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The concept of multi-constrained analysis of the cutting process is presented for the first time in the paper. The paper adopts a method to solve an important problem which is how to judge the influence of constrains during the cutting process. The research results are applied for HSS drills for cutting stainless steel. On the basis of the multi-constrained analysis combined with methods of simulations and standard experiments, the optimum methods are provided for structure, coating and cutting parameters of cutting tools. For geometric structure of tools, optimization is to increase thickness of cutting and rake angle. Coating optimization strategy is choosing high temperature hardness and low thermal conductivity coating. Optimization of cutting parameter is to adjust feed fate, then select proper cutting speed. The conclusion of paper is helpful for the cutting optimization.

Due to a variety of electrical equipment using, the grid power quality severely polluted. For current harmonic signal is generated in hoist converter, the methods is proposed based on Hilbert-Huang Transform (HHT) to detect current harmonic signal and improved Active Power Filter (APF). The simulation mode is established by MATLAB/Simulink software about shunt APF+SPWM inverter hybrid active filter device for harmonic motion detection and suppression simulation. The results show that the harmonic of hoist converter can be detected by this design method real-time and the harmonic can also be suppressed validly.

Gas monitoring is considered as the most important mean in the safe production of coalmine. Time delay inevitably exists in the current gas monitoring technology widely used today. This research uses Support vector machine to forecast gas concentration. ZigBee wireless network protocol is adopted so that a wireless gas monitoring network with concentration predicting function is obtained. In this way the present time delay in Gas concentration monitoring will be improved and the scope of monitoring will be expanded at the same time

A supervisory control and data acquisition system is designed for wind farms, including the local controller and remote monitoring terminal. The data of the sensors collected by the lower-computer is transmitted to the host computer monitor terminal through the GPRS wireless network after preliminary treatment. In the host computer, the data is processed and displayed by the virtual instrument. The remote monitoring terminal can also send commands to control the actuators in the wind farm. Wavelet de-noising principle is used to process the data collected, improving the reliability and stability of the system.

Along with the tension of global energy and the improvement of environmental awareness, more and more Research institute begin examining how to change low-concentration gas into treasure. So we design the intelligent controller with ARM920T as its main control chip, set up an intelligent controller with two inputs, which will dilute the concentration from 4%-8% to 3.8% and the transmission can be carried out under constant pressure. We have made simulation toward the system by using Simulink in MATLAB and Fuzzy toolbox. The results show that the control effect turns out to be fine and has reached the performance indicators of power supply control system of low-concentration gas. This program will be proved to be an ideal intelligent control plan.

To reduce the frequent occurrence accidents of mining areas, a set of monitoring system of monitoring the operational status of mining equipment is designed. The information of electromechanical equipment are collected by the on-off sensors with anti-interference, which are converted to the standard RS485 interface signal though the MCU（Microprogrammed Control Unit）, and transmission to the monitoring platform by the bus transfer. The monitoring system is convenient and saves the cable, which can monitor the operational status of the field devices with accurate and real-time.