scholarly journals Vibration Parameters Study of Ship Structures Using Wavelet Analysis of Vibrogram

2021 ◽  
pp. 292-305
Author(s):  
Pavel A. Starodubtsev ◽  
Grigory V. Dorofeev ◽  
Andrey O. Lipovetskiy
Keyword(s):  
Fourier Transform ◽  
Wavelet Analysis ◽  
Measurement Data ◽  
Noise Signal ◽  
Vibration Measurement ◽  
Ship Structures ◽  
Average Value ◽  
Signal Synthesis ◽  
Frequency Transformations ◽  
Vibration Parameters

The study of the vibration parameters of ship structures is important for developing measures to ensure their reliable operation on ships. The commonly used analysis of vibrograms using the Continuous Fourier Transform (CFT) to accurately represent non-stationary functions in general and noise source signals in particular is unsuitable due to a number of drawbacks. The problems of spectral analysis and time-limited signal synthesis can be partially solved by switching to the Window Fourier Transform (WFT). The disadvantage of the WFT is that its calculation uses a fixed window, which cannot be adapted to the local properties of the signal. In order to get rid of this shortcoming for the analysis of vibrogram you can use wavelet transform. It also solves a number of other problems related to the processing of a noise signal. The word “wavelet” means small waves following each other (some sources have introduced the concept of “splash”). In a narrow sense, wavelets are a family of functions obtained by scaling and shifting a single, parent function. In a broad sense, wavelets are functions with frequency localization, whose average value is zero. The article shows the signs of a wavelet. Examples of the most common wavelet functions are given. The use of wavelet functions is proposed not only on the basis of time, but also frequency transformations. The implementation of the algorithm for analyzing vibration measurement data is proposed. An example of vibration measurement data and the results of their processing based on frequency wavelet analysis are given

scholarly journals Vibration Parameters Study of Ship Structures Using Wavelet Analysis of Vibrogram

2021 ◽  
pp. 292-305
Author(s):  
Pavel A. Starodubtsev ◽  
Grigory V. Dorofeev ◽  
Andrey O. Lipovetskiy
Keyword(s):  
Fourier Transform ◽  
Wavelet Analysis ◽  
Measurement Data ◽  
Noise Signal ◽  
Vibration Measurement ◽  
Ship Structures ◽  
Average Value ◽  
Signal Synthesis ◽  
Frequency Transformations ◽  
Vibration Parameters

The study of the vibration parameters of ship structures is important for developing measures to ensure their reliable operation on ships. The commonly used analysis of vibrograms using the Continuous Fourier Transform (CFT) to accurately represent non-stationary functions in general and noise source signals in particular is unsuitable due to a number of drawbacks. The problems of spectral analysis and time-limited signal synthesis can be partially solved by switching to the Window Fourier Transform (WFT). The disadvantage of the WFT is that its calculation uses a fixed window, which cannot be adapted to the local properties of the signal. In order to get rid of this shortcoming for the analysis of vibrogram you can use wavelet transform. It also solves a number of other problems related to the processing of a noise signal. The word “wavelet” means small waves following each other (some sources have introduced the concept of “splash”). In a narrow sense, wavelets are a family of functions obtained by scaling and shifting a single, parent function. In a broad sense, wavelets are functions with frequency localization, whose average value is zero. The article shows the signs of a wavelet. Examples of the most common wavelet functions are given. The use of wavelet functions is proposed not only on the basis of time, but also frequency transformations. The implementation of the algorithm for analyzing vibration measurement data is proposed. An example of vibration measurement data and the results of their processing based on frequency wavelet analysis are given

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.

THE ADVANTAGE OFTHEWAVELET TRANSFORM IN PROCESSING OF SPEECH SIGNALS

2021 ◽  
Vol 4 (3) ◽  
pp. 37-41
Author(s):  
Sayora Ibragimova ◽  
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Speech Processing ◽  
High Performance ◽  
Speech Sound ◽  
Digital Signal ◽  
Speech Signals ◽  
Multi Scale ◽  
Processing Of Speech Signals

This work deals with basic theory of wavelet transform and multi-scale analysis of speech signals, briefly reviewed the main differences between wavelet transform and Fourier transform in the analysis of speech signals. The possibilities to use the method of wavelet analysis to speech recognition systems and its main advantages. In most existing systems of recognition and analysis of speech sound considered as a stream of vectors whose elements are some frequency response. Therefore, the speech processing in real time using sequential algorithms requires computing resources with high performance. Examples of how this method can be used when processing speech signals and build standards for systems of recognition.Key words: digital signal processing, Fourier transform, wavelet analysis, speech signal, wavelet transform

scholarly journals CO measurements from the ACE-FTS satellite instrument: data analysis and validation using ground-based, airborne and spaceborne observations

2008 ◽  
Vol 8 (9) ◽  
pp. 2569-2594 ◽  
Author(s):  
C. Clerbaux ◽  
M. George ◽  
S. Turquety ◽  
K. A. Walker ◽  
B. Barret ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Atmospheric Chemistry ◽  
Measurement Data ◽  
Upper Troposphere ◽  
Remote Sensors ◽  
Key Species ◽  
Vibrational Bands ◽  
Good Tracer ◽  
Chemistry Experiment ◽  
Better Than

Abstract. The Atmospheric Chemistry Experiment (ACE) mission was launched in August 2003 to sound the atmosphere by solar occultation. Carbon monoxide (CO), a good tracer of pollution plumes and atmospheric dynamics, is one of the key species provided by the primary instrument, the ACE-Fourier Transform Spectrometer (ACE-FTS). This instrument performs measurements in both the CO 1-0 and 2-0 ro-vibrational bands, from which vertically resolved CO concentration profiles are retrieved, from the mid-troposphere to the thermosphere. This paper presents an updated description of the ACE-FTS version 2.2 CO data product, along with a comprehensive validation of these profiles using available observations (February 2004 to December 2006). We have compared the CO partial columns with ground-based measurements using Fourier transform infrared spectroscopy and millimeter wave radiometry, and the volume mixing ratio profiles with airborne (both high-altitude balloon flight and airplane) observations. CO satellite observations provided by nadir-looking instruments (MOPITT and TES) as well as limb-viewing remote sensors (MIPAS, SMR and MLS) were also compared with the ACE-FTS CO products. We show that the ACE-FTS measurements provide CO profiles with small retrieval errors (better than 5% from the upper troposphere to 40 km, and better than 10% above). These observations agree well with the correlative measurements, considering the rather loose coincidence criteria in some cases. Based on the validation exercise we assess the following uncertainties to the ACE-FTS measurement data: better than 15% in the upper troposphere (8–12 km), than 30% in the lower stratosphere (12–30 km), and than 25% from 30 to 100 km.

On-Line Test System for Vibration Measurement and Sorting of Ball Bearings

2010 ◽  
Vol 437 ◽  
pp. 502-506 ◽  
Author(s):  
Yu Xue Chen ◽  
Jian Liu
Keyword(s):  
Test System ◽  
Automatic Testing ◽  
Vibration Measurement ◽  
Ball Bearings ◽  
Abnormal Sound ◽  
Line Measurement ◽  
Vibration Model ◽  
On Line ◽  
Vibration Parameters ◽  
And Control

A system for on-line measurement and sorting of ball bearings is presented in this paper. The structures and functions of its automatic testing mechanics and control system are described in detail. The system sorts the tested bearings into four grades by measured values of vibration parameters such as root-mean-square value, peak value, crest factor and kurtosis. Its stability of indication values is between ± 1.0 dB. The mechanism generating abnormal sounds of bearings is also investigated emphatically and the characteristics of abnormal sound signals are described on the basis of vibration model of tested bearing.

Spatial Probabilistic Modeling of Corrosion in Ship Structures

2017 ◽  
Vol 3 (3) ◽  
Author(s):  
Jesus Luque ◽  
Rainer Hamann ◽  
Daniel Straub
Keyword(s):  
Spatial Variability ◽  
Spatial Dependence ◽  
Measurement Data ◽  
Corrosion Process ◽  
Model Parameters ◽  
Plate Element ◽  
Structural Element ◽  
Ship Structures ◽  
Operational Conditions ◽  
Corrosion Model

Corrosion in ship structures is influenced by a variety of factors that are varying in time and space. Existing corrosion models used in practice only partially address the spatial variability of the corrosion process. Typical estimations of corrosion model parameters are based on averaging measurements for one ship type over structural elements from different ships and operational conditions. Most models do not explicitly predict the variability and correlation of the corrosion process among multiple locations in the structure. This correlation is of relevance when determining the necessary inspection coverage, and it can influence the reliability of the ship structure. In this paper, we develop a probabilistic spatiotemporal corrosion model based on a hierarchical approach, which represents the spatial variability and correlation of the corrosion process. The model includes as hierarchical levels vessel–compartment–frame–structural element–plate element. At all levels, variables representing common influencing factors (e.g., coating life) are introduced. Moreover, at the lowest level, which is the one of the plate element, the corrosion process can be modeled as a spatial random field. For illustrative purposes, the model is trained through Bayesian analysis with measurement data from a group of tankers. In this application, the spatial dependence among corrosion processes in different parts of the ships is identified and quantified using the proposed hierarchical model. Finally, how this spatial dependence can be exploited when making inference on the future condition of the ships is demonstrated.

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