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In the light of the structure and function properties of the GJW111 excavator, We propose the overall design and the framework system of fault diagnosis based on Multi-Agent System (MAS), express the process of fault diagnosis and introduce the components of the system. The system supports plug and play, which can improve its scalability.

Method of Moment is used to calculate vertical tail's radar cross section(RCS). The impact of leading-edge sweep angle, span and inclination on vertical tail's RCS is analyzed and then vertical tail's RCS curves and function expressions with leading-edge sweep angle,span and inclination are fitted by the calculation results.The results show that by optimizing the vertical tail leading-edge sweep angle, span, inclination and other geometrical parameters, can improve the stealth performance of the vertical tail. To optimize the design of the vertical tail of the stealth provide the technical foundation.

Due to the single BP network with the vehicle model is difficult to adapt to the complex traffic environment. Select the subject speed, the relative distance and relative velocity as the model variables. Construct the BP neural network of carfollowing model based on the real vehicle test, and use genetic algorithm to optimize the car-following model. The results show that the model has the highest accuracy, and the accuracy of the model is improved to 94.17% after optimization of the genetic algorithm.

The substance of the deployment of radar network is a multi-parameter optimization problem. This paper presents an objective function to deploy the radar network and a shuffled frog leaping algorithm (SFLA) is proposed to implement the radar network deployment. The proposed cultural shuffled frog leaping algorithm (CSFLA) makes use of mechanism of cultural evolution to update the locations of cultural frogs. Simulation results show that the proposed CSFLA has stronger abilities of exploitation and exploration by designing new leaping equations based on knowledge strategy and information communication, which may obviously improve the performance of SFLA. The radar network deployment based on the CSFLA is superior to previous deployment based on particle swarm optimization (PSO) and the SFLA in the convergence speed and optimization results. It provides a new idea to the radar network deployment.