This paper establishes the prediction model of low cycle fatigue damage of steam turbine rotor using the rich data from finite element analysis. In order to monitor the damage, a multiple regression analysis of input ...
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This paper establishes the prediction model of low cycle fatigue damage of steam turbine rotor using the rich data from finite element analysis. In order to monitor the damage, a multiple regression analysis of input data/output data with high correlation is made via dynamic PLS. The variation of the process parameters is extracted and it restrains the multiple dependency of the several parameters in different time series. Finally, a simulation of rolling process of a domestic 300MW turbine unit validates the effectiveness and accuracy of the prediction model based on dynamic PLS.
The purpose of HVAC system is to make occupants comfortable by adjusting the indoor thermal environment. The predicted mean vote (PMV) index is widely used to evaluate the indoor thermal comfort. However, PMV is diffi...
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The purpose of HVAC system is to make occupants comfortable by adjusting the indoor thermal environment. The predicted mean vote (PMV) index is widely used to evaluate the indoor thermal comfort. However, PMV is difficult to calculate in real time as its complicated mathematical functions. Meanwhile, the physical conception of the model and the impact on the output of model by the human conditions are often neglected by PMV modeling in previous literatures. In this paper, all the six variables of PMV are considered. The prior knowledge about the current working conditions are used to build the initial T-S fuzzy model. Then the ANFIS is used to train and adjust the parameters of the fuzzy model through the existing dataset. Simulation results show that this ANFIS method which is based on prior knowledge not only keeps the physical means of this fuzzy model but also improves the accuracy. Moreover it is superior to the model which does not consider the human variables in accuracy of model. The proposed method is effective and accurate.
In this paper, we investigate the dynamic modeling and trajectory tracking control of hard rock Tunnel Boring Machine(TBM). The acceleration equation, moment of momentum equation, kinematics equation and orientation e...
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ISBN:
(纸本)9781479937097
In this paper, we investigate the dynamic modeling and trajectory tracking control of hard rock Tunnel Boring Machine(TBM). The acceleration equation, moment of momentum equation, kinematics equation and orientation equation of TBM are built up. The dynamic mathematical model of TBM attitude is presented by composing of these four equations. The model provides a foundation for the trajectory tracking control of TBM behavior. Fuzzy PID controller is used to design velocity controller, vertical controller and lateral controller. The effectiveness of the proposed methods is shown by illustrative example.
The results of traditional traffic status analysis are mostly single values,whose accuracy can’t be determined;fuzzy c-means clustering(FCM)algorithm based on fuzzy theory can calculate the clustering center of plent...
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The results of traditional traffic status analysis are mostly single values,whose accuracy can’t be determined;fuzzy c-means clustering(FCM)algorithm based on fuzzy theory can calculate the clustering center of plenty data quickly and easily;linguistic dynamic systems could describe the dynamic rules of complex systems in the language *** this paper,membership functions are decided by FCM;result of a specific time period taken as one example is obtained;it’s discussed that linguistic dynamic analysis of traffic status in different period within a day by the same method.
In this paper, we present a new adaptive backstepping control design method to solve the overparametrization problem in parameter estimation. Unlike the existing schemes, the concept of tuning functions is not ***, th...
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In this paper, we present a new adaptive backstepping control design method to solve the overparametrization problem in parameter estimation. Unlike the existing schemes, the concept of tuning functions is not ***, the number of parameter estimates is reduced to be minimal, which is exactly the same as that of unknown parameters. The parametric strict-feedback system is employed to illustrate our design procedure.
This paper presents a compound fuzzy PID control strategy for the thrust hydraulic controlsystem of hard rock tunnel boring *** dynamic mathematical model of thrust hydraulic system is built and implemented in DSHplu...
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This paper presents a compound fuzzy PID control strategy for the thrust hydraulic controlsystem of hard rock tunnel boring *** dynamic mathematical model of thrust hydraulic system is built and implemented in DSHplus software *** control strategy of speed and pressure is proposed to handle the control problem of thrust hydraulic *** logic PID technique is adopted to deal with the nonlinearity of the thrust hydraulic *** are carried out to verify the performance of proposed compound control strategy.
In recent years, more and more plug-in hybrid electric vehicles (PHEVs) have been put to use in smart grid. In this paper, we consider a dynamic aggregator-PHEV system, where the aggregator convinces the PHEVs to use ...
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In recent years, more and more plug-in hybrid electric vehicles (PHEVs) have been put to use in smart grid. In this paper, we consider a dynamic aggregator-PHEV system, where the aggregator convinces the PHEVs to use electricity rather than gas by setting an appropriate charging price dynamically. We propose a payoff-maximizing algorithm for the aggregator to decide not only the charging price but also the electricity amount purchased from real-time power market based on Lyapunov optimization. Furthermore, we transform the power purchase problem into the energy allocation problem among all the PHEVs. The proposed algorithm operates in real time and does not require any prior knowledge of the statistical information of the system. Theoretically, we demonstrate the proposed algorithm can guarantee system stability and achieve a result that is away from the optimum by O(1/V ), where V is a control parameter. The effectiveness and robustness of the algorithm is validated through simulation results.
Dongba pictograph of China is presently accepted as the only pictograph in use,and Ancient Dongbaclassics are listed by the UNESCO as the "Memory of the World" in urgent need of rescue and inheritance throug...
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Dongba pictograph of China is presently accepted as the only pictograph in use,and Ancient Dongbaclassics are listed by the UNESCO as the "Memory of the World" in urgent need of rescue and inheritance through modern information *** paper argues the theory of Dongba pictograph character recognition based on the unique structural features of Dongba pictograph,and initially puts forward the implementation methods from image preprocessing stage to other processing stages like feature extraction,template matching,and neural network recognition,*** proves that these methods are feasible after the verification of experiments.
In the combustion system and ash fouling system of boiler,the furnace exit gas temperature(FEGT)is the key parameter for ensuring high *** it is hard to achieve satisfactory performance through conventional control st...
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In the combustion system and ash fouling system of boiler,the furnace exit gas temperature(FEGT)is the key parameter for ensuring high *** it is hard to achieve satisfactory performance through conventional control strategy,the control problem of FEGT has become critical and significant in coal-fired boiler *** this paper,a new predictive control scheme based on particle swarm optimization(PSO)and CM-LSSVM-PLS model is *** the proposed control scheme,a new CM-LSSVM-PLS method is proposed and used as the predictive model to predict the future *** the process of CM-LSSVM-PLS method,c-means cluster(CM)algorithm is used to partition the training data into several different subsets by considering the characteristics of operational *** sub-models are subsequently developed in the individual subsets based on least squares support vector machine(LSSVM).Then,partial least squares algorithm(PLS)is employed as the combination ***,PSO is used as the receding optimization *** proposed control is verified through operation data of a 300MW generating *** simulation results show that the effectiveness of our proposed control scheme.
The increasing demands on the indoor location service inspire the wide attentions to investigate the indoor position algorithms. Access point(AP) selection is critical important for increasing the estimation accuracy ...
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The increasing demands on the indoor location service inspire the wide attentions to investigate the indoor position algorithms. Access point(AP) selection is critical important for increasing the estimation accuracy of the indoor location. In this paper, the key features in influencing the accuracy of indoor location systems are investigated. Base on the analysis results, we present an AP selection strategy for indoor location by proposing a novel AP selection index for test point. By using the experiment data, the K-Nearest Neighbor(KNN) and weighted-KNN(WKNN) indoor location methods are carried out to illustrate the performance proposed AP selection strategy. The performance of our AP selection strategy is validated by comparing with the exhaustive AP selection strategy, the fisher AP selection strategy and the largest RSSI strength AP selection strategy. The experiment results show that the proposed AP selection strategy can improve the location accuracy of indoor location with Wi-Fi.
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