Lian Xiaofeng

Image Fusion Method Based on NSCT and Robustness Analysis

Infrared and visible image fusion technology can effectively improve the image contrast and clarity, and enhance the night vision effective. Non-sub sampled contourlet transform (NSCT) in image fusion field has made some achievements. A regional standard deviation-weighted image fusion method based on non-sub sampled Contourlet transform was proposed, and the robustness of the method was analyzed. First, the reiterated infrared and visible images from the same scene were transformed by non-sub sampled contourlet transform, followed the approximate weight averaged, high-frequency detail components in accordance with the weighted of the regional standard deviation proportion, then the fusion image is obtained by inverse non-sub sampled contourlet transform, Finally, the fusion images were compared with the results obtained by Laplace transform, wavelet transform and contourlet transform through a large number of experiments, and the robustness analysis was done through the noise test. The results show that: non-sub sampled contourlet transform can achieve better fusion effect, and high robustness.

Fault diagnosis system for A 2 O process of urban sewage based on ASM2 model and expert system

For urban sewage treatment process of A2O, a fault diagnosis method based on parameter estimation of Activated Sludge Model No.2 (ASM2) model and expert system is proposed. Firstly, the A2O process is simulated based on Activated Sludge Model No.2 (ASM2) model, and then according it to calculate the estimated value of components parameter of biochemical reaction process, and compare it with the real value of corresponding parameter which provide auxiliary fault knowledge support for expert system. Furthermore, an expert system can draw fault diagnosis results is designed by means of uncertainty reasoning for expert knowledge based on RETE algorithm, which making full use of priori knowledge to diagnose effective for the fault reasoning. Finally, a fault diagnosis system for A2O process is developed. For a sewage treatment plant of Kunming, experiment result has shown that the fault diagnosis system for A2O process can make effective diagnosis of the actual process issues, and it has certain engineering practicability.

A novel ASM2 and SVM compensation method for the effluent quality prediction model of A 2 O process

For the soft measurement of water quality for sewage treatment process, a novel prediction model is proposed to predict the effluent water quality in this paper, which combines the mechanism model with compensation model. Firstly, the ASM2 model is built as the mechanism model to imitate the sewage treatment process, as well as PSO algorithm is used to adjust the kinetic parameters of the ASM2 model. Next, SVM regression is adopted to compensate the prediction error of mechanism model. Finally, the model is tested with real data collected in a sewage treatment plant. The simulation results show that the model can obtain accuracy prediction results and reflect the behavior of sewage treatment efficiently.

Panoramic image matching based on graph cuts algorithm

This paper proposes a method based on graph cut algorithm to match panoramic images. Label is denoted by disparity and the energy function is established, then the problem of matching can be converted into that of energy function minimization. A graph is constructed such that the energies can be related to the capacities of the cuts of the graph. The minimal energy is obtained by the network-flow theory, and hence the disparity data has been gotten. Consequently, we obtain the dense depth image. The experimental result shows that compiling with the other existing matching algorithm, the graph cuts algorithm can get better depth image, the high accuracy in the process to match the panoramic images reveal that it can be widely used in 3d indoor scene reconstruction.

Study on moving-objects identification based on evidence theory

A novel method of moving target identification based on multi-features fusion is proposed in this paper. Firstly, the distribution model of evidence weights is set up by the improved Dempster-Shafter (D-S) algorithm in order to solve the invalidation problem of highly conflict evidences. Then applies particle swarm optimization method to get the optimum evidence weights, which modify the original basic assignment function in the condition of ensuring the minimum of whole evidence conflict. This algorithm is used for video surveillance system to distinguish vehicle, people and other objects. Through analyzing the simulation example, the results show that the algorithm can gives a more reasonable combination results and has a good adaptive ability.

Research on DO control based on Fuzzy Smith-PID controller for sewage disposal

Considering the characteristics of the time-delay, inertia and time-varying of the dissolved oxygen (DO) control in the sewage disposal process, a Fuzzy Smith-PID control model is proposed based on the analysis of the regular PID and Fuzzy control in this paper, which integrates the advantages of the high robustness of the Fuzzy controller, the compensation of the time delay problem of Smith Estimation Machine and the high accuracy of PID controller. Simulation results show that this complex strategy has good robustness and stability in both of the model matching and mismatching situation, and provides an effective way to solve the problem of the time-delay, inertia and time-varying for sewage disposal system.

Remote control for robot manipulators with neural network compensation

A new remote time-delay feedback controller is presented for a class of robot manipulator systems with unknown nonlinear dynamics and communication time-delay. The proposed control scheme consists of a local neural network (NN) compensation and a time-delay feedback controller. A NN-based identification is first employed to identify the robot manipulator system. Local linearization compensation is then used to cancel the unknown nonlinearity of the system. The filter technology is utilized to obtain the time-delay-free inverse model of the linearized system and a desired reference model is used to constitute the feedback controller, which can achieve the tracking performance. Rigorous stability analysis and simulation are both included to verify the effectiveness of the proposed scheme.

A self-localization method for stereo camera on the mobile robot

In order to determine the position of stereo camera on the mobile robot, whose motion center is unknown, a simple and effective method is proposed. No calibration equipment is needed. By extracting natural scene features based on non-maximal eigenvalue suppress and Harris corner detector, and matching them using grey level correlation and scene constrains, the space transformation relation between robot motion coordinate and stereo vision coordinate is calculated analytically. Accuracy and error analysis and experiments show that the total error is less than 1 cm and the self-localization process is rapid, so it can satisfy the requirements of objects tracking, 3D environment reconstruction and mapping via stereo vision.