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In view of the nonlinear, fuzzy relationship between fan fault reason and fault symptom, put forward a kind of threshold diagnosis strategy combined with fuzzy rules and case reasoning. Using a fan fault vector through fuzzy fault diagnosis model to compare with a given threshold, then generate the initial fault solution set, and finally using case-based reasoning thinking, accurate fault location. Then we verify the method’s effectiveness through a fault analysis of fan rotor vibration. The results show that the combination with fuzzy rules and case reasoning can effectively solve the problem of multi factors of failure reasons.

This paper introduces a kind of grid-connected micro-inverter system. Photovoltaic micro-inverter system is a highly nonlinear and time-varying system. Compared to traditional linear control strategy, Fuzzy Controller has better robustness and stability in the changing or non-linear application. Matlab simulation model for current tracking PV Grid-connected Micro-inverter was completed based on the Fuzzy self-tuning PI controller and the control strategy was tested on the micro-inverter prototype. The resu1ts show that this control strategy can effectively reduce the tracking error of the net current, and improve the system’s dynamic response.

In order to solve the problems of strong coupling and nonlinear parameters of superheater model, in this paper, we aimed at a 600MW subcritical drum boiler high temperature superheater as the object of study .On the basis of mechanism analysis and its dynamic characteristics I built a dynamic model of high superheater contains 9 typical working conditions .I optimized the model parameters by using field data. A continuous nonlinear model is obtained by curve fitting. The simulation results show that superheater model built by this method can better simulate the field characteristic. This model provides a reference design of automatic control system of main steam temperature .This paper aims to provide the basis for the application of advanced control algorithms in the field. Furthermore, this model can provide higher accuracy for on-site training to improve training effect.

In wireless sensor networks, the precise positioning of unknown nodes is the precondition and security for all kinds of applications. In this paper, by analyzing the present research status of personnel positioning algorithm and on the basis of the study of traditional centroid algorithm, an improved based on RSSI (Received Signal Strength Indicator) of the weighted centroid localization algorithm is proposed. The algorithm takes the signal intensity meanwhile the distance between the unknown nodes and beacon nodes as a reference to correct RSSI value. Through the simulation of the localization algorithm it proves that the improved localization algorithm has higher precision than the traditional algorithm. Once the accidents can be timely and efficient rescue for the underground staff, better meet the actual demand of safety management.

Whether the bed temperature of circulating fluidized bed boiler (CFBB) is stable or not affects the efficiency of the entire unit. According to the characteristics of an uncertain system with large delay, large inertia and time-varying of the bed temperature system, this paper proposed an adaptive dynamic matrix control (DMC) algorithm based on the real-time error correction. The algorithm can make the dynamic matrix controller more accurately, more flexibly and more applicably on reflecting system changes by revising the errors during the feedback regulating. The simulation results show that the control algorithm is of good adaptability and robustness and satisfactory control effect in the bed temperature system can be achieved.

The main steam temperature process has the characteristics of large inertia, large time delay and time-variation , to solve this problem, the fuzzy PID cascade control system with Smith predictor is presented .The improved Smith predictor with the effect of filtering was used in the main loop of the cascade control system, and fuzzy PID compound controller was used as the main controller based on the advantage of fuzzy control and PID. Through establishing the mathematical model and simulating the main steam temperature control system, either the parameter changed or invariable, the results show that the method can improve the control qualities and enhance the robustness and stability of the control system.

Aiming at the fault characteristics of high-speed gearbox fault diagnosis of wind turbine, a fault diagnosis method of combining wavelet analysis with least square-support vector machine (LS-SVM) is proposed. According to the method, the energy of frequency bands generated by wavelet decomposition and reconstruction of the high-speed gearbox's vibration signals in different fault states is normalized as eigenvectors, forming training and testing samples of LS-SVM fault classifier. Train the LS-SVM fault diagnosis model with the training samples and test the accuracy with the testing samples. The result of research shows that the fault diagnosis method based on the wavelet analysis and LS-SVM has good diagnostics effect.

In this paper, the Guodian Zhishen development of DCS as a platform, set up a thermal power plant 1000MW unit auxiliary power electrical system diagram AnySimu platform for simulation support system, and electrical network designed according to the principle of power flow calculation algorithm to calculate theeach node voltage, phase, and thus the load operator. After the simulation, verify the validity of the algorithm.

Abstract: For the control problem of nonlinear discrete systems, this paper describes the status of current research and analyzes the advantages and disadvantages of open-loop and closed-loop iterative learning controller. A class of nonlinear discrete systems will be extended to the general nonlinear discrete systems. To the general nonlinear discrete systems, a open-closed-loop PD-type iterative learning controller which based on current and last output error instead of last output error only is proposed. It makes use of information on system operation more fully and accurately. Besides, based on norm of λ and mathematical induction, its sufficient condition for convergence is given. In order to test its robustness, a simulation is done in the case of a persistent interference. Simulation results show that it is efficient.

Abstract: In order to solve the problem of slow convergence, an iterative learning control algorithm based on vector plots analysis is proposed. By introducing the geometric principle, that angle and side length of corresponding relationship in the same triangle, and transforming output’s error relationship into the relationship of the angel, the P-type is rewarded or penalized. The new algorithm with angle-correction speeds up significantly the convergence process. For illustration, a numerical simulation is utilized to show its efficiency and superiority. Empirical results show that the new algorithm is faster than P-type to make the system convergence .The method modifying P-type by angle is entirely feasible. The system’s output converges to the desired trajectory. The new algorithm can effectively solve the slow convergence problem. Introduction

ABSTRACTThe purpose of the research is to provide an example to analyze process performance for system assembly lines of notebook computer plants. The contributions include: 1) refining a manufacturing management model for system assembly line; 2) benchmarking performance indices in system assembly line; 3) conducting inefficiency analysis for the four plants and providing improvement suggestions; 4) using simulation method to simulate and evaluate the benefits after the process improvement. Simulations indicated that substantial improvements can be gained if the recommendations are adopted.

For the non-stationary characteristics of rotating machinery fault vibration signal, proposed a fault diagnosis method that based on ensemble local mean decomposition (ELMD) to extract fault feature, and fuzzy C-means clustering (FCM) to perform the fault identification. ELMD method can effectively solve the problem of aliasing modes in LMD. Firstly, decomposing the fault vibration signal by ELMD, PF components were obtained in which the initial feature vector matrix, The PF components compose a initial feature vector matrix, and do singular value decomposition, using the singular value decomposition feature vector as the fault characteristic vectors. Finally, using FCM clustering as a fault classifier. Achieved the identification of different fault types. Experimental results show that this method can effectively achieve the bearing fault diagnosis.