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Tissue roll handling with an agvs, TAPPI JOURNAL, February 2000, Vol. 83(2)

Tissue roll handling with an agvs, TAPPI JOURNAL, February 2000, Vol. 83(2)

Tissue roll handling with an agvs, TAPPI JOURNAL, February 2000, Vol. 83(2)

Tissue roll handling with an agvs, TAPPI JOURNAL, February 2000, Vol. 83(2)

Optimizing Heat Transfer for Steam-Heated Tissue and Paper Machines, Paper360º November/December 2014

Optimizing Heat Transfer for Steam-Heated Tissue and Paper Machines, Paper360º November/December 2014

Effects of creping conditions on surface softness of tissue paper - application of sled method, TAPPI JOURNAL, December 2000, Vol. 83(12)

Effects of creping conditions on surface softness of tissue paper - application of sled method, TAPPI JOURNAL, December 2000, Vol. 83(12)

Tissue 2018 Comes to Appleton, Tissue360º Fall/Winter 2018

Tissue 2018 Comes to Appleton, Tissue360º Fall/Winter 2018

Second iT’s Tissue Attracts 1,000-Plus Visitors to Italy ,Ti

Second iT’s Tissue Attracts 1,000-Plus Visitors to Italy ,Tissue360º Fall/Winter 2015

Von Drehle Starts Up First Valmet NTT Tissue Machine in the

Von Drehle Starts Up First Valmet NTT Tissue Machine in the U.S., Tissue360º Fall/Winter 2016

Prepare to Expect the Unexpected, Tissue360º Fall/Winter 2022

Are we running out of recycled Fiber?, Tissue360º Spring/Sum

Are we running out of recycled Fiber?, Tissue360º Spring/Summer 2014

Research on improving the basis weight measurement accuracy of tissue paper based on PSO-BP neural network, TAPPI Journal October 2022

ABSTRACT: The near-infrared (NIR) sensor can be used for measuring the basis weight and moisture of tissue paper, but the measurement accuracy is not ideal for this paper grade. The weight range of the tissue is 10~30 g/m2, indicating that it is a low gram weight paper. The temperature and humidity of the production environment significantly impact an NIR sensor. This paper focuses on improving the measurement accuracy of tissue paper basis weight. In order to reduce the influences of temperature and humidity, a mathematical model based on a particle swarm optimization back propagation (PSO-BP) neural network is proposed. In comparison with multiple linear regression measurement models, the basis weight measurement error with the PSO-BP model is within ± 0.5 g/m2. This model can effectively improve the measurement accuracy and has a good effect on overcoming the basis weight nonlinear effect caused by the changes in ambient temperature and humidity.