Thickness Control and Prediction of Industrial Plastic Film

Title:Thickness Control and Prediction of Industrial Plastic Film

Volume: 9 Issue: 1

Author(s): Cai Li and Tan Yuegang

Affiliation:

Keywords: Plastic film, BP neural network, forecasting control.

Abstract: Thickness controlling of plastic film is a very important aspect in industrial film technology. According to the thickness uniformity parameter, we should control the uniformity of the plastic film accurately on the production line. However there must be a large amount of actual sensors as the analysis basis, which increases the complexity of the operation of sensor layout. Aiming at the shortcomings of the existing detection, this paper proposes a controlling scheme with mobile sensing detection device for thickness controlling, and forecasting the thickness of plastic film by BP neural network. This paper examines eight recent patents that were awarded from January 2003 to March 2014 in the area of industrial plastic film measurements. On the basis of this, it further states the thickness detection principle and the whole control scheme. Then, the BP neural network is introduced, which can predict the thickness of plastic film by setting the appropriate parameters. The simulation results show that monitoring method based on the BP neural network can reduce production cost, combining the traditional film production line with a new idea of controlling the opening degree of wind ring.

Cite this article as:

Li Cai and Yuegang Tan, Thickness Control and Prediction of Industrial Plastic Film, Recent Patents on Computer Science 2016; 9 (1) . https://dx.doi.org/10.2174/2213275908666150310213635