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Dequn Li

Bio: Dequn Li is an academic researcher from Huazhong University of Science and Technology. The author has contributed to research in topics: Materials science & Finite element method. The author has an hindex of 15, co-authored 54 publications receiving 717 citations.


Papers
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TL;DR: In this article, an energy aggregation characteristic-based Hilbert Huang transform method was proposed for online chatter detection, where the measured vibration signal is firstly decomposed into a series of intrinsic mode functions (IMFs) using ensemble empirical mode decomposition.

127 citations

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TL;DR: In this paper, the authors reported an approach of fused deposition modeling (FDM), one of 3D printing methods, which enables the creation of optimized digital designs for TENG devices for the purpose of efficiently harvesting ambient vibration energy.

56 citations

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TL;DR: In this article, a fast strip analysis model is adopted as a surrogate model to approximate the time-consuming computer simulation software for predicating the filling characteristics of injection molding, in which the original part is represented by a rectangular strip, and a finite difference method is adopted to solve one dimensional flow in the strip.
Abstract: Injection molding process parameters such as injection temperature, mold temperature, and injection time have direct influence on the quality and cost of products. However, the optimization of these parameters is a complex and difficult task. In this paper, a novel surrogate-based evolutionary algorithm for process parameters optimization is proposed. Considering that most injection molded parts have a sheet like geometry, a fast strip analysis model is adopted as a surrogate model to approximate the time-consuming computer simulation software for predicating the filling characteristics of injection molding, in which the original part is represented by a rectangular strip, and a finite difference method is adopted to solve one dimensional flow in the strip. Having established the surrogate model, a particle swarm optimization algorithm is employed to find out the optimum process parameters over a space of all feasible process parameters. Case studies show that the proposed optimization algorithm can optimize the process parameters effectively.

55 citations

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TL;DR: Time complexity analysis proves this pictured signal image representation based CNN method to be capable to be real-time, with high flexibility, and may be a promising framework for monitoring or fault diagnosis tasks.

53 citations

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TL;DR: Benefitting from the potential capability in information fusion, deep learning method would be a promising solution for more complex applications, like tool wear monitoring, machining surface prediction et al.

52 citations


Cited by
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Journal ArticleDOI
TL;DR: The applications of deep learning in machine health monitoring systems are reviewed mainly from the following aspects: Auto-encoder and its variants, Restricted Boltzmann Machines, Convolutional Neural Networks, and Recurrent Neural Networks.

1,569 citations

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TL;DR: In this paper, a kind of highly electronegative and conducting material of MXene nanosheet has been innovatively integrated with polyvinyl alcohol (PVA) for electrospinning nanofibers film to fabricate flexible all-electrospun triboelectric nanogenerator (TENG).

282 citations

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TL;DR: A conductive, stretchable and healable composite is used to achieve sustained performance in a triboelectric nanogenerator under extreme deformation and after severe mechanical damage.
Abstract: Advances in next-generation soft electronic devices rely on the development of highly deformable, healable, and printable energy generators to power these electronics. Development of deformable or wearable energy generators that can simultaneously attain extreme stretchability with superior healability remains a daunting challenge. We address this issue by developing a highly conductive, extremely stretchable, and healable composite based on thermoplastic elastomer with liquid metal and silver flakes as the stretchable conductor for triboelectric nanogenerators. The elastomer is used both as the matrix for the conductor and as the triboelectric layer. The nanogenerator showed a stretchability of 2500% and it recovered its energy-harvesting performance after extreme mechanical damage, due to the supramolecular hydrogen bonding of the thermoplastic elastomer. The composite of the thermoplastic elastomer, liquid metal particles, and silver flakes exhibited an initial conductivity of 6250 S cm−1 and recovered 96.0% of its conductivity after healing. Development of wearable devices relies on advance in power sources with complementary mechanical properties. Here the authors use a conductive, stretchable and healable composite to achieve sustained performance in a triboelectric nanogenerator under extreme deformation and after severe mechanical damage.

258 citations

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TL;DR: In this article, a review of the additive manufacturing of structural materials is presented, including multi-material additive manufacturing (MMa-AM), multi-modulus AM (MMo-AM) and multi-scale AM (MSc-AM).
Abstract: Additive manufacturing (AM), also known as three-dimensional (3D) printing, has boomed over the last 30 years, and its use has accelerated during the last 5 years AM is a materials-oriented manufacturing technology, and printing resolution versus printing scalability/speed trade-off exists among various types of materials, including polymers, metals, ceramics, glasses, and composite materials Four-dimensional (4D) printing, together with versatile transformation systems, drives researchers to achieve and utilize high dimensional AM Multiple perspectives of the AM of structural materials have been raised and illustrated in this review, including multi-material AM (MMa-AM), multi-modulus AM (MMo-AM), multi-scale AM (MSc-AM), multi-system AM (MSy-AM), multi-dimensional AM (MD-AM), and multi-function AM (MF-AM) The rapid and tremendous development of AM materials and methods offers great potential for structural applications, such as in the aerospace field, the biomedical field, electronic devices, nuclear industry, flexible and wearable devices, soft sensors, actuators, and robotics, jewelry and art decorations, land transportation, underwater devices, and porous structures

194 citations