Lateral Deflections of Webs in Air-Flotation Ovens

Moretti, P. M.

doi:10.1115/1.1756922

Cited by 13 publications

(14 citation statements)

References 5 publications

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“…In the parameters optimization process, first, the initial population is created by encoding the network parameters. Subsequently, the trial individuals are created based on Equation ( 3) and (5). To avoid uniformity of parameters from being destroyed, the discrepancy is detected.…”

Section: B Low Discrepancy Heuristic Evolution Extreme Learning Machinementioning

confidence: 99%

“…The trial VOLUME XX, 2017 individuals whose discrepancy is less than δ are regarded as superior trial individuals; otherwise they are regarded as inferior trial individuals. If the trial individual is inferior, it will be replaced with new trial individual that is recreated by Equation (3) and (5). Then, the fitness of individuals is calculated by Equation (28).…”

Section: B Low Discrepancy Heuristic Evolution Extreme Learning Machinementioning

confidence: 99%

“…Based on Navier-Stokes equation and continuity equation, Chen et al established the analytic formula of floating height and validated the effectiveness of this analytic formula [4]. Moretti analyzed the mapping relationship between air box pressure and floating height under different lateral deflections of webs [5]. Chang et al validated the effectiveness of different ground effect theories for analyzing aerodynamic characteristics of pressure-pad air bars.…”

Section: Introductionmentioning

confidence: 99%

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A Low Discrepancy Heuristic Evolution ELM and Ground Effect Theory-Based Serial Hybrid Soft Sensor Model of Floating Height in Air Cushion Furnace

et al. 2021

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In air cushion furnace, the floating height is a key process parameter which greatly affects the quality and production efficiency of high quality mental strips. However, the floating height is hard to be collected in the complex and abominable industry environment. Furthermore, due to the flow field characteristics, some important process variables are difficult to accurately calculate by traditional mechanism modeling methods. In order to accurately predict the floating height, firstly, a low discrepancy heuristic evolution ELM and ground effect theory based serial hybrid soft sensor model is proposed, which constituted by a mechanism model and two data driven models. Secondly, based on the force equilibrium equation and ground effect theory, the mechanism model is constructed, which describes the relationship between the floating height and the process variables including the jet impact angle. Thirdly, a low discrepancy heuristic evolution ELM is proposed as the data driven model to predict the jet impinging angle. In the data driven model, the novel dual mutation strategies collaboration differential evolution is proposed to guarantee the low discrepancy and physical applicability of data driven model. The effectiveness of the proposed method was validated on the self-developed air cushion experiment platform and got desirable experimental results. The research lays an important foundation for the successful implementation of monitoring and control of the strip floating process.

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Section: B Low Discrepancy Heuristic Evolution Extreme Learning Machinementioning

confidence: 99%

Section: B Low Discrepancy Heuristic Evolution Extreme Learning Machinementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Low Discrepancy Heuristic Evolution ELM and Ground Effect Theory-Based Serial Hybrid Soft Sensor Model of Floating Height in Air Cushion Furnace

et al. 2021

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“…For example, Hornig et al [11] studied the relationship between the floating height and the pressure coefficient through the numerical simulation method. Moretti developed the governing Partial Differential Equations to predict the floating height of strip [12]. Cho used the flexible cantilever beam and ground effect theory to formulate the mechanism model of floating height [13].…”

Section: Introductionmentioning

confidence: 99%

Hard-Division and Multi-Model Based Floating Height Prediction for Air Cushion Furnace With Hybrid Nozzles

et al. 2020

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The strip floating height is a key factor affecting production efficiency and quality of the air cushion furnace. At present, the air cushion furnace with hybrid nozzles is the most typical heating and drying equipment. In order to predict the floating height of the strip in this equipment, a hard-division and multi-model based floating height prediction method is proposed. In hard division method, the process is divided into several stable and vibration stages. On the one hand, time interval based novel density clustering algorithm is proposed so as to avoid the wrong division caused by noise at hard division stage. On the other hand, covariance matrices based local density is presented to better capture dynamic characteristics of the process. In the multi-model stage, a hybrid prediction model under stable state and XGBoost-based model under vibration state are established to predict the strip floating height. The hybrid prediction model is composed of mechanism model and data driven model. The mechanism model is proposed by combining the force balance equation and inviscid theory which can predict the major information of the floating height and the data driven model compensates the error of the mechanism model. A mount of experiments have been carried out on the existing air cushion experimental platform and show desirable prediction effect.

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“…Chen et al predicted the flotation height of strip under stable state by using the data fitting method [11]. Moretti combined the axially moving beam, thin-wall jet theory, and thick-wall jet theory with other ground effect models to establish a mechanism flotation height prediction model of the strip in the air flotation furnace [12]. Hou et al proposed a parallel hybrid flotation height prediction model, i.e., SBEH, which is composed of the mechanism prediction model and the data error compensation model.…”

Section: Introductionmentioning

confidence: 99%

Flotation Height Prediction under Stable and Vibration States in Air Cushion Furnace Based on Hard Division Method

Hou

Liu

2019

Mathematical Problems in Engineering

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Air cushion furnace is indispensable equipment for the production of high quality strip, and it is significant to national economy. e flotation height is a key factor to the quality and efficiency of the product. However, the current prediction models can merely predict the flotation height of strip in air cushion furnace at single working state. e precision of prediction model is inaccurate at the circumstance of low flotation height. To solve the above problem, firstly, this paper proposes a framework which can predict the flotation height of strip under both stable and vibration states. e framework is composed of the hard division model and prediction model. Secondly, a hard division method is proposed based on clustering which combines stacked denoising autoencoder and floating process knowledge. irdly, a parallel hybrid flotation height prediction model is proposed, which can provide desirable prediction results at the circumstance of low flotation height. Finally, the LSSVR model is used to predict the maximum and minimum flotation height of strip at vibration state. e experimental results show that the framework can accurately divide the stable and vibration states of the strip and can accurately predict the flotation height of the strip under the stable and vibration states. e research contents of this paper lay an important theoretical foundation for the precise process control in air cushion furnace.

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Lateral Deflections of Webs in Air-Flotation Ovens

Cited by 13 publications

References 5 publications

A Low Discrepancy Heuristic Evolution ELM and Ground Effect Theory-Based Serial Hybrid Soft Sensor Model of Floating Height in Air Cushion Furnace

A Low Discrepancy Heuristic Evolution ELM and Ground Effect Theory-Based Serial Hybrid Soft Sensor Model of Floating Height in Air Cushion Furnace

Hard-Division and Multi-Model Based Floating Height Prediction for Air Cushion Furnace With Hybrid Nozzles

Flotation Height Prediction under Stable and Vibration States in Air Cushion Furnace Based on Hard Division Method

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