Modal identification method based on local density peak clustering

Abstract

The invention discloses a modal identification method based on local density peak clustering, and belongs to the field of modal identification of a multi-modal industrial process, and the method comprises the steps: collecting data in different modals of the multi-modal industrial process, and forming a to-be-identified modal data set; calculating an Euclidean distance between every two sample points in the data set, and determining a k-nearest neighbor set of each sample point; calculating the local density value of each sample point under the k neighbor set, and determining the minimum Euclidean distance from each sample point to the sample point higher than the local density value of the sample point; determining a sample point as a clustering center; distributing residual sample pointsto obtain a preliminary clustering result; and performing window division on the data set, and updating the sample points contained in each mode to obtain a final mode identification result. Loss ofthe clustering center of the transition mode can be avoided, and accurate identification of the starting point and the end point of the transition mode is realized.

Description

technical field [0001] The invention belongs to the field of multimodal industrial process mode identification, and more specifically relates to a mode identification method based on local density peak clustering. Background technique [0002] Multimodal processes widely exist in current industrial production. The multimodal characteristics of the process are often caused by factors such as changes in production environment and other conditions, changes in production plans, or inherent characteristics of the process itself. The multi-modal process includes stable mode and transition mode, and the statistical characteristics of different modes are obviously different. Different models should be established for process monitoring for different modes. Therefore, how to accurately distinguish and identify different stable modes and transition modes is the basis of statistical modeling of multi-modal industrial processes. [0003] At present, the commonly used multi-modal indust...

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Problems solved by technology

[0006] In view of the defects of the prior art, the purpose of the present invention is to provide a mode identification method based on local density peak clustering, which aims to solve the problem of low accuracy of mode identification in the existing mode identification method

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