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1.
抄纸过程中水分定量控制是一种复杂的多变量耦合过程.它具有大滞后、非线性、时变、不确定等特性,因此一般采用常规方法很难准确建立其数学模型.神经网络是一种很好的非线性数学模型,运用多输入多输出的小波神经网络对抄纸过程中水分定量控制进行数学建模,并在小波神经的嘲络训练过程中采用了两种训练方法,加快了训练速度.结果表明,小波神经网络输出值与实际模型输出值的误差在允许范围内,可以很好的逼近抄纸过程的数学模型. 相似文献
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This paper presents a novel approach to detect and diagnose faults in the dynamic part of a class of stochastic systems . the Such a group of systems are subjected to a set of crisp inputs but the outputs considered are the measurable probability density functions (PDFs) of the system output, rather than the system output alone. A new approximation model is developed for the output probability density functions so that the dynamic part of the system is decoupled from the output probability density functions. A nonlinear adaptive observer is constructed to detect and diagnose the fault in the dynamic part of the system. Conver-gency analysis is performed for the error dynamics raised from the fault detection and diagnosis phase and an applicability study on the detection and diagnosis of the unexpected changes in the 2D grammage distributions in a paper forming process is included. 相似文献
3.
本文针对造纸过程定量控制时滞大、干扰多及可靠性低的问题,设计出一种采用二级控制结构,并引入容错控制方式的控制系统,并通过仿真证明了该系统能够高效、可靠地运行. 相似文献
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We consider flow of a viscous Newtonian fluid in a curved channel with moving porous walls; the upper wall is flexible and its position in unknown a priori. This work is motivated from a papermaking application namely roll forming. We solve the leading order terms in equations of motion using perturbation methods and present analytical expressions for the variation in channel size, pressure, and viscous shear. The stability of the solution is also examined and we report the conditions for marginal stability. 相似文献
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本文对杨木中性亚硫酸盐-蒽醌浆进行了漂白研究。实验表明,用中小型造纸厂的设备和条件,进行次氯酸钙单段漂泊发有效氯用量为10%时,可使NS-AQ杨木浆白度达到76.4%SBD以上;但当有效氯用量为10%时,用二段漂白、可使其白摭达到:81.6度,得率:55.8%,特性粘度:728mL/g;用HPH三段漂白则可使其白度达到:85%ZBD,得率;53.7%,特性粘度,714mL/G,返黄值:14.7。 相似文献
8.
Multiobjective optimization methodology for the development of the papermaking process is considered. The aim is to find efficient
and reliable solution procedures for the process line model consisting of sequential unit-process models; some of them based
on physics, whereas others on experimental data. By the consequence of modeling procedures, nonphysical states or inherited
from modeling data in statistical case, the unit-process models may suffer from undesired unreliability. To control the uncertainty
resulting from the unit-process models, a new multiobjective optimization approach is introduced where both the papermaking
targets as well as the uncertainty related unit-process models are simultaneously taken into account. We illustrate the solution
process by numerical examples related to the quality of the produced paper. 相似文献
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