NDLI: Cutting tool wear identification based on wavelet package and SVM

Content Provider	IEEE Xplore Digital Library
Author	Xu Tao Wang Tao
Copyright Year	2010
Description	Author affiliation: Department of Automation, Shenyang Institute of Aeronautical Engineering, 110136, China (Xu Tao; Wang Tao)
Abstract	By contrast with conventional methods, Acoustic Emission (AE) sensor possesses better performance for tool wear identifying. So, AE sensor is employed into cutting tool wear identification in this paper. Because of the diversity and time varying of AE, wavelet package decomposition and Support Vector Machine (SVM) are employed to process AE signal. Wavelet package is suitable for analyzing non-stationary signal, and SVM possesses excellent classification capacity for small sample. According to these features, signal processing method for identifying fault of cutting tool wear based on wavelet package and SVM was presented. The characteristics of the cutting tool wear under different conditions were extracted by wavelet package, and cutting tool wear was identified by SVM classifier. Experiment results show that the method based on wavelet package and SVM is suitable for identifying cutting tool wear, and the rate of successfully identifying is 93.3%.
Starting Page	5953
Ending Page	5957
File Size	694159
Page Count	5
File Format	PDF
ISBN	9781424467129
e-ISBN	9781424467129
DOI	10.1109/WCICA.2010.5554471
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cutting tools Support vector machines Feature extraction Wavelet analysis Wavelet transforms Testing Frequency domain analysis Support Vector Machine Cutting Tool Wear AE Ssensor Wavelet Package
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Tool wear identifying based on EMD and SVM with AE sensor

Crank Bearing Wear Fault Diagnosis of Emulsion Pump Based on Fuzzy Support Vector Machine

Texture classification based on support vector machine and wavelet transform

Improved defect detection using support vector machines and wavelet feature extraction based on vector quantization and SVD techniques

Study on identification method of tool wear based on feature fusion and least squares support vector machine

Intelligent Fault Identification Based On Wavelet Packet Energy Analysis and SVM

Power quality disturbance signals identification based on wavelet packet and SVM

Cartoon Image Classification Based on Wavelet Transform

Features Extraction Based on Wavelet Entropy of Decomposed Signals and Flaws Identification with Support Vector Machine in Ultrasonic Inspection

Cutting tool wear identification based on wavelet package and SVM

Similar Documents

Tool wear identifying based on EMD and SVM with AE sensor

Crank Bearing Wear Fault Diagnosis of Emulsion Pump Based on Fuzzy Support Vector Machine

Texture classification based on support vector machine and wavelet transform

Improved defect detection using support vector machines and wavelet feature extraction based on vector quantization and SVD techniques

Study on identification method of tool wear based on feature fusion and least squares support vector machine

Intelligent Fault Identification Based On Wavelet Packet Energy Analysis and SVM

Power quality disturbance signals identification based on wavelet packet and SVM

Cartoon Image Classification Based on Wavelet Transform

Features Extraction Based on Wavelet Entropy of Decomposed Signals and Flaws Identification with Support Vector Machine in Ultrasonic Inspection

Cutting tool wear identification based on wavelet package and SVM