A hybrid teaching model which combines traditional classroom with online learning emerges as the times require. Hybrid teaching uses information technology to reorganize the various elements of teaching so that traditional teaching and new technology application can complement each other, and gradually get the attention and attention of teachers and students. This paper compares the mixed teaching with the traditional single teaching, and discusses the role of the mixed teaching mode in promoting the personalized learning of the public basic courses of electrical engineering major in higher education and its impact on the learning quality of students. This paper has consulted a large number of relevant materials of mixed teaching evaluation, the methods of mixed teaching evaluation by different experts are sorted out, and the necessity of mixed teaching is verified through the combination of questionnaire and practice. This study finds that, compared with a single teaching method, mixed teaching is conducive to improving students’ autonomous learning ability and promoting students’ individualized learning. By comparison, the handing-in rate of students’ homework with mixed teaching is as high as 98.67%, and the quality of homework is also significantly improved. Students’ acceptance of the mixed teaching model is as high as 95%, which provides a very important reference value for the education industry to carry out the mixed teaching.

To improve the reconfigurable micro mobile robot cluster system based on precision detection, a positioning and tracking system based on computer digital image processing technology was developed. The system consisted of three subsystems: image acquisition and preprocessing subsystem, rapid positioning subsystem based on robot marker recognition, and tracking subsystem based on position estimation. First, after studying the related algorithms in the subsystem, the threshold selection method of adaptive gray weight conversion was proposed for image preprocessing. Then, a fast positioning method based on marker recognition for miniature mobile robots was proposed. The selection of micro-robot markers and the basis for judging the selection of moments were given. A triangular projection positioning method was implemented, and related experimental results were given. Finally, the windowing scanning algorithm was optimized. According to the speed and direction of the robot, a tracking algorithm for position estimation was proposed. Through the simulation experiment, the effect of system positioning tracking and the system reference time in 0.270 s were given. The results showed that the system had high real-time performance.

The application of remote digital video surveillance and image recognition technology in online monitoring of power equipment is conducive to timely equipment maintenance and troubleshooting. In order to solve the problem of slow speed and large amount of computation of traditional template matching algorithm for power image recognition, a second template matching algorithm for fast recognition of target image is proposed in this article. Firstly, a quarter of the template data is taken and matched within a quarter of the source image, and a reasonable error threshold is given in the matching process. Then, the neighborhood of the minimum error point in rough matching is matched to get the final result. Finally, the algorithm is applied to identify the power equipment and detect the abnormal state of the power equipment. The experimental results show that the matching algorithm can not only accurately locate and identify power equipment and detect equipment faults, but also greatly improve the matching speed compared with other commonly used template matching algorithms.

Single phase grounded fault of small current often occurrs in distribution network. In order to assure consumer an uninterruptible power supply. These are necessary: increase the diagnosis precision of single phase grounded fault in distribution network, locate the fault point of small current grounded and cut off the fault. This paper proposes an fault location algorithm based on RBFneural network. Some datas are analysed which are collected by the feedback terminal device in distribution network. The analysis results show that the change of zerosequence current is most evident. Therefore the zero-sequence current's value is consider as the input value of RBF neural network, the fault location of small current grounded is analyzed that based on the sample's trainning of existing zero-sequence current parameter. In the same time the ground fault of small current realize the real-time self-adapting location. In this paper, the MATLAB is used to do the simulation, the simulation results is close to the expect result. It shows the network can real-time accurately proceed test for the small current grounded fault of distribution network. In addition, field test demonstrates that the fault location of online state is feasible.

Wood is an organic renewable natural resource. Cellulose, hemicellulose and lignin in wood are used in tissue engineering, biomedicine and other fields because of their good properties. This paper reported that the possibility of wood fiber gel material molding and the preparing of gel material were researched based on the wood fiber gel material as a 3D printing material. A five-degree of freedom hybrid three nozzle 3D printer was designed. The structural analysis, static analysis, modal analysis and transient dynamic analysis of 3D printers were researched, and the theoretical basis of the 3D printer was confirmed as correct and structurally sound. The results showed that the 5-DOF hybrid 3-nozzle 3D printer achieved the 3D printing of wood fiber gel material and that the printer is capable of multi-material printing and multi-degree-of-freedom printing.