The invention relates to the technical field of crane swing angle prediction, in particular to a crane hook swing angle prediction method based on machine learning, which comprises the following steps: S1, collecting primary swing angle characteristic data of a crane under different wind loads; s2, preprocessing the primary pendulum angle characteristic data collected in the S1, establishing a data set, and dividing the data set into a training set and a test set; s3, training the data set to obtain a prediction model of the crane; s4, verifying the prediction effect of the prediction model; and S5, predicting the swing angle characteristics of the real crane hook by using the prediction model. The crane swing angle prediction method based on machine learning further has the following advantages that firstly, the learning process is fast, the training speed is high, the model generalization ability is high, and errors of an unbalanced data set can be balanced; and secondly, an optimization algorithm is adopted, so that an optimal result can be obtained.

    本发明涉及起重机摆角预测技术领域,具体涉及一种基于机器学习的起重机吊钩摆角预测方法,包括:S1:收集起重机在不同风载荷下的一级摆摆角特征数据;S2:对S1收集的一级摆摆角特征数据进行预处理,建立数据集,并将所述数据集分为训练集和测试集;S3:训练数据集,得到起重机的预测模型;S4:验证预测模型预测效果;S5:使用预测模型对真实起重机吊钩摆角特征进行预测。本发明基于机器学习的起重机摆角预测方法还具有以下优点:一是学习过程很快,训练速度快,模型泛化能力强,对不平衡的数据集,可以平衡误差;二是采用了优化算法,可以得到最优结果。


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    Title :

    Crane hook swing angle prediction method based on machine learning


    Additional title:

    一种基于机器学习的起重机吊钩摆角预测方法


    Contributors:
    QIAO WEILIANG (author) / LIN GUANGQING (author) / HAN BING (author) / HUANG ENZE (author) / GUO HONGTONGYANG (author)

    Publication date :

    2024-03-08


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B66C Krane , CRANES / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung



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