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    State monitoring variable optimization method based on mechanism data double-layer association network

    State monitoring variable optimization method based on mechanism data double-layer association network

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    The invention discloses a state monitoring variable optimization method based on a mechanism data double-layer association network. The method comprises the following steps: S1, obtaining a function module set, a state monitoring variable set and a corresponding time sequence data set; s2, establishing a monitoring variable correlation sub-network model G [alpha] oriented to mechanism correlation; s3, establishing a monitoring variable correlation sub-network model G [beta] oriented to data correlation; s4, constructing a mechanism-data double-layer association network according to the two sub-networks obtained in the steps S2 and S3; s5, according to the dual relevance of variables in the network, obtaining a low-relevance monitoring variable set from the two sub-networks by using the node degree and the relevance threshold value; and S6, obtaining an intersection, obtaining a monitoring variable set after preliminary screening, and screening out a final optimal variable set from the DV according to a minimum correlation principle. According to the method, comprehensive modeling analysis is carried out on the two relevance through a complex network, and the accuracy and comprehensiveness of relevance analysis can be effectively improved.

    本发明公开了一种基于机理数据双层关联网络的状态监测变量优选方法，包括以下各步骤：S1：获取其功能模块集合、状态监测变量集合及其对应的时间序列数据集合；S2：建立面向机理相关性的监测变量关联子网络模型Gα；S3：建立面向数据相关性的监测变量关联子网络模型Gβ；S4：根据步骤S2和S3得到的两个子网络，构建机理‑数据双层关联网络；S5：依据网络中变量的双重关联性，分别利用节点度和相关性阈值从两个子网络中得到低关联性监测变量集合；S6：求交集，得到初步筛选后监测变量集合，根据最小相关性原则，从DV中筛选出最终的优选变量集合。该方法通过复杂网络对这两种关联性进行综合建模分析，能有效提升关联分析的精准性和全面性。

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    Titel :

    State monitoring variable optimization method based on mechanism data double-layer association network

    Weitere Titelangaben:

    基于机理数据双层关联网络的状态监测变量优选方法

    Beteiligte:
    XU XIAOBIN (Autor:in) / JIANG KUAN (Autor:in) / ZHANG ZHENJIE (Autor:in) / HE HONG (Autor:in) / HOU PINGZHI (Autor:in) / ZHANG ZEHUI (Autor:in) / FENG JING (Autor:in) / CHANG LEILEI (Autor:in)
    Erscheinungsdatum :

    2024-04-19

    Medientyp :

    Patent

    Format :

    Elektronische Ressource

    Sprache :

    Chinesisch

    Klassifikation :

    IPC:    G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / B66B Aufzüge , ELEVATORS

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