FUZZY MEASURES FOR SENSOR DATA FUSION IN INDUSTRIAL RECYCLING

During recent years it has become more and more obvious that we need t o take care of products when they are worn out if we are to be more en vironmentally responsible. To make this possible much of the related w ork has to be performed in an automized way. When a disassembly proces s is automized a number of sensors is needed. These sensors gather a l arge amount of information which must be fused in an effective way. To this end we need a method that is fast, flexible, robust and easy to adapt to all kind of sensors. The first attribute (fastness) can be ob tained by using a distributed sensor data processing architecture with local processors which pre-process data close to the sensors. The oth er attributes are obtained by using a fusion algorithm based on a nove l fuzzy operator. In this article, this fuzzy operator is described an d its properties investigated. A simulation is performed, applying the fuzzy operator to a sensor-based classification by size of electrical motors aimed for disassembly. The simulation clearly demonstrates the superiority of our fuzzy operator when compared to common AND and OR operators.