| 1. |
- Peng, Kunkun, et al.
(author)
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A new joint data-model driven dynamic scheduling architecture for intelligent workshop
- 2019
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In: Proceedings of the ASME 14th International Manufacturing Science and Engineering Conference, 2019, vol 1. - : AMER SOC MECHANICAL ENGINEERS.
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Conference paper (peer-reviewed)abstract
- Intelligent manufacturing plays a significant role in Industry 4.0. Dynamic shop scheduling is a key problem and hot research topic in the intelligent manufacturing systems, which is NP-hard. However, traditional shop scheduling mode, dynamic event prediction approach, scheduling model and scheduling algorithm, cannot cope with increasingly complicated problems under kinds of scales production disruptions in the real-world production. To deal with these problems, this paper proposes a new joint data-model driven dynamic scheduling architecture for intelligent workshop. The architecture includes four new and key characteristics in the aspects of scheduling mode, dynamic event prediction, scheduling model and algorithm. More specifically, the new scheduling mode introduces data analytics methods to quickly and accurately deal with the dynamic events encountered in the production process. The new prediction model improves the deep learning method, and further applies it predict the dynamic events accurately to provide reliable input to the dynamic scheduling. The new scheduling model proposes a new hybrid rescheduling and inverse scheduling model, which can cope with almost scales of abnormal production problems. The new scheduling algorithm hybridizes dynamic programming and intelligent optimization algorithm, which can overcome the disadvantages of the two methods based on the analysis of solution space. The dynamic programming is employed to provide high-quality initial solutions for the intelligent optimization algorithm by reducing the computation time greatly. To sum up, the presented architecture is a new attempt to understand the problem domain knowledge and broaden the solving idea, which can also provide new theories and technologies to manufacturing system optimization and promote the applications of the theoretical results.
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| 2. |
- Sun, Jianwu, et al.
(author)
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Solar driven energy conversion applications based on 3C-SiC
- 2016
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In: 16th International Conference on Silicon Carbide and Related Materials, ICSCRM 2015. - : Trans Tech Publications Ltd. - 9783035710427 ; , s. 1028-1031
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Conference paper (peer-reviewed)abstract
- There is a strong and growing worldwide research on exploring renewable energy resources. Solar energy is the most abundant, inexhaustible and clean energy source, but there are profound material challenges to capture, convert and store solar energy. In this work, we explore 3C-SiC as an attractive material towards solar-driven energy conversion applications: (i) Boron doped 3C-SiC as candidate for an intermediate band photovoltaic material, and (ii) 3C-SiC as a photoelectrode for solar-driven water splitting. Absorption spectrum of boron doped 3C-SiC shows a deep energy level at ~0.7 eV above the valence band edge. This indicates that boron doped 3C-SiC may be a good candidate as an intermediate band photovoltaic material, and that bulk like 3C-SiC can have sufficient quality to be a promising electrode for photoelectrochemical water splitting.
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| 3. |
- Wei, Xinyu, et al.
(author)
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Holey Au-Ag alloy nanoplates with built-in hotspots for surface-enhanced Raman scattering
- 2016
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In: Nanoscale. - : Royal Society of Chemistry (RSC). - 2040-3364 .- 2040-3372. ; 8:34, s. 15689-15695
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Journal article (peer-reviewed)abstract
- Plasmonic noble metal nanocrystals with interior nanogaps have attracted great attention in surface-enhanced Raman scattering (SERS) applications due to the presence of built-in hotspots. Herein, we report a synthesis route to holey Au-Ag alloy nanoplates by controlled galvanic replacement with Ag nanoplates as the sacrificial template, a sulfite-coordinated Au(I) salt as the Au source, and polyvinylpyrrolidone (PVP) as the capping agent. PVP helps regulate the anisotropic growth of nanopores on the Ag nanoplates to afford a highly holey nanostructure, and the monovalent Au(I) salt plays a critical role in stabilizing these holey nanoplates by rapidly enriching Au in the alloy nanostructures. Numerical simulations and experimental results suggest that these holey Au-Ag alloy nanoplates possess enormous internal hotspots for high sensitivity in the SERS analysis, and high stability for excellent reliability of the analysis under many harsh conditions. We believe that this strategy is potentially applicable to the synthesis of many other types of plasmonic nanostructures with inherent nanogaps for many sensing and imaging applications.
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| 4. |
- Yang, Lei, et al.
(author)
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Sulfur vs. tellurium: the heteroatom effects on the nonfullerene acceptors
- 2019
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In: Science in China Series B. - : SCIENCE PRESS. - 1674-7291 .- 1869-1870. ; 62:7, s. 897-903
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Journal article (peer-reviewed)abstract
- The effect of chalcogen heteroatom variation on donor materials has been systematically investigated. However, this effect on acceptors has rarely been explored. Herein, nonfullerene acceptors BFPSP and BFPTP were reported by simply changing the chalcogen atoms from S to Te. The differences between BFPSP and BFPTP in light absorption, energy levels, excited-state lifetimes, energy loss, charge mobilities, morphology, and photovoltaic properties were systematically investigated to understand the heteroatom effects. More importantly, the electroluminescence spectra, external quantum efficiency of photovoltaics and TD-DFT calculations revealed that the triplet excited state (T-1) in energy of BFPTP equals to the charge transfer (CT) state in PBDB-T:BFPTP, which allows T-1 excitons, generated by intersystem crossing, to split into free charges to contribute to the efficiency. This contribution provides a strategy for tuning the photophysical properties of nonfullerene acceptors and designing high performance triplet materials for OSCs.
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| 5. |
- Zhang, Yuyan, et al.
(author)
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Imbalanced data fault diagnosis of rotating machinery using synthetic oversampling and feature learning
- 2018
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In: Journal of manufacturing systems. - : ELSEVIER SCI LTD. - 0278-6125 .- 1878-6642. ; 48, s. 34-50
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Journal article (peer-reviewed)abstract
- Imbalanced data problems are prevalent in the real rotating machinery applications. Traditional data-driven diagnosis methods fail to identify the fault condition effectively for lack of enough fault samples. Therefore, this study proposes an effective three-stage fault diagnosis method towards imbalanced data. First, a new synthetic oversampling approach called weighted minority oversampling (WMO) is devised to balance the data distribution. It adopts a new data synthesis strategy to avoid generating incorrect or unnecessary samples. Second, to select useful features automatically, an enhanced deep auto-encoder (DA) approach is adopted. DA is improved in two aspects: 1) a new cost function based on maximum correntropy and sparse penalty is designed to learn sparse robust features; 2) a fine-tuning operation with a self-adaptive learning rate is developed to ensure the good convergence performance. Finally, the C4.5 decision tree identifies the learned features. The proposed method named WMODA is evaluated on 25 benchmark imbalanced datasets. It achieves better results than five well-known imbalanced data learning methods. It is also evaluated on a real engineering dataset. The experimental results show that WMODA can detect more fault samples than the traditional data-driven methods.
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