A Visual Particle System Based on Mechanism Model Data in Digital Twin

AbstractCondition monitoring and fault diagnosis of diesel engines are of great significance for safety production and maintenance cost control. The digital twin method based on data-driven and physical model fusion has attracted more and more attention. However, the existing methods lack deeper integration and optimization facing complex physical systems. Most of the algorithms based on deep learning transform the data into the substitution of the physical model. The lack of interpretability of the deep learning diagnosis model limits its practical application. The attention mechanism is gradually developed to access interpretability. In this study, a digital twin auxiliary approach based on adaptive sparse attention network for diesel engine fault diagnosis is proposed with considering its signal characteristics of strong angle domain correlation and transient non-stationary, in which a new soft threshold filter is designed to draw more attention to multi decentralized local fault information dynamically in real time. Based on this attention mechanism, the distribution of fault information in the original signal can be better visualized to help explain the fault mechanism. The valve failure experiment on a diesel engine test rig is conducted, of which the results show that the proposed adaptive sparse attention mechanism model has better training efficiency and clearer interpretability on the premise of maintaining performance.

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A Multi-level Heterogeneous Model data Framework for Intelligent Factory Digital-Twin Systems

10.46354/i3m.2021.emss.021 ◽

2021 ◽

Author(s):

Zheng Li

Keyword(s):

Model Data ◽

Heterogeneous Model ◽

Digital Twin ◽

Data Framework ◽

Multi Level

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Kinetic Resolution of Ethyl-2-hydroxy-4-phenylbutyrate with Lipase AK as Catalyst

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.560-561.333 ◽

2012 ◽

Vol 560-561 ◽

pp. 333-337

Author(s):

Zhi Min Ou ◽

Ren Wei Li

Keyword(s):

Experimental Data ◽

Kinetic Resolution ◽

Enantiomeric Excess ◽

Model Data ◽

Mechanism Model ◽

Ping Pong ◽

Optimal Resolution ◽

Resolution Model ◽

Double Substrate

Ethyl (R)-2-hydroxy-4-phenylbutyrate was prepared by enzyme resolution of racemic ethyl- 2-hydroxy-4-phenylbutyrate. The optimal resolution conditions were 0.074 mol/L ethyl-2-hydroxy-4-phenylbutyrate, 20 mg lipase AK in 2.0 ml ethenylethanoate, 30 0C, 100 rpm. Enantiomeric excess of ethyl (R)-2-hydroxy-4-phenylbutyrate was up to 99%. Kinetic resolution model of ethyl- 2-hydroxy-4-phenylbutyrate by lipase AK was described by double substrate ping-pong mechanism. Model data agreed well with experimental data.

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Adaptive Modification of Digital Twin Model of CNC Machine Tools Coordinately Driven by Mechanism Model and Data Model

Journal of Physics Conference Series ◽

10.1088/1742-6596/1875/1/012003 ◽

2021 ◽

Vol 1875 (1) ◽

pp. 012003

Author(s):

Peng Zhao ◽

Beibei Sun

Keyword(s):

Data Model ◽

Machine Tools ◽

Cnc Machine Tools ◽

Cnc Machine ◽

Digital Twin ◽

Adaptive Modification ◽

Mechanism Model ◽

Twin Model

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Employee Strengths Use and Thriving at Work

Journal of Personnel Psychology ◽

10.1027/1866-5888/a000262 ◽

2020 ◽

Vol 19 (4) ◽

pp. 197-205

Author(s):

He Ding ◽

Xixi Chu

Keyword(s):

Self Efficacy ◽

Mediation Model ◽

Model Data ◽

Strengths Use ◽

Moderated Mediation Model ◽

Indirect Relationship ◽

Relationship Of ◽

The Relationship ◽

Humble Leadership ◽

Thriving At Work

Abstract. This study aimed to investigate the relationship of employee strengths use with thriving at work by proposing a moderated mediation model. Data were collected at two time points, spaced by a 2-week interval. A total of 260 medical staff completed strengths use, perceived humble leadership, self-efficacy, and thriving scales. The results of path analysis showed that strengths use is positively related to thriving, and self-efficacy mediates the relationship of strengths use with thriving. In addition, this study also found perceived humble leadership to positively moderate the direct relationship of strengths use with self-efficacy and the indirect relationship of strengths use with thriving via self-efficacy. This study contributes to a better understanding of how and when strengths use affects thriving.

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