Good response, in particular high sensitivity, of polyvinylidene fluoride (PVDF) attracts a lot of research works on its manufacturing process and applications. Polarization is an important factor that is influential to the performance of PVDF. In this article, a new polarization method using ITO (Indium Tin Oxide) glass is proposed. Different from the conventional poling method using metal eletrode coated onto PVDF film, ITO glass is used as electrode to transmit the electric field voltage into PVDF film for poling. With the advantage of applying higher electric field in the process of polarization and eliminating the occurrence of flashover and arcing efficiently, this approach can thus make PVDF film gain better electric output response. Also, thinner film is constructed would be another advantage of sensitivity improvement. Comparison with conventional method for regular polarization area is carried out by using both FTIR and DSC equipment. Piezoelectric charge constant d 33 and electricity output response as well as sensitivity of PVDF are measured in experiment, which indicate ITO glass poling method is superior to conventional technique.
This study proposes a hybrid optimization method which can help users to find optimal cutting parameters which will provide better efficiency and lower power consumption for a milling process. Empirical models including performance-power consumption characteristic curves of servo motors were built, and an optimization algorithm adopting the empirical models with procedure guiding function was developed. The empirical models were built based on the measurements from planned machining experiments with different combination of machining parameters including spindle speed, feedrate, and chip load, etc. After integrating the models and algorithm, an optimization system with human machine interface, which has procedure guiding function, was developed. The system can recommend optimal machining parameters for a milling process for shorter machining time and lower electricity costs based on the original machining parameters. Finally, cutting experiments were conducted to verify the proposed system, and the results showed that the proposed method can effectively enhance efficiency by 42.06% and save 34.74% in machining costs through reducing machining time and electrical power consumption.
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