Abstract
The article proposes concept of solution development for diagnosis and control of real-time cutting tool in for edge cutting machining. The functional model of a diagnosis subsystem based on data reading from sensors of various types established in a cutting zone is developed. Algorithms of subsystem accepted signals processing and averaging, allowing define condition of cutting tool with defined preciseness and it’s condition forecast in future are offered. Architectural features of subsystem program realization are exposed and solutions for integration into CNC system are described. Testing results of the diagnosis subsystem and its main algorithms during manufacturing processes control on turning machine tools are presented.
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Martinov, G.M., Grigoryev, A.S., Nikishechkin, P.A. (2015). Real-Time Diagnosis and Forecasting Algorithms of the Tool Wear in the CNC Systems . In: Tan, Y., Shi, Y., Buarque, F., Gelbukh, A., Das, S., Engelbrecht, A. (eds) Advances in Swarm and Computational Intelligence. ICSI 2015. Lecture Notes in Computer Science(), vol 9142. Springer, Cham. https://doi.org/10.1007/978-3-319-20469-7_14
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DOI: https://doi.org/10.1007/978-3-319-20469-7_14
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