Aiming at fault detection in industrial processes with nonlinear or high dimensions, a novel method based on locally linear embedding preserve neighborhood for fault detection is proposed in this paper. Locally linear embedding preserve neighborhood is a feature-mapping method that combines Locally linear embedding and Laplacian eigenmaps algorithms. First, two weight matrices are obtained by the Locally linear embedding and Laplacian eigenmaps, respectively. Subsequently, the two weight matrices are combined by a balance factor to obtain the objective function. Locally linear embedding preserve neighborhood method can effectively maintain the characteristics of data in high-dimensional space. The purpose of dimension reduction is to map the high-dimensional data to low-dimensional space by optimizing the objective function. Process monitoring is performed by constructing T2 and Q statistics. To demonstrate its effectiveness and superiority, the proposed locally linear embedding preserve neighborhood for fault detection method is tested under the Swiss Roll dataset and an industrial case study. Compared with traditional fault detection methods, the proposed method in this paper effectively improves the detection rate and reduces the false alarm rate.

Abstract-Utilization of window functions and interpolation algorithms for Fast Fourier transform can effectively restrain the spectral leakage and picket fence effect in situation of nonsynchronized sampling and non-interger cycle truncation. In this paper, an improved FFT approach for harmonic based on Nuttall self-convolution window triple-spectral-line interpolation is improved. The simulation results showed that the proposed method have a higher accuracy of harmonic analysis and could improve the anti-noise performance. In the paper ， triplespectral-line interpolation correction algorithm for Nuttall selfconvolution window is used to improve the accuracy and anti noise is the latest research results, by the simulation can prove the superiority of this algorithm.

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Nowadays, during the international negotiation on separating dispute areas, manual adjusting is lonely applied to the match between delimitation line and real terrain, which not only consumes much time and great labor force, but also cannot ensure high precision. Concerning that, the paper mainly explores automatic match between them and study its general solution based on Least-Cost Path Analysis. First, under the guidelines of delimitation laws, the cost layer is acquired through special disposals of delimitation line and terrain features line. Second, a new delimitation line gets constructed with the help of Least-Cost Path Analysis. Third, the whole automatic match model is built via M odule Builder in order to share and reuse it. Finally, the result of automatic match is analyzed from many different aspects, including delimitation laws, two-sided benefits and so on. Consequently, a conclusion is made that the method of automatic match is feasible and effective.

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