Wind turbine spindle is the connecting part of impeller and *** has the function of transmitting torque and energy in the transmission chain of the *** needs to bear the bending moment and thrust of the wind wheel,so ...
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ISBN:
(纸本)9781509046584
Wind turbine spindle is the connecting part of impeller and *** has the function of transmitting torque and energy in the transmission chain of the *** needs to bear the bending moment and thrust of the wind wheel,so the failure rate of spindle is ***,the condition monitoring of the spindle is directly related to the stability of wind turbine and power *** spindle temperature model is established and used to predict by the nonlinear state estimate technology under the normal operating condition of the *** the spindle fails,the observation vector of the model input changes obviously,resulting in a significant change of the prediction *** order to improve the sensitivity and reliability of the spindle anomaly early warning,using the double moving window calculate the statistic properties of the residual sequence based on the Lewitt *** the residual mean or standard deviation exceeds the set fault alarm threshold,an alarm message will be *** the actual operating data of wind turbine spindles verify the validity of this method.
As an important research topic in computer vision, fine-grained classification which aims to recognition subordinate-level categories has attracted significant attention. We propose a novel region based ensemble learn...
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Randomness is common in many real industrial processes, its modeling problem has always been an important research content in the field of industrial control. Probability density function(PDF) is an effective means to...
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Randomness is common in many real industrial processes, its modeling problem has always been an important research content in the field of industrial control. Probability density function(PDF) is an effective means to solve the problem of stochastic distributed system modeling This paper based on Bspline basis function sets up the model of output and input data. Due to the fact that there are often many constraints in the actual industrial process and high requirements for real-time and accuracy, this paper proposes to combine the PDF model with predictive control to achieve effective tracking of system output setpoints. Predictive control optimization is more complicated and computationally intensive, so the predictive functional control (PFC) strategy is adopted to reduce the degree of freedom of the optimization problem. Applying PFC based on PDF modeling to the molecular weight distribution (MWD) of the polymerization process, and compared with generalized predictive control (GPC) algorithm, the validity of the proposed method is verified.
The output power of photovoltaic(PV) power generation system is related to solar irradiance,temperature,humidity and other meteorological *** output powers in the similar days,which are much alike in meteorological co...
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ISBN:
(纸本)9781538629185
The output power of photovoltaic(PV) power generation system is related to solar irradiance,temperature,humidity and other meteorological *** output powers in the similar days,which are much alike in meteorological conditions and social activities,will be more likely *** this paper,a prediction algorithm combining the time series and similar day is proposed to predict the power output of a PV *** this algorithm,the meteorological conditions of target days are predicted by the time series analysis,and the subjective weight and the entropy weight method are used to select the similar *** that,the target day's power output will be forecasted by tuning the weights of similar days' power *** on the actual data collected from an experimental system,the accuracy of prediction method is verified.
In recent years,the rapid development of big data technology has also been favored by more and more *** data storage and calculation problems have also been *** the same time,outlier detection problems in mass data ha...
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In recent years,the rapid development of big data technology has also been favored by more and more *** data storage and calculation problems have also been *** the same time,outlier detection problems in mass data have also come along with ***,more research work has been devoted to the problem of outlier detection in big ***,the existing available methods have high computation time,the improved algorithm of outlier detection is presented,which has higher performance to detect *** this paper,an improved algorithm is *** SMK-means is a fusion algorithm which is achieved by Mini Batch K-means based on simulated annealing algorithm for anomalous detection of massive household electricity data,which can give the number of clusters and reduce the number of iterations and improve the accuracy of *** this paper,several experiments are performed to compare and analyze multiple performances of the *** analysis,we know that the proposed algorithm is superior to the existing algorithms.
Taking an electrode-type electric boiler as the object, the factors influencing the thermal load of the electric boiler are analyzed. A prediction model for the thermal load is established with neural network, and the...
ISBN:
(纸本)9781538680988;9781538680971
Taking an electrode-type electric boiler as the object, the factors influencing the thermal load of the electric boiler are analyzed. A prediction model for the thermal load is established with neural network, and the model parameters are optimized by Gravitational Search Algorithm (GSA)to improve the convergence performance of its training process. The results show that, the neural network model can fit the nonlinear characteristics among input and output variables, and GSA significantly improves the training speed of the neural network model. The model can predict the electric boiler thermal load accurately under various conditions. It can also participate in peak regulation and frequency regulation of power grid combining with thermal power units, which can improve the operational flexibility of thermal power unit.
This paper applies ADRC algorithm to the inverted pendulum stabilization *** the extended state observer and control law can be nonlinear or linear,different combinations are designed to balance the pendulum's ***...
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ISBN:
(纸本)9781509046584
This paper applies ADRC algorithm to the inverted pendulum stabilization *** the extended state observer and control law can be nonlinear or linear,different combinations are designed to balance the pendulum's *** also offers a practical solution that the nonlinear parameters are tuned as the linear *** output response speed and control variable are compromised to determine the preferable *** showed that ADRC has good performance on stability,anti-interference and robustness.
The boiler drum water level reflects the equilibrium relationship between the steam load and the water supply of the drum boiler,which is an important monitoring parameter in boiler *** object has the characteristics ...
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ISBN:
(纸本)9781509046584
The boiler drum water level reflects the equilibrium relationship between the steam load and the water supply of the drum boiler,which is an important monitoring parameter in boiler *** object has the characteristics of non-self-balancing and pure delay,and its control quality directly affects the safe operation of a boiler-turbine *** on the improved gravitational search algorithm,the parameter optimization method of the main controller is put forward according to the wide-used cascade control structure of drum water level in power *** gravitational search algorithm has the advantages of simple process,little parameter setting,strong universality of the algorithm,but easy to fall into local *** with the memory function of particle swarm optimization algorithm and the high precision of other improved algorithms,the formulas of position and velocity are improved,an improved gravitational search algorithm(IGSA) is *** applying this method to the optimization control of the drum water level,and comparing with trial-and-error method(TEM),genetic algorithm(GA),and the standard algorithm(GSA),simulation tests are carried out to verify its effectiveness.
The main-steam temperature of thermal power units is an important control parameter to the safety and economic operation of the thermal power plant. In this paper, an ADRC based cascade control strategy is adopted in ...
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The main-steam temperature of thermal power units is an important control parameter to the safety and economic operation of the thermal power plant. In this paper, an ADRC based cascade control strategy is adopted in main-steam temperature system and its parameters are optimized by an adaptive chaotic particle swarm optimization (ACPSO) algorithm. This parameters optimization method breaks through the limitations of the conventional bandwidth method and the optimal ADRC parameters could be founded automatically to meet the practical control requirements. Simulation results indicate that the optimal design method is feasible, and that the ACPSO-optimized ADRC has better performance.
This paper covers the application of the cross-correlation method for measuring the velocity of solid particles. Capacitive electrodes are used as primary sensors to measure the time required by the solid particles to...
This paper covers the application of the cross-correlation method for measuring the velocity of solid particles. Capacitive electrodes are used as primary sensors to measure the time required by the solid particles to cover a known distance between the electrodes. The capacitive variations of both the electrode sensors are stored in computer synchronously for offline estimation of the velocity of the solid particles. Single glass marble is used as a solid particle to conduct the performance in the lab for its good signal to noise ratio (SNR) and vivid graphs. Matlab R2018a is used as a programming tool to perform the cross-correlation algorithm. The distance between the sensors is adjusted optimally. The results were realistic to ensure the correctness of the system.
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