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Citations for "Wavelet Coefficient Extraction Algorithm for Extracting Fatigue Features in Variable Amplitude Fatigue Loading"

Citation to this article as recorded by ASCI logo

Hasan, A.M., K. Samsudin, A.R. Ramli and R.S. Azmir, 2010. Wavelet-based pre-filtering for low cost inertial sensors. J. Applied Sci., 10: 2217-2230.
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Karim, Z., M.Z. Nuawi, A.Y.M. Said, J.A. Ghani and S. Abdullah, 2013. Integrated kurtosis-based algorithm for Z-notch filter (I-Kaz™) multilevel coefficients responses toward the simultaneous changes in amplitude and frequency of signals. J. Applied Sci., 13: 232-241.
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Citations in impact factor journal as recorded by Crossref logo

Reducing cyclic testing time for components of automotive suspension system utilising the wavelet transform and the Fuzzy C-Means
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Citation to this article as recorded by Crossref logo

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Application of a Multi-Objective Approach and Sequential Covering Algorithm to the Fatigue Segment Classification Problem
Arabian Journal for Science and Engineering Vol. 39, Issue 3, 2165, 2014

Power density based fatigue load spectrum editing for accelerated durability testing for tractor front axles
Biosystems Engineering

FCM-based Optimisation to Enhance the Morlet Wavelet Ability for Compressing Suspension Strain Data
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Fatigue & Fracture of Engineering Materials & Structures

Methods for editing random load spectra based on multi-parameter index preservation for accelerated durability testing
Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science

Wavelet-based Pre-filtering for Low Cost Inertial Sensors
Journal of Applied Sciences Vol. 10, Issue 19, 2217, 2010

Genetic Algorithm-Based Fatigue Data Editing Technique
Applied Mechanics and Materials

Comparative Study on Data Editing Techniques for Fatigue Time Series Signals
Advanced Materials Research

Wavelet-Based Feature Extraction Algorithm for Fatigue Strain Data Associated with the <i>k</i>-Means Clustering Technique
Advanced Materials Research

Vibrational Fatigue Analysis of a Strain Loading Using the Frequency and Wavelet Filtering Methods
Key Engineering Materials

Fatigue Data Analysis Using Continuous Wavelet Transform and Discrete Wavelet Transform
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