In electronics manufacturing the time-pressure dispensing system has been widely used to squeeze adhesive fluid in a syringe onto boards or substrates with pressurised air. For accurate control of the fluid volume, it is vital to have a thorough understanding of the whole process. However, the complexity of the process, which includes air-fluid coupling and their nonlinear uncertainties, makes it difficult to obtain an accurate process model. Using the spectral method, an approximate fluid flow model for both the Newtonian and non-Newtonian fluid can be developed. By taking into account nonlinear flow passing through the valve, attenuation and time delay in the pneumatic lines, syringe chamber dynamics and fluid flow dynamics, a simple but effective model is derived to describe the whole dispensing system with reasonable accuracy. Experiments performed thereafter validate the model.
Gas sensors based on tin dioxide-carbon nanotube composite films were fabricated by a simple inexpensive sol-gel spin-coating method using PEG400 as a solvent. Nanostructured copper was coated on CNTs/SnO 2 film, and then copper was transformed into copper oxide at 250°C. Resistivity of the final composite films is highly sensitive to the presence of H 2 S, which became easily attached or detached at room temperature. The response and recovery time of the sensor are 4 min and 10 min, and the value of sensitivity is 4.41, respectively. Meanwhile, the CNTs/SnO 2 /CuO sensor also has low detection limit, high selectivity toward H 2 S, and stable performance with different concentrations of H 2 S.
In order to improve the control efficiency and balance accuracy of rotor automatic balance, a fuzzy self-tuning single neuron PID control method is proposed in this paper. Based on the single neuron PID control method, the fuzzy control theory is introduced to adjust the output gain K of single neuron PID control to realize single neuron PID control with variable step size. In order to verify the superiority of this method, the method we designed in this paper is compared with the traditional PID control method and the single neuron PID control method by the simulation and self-built experimental platform. Experiments and simulation results show that the fuzzy self-tuning single neuron PID control method has faster response time, less overshoot amount and fewer oscillation times than the traditional PID control method and the single neuron PID control method, and has strong robustness and good stability.
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