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This Study Propose A New Approach To Impliment A Intelligent Robot Control Based on Voice Recognition For Smart Factory Automation Since human usually communicate each other by voices, it is very convenient if voice is used to command humanoid robots or the other type robot system. A lot of researches has been performed about voice recognition systems for this purpose. Hidden Markov Model is a robust statistical methodology for efficient voice recognition in noise environments. It has being tested in a wide range of applications. A prediction approach traditionally applied for the text compression and coding, Prediction by Partial Matching which is a finite-context statistical modeling technique and can predict the next characters based on the context, has shown a great potential in developing novel solutions to several language modeling problems in speech recognition. It was illustrated the reliability of voice recognition by experiments for humanoid robot with 26 joints as the purpose of application to the manufacturing process.
The flow characteristics of inertance pulse tube cryocooler(IPTC) was investigated with a computational thermal fluid dynamics for the reciprocating flow in IPTC including the piston movement of linear compressor. Two dimensional axisymmetric modeling was applied for the flow in an IPTC with a clearance between the piston and cylinder wall of linear compressor. The pressure, velocity, and temperature distribution were examined for the steady state. These were compared with previous results to confirm the validity in the modeling and computational results. The leakage between piston and cylinder wall affect the cooling capacity seriously. The dependence on mesh numbers were also examined to obtain a proper mesh numbers to improve the accuracy of calculation, which showed significant effect on the results. The user-defined function was used for the process of compression and expansion of piston.