A novel control system design for automatic feed drilling operation of the PLC-based oil rig

Aiming at the difficulties in realizing the accurate control due to the nonlinearity of the automatic drilling system of oil drilling rig, a design scheme is proposed by giving a constant drilled-pressure to the rig for fuzzy control. Sampling error with changes in the signal was sent into the fuzzy controller, which turned the signal into a fuzzy volume. Subsequently, a precise volume was obtained accordingly and then added to an actuator for the motor control. According to the MATLAB simulation results, the response could be faster and more stable compared with the traditional control

Preparation of Freeze-Dried Porous Chitosan Microspheres for the Removal of Hexavalent Chromium

Novel porous chitosan microspheres were successfully produced by a freezing–lyophilization drying method in this study and were then used as adsorbents to remove a toxic iron metal, hexavalent chromium (Cr(VI)). The effects of the concentration of the chitosan solution, syringe diameter, and freezing time on the morphologies of porous chitosan microspheres were characterized. The metal ion adsorption for Cr(VI) was also studied. Results showed that freezing chitosan hydrogel beads at a temperature of −20 °C and subsequently lyophilizing the frozen structure allowed to easily obtain the porous chitosan microspheres with rough surfaces and large pores, which were more suitable for adsorption materials to remove metal ions. A chitosan solution concentration of 3% (w/v) and a syringe diameter of 500 μm allowed the porous microspheres to have a good sphericity, thinner pore walls, and small pore sizes. The adsorption capacity of porous chitosan microspheres for Cr(VI) increased with the increase in freezing time. The pH of the initial adsorption solution ranged from 3.0 to 5.0 and was beneficial to the maximum adsorption efficiency for Cr(VI). The porous chitosan microspheres prepared with 3% (w/v) chitosan solution at −20 °C for a freezing time of 72 h had a higher adsorption capacity of 945.2 mg/g for Cr(VI) than the those at 24-h and 48-h freezing times. Kinetic study showed that the adsorption process could be described by a pseudo-second order (PSO) kinetic model. The equilibrium adsorption rate constant and the adsorption amount at equilibrium for the porous chitosan microspheres increased with an increase in the freezing time, and those for the porous microspheres prepared with 3% chitosan solution at −20 °C for a 72-h freezing time were 1.83 × 10−5 g mg−1 min−1 and 1070.5 mg g−1, respectively. The porous chitosan microspheres have good potential to facilitate the separation and recycling of expensive and toxic Cr(VI) from wastewater

An Intelligent Multi-Sensor Variable Spray System with Chaotic Optimization and Adaptive Fuzzy Control

During the variable spray process, the micro-flow control is often held back by such problems as low initial sensitivity, large inertia, large hysteresis, nonlinearity as well as the inevitable difficulties in controlling the size of the variable spray droplets. In this paper, a novel intelligent double closed-loop control with chaotic optimization and adaptive fuzzy logic is developed for a multi-sensor based variable spray system, where a Bang-Bang relay controller is used to speed up the system operation, and adaptive fuzzy nonlinear PID is employed to improve the accuracy and stability of the system. With the chaotic optimization of controller parameters, the system is globally optimized in the whole solution space. By applying the proposed double closed-loop control, the variable pressure control system includes the pressure system as the inner closed-loop and the spray volume system as the outer closed-loop. Thus, the maximum amount of spray droplets deposited on the plant surface may be achieved with the minimum medicine usage for plants. Multiple sensors (for example: three pressure sensors and two flow rate sensors) are employed to measure the system states. Simulation results show that the chaotic optimized controller has a rise time of 0.9 s, along with an adjustment time of 1.5 s and a maximum overshoot of 2.67% (in comparison using PID, the rise time is 2.2 s, the adjustment time is 5 s, and the maximum overshoot is 6.0%). The optimized controller parameters are programmed into the hardware to control the established variable spray system. The experimental results show that the optimal spray pressure of the spray system is approximately 0.3 MPa, and the flow rate is approximately 0.08 m3/h. The effective droplet rate is 89.4%, in comparison to 81.3% using the conventional PID control. The proposed chaotically optimized composite controller significantly improved the dynamic performance of the control system, and satisfactory control results are achieved

Infrared and Visible Image Fusion Technology and Application: A Review

The images acquired by a single visible light sensor are very susceptible to light conditions, weather changes, and other factors, while the images acquired by a single infrared light sensor generally have poor resolution, low contrast, low signal-to-noise ratio, and blurred visual effects. The fusion of visible and infrared light can avoid the disadvantages of two single sensors and, in fusing the advantages of both sensors, significantly improve the quality of the images. The fusion of infrared and visible images is widely used in agriculture, industry, medicine, and other fields. In this study, firstly, the architecture of mainstream infrared and visible image fusion technology and application was reviewed; secondly, the application status in robot vision, medical imaging, agricultural remote sensing, and industrial defect detection fields was discussed; thirdly, the evaluation indicators of the main image fusion methods were combined into the subjective evaluation and the objective evaluation, the properties of current mainstream technologies were then specifically analyzed and compared, and the outlook for image fusion was assessed; finally, infrared and visible image fusion was summarized. The results show that the definition and efficiency of the fused infrared and visible image had been improved significantly. However, there were still some problems, such as the poor accuracy of the fused image, and irretrievably lost pixels. There is a need to improve the adaptive design of the traditional algorithm parameters, to combine the innovation of the fusion algorithm and the optimization of the neural network, so as to further improve the image fusion accuracy, reduce noise interference, and improve the real-time performance of the algorithm