Papers by Author: Jian Guo Cui

Abstract: Because of the complex structure, poor working conditions and lots of fault modes of aeroengine , it is necessary to monitor the operational status, accurate localization of aeroengine fault and identify fault to improve the safety and reliability of aircraft. Based on consistency fusion, this paper uses probabilistic neural network to monitor health condition of aeroengine and puts forward a combined method of health condition monitoring based on the consistency fusion and the neural network. The results of test show that this method can quickly monitor the health condition of the aeroengine and has certain reference value for other mechanical equipments condition monitoring.

Abstract: There is a great deal of uncertainty in spare parts inventory support process of aircraft hydraulic system, which cause its support decision difficult. Built integrated support decision model of the spare parts inventory based on sequence operation theory. Regard the quantity of the spare parts demand, maintenance and store as one-dimensional discrete random variable, analyzing the mutual effect among the random events utilizing addition type convolution, subtraction type convolution, and type product, thus give a dynamic description of the spare parts inventory integrated support process. Provide optimal decision basis for the spare parts inventory integrated support of aircraft hydraulic system. Results of the experimental indicated that the result of the support decision modeling consistent with the actual demand and the support decision model proved to be validated.

Abstract: In this paper, we discussed the trajectory tracking control problem of the kinematic model of wheel mobile robot. Designed an asymptotic stability tracking controller, using visual servo method based on inverse system and sliding mode variable structure control, and proposed a method to measure motion state of a target mobile robot. Simulation results show this method is feasible.

Abstract: In order to diagnose the health state of Aircraft effectively, a new method based on ARMA Model and probabilistic neural network(PNN) is proposed in this paper. First, an ARMA model is built using the original acoustic emission signal of aircraft crucial components, then use the autoregressive approximation theory to estimate model parameters, and order of the model is calculated according to Akaike Information Criterion(AIC). Use the autoregressive parameters to build feature vectors, then the probabilistic neural network is used to carry out the recognition of these feature vectors, and the health state of aircraft crucial components is effectively diagnosed. After the application on certain type of real aircraft, this method is proved to be capable of detecting the fatigue crack on crucial structural components. And we can conclude that the method is an effective way to carry out aircraft health diagnosis.

Abstract: On the basis of analyzing the character of target detecting and tracking algorithm, referencing the successful application of embedded system in the fields of electronics，signal processing and computer technology, combining target detecting and tracking and embedded technology, an embedded target tracking system is proposed which based on s3c24lO on which running clipping Linux system, and a tracking example of flying target is given. The whole system reaches the target of small size and good real-time. It’s a useful attempt to realize the small and intelligent of target tracking system.

Abstract: The SIFT feature matching can overcome the influence of revolve and scale. It can recognize runway effectively under the complex flight environment, but its computation is heavy. In order to reduce the computation, this paper proposes a new fast method of SIFT feature extraction. This method uses a group of concentric squares to construct the Pyramid-feature-descrptor, calculates each seed vector of the Pyramid-feature-descrptor by using the recursion algorithm, and carries simple sort on the elements of each seed vector to maintain the revolving invariability. The experimental result of identifing the runway indicates that this algorithm not only can increase the speed, but also can identify the runway effectively in revolving and scale.