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A multi-jet electrospinning direct writing deep learning control system and control method

A deep learning and control system technology, which is applied in the fields of comprehensive factory control, textile and paper making, filament/thread forming, etc., can solve problems such as complex process and lack of suitable control strategy, so as to improve uniformity and achieve long-term stable injection , to overcome the effects of uncertainty and nonlinearity

Active Publication Date: 2022-06-03
福建微纳丝智造科技有限公司
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Therefore, it is necessary to provide a multi-jet electrospinning direct writing deep learning control system and control method to solve the problems in the prior art that the electrospinning direct writing printing process is complicated and lack a suitable control strategy, and to improve the stability of the jet jetting of the spinning nozzle The uniformity of the nanofiber diameter and the micro-nano structure can be improved while the morphology of the product nanofiber can be adjusted.

Method used

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  • A multi-jet electrospinning direct writing deep learning control system and control method
  • A multi-jet electrospinning direct writing deep learning control system and control method
  • A multi-jet electrospinning direct writing deep learning control system and control method

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Embodiment Construction

[0067] In step (7), use the built-up deep learning model to carry out electrospinning direct writing system parameter identification. in each pick

[0070]

[0071] represents the activation of hidden neuron j when the input data is x. In order to make the average activation

[0072] The loss function expression without sparse constraints is:

[0073]

[0074] After adding the sparse constraint to the hidden layer, the loss function is:

[0075]

[0077] After obtaining high-level features from the stacked sparse denoising autoencoder network, support vector regression by estimating the model

[0078] The SVR nonlinear regression function is expressed as:

[0085] Although the above embodiments have been described, those skilled in the art will recognize the basic

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Abstract

The invention relates to the technical field of electrospinning direct writing, and discloses a multi-jet electrospinning direct writing deep learning control system, including a liquid storage tank, a liquid supply device, a plurality of spinning nozzles, a mounting bracket, a liquid supply device, and a high-voltage power supply , collection board, current detector, environmental sensor, data collector and control computer, the signal input terminal of the data collector is connected with the signal output terminal of the environmental sensor and current detector; the signal output terminal of the data collector is connected with the signal of the control computer In and out terminals, the signal output terminal of the control computer is connected with the signal input terminal of the high-voltage power supply and the signal input terminal of the liquid supply device. The control computer is equipped with a parameter input port and a deep learning control system. The adjustment rules of the liquid supply flow and velocity of the device are automatically adjusted by the deep learning control system according to different production conditions, so as to realize the control of the multi-jet electrospinning direct writing process of different spinning solutions.

Description

A multi-jet electrospinning direct writing deep learning control system and control method technical field The present invention relates to the technical field of electrospinning direct writing, particularly a kind of multi-jet electrospinning direct writing deep learning control system and control methods. Background technique Electrospinning direct writing technology is to utilize electrostatic field force to stretch viscoelastic fluid deformation, make it produce jet flow to carry out spray printing, spray The printing jet comes from the Taylor cone tip, and the jet diameter has little dependence on the inner diameter of the nozzle, which can effectively reduce the printing micro-nano structure. Feature size. The electrospinning direct writing technology overcomes the traditional spinning process by reducing the distance from the nozzle to the collecting plate (0.1-5mm). Bifurcation of medium jets, helical unstable motion behavior and multi-jet printing, depositi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): D01D5/00
CPCD01D5/0061Y02P90/02
Inventor 郑高峰康国毅陈华坛方正姜佳昕柳娟郑建毅刘益芳
Owner 福建微纳丝智造科技有限公司