Boe Technology Group Co., Ltd.

Beijing Boe Sensor Technology Co., Ltd.

Beijing University of Technology

Xiaolong Wu

Ying Wang

Chunlei Wang

Juan Chen

Sikai Zhang

Yongzhong Zhang

Peng Liang

Jing Pang

Changyin Wang

Deshen Zhai

Xiaoqian Ju

Junfei Qiao

Honggui Han

Zhan Li

Jiaming Li

A dimming module and method for manufacturing the same, and a dimming glass, relate to the field of smart glass technology. The dimming module includes: a first dimming structure () and a second dimming structure (). Each of the first dimming structure () and the second dimming structure () includes a first substrate (), a second substrate () and a liquid crystal layer (), and a first flexible circuit board () and a second flexible circuit board (). The first substrate () is provided with a first binding area (), and a first electrode () on one side facing the liquid crystal layer (). The second substrate () is provided with a second binding area (), and a plurality of second electrodes () on one side facing the liquid crystal layer ().

Dimming module and method for manufacturing the same, and dimming glass

The present disclosure provides a dimming glass and a method for manufacturing the dimming glass. The dimming glass includes: at least one dimming functional layer sandwiched between two glass substrates, where a plurality of conductive leads is connected to a bonding circuit board, and a sealant filled between sealant regions of the two glass substrates. Each conductive lead includes a connecting end, a protruding end and an extension segment. The connecting end is connected to the bonding circuit board, the protruding end extends out of an outer side of an edge of the glass substrate, at least a part of the extension segment extends in a first direction which is an extension direction of an edge of the bonding side of the dimming functional layer, and the extension segment is located in the sealant region and is secured through the sealant.

Dimming glass and manufacturing method thereof

A cooperative fuzzy-neural control method is designed in this present invention. Due to the difficulty for cooperatively controlling the concentrations of the dissolved oxygen and nitrate nitrogen in wastewater treatment process, a cooperative fuzzy-neural control method is investigated. In this proposed method, firstly, a interval type-2 fuzzy neural network is employed to construct the cooperative fuzzy-neural controller. Secondly, a parameter cooperative strategy is proposed to cooperatively optimize the global and local parameters of the cooperative fuzzy-neural controller to meet the control requirements. This proposed cooperative fuzzy-neural control method can cooperatively control the concentrations of the dissolved oxygen and nitrate nitrogen in wastewater treatment process. The results illustrate that the proposed cooperative fuzzy-neural control method can achieve the high control accuracy and guarantee the normal operations of wastewater treatment process under the different operation conditions.

Type-2 fuzzy neural network-based cooperative control method for wastewater treatment process

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Beijing, China

Xiaolong Wu