Ma Xianmin

Propulsion system control and simulation of electric vehicle in MATLAB software environment

According to vehicles dynamic characteristics and dynamics principle, the computer simulation model of electric vehicle (EV) is proposed to improve the design method for the propulsion drive system of electric vehicles. Mathematical models for every component in EV can be modeled in the corresponding blocks, and the transfer function of each block for simulation in MATLAB software environment is introduced. The suggested method is verified through design of an electric sedan in MATLAB environment, and may be useful reference in applications of design, control and simulation of electric vehicles.

Research on fuel injection intelligent control system

The novel fuel injection intelligent control system for SYT240 test platform is introduced in the paper. The design principle is described, the system architecture of the fuel injection automatic testing system is presented, the fuel injection intelligent control system is realized on the basis of PC and AT89C52 single chip microcomputer, and the function relationship of the injection oil capacity in different revolution and injection pressures is obtained. By the comparison experiment of the proposed system with the traditional control system, the fuel injection capacity of the fuel injection pump is improved in different revolutions and pressures, the system dynamic data can be real time displayed and monitored through the data communication module between PC and AT89C52 single chip microcomputer, which indicates that the designed system can automatically fulfill data acquisition of the fuel injection pump and has high test precision.

Analysis and Design of PDM Converter with High Frequency Link for HEV Drive System

A discrete pulse density modulation (PDM) converter with high frequency (HF) link is introduced to improve the performance of hybrid electric vehicle (HEV) drive system requiring high power density. The drive system is made of HF resonant inverter, HF transformer and PDM converter. The inverter changes battery DC voltage into AC signal with 20kHz, which is distributed as power sources for different equipments in HEV by the transformer. By mean of zero-voltage switching technique, the PDM converter transfers the HFAC signal into the single phase AC power with low frequency to drive induction motor. Based on the vehicle dynamic characteristics, the mathematic analysis of the PDM converter is presented, the operation principle and control strategy are described. The theory analysis shows that the proposed system has the advantages of higher energy density, flexibility in the choice of voltage levels in the HEV, and freedom from acoustic noise. The simulation results prove that the system has the merit of easy control, faster system response, and the lower switch losses

Fire detection method of mine belt conveyor based on Artificial Bee Colony algorithm

The detection of fire on mine belt conveyor is very difficult in traditional image processing method, a novel image processing method is proposed in this paper, which integrates Artificial Bee Colony algorithm, gray scale morphology and information entropy. In Artificial Bee Colony algorithm the best threshold is approached in parallel via the division of labor, cooperation and information sharing of employed bees, onlookers and scouts. The fitness function of Artificial Bee Colony algorithm is designed by 2D maximum entropy method and fire image thresholds are regarded as nectar source. In order to reduce image noise the close operation is applied based on gray scale morphology. Theory analysis and simulation experimental results indicate that the proposed method is useful to detect fire of mine belt conveyor in complex coal under ground environment.

Research on avoidance obstacle strategy of coal underground inspection robot based on binocular vision

In this paper, aiming at the problem of obstacle avoidance in coal underground inspection robot, a control strategy to improve the avoidance obstacle precision of the robot is put forward, which combines the ultrasonic detection ranging technology and image processing method of machine vision. Firstly the ultrasonic detection technology is used to detect the remote distance obstacle, then the image processing method is adopted to perform closed ranging observation of the shape. The experimental simulation results show that the proposed obstacle avoidance combined strategy has a good effect on the inspection and avoidance obstacle of the underground inspection robot.

A New Method of Image Denoising for Furnace Flame

Furnace flame image mainly contain impulse noise and Gaussian noise. For this feature, the denoise method of median filter and wavelet transform combined are proposed. The specific method is: Firstly, remove the impulsive noise for furnace flame with adaptive weight median filter, and then decompose the image with Daubechies. At last more effective filtering are used in different sub-bands, it adopt different approaches against the characteristics of the different sub-bands. Experimental results show that the proposed method can effectively remove the impulse noise and Gaussian noise and improve the quality of the flame image, and it is better than the traditional denoising method.

Monitoring System of Coal Electrical Haulage Shearer Based on Data Fusion Theory

The electrical haulage coal shearer is very important cutting equipment in underground digging coal working space and plays a vital role for the coal mining production. But the coal mining environments are very harsher than ground, the shearer is often broken and stopping work, so its working states must be monitored. In this paper, a novel coal real-time monitoring system for the electrical haulage coal shearer is proposed based on multi-sensor data fusion theory. The four different kinds of sensors are used to supervise temperature, smog thickness, motor voltage and current for the key parts of the shearer. Fuzzy logic characteristic fusion algorithm and the quantum neural network fusion algorithm are adopted for fault diagnosis. The ARM12 is used as the master chip to carry out the on-line monitoring running parameters, and the Lab VIEW software is used to real-time display the running state of the shearer via CAN bus. The theory analysis and simulation results show that the system has higher reliable and more practical.

Fire Detection Based on Image Processing in Coal Mine

Fire detection is very important in safety area, and at all times it is a difficult problem in coal mine. In this paper, a real-time fire-detector algorithm is proposed. In early stage there is no evident flame, and the temperature is low, the visible light is scarce, so the signal is difficult to achieve by ordinary color CCD. Here infrared CCD is employed as a probe, and obtained infrared image is input the computer, then fire recognition is determined based on image processing. Firstly, the grey scale binary image is partitioned by entropy threshold method and then smoothed by Median filtering. Then significant characteristics of flame are extracted and after normalization the foregoing data are input neutral network for recognition. All of the above clues are combined to reach a final decision. Experiment results show that the proposed method is successful in detecting fire or flames. In addition, it reduces the false alarms remarkably. It is also shown that the method works in a variety of conditions. The system has high validity and accuracy.

Optimization of PID parameters for coal gas monitored control system based on aritificial immune algorithm

Based on immune algorithm a novel optimization design scheme of PID speed controller parameters is proposed for the coal mine gas monitored control system in this paper. The principle of Immune algorithm is introduced, and the strategy of PID controller parameters based immune algorithm is discussed. According to the response between antigen and antibody, the PID controller parameters are optimized in order to make the local fan adjusted quickly and stably. The simulation show that immune algorithm PID controller has a faster response time and smaller overshoot compared with the traditional tuning method. It not only improved the adjusting time of local fan, but also achieved energy saving and wind saving. The strong robustness and high tracking performance of the control system applies to the coal mine environment.

Coal gas outburst predication and control based on RBF neural network

Coal gas outburst is very dangerous to mining workers, so the coal gas prediction and control in digging workplace are very important for safety production. In this paper, a novel the radial basis function (RBF) neural network gas prediction model is established to forecast the gas rush in coal workplace. The factors of producing gas are studied and the sample data are acquired from digging field, the input and output characteristics of RBF predicting model is analyzed, the fresh air flow press distribution in digging workplace is introduced and the control principle and schedule are described. The theory analysis and experiment results show that the proposed coal gas prediction and control model is feasible, and the predicting precise is enough for engineering application.