Journal ArticleDOI
A new time-frequency method for identification and classification of ball bearing faults
Reads0
Chats0
TLDR
In this paper, a new feature extraction step that combines the classical wavelet packet decomposition energy distribution technique and a feature extraction technique based on the selection of the most impulsive frequency bands is presented.About:
This article is published in Journal of Sound and Vibration.The article was published on 2017-06-09. It has received 99 citations till now. The article focuses on the topics: Wavelet packet decomposition & Dimensionality reduction.read more
Citations
More filters
Journal ArticleDOI
Rolling Bearing Fault Diagnosis Using Modified LFDA and EMD With Sensitive Feature Selection
TL;DR: A novel features extraction method that combines K-means method and standard deviation to select the most sensitive characteristics and a modified features dimensionality reduction method is proposed, to realize the low-dimensional representations for high-dimensional feature space.
Journal ArticleDOI
A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis
Chuan Li,José Valente de Oliveira,Mariela Cerrada,Diego Cabrera,René-Vinicio Sánchez,Grover Zurita +5 more
TL;DR: The main contribution is an updated, unbiased, and (to a higher extend) repeatable search, review, and analysis of the available approaches resorting to fuzzy formalisms in this trendy topic.
Journal ArticleDOI
Bearing fault diagnosis based on EMD and improved Chebyshev distance in SDP image
TL;DR: This method can effectively diagnose the faults of rolling bearing using the improved Chebyshev distance of IMF1 as feature and bridges the gap between the local matrix of each IMF component and the average matrix.
Journal ArticleDOI
A novel feature extraction method for bearing fault classification with one dimensional ternary patterns.
TL;DR: A novel feature extraction method for bearing faults called one-dimensional ternary pattern (1D-TP) is applied, which uses patterns obtained from comparisons between neighbors of each value on vibration signals to identify the size (mm) of the fault.
Journal ArticleDOI
Fault diagnosis of rolling bearing based on empirical mode decomposition and improved manhattan distance in symmetrized dot pattern image
TL;DR: A novel fault diagnosis approach based on improved manhattan distance in Symmetrized Dot Pattern (SDP) image is proposed, and different vibration signal of rolling bearing is classified according to this improved man Manhattan distance.
References
More filters
Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Journal ArticleDOI
ANFIS: adaptive-network-based fuzzy inference system
TL;DR: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference System implemented in the framework of adaptive networks.
Journal ArticleDOI
An introduction to variable and feature selection
Isabelle Guyon,André Elisseeff +1 more
TL;DR: The contributions of this special issue cover a wide range of aspects of variable selection: providing a better definition of the objective function, feature construction, feature ranking, multivariate feature selection, efficient search methods, and feature validity assessment methods.
Journal ArticleDOI
Wrappers for feature subset selection
Ron Kohavi,George H. John +1 more
TL;DR: The wrapper method searches for an optimal feature subset tailored to a particular algorithm and a domain and compares the wrapper approach to induction without feature subset selection and to Relief, a filter approach tofeature subset selection.