In this paper, for the frequent faults problems of the mine air compressor main motor, we use the BP neural network learning algorithms on the basis of the theory of multi-sensor data fusion. The collected characteristic signals were processed by the method of data fusion, and we could get the current motor fault state value. Compared to the experimental results, it can realize the fault diagnosis of mine equipment obviously.

The equivalent circuit diagram was established based on the internal structure of the photovoltaic cells, and a simulation model of the photovoltaic cells was built in Matlab/Simulink, which could simulate the output characteristics of the cells under different temperatures and light conditions. According to the separate simulation of the perturbation & observation and fuzzy-control algorithms, the results show that fuzzy control has better performance when dealing with this non-line system.

In order to solve the air supply pressure instability problem in mine compressor, a fuzzy-PID controller is designed to be combined with conventional proportional-integral-derivative (PID) control and fuzzy control technology based on the programmable logic controller (PLC), where the compressor air supply system can achieve optimal control based on the system requirements and the actual usage, realizing air supply with constant pressure for compressor.

In order to establish a larger sensing area (10m×10m) and perform higher precision of the measurement system during barrel weapon test of vertical target dispersion, an optical detector is provided additionally in acoustic array to form a new measurement model, which does not only have the advantage of large sensing area, but also of higher precision. The paper presents and gives the measuring formula of the measuring model, and provides analysis on the measurement error. The simulation result showes that the errors of x and y Coordinates are 5mm and 15mm respectively.

A well-performed switched reluctance motor drive system was designed, and the diagram of the hardware on the basis of control system by TMS320F28335 chip was given. A fuzzy PI control method is developed to control SRM in drive system. On the platform of MATLAB/Simulink, the SRM drive system was researched and simulated. The stability of system is analyzed. The results indicated that the performance of SRM speed control system by fuzzy PI control algorithm is obviously better than that by conventional PI control algorithm.