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A METHOD FOR AUTOMATIC FUZZY SET GENERATION USING SENSOR DATA

机译:一种利用传感器数据自动生成模糊集的方法

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This paper discusses a new generic method for automatically generating fuzzy sets from acquired sensor data, for monitoring purposes. The novel method, denoted Accumulated Step Deviation (ASD), was devised within the scope of a European Space Agency (ESA) project, which main objective was to develop two monitoring systems: one for monitoring a drill and another for terrain detection. This project included an automatic learning module, where the ASD method was used. The ASD method is based on the traditional data preparation process, which begins with data acquisition from sensors and ends with the automatic generation of fuzzy sets to be used as input variables by the monitoring system. An illustrative example is used to discuss the behaviour of the ASD method and perform a comparative study between the ASD method and a traditional Trapezoidal method.
机译:本文讨论了一种新的通用方法,该方法可从采集的传感器数据自动生成模糊集,以进行监控。这种新方法称为累积步距偏差(ASD),是在欧洲航天局(ESA)项目范围内设计的,其主要目标是开发两种监视系统:一种用于监视钻探,另一种用于地形检测。该项目包括一个自动学习模块,其中使用了ASD方法。 ASD方法基于传统的数据准备过程,该过程始于从传感器获取数据,结束于自动生成模糊集以供监控系统用作输入变量。一个说明性示例用于讨论ASD方法的行为,并在ASD方法和传统梯形方法之间进行比较研究。

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