孙广西, 曹辉, 张子威, 等. 基于GA-GMDH算法的离心泵退化识别[J]. 中国舰船研究, 2024, 19(X): 1–9. doi: 10.19693/j.issn.1673-3185.03513
引用本文: 孙广西, 曹辉, 张子威, 等. 基于GA-GMDH算法的离心泵退化识别[J]. 中国舰船研究, 2024, 19(X): 1–9. doi: 10.19693/j.issn.1673-3185.03513
shu
SUN G X, CAO H, ZHANG Z W, et al. Centrifugal pump degradation identification based on GA-GMDH algorithm[J]. Chinese Journal of Ship Research, 2024, 19(X): 1–9 (in Chinese. doi: 10.19693/j.issn.1673-3185.03513
Citation: SUN G X, CAO H, ZHANG Z W, et al. Centrifugal pump degradation identification based on GA-GMDH algorithm[J]. Chinese Journal of Ship Research, 2024, 19(X): 1–9 (in Chinese. doi: 10.19693/j.issn.1673-3185.03513
shu

基于GA-GMDH算法的离心泵退化识别

Centrifugal pump degradation identification based on GA-GMDH algorithm

    摘要
  • 摘要:
    目的 为实时监测离心泵的健康状态，提出一种可实时识别离心泵退化状态的模型。
    方法 首先，基于离心泵的运行参数和退化机理，利用主客观相结合的组合赋权模型来计算组合权重，进而构建离心泵退化过程中的健康指标；然后，基于现有离心泵的退化数据，提出基于遗传优化–数据分组处理（GA-GMDH）算法的离心泵退化识别模型。
    结果 GA-GMDH监测模型的可靠性较高，其健康指标输出值与真实值的均方根误差为0.029 216，依据该模型输出结果进行退化状态识别的精度为93.333%。
    结论 研究成果可为离心泵的健康状态监测以及维护运营管理提供参考。

     

    Abstract:
    Objectives In order to monitor the health status of centrifugal pumps in real-time, a model for real-time identification of the degradation state of centrifugal pumps is proposed.
    Methods Firstly, based on the operating parameters and degradation mechanism of centrifugal pumps, a combined weighting model using a combination of subjective and objective weights is used to calculate the combined weights, and then a health index during the degradation process of centrifugal pumps is constructed. Secondly, based on existing degradation data of centrifugal pumps, a degradation identification model based on the genetic algorithm - group method of data handling (GA-GMDH) algorithm is proposed.
    Results The reliability of the GA-GMDH monitoring model is relatively high, with a root mean square error of 0.029 216 between the output values of the health index and the actual values. The accuracy of degradation state identification based on the model's output results is 93.333%.
    Conclusions The research results can provide reference for the health monitoring and maintenance operation management of centrifugal pumps.

     

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