Fault detection based on k-nearest neighbor (FD-kNN) is one of the most widespread fault detection techniques for industrial processes under complex working conditions, owing to its characteristic of local modeling. However, its state separation ability tends to worsen when the operating data is heterogeneous distribution. To tackle this challenge, a weighted k-nearest neighbor fault detection method based on multistep index and dynamic neighbor scale is proposed. The multistep nearest neighbor index is defined to evaluate the state separation ability, and a weighted k-nearest neighbor fault detection framework is formed by the assigned weights obtained from kernel principal component analysis. On the basis above, a dynamic neighborhood scale correction method and a dynamic threshold setting strategy are proposed to deal with the heterogeneous distribution of operating data and track the abrupt change of the operation state. 10 common faults of wind turbines with complex operation conditions are used to verify the effectiveness of the proposed method.
Because multiple wind farms are connected to the grid at the same time and the total amount of energy in the same wind zone is limited, there is a strong correlation between wind farms with similar geographical locations. Neglecting this correlation can lead to a large difference between wind power analysis and actual operation, which in turn leads to a series of adverse consequences. In this paper, we use nuclear density estimation to establish the edge distribution of wind power output, compare and analyze various Copula functions based on correlation parameters and entropy weight optimization theory. The simulation analysis results show that the Clayton-Copula function is the best correlation function, which can describe the tail part of the random time series more accurately.
This paper attempts to present an optimal design strategy and characteristics of multipolar permanent magnet synchronous motor(MPMSM) with wide power for fully electric drive system(EDS). The structures of stator lamination, rotor lamination and stator winding are analyzed. And how temperature influences the performance of the motor is presented. Moreover, how to calculate air-gap length and the size of permanent magnet of MPMSM are discussed.
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