面向复杂数字化人机界面的感性意象设计研究

Kansei Image Design for Complex Digital Human-Machine Interface

随着数字化仪控技术的不断发展,以数字化人机界面为主的操作方式正在工业控制系统领域得到广泛应用,有效地满足用户的生理和心理需求是设计师开发过程中面对的重要任务。以某新型远程操控清障车的复杂数字化人机界面设计为依托,提出基于BP神经网络对该数字化人机界面感性意象设计进行研究,确定界面布局样式、主要色彩样式、字体样式以及核心元件表现方式等4方面作为其界面设计要素,并构建其与感性意象间的非线性映射及数学预测模型,最后检验了该方法的可行性,能有效匹配用户对复杂数字化人机界面的特定感性需求,并用于后期构建设计决策支持数据库。

With the continuous development of digital instrument control technology,digital human-machine interface （DHMI） operation mode was widely applied in the field of industrial control system,and it was an important task for designers to satisfy user＇s physiology and psychological needs effectively in the development process.The BP Neural Network （BP NN） was implemented to the Kansei image design for the complex DHMI of a new type of remote control wrecker in this paper.It built the nonlinear mapping and prediction mathematical model through the correlation relationship analysis between interace design elements including layout style,main color style,font style and core component expression,and the Kansei images.Finally,the feasibility of this method was verified by experiment,effectively matching users＇ specific Kansei demand to complex DHMI,which can help to build the design decision support database.