Selection of metrological support of management of complex foundry objects with hardly measurable parameters
Year: 2014
Type: article
Abstract: It is shown that the parameters of foundry objects are usually hardly measurable, which creates serious metrological problems in the organization of the ACS for such processes. The system of selection of the metrological support, including obtaining the time-space mapping from the object and its convolution to the measurement result based on the classification of the measurement methods using Kohonen neural networks with an open set of classes is proposed.On the example of sand casting process, the operation of the system of selection of measurement methods for various manufacturing process stages with six-tuple of discrete characteristics of the measurement object at the system input and one of the known methods at the output is shown.The system provides for the expansion of the known list of measurement methods, thereby determining the direction of the scientific search for researchers-metrologists.
Institution: Odesа Polytechnic National University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $242
OpenAlex ID: W1964337092