Tutorial 21 wavelet transform: a mathematical tool for non-stationary signal processing in measurement science part 2 in a series of tutorials in instrumentation and measurement

2009 ◽  
Vol 12 (5) ◽  
pp. 35-44 ◽  
Author(s):  
Ruqiang Yan ◽  
Robert X. Gao
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Mathematical Tool ◽  
Measurement Science ◽  
Non Stationary Signal ◽  
Science Part

Wavelet Transform Technology in the Non-Stationary Signal Fault Diagnosis in Engineering Application

2012 ◽  
Vol 518-523 ◽  
pp. 1355-1358 ◽  
Author(s):  
Feng Lu ◽  
Fu Zhou Feng
Keyword(s):  
Signal Processing ◽  
Feature Extraction ◽  
Control System ◽  
Wavelet Transform ◽  
Wavelet Decomposition ◽  
Wavelet Transformation ◽  
Engineering Application ◽  
Digital Content ◽  
Mechanical Equipment ◽  
Non Stationary Signal

Certain mechanical equipment control system of sampling signal processing in the digital content are discussed. Based on the wavelet transformation and multiresolution wavelet decomposition mathematics theory, the application of wavelet transform on feature extraction and noise removing; Instance are given.

A New Application of Continuous Wavelet Transform to Overlapping Chromatograms for the Quantitative Analysis of Amiloride Hydrochloride and Hydrochlorothiazide in Tablets by Ultra-Performance Liquid Chromatography

2012 ◽  
Vol 95 (3) ◽  
pp. 751-756 ◽  
Author(s):  
Erdal Dinç ◽  
Eda Büker
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Quantitative Analysis ◽  
Continuous Wavelet Transform ◽  
Standard Addition ◽  
Ultra Performance Liquid Chromatography ◽  
Continuous Wavelet ◽  
Constant Flow Rate ◽  
Acquity Uplc ◽  
Amiloride Hydrochloride

Abstract A new application of continuous wavelet transform (CWT) to overlapping peaks in a chromatogram was developed for the quantitative analysis of amiloride hydrochloride (AML) and hydrochlorothiazide (HCT) in tablets. Chromatographic analysis was done by using an ACQUITY ultra-performance LC (UPLC) BEH C18 column (50 × 2.1 mm id, 1.7 μm particle size) and a mobile phase consisting of methanol–0.1 M acetic acid (21 + 79, v/v) at a constant flow rate of 0.3 mL/min with diode array detection at 274 nm. The overlapping chromatographic peaks of the calibration set consisting of AML and HCT mixtures were recorded rapidly by using an ACQUITY UPLC H-Class system. The overlapping UPLC data vectors of AML and HCT drugs and their samples were processed by CWT signal processing methods. The calibration graphs for AML and HCT were computed from the relationship between concentration and areas of chromatographic CWT peaks. The applicability and validity of the improved UPLC-CWT approaches were confirmed by recovery studies and the standard addition technique. The proposed UPLC-CWT methods were applied to the determination of AML and HCT in tablets. The experimental results indicated that the suggested UPLC-CWT signal processing provides accurate and precise results for industrial QC and quantitative evaluation of AML-HCT tablets.

scholarly journals Energy Analysis Method Based on Wavelet Transform for Sensor Fault Diagnosis

2011 ◽  
Vol 2-3 ◽  
pp. 117-122 ◽  
Author(s):  
Peng Peng Qian ◽  
Jin Guo Liu ◽  
Wei Zhang ◽  
Ying Zi Wei
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Energy Analysis ◽  
Sensor Faults ◽  
Analysis Method ◽  
Sensor Fault ◽  
Fault Type ◽  
Ideal Tool ◽  
Non Stationary Signal

Wavelet analysis with its unique features is very suitable for analyzing non-stationary signal, and it can also be used as an ideal tool for signal processing in fault diagnosis. The characteristics of the faults and the necessary information on the diagnosis can be constructed and extracted respectively by wavelet analysis. Though wavelet analysis is specialized in characteristics extraction, it can not determine the fault type. So this paper has proposed an energy analysis method based on wavelet transform. Experiment results show the method is very effective for sensor fault diagnosis, because it can not only detect the sensor faults, but also determine the fault type.

Study of Segmentation Threshold Based on Wavelet Transform

2013 ◽  
Vol 756-759 ◽  
pp. 3855-3859
Author(s):  
Jian Yi Li ◽  
Hui Juan Wang
Keyword(s):  
Wavelet Transform ◽  
Digital Image ◽  
Region Growing ◽  
Detection Methods ◽  
Mathematical Tool ◽  
Matlab Simulation ◽  
Segmentation Method ◽  
Transform Method ◽  
Threshold Segmentation ◽  
Digital Image Enhancement

Based on the research of the four kinds of algorithms of digital image segmentation, based on edge detection methods, based on region growing method, threshold segmentation method and digital image threshold segmentation method based on wavelet transform, using MATLAB simulation of all digital image enhancement and segmentation process, the obtained results are analyzed, proving the threshold segmentation wavelet transform method has unparalleled advantages in information extraction in medical image. Wavelet transform is a mathematical tool widely used in recent years, compared with the Fu Liye transform, the window of Fu Liye transform, wavelet transform is the local transform of space and frequency, it can be very effective in extracting information from the signal [[1.

scholarly journals Geological Stratigraphy and Spatial Distribution of Microfractures over Costa Rica Convergent Margin, Central America – A Wavelet-Fractal Analysis

2016 ◽  
Author(s):  
Upendra K. Singh ◽  
Thinesh Kumar ◽  
Rahul Prajapati
Keyword(s):  
Fractal Dimension ◽  
Wavelet Transform ◽  
Costa Rica ◽  
Central America ◽  
Gamma Ray ◽  
Total Porosity ◽  
Discrete Wavelet ◽  
Mathematical Tool ◽  
Convergent Margin ◽  
Frequency Scale

Abstract. Identification of spatial variation of lithology, as a function of position and scale, is very critical job for lithology modelling in industry. Wavelet Transform (WT) is an efficacious and powerful mathematical tool for time (position) and frequency (scale) localization. It has numerous advantages over Fourier Transform (FT) to obtain frequency and time information of a signal. Initially Continuous Wavelet Transform (CWT) is applied on gamma ray logs of two different Well sites (Well-1039 & Well-1043) of Costa Rica Convergent Margin, Central America for identifications of lithofacies distribution and fracture zone later Discrete Wavelet Transform (DWT) applied to DPHI log signals to show its efficiency in discriminating small changes along the rock matrix irrespective of the instantaneous magnitude to represent the fracture contribution from the total porosity recorded. Further the data of the appropriate depths partitioned using above mathematical tools are utilized separately for WBFA. As consequences of CWT operation it is found that there are four major sedimentary layers terminated with a concordant igneous intrusion passing through both the wells. In addition of WBFA analysis, it is clearly understanding that the fractal dimension value is persistent in first sedimentary layers and the last gabbroic sill intrusions. Inconsistent value of fractal dimension is attributed to fracture dominant in intermediate sedimentary layers it is also validate through core analysis. Fractal Dimension values suggest that the sedimentary environments persisting in that well locations bears abundant shale content and of low energy environments.

scholarly journals Метод трансляционного переноса для оценки стабильности нестационарного квантового стандарта частоты

2021 ◽  
Vol 91 (1) ◽  
pp. 32
Author(s):  
С.В. Божокин ◽  
К.А. Баранцев ◽  
А.Н. Литвинов
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Frequency Standard ◽  
Continuous Wavelet ◽  
Quantum Frequency ◽  
Quantum Frequency Standard ◽  
Standard Signal ◽  
Wavelet Variance ◽  
Non Stationary Signal

Continuous wavelet transform is used to analyze the operation of a non-stationary signal of a quantum frequency standard. The method of translational transfer is proposed, with the help of which the boundary phenomena in this transformation are eliminated. The spectral integrals of the quantum frequency standard signal in various frequency ranges are calculated. A wavelet dispersion is introduced, which makes it possible to determine the moments of time when the signal fluctuations are the strongest. The comparison of the wavelet variance with the usual variance and with the Allen variance is carried out.

scholarly journals Leakage Detection in Pipeline using Wavelet Transform Method

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Mohd Fairusham Ghazali ◽  
Abdul Kadir Samta
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Correlation Analysis ◽  
Pipeline System ◽  
Leakage Detection ◽  
Transient Method ◽  
Research Project ◽  
Transform Method ◽  
Cepstrum Analysis ◽  
Transient Methods

This research project is focusing on the leakage detection in the pipelines using wavelet and cepstrum analysis. To fully complete this research project, experimental and analysis by using signal processing are required. This research project proposed a technique which is a transient method. The basic principle is the fact that water spouting out of a leak in a pressurized pipe generates a signal, and this signal contains information to whether a leak exists and where it is located. The present transient methods for finding leaks are mainly based upon correlation analysis, where one sensing device is installed at each side of a leak. This method is hard to operate because it needs many operators to operate it due to equipment in different place. This research project proposed a wavelet transform method to detect leakage in the pipeline system. The experimental results show appears  to improve the ability of the method to identify features in the signal.

Sign in / Sign up

Export Citation Format

Share Document