Biomedical subjects

Zhao-tong Wu

Publications and source records attributed to Zhao-tong Wu.

3 recordsLinked to original sources

PubMed2004

A robust tolerance design method based on process capability.

This paper presents a method for robust tolerance design in terms of Process Capability Indices (PCI). The component tolerance and the suitable manufacturing processes can be selected based on the real manufacturing context. The robustness of design feasibility under the effect of uncertainties is also discussed. A comparison between the results obtained by the proposed model and other methods indicates that robust and reliable tolerance can be obtained.

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PubMed2004

Inversion of thicknesses of multi-layered structures from eddy current testing measurements.

Luquire et al.'s impedance change model of a rectangular cross section probe coil above a structure with an arbitrary number of parallel layers was used to study the principle of measuring thicknesses of multi-layered structures in terms of eddy current testing voltage measurements. An experimental system for multi-layered thickness measurement was developed and several fitting models to formulate the relationships between detected impedance/voltage measurements and thickness are put forward using least square method. The determination of multi-layered thicknesses was investigated after inversing the voltage outputs of the detecting system. The best fitting and inversion models are presented.

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PubMedDate not supplied

Extracting invariable fault features of rotating machines with multi-ICA networks.

This paper proposes novel multi-layer neural networks based on Independent Component Analysis for feature extraction of fault modes. By the use of ICA, invariable features embedded in multi-channel vibration measurements under different operating conditions (rotating speed and/or load) can be captured together. Thus, stable MLP classifiers insensitive to the variation of operation conditions are constructed. The successful results achieved by selected experiments indicate great potential of ICA in health condition monitoring of rotating machines.

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