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A knowledge based system for the selection of industrial sensors.

Korsten M., Regtien P.

Systems Science

2000

Vol. 26, nr 2

111-124

A method is proposed to assist the designer of a measurement system in finding the optimal set of sensors for a given measurement problem. The method can be implemented on a computer system and contains a framework for optimality, where the user can define an optimal setting to his/her requirement. To combat the combinatorial explosion during a search, solutions are generated on different levels of abstraction. A solution at a high level of abstraction represents a large number of solutions at a lower level. This paper focuses on modelling the physical world and the measurement system(s), which is necessary to identify possible sensor solutions. Modelling is performed in a systematic and modular way in order to enable an efficient search process.

Laboratory versus industrial cutting force sensor in tool condition monitoring

Jemielniak K., Balazinski M.

Prace Naukowe Instytutu Technologii Maszyn i Automatyzacji Politechniki Wrocławskiej. Konferencje

2000

Vol. 76, nr 35

109-116

Research works concerning the utilisation of cutting force measurements in tool condition monitoring usually present results and deliberations based on laboratory sensors. These sensors are too fragile to be used in industrial practice. Industrial sensors employed on the factory floor are less accurate, and this must be taken into account when creating a tool condition monitoring strategy. Another drawback of most of these works is that constant cutting parameters are used for the entire tool life. This does not reflect industrial practice where the same tool is used at different feeds and depths of cut in sequential passes. The paper presents a comparison of signals originating from laboratory and industrial cutting force sensors. The usability of the sensor output was studied during a laboratory simulation of industrial cutting conditions. Instead of building mathematical models for the correlation between tool wear and cutting force, an FFBP artificial neural network was used to find which combination of input data would provide an acceptable estimation of tool wear. The results obtained proved that cross talk between channels has an important influence on cutting force measurements, however this input configuration can be used for a tool condition monitoring system.