NDLI: Study on fault detection using wavelet packet and SOM neural network

Content Provider	IEEE Xplore Digital Library
Author	Xiaochuang Tao Zili Wang Jian Ma Huanzhen Fan
Copyright Year	2012
Description	Author affiliation: School of Reliability and Systems Engineering, Beihang University, Beijing, 100191, China (Xiaochuang Tao; Zili Wang; Jian Ma; Huanzhen Fan)
Abstract	Successful fault detection is based on effective feature exaction and selection processes. Feature map is one of the current fault diagnosis methods. By continuously tracking the trajectories, degradation trend in feature space can be detected. The challenge is how to construct a feature space that can consistently exhibit the degradation pattern. Self Organizing Map (SOM) neural network can map any high-dimensional input into a low-dimensional space, remaining its original topological structure. In this paper, the energy values of different frequency channels of acquired vibration signal are extracted as feature vector by wavelet packets decomposition. SOM based method is proposed to address the problem of feature space construction. Fault detection can be achieved by Minimum Quantization Error calculation (MQE), which can also be transformed into normalized Confidence Value(CV). Finally, the proposed method was also verified to be effective and pragmatic for fault detection via a hydraulic pump test.
Starting Page	1
Ending Page	5
File Size	1374334
Page Count	5
File Format	PDF
ISBN	9781457719097
ISSN	21665656
e-ISBN	9781457719110
e-ISBN	9781457719103
DOI	10.1109/PHM.2012.6228817
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-05-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vibrations fault detection wavelet packets SOM neural network confidence value Vectors
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

Fault detection method for the rolling bearings of metro vehicle based on RBF neural network and wavelet packet transform

Fault Bearing Identification Based on Wavelet Packet Transform Technique and Artificial Neural Network

Online motor bearing fault diagnosis using wavelet packet transform and immune neural network

Fault Diagnosis Based on Wavelet Neural Network

Engine Fault Diagnosis Based on Wavelets Packet and Neural Networks

A new fault diagnosis method for HV circuit breakers based on wavelet packet-neural network

Rolling element bearing fault diagnosis using recursive wavelet and SOM neural network

Condition monitoring for helicopter main gearbox based on wavelet packet transform and wavelet neural network

Fault detection and identification for quadrotor based on airframe vibration signals: A data-driven method

Study on fault detection using wavelet packet and SOM neural network

Similar Documents

Fault detection method for the rolling bearings of metro vehicle based on RBF neural network and wavelet packet transform

Fault Bearing Identification Based on Wavelet Packet Transform Technique and Artificial Neural Network

Online motor bearing fault diagnosis using wavelet packet transform and immune neural network

Fault Diagnosis Based on Wavelet Neural Network

Engine Fault Diagnosis Based on Wavelets Packet and Neural Networks

A new fault diagnosis method for HV circuit breakers based on wavelet packet-neural network

Rolling element bearing fault diagnosis using recursive wavelet and SOM neural network

Condition monitoring for helicopter main gearbox based on wavelet packet transform and wavelet neural network

Fault detection and identification for quadrotor based on airframe vibration signals: A data-driven method

Study on fault detection using wavelet packet and SOM neural network