Weiting He
Zhejiang University
8 Papers
27 Citations
Weiting He is an academic researcher from Zhejiang University. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 2, co-authored 3 publications.
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Papers
Acoustic feature enhancement in rolling bearing fault diagnosis using sparsity-oriented multipoint optimal minimum entropy deconvolution adjusted method
Yaochun Hou,Changqing Zhou,Changming Tian,Da Wang,Weiting He,Wenjun Huang,Peng-hui Wu,Dazhuan Wu +7 more
TL;DR: In this paper , a sparsity-oriented multipoint optimal minimum entropy deconvolution adjusted (MOMEDA) method is proposed for bearing fault feature enhancement and diagnosis based on acoustic signals.
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Vibration-based incipient surge detection and diagnosis of the centrifugal compressor using adaptive feature fusion and sparse ensemble learning approach
TL;DR: Wang et al. as mentioned in this paper proposed a data-driven-based intelligent diagnostic model based on adaptive feature fusion and sparse ensemble learning approach to detect the incipient surge of the centrifugal compressor.
19
Patent
Safety digital quantity acquiring circuit and realizing method thereof
Zhihua Chen,Hong-ming Zhao,Ping Tan,Weiting He,Jia Lin +4 more
- 14 Sep 2011
TL;DR: In this article, a safety digital quantity acquiring circuit and a realizing method for self-checking to the self-circuit can be realized, although the technical problems that the prior acquiring circuit lacks of real-time, cannot discover the fault at first although the self checking to self circuit can still be realized.
13
Design and reliability, availability, maintainability, and safety analysis of a high availability quadruple vital computer system
TL;DR: The HAQVC system is a system with high availability and safety, with prominent characteristics such as fire-new internal architecture, high efficiency, reliable data interaction mechanism, and operation state change mechanism, which is more reliable than the all voting triple modular redundancy system and double 2-out-of-2 system.
13
A Nonparametric Cumulative Sum-Based Fault Detection Method for Rolling Bearings Using High-Level Extended Isolated Forest
TL;DR: In this paper , a low-dimensional data transformation method based on EIF with high extension level and an early fault detection strategy for rolling bearings based on feature combination are proposed due to the limitation of EIF extension level on low dimensional data.
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