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The electrical automation technology is an advanced technology, in power plants, mainly giving play to the role of monitoring, monitoring analysis for the operation condition of the electric, also can have the data signal feedback function. Electrical automation technology is mostly play the function of monitoring, during the running of the electrical equipment, the equipment running status monitoring, through the analysis of the data and feedback, can timely find problems arising from the operation, and warning. In power plants, the use of automation technology also analysis and remote data transmission, realize the online management of equipment, improving the efficiency and quality of power plants. Electrical automation technology applications for the future development of the power plant provide a favorable environment.

With the development of science and technology, people's demand for energy is more and bigger, in addition to consider renewable energy. Electricity management system to study the effects of energy saving effect is also very necessary measures. Development of a complete set of monitoring, energy saving, control of intelligent power management system has very important practical significance. Finally, the paper puts forward the energy saving effect of validation, the energy saving analysis and evaluation. Based on the research of the content of this article, it finally realizes the intelligent management and scientific control of electric equipment, to solve the management of electric equipment of large power place management control is limited by geographical, effectively eliminate the phenomenon of energy waste. This system has good scalability can be slightly modified to meet more big power.

Modern cameras typically consist up to dozens of individual optical elements to compensate for geometric and chromatic aberrations. In recent year, high-quality single lens imaging has been proved possible by eliminating aberrations with computationally. Point spread function (PSF) calibration is key technique for single lens imaging. However, the existing PSF calibration method is time-consuming and has to be completely repeated for every new lens. This paper proposes a fast PSF calibration to accelerate the process. A PSF model is firstly estimated from a group of single lenses, which is close to the ideal PSF for specific tested single lenses. Then the PSF model is used as the iterative starting point in the calibration optimization. Experimental results show that this method can significantly improve the efficiency of PSF calibration process, and deconvolution performance is competitive with existing methods.

Denoising is an important issue for laser active image. This paper attempted to process laser active image in the low-dimensional sub-space. We adopted the principal component analysis with local pixel grouping (LPG-PCA) denoising method proposed by Zhang [1], and compared it with the conventional denoising method for laser active image, such as wavelet filtering, wavelet soft threshold filtering and median filtering. Experimental results show that the image denoised by LPG-PCA has higher BIQI value than other images, most of the speckle noise can be reduced and the detail structure information is well preserved. The low-dimensional sub-space idea is a new direction for laser active image denoising.

In order to get precise thermal conductivity of biomaterial which is usually with a variety of shapes and sizes, small thermal conductivity sensor that could adjust to the features of biomaterial has been produced by MEMS (Micro-electromechanical Systems) technology. Experiments have been performed to test the performance of the sensor, and the results have shown that the sensor has a good performance in the measurement of thermal conductivity of biomaterial. In this paper, a numerical model was built to study the performance of the MEMS-based sensor in theory. Thermal conductivities of a series of materials were measured by numerical method using this model. Compared with the standard thermal conductivities of materials, the simulation results showed that this kind of the sensor is able to get an accurate thermal conductivities efficiently. The results in this paper have some guide meaning in the improvement of the MEMS-based thermal conductivity sensor.

New type Fe-Cu alloy is used in the bar of induction motor with compound cage rotor(IMCCR). In this paper, the preparation of three kinds of Fe-Cu alloy is introduced. The influence of its microstructures, hardness and impact toughness is studied by using metalloscope and scanning electron microscope. Meanwhile, physical propertie such as resistivity, and B-H curve is tested by using magnetic testing device and bridge circuit. The influence of carbon content changing on microstructure and performance of Fe-Cu alloy is analysised, which has positive significance to the new type material using in motor.

3kW two poles induction motor with compound cage rotor is illustrated in this paper, and 2-D thermal stress field of induction motor rotor is calculated and analyzed by finite element. Contrasting with common induction motor, induction motor with compound cage rotor has specific rotor shot shape and the bar is comprised of the upper compound material and the lower cast aluminium, which cause distribution of thermal stress is special. The motor with the rotor shot of compound material laid at single site is chosen to analyzing. The maximum thermal stress in the bar is calculated at different load, and the distribution of thermal stress in the bar is analyzed at rate load. The law of distribution of thermal stress in the bar has same reference value for designing new type of induction motor.

The problem of tracking for second-order dynamical systems subject to disturbance input is considered by using a complete parametric design approach. The goal of this problem is to design a controller such that the output of the controlled system robustly asymptotically tracks the output of the reference model, and the transfer function from the exogenous disturbance to the tracking error meets a prescribed norm upper bound constraint. Based on the complete parametric solution to a class of generalized second-order Sylvester matrix equations, complete parameterizations for all the controller gain matrices are established in terms of two set of freedom parameters. Also, based on these parametric gain matrices, the prescribed norm upper bound constraint is transformed into an equivalent constraint condition which restricts the choice of the freedom parameters. An example is utilized to show the effect of the proposed approach.