantly. Two major components have been added to this course. Those are theoretical topics on preventive maintenance and laboratory experiments. As a part of laboratory experiments, Fast Fourier Transform (FFT) was introduced as a possible tool for vibration analysis for the purposes of machine diagnosis. Utilizing the current laboratory set up for the data acquisition systems, LabView software has been used for FFT analysis of signals from various sources. Four different modules were developed and implemented. The modules are as follows: random variation in acceleration of a toy cart due to roughness of the track and pulley, regular uniform wave signal which is generated by the lateral vibration of a cantilever beam at its natural frequency, signal generated by the imported raw data from other sources (e.g. MATLAB) and vibration signal of a shaft mounted on ball bearings in order to detect the defects in the bearing. Each of these modules is illustrated in this paper with suitable examples and suggested student activities and involvements. The results from FFT analysis have been cross checked using other methods and observations. As a follow up, students have been taken to a local industry where significant amount of emphasis is given to preventive maintenance of machineries by vibration data analysis using FFT. Future possible projects include the analysis of vibration data gathered from actual machine shop. This project opens the scope for greater collaborative effort between local industries and classroom activities.

scholarly journals Vibration-based tool life monitoring for ceramics micro-cutting under various toolpath strategies

ACTA IMEKO ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 125
Author(s):  
Zsolt János Viharos ◽  
László Móricz ◽  
Máté István Büki
Keyword(s):  
Tool Path ◽  
High Efficiency ◽  
Vibration Signal ◽  
Ceramic Materials ◽  
Micro Milling ◽  
The Novel ◽  
Feature Selection Technique ◽  
Tool Condition ◽  
Signal Features ◽  
Milling Tool

The 21st century manufacturing technology is unimagined without the various CAM (Computer Aided Manufacturing) toolpath generation programs. The aims of developing the toolpath strategies which are offered by the cutting control software is to ensure the longest possible tool lifetime and high efficiency of the cutting method. In this paper, the goal is to compare the efficiency of the 3 types of tool path strategies in the very special field of micro-milling of ceramic materials. The dimensional distortion of the manufactured geometries served to draw the Taylor curve for describing the wearing progress of the cutting tool helping to determine the worn-in, normal and wear out stages. These isolations allow to separate the connected high-frequency vibration measurements as well. Applying the novel feature selection technique of the authors, the basis for the vibration based micro-milling tool condition monitoring for ceramics cutting is presented for different toolpath strategies. It resulted in the identification of the most relevant vibration signal features and the presentation of the identified and automatically separated tool wearing stages as well.

scholarly journals Pulsating fields of a thin film in a static magnetic field under vertical vibrations

2021 ◽  
Vol 2103 (1) ◽  
pp. 012233
Author(s):  
I V Volodin ◽  
A A Alabuzhev
Keyword(s):  
Magnetic Field ◽  
Thin Film ◽  
Surface Wave ◽  
Film Thickness ◽  
Static Magnetic Field ◽  
Surface Profile ◽  
Vertical Vibration ◽  
Vibrational Amplitude ◽  
Gravitational Forces ◽  
Vertical Vibrations

Abstract In the present paper a dynamics of a thin ferrofluid film under the vertical vibration in a static magnetic field is examined. The vibrational amplitude is assumed to be greater than film thickness so that vibrational force is greater than magnetic and gravitational forces. The pulsating part and the averaged part of the hydrodynamics fields are obtained. The solution of pulsating part for the traveling surface wave is found. The equation for the averaged surface profile is found.

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.

The Wavelet Analysis and Processing of Weak Vibration Signal

2011 ◽  
Vol 189-193 ◽  
pp. 1426-1431
Author(s):  
Ze Ning Xu ◽  
Hong Yu Liu ◽  
Yong Guo Zhang
Keyword(s):  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Signal To Noise Ratio ◽  
Vibration Signal ◽  
Basic Feature ◽  
Wavelet Function ◽  
Fault Analysis ◽  
Bearing Fault Diagnosis ◽  
Gear Fault ◽  
Vibratory Signals

Signal measuring is an important link in machine fault diagnosis. Accurate and reliable fault signals can be achieved by reasonable signal measuring. When the distance between sensor and measuring gear or bearing is comparatively far, the collected signals became weak and disturbed by other vibratory signals in equipments on bearing and gear fault analysis. Useful signals often were submerged in powerful noise, so caused difficult in extracting fault feature. In this paper, according to the feature of vibratory signals in machine test, wavelet analysis basic theory was applied on researching basic feature of wavelet analysis. By selecting suitable wavelet function and applying wavelet elimination noise technology the signal to noise ratio of signal was raised, thus the vibratory impact component can be measured in weak signals. Finally, wavelet analysis was applied on bearing fault diagnosis.

Wavelet Analysis of Vibration: Part 2—Wavelet Maps

1994 ◽  
Vol 116 (4) ◽  
pp. 417-425 ◽  
Author(s):  
D. E. Newland
Keyword(s):  
Wavelet Analysis ◽  
Vibration Analysis ◽  
Vibration Signal ◽  
Wavelet Method ◽  
Harmonic Wavelets

Wavelet maps provide a graphical picture of the frequency composition of a vibration signal. This paper, which is Part 2 of a pair, describes their construction and properties. In the case of harmonic wavelets, there are close similarities between wavelet maps and sonograms. A range of practical examples illustrate how the wavelet method may be applied to vibration analysis and some of its advantages.

Vertical vibration modelling and vibration response analysis of Chinese high-speed train passengers at different locations of a high-speed train

2020 ◽  
Vol 235 (1) ◽  
pp. 35-46 ◽  
Author(s):  
Chun-jun Chen ◽  
Chao Fang ◽  
Guo-qing Qu ◽  
Zhi-ying He
Keyword(s):  
High Speed ◽  
Degrees Of Freedom ◽  
Vibration Signal ◽  
Vertical Vibration ◽  
Response Analysis ◽  
High Speed Train ◽  
Vehicle Model ◽  
Internal Organs ◽  
Damping Coefficients ◽  
Track Irregularity

To study the vibration of a passenger's head and internal organs at different locations of a high-speed train, a 9-degrees-of-freedom (DOF) model of seated passengers is proposed in this paper, and its parameters of the damping coefficients and stiffnesses are identified. Next, the response of the head and internal organs is simulated by applying the vibrational stimulation generated by a 27-DOF vehicle model under track irregularity. Moreover, by applying the measured vibration signal, the following conclusions can be drawn: (1) the weakest response is detected at the centre of the compartment of the wagon, and a stronger response is detected at the centre of the bogie, with the rolling motion having a greater effect 1 m away from the centre of the bogie; (2) the response of the human internal organs is stronger than that of the head under stimulation with a lower frequency of less than 3 Hz, and a similar conclusion can be drawn in the range of 5 to 8 Hz. However, if the frequency is in the range between 8 and 15 Hz, the situation is entirely different. The responses of both the head and internal organs are reduced at frequencies over 20 Hz; (3) from the real application, it can be inferred that the greatest response can be detected at approximately 3 Hz for internal organs and at 8 Hz or higher for the head.

scholarly journals Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4264 ◽  
Author(s):  
Peng Li ◽  
Liuwei Huang ◽  
Jiachao Peng
Keyword(s):  
Wavelet Decomposition ◽  
Principal Component ◽  
Experimental System ◽  
Vibration Signal ◽  
The Finite Element Method ◽  
Nsga Ii ◽  
Impact Monitoring ◽  
Impact Location ◽  
Average Accuracy ◽  
The Impact

Optimal sensor placement is a significant task for structural health monitoring (SHM). In this paper, an SHM system is designed which can recognize the different impact location and impact degree in the composite plate. Firstly, the finite element method is used to simulate the impact, extracting numerical signals of the structure, and the wavelet decomposition is used to extract the band energy. Meanwhile, principal component analysis (PCA) is used to reduce the dimensions of the vibration signal. Following this, the non-dominated sorting genetic algorithm (NSGA-II) is used to optimize the placement of sensors. Finally, the experimental system is established, and the Product-based Neural Network is used to recognize different impact categories. Three sets of experiments are carried out to verify the optimal results. When three sensors are applied, the average accuracy of the impact recognition is 59.14%; when the number of sensors is four, the average accuracy of impact recognition is 76.95%.

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