基于IDBO-GRU的电磁斥力操动机构故障诊断模型研究

丁璨; 刘佳宇; 付博民; 贾振威

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基于IDBO-GRU的电磁斥力操动机构故障诊断模型研究

研究与分析 | 更新时间：2026-02-11

- 基于IDBO-GRU的电磁斥力操动机构故障诊断模型研究
- Fault Diagnosis Model of Electromagnetic Repulsive Actuator Mechanism Based on IDBO-GRU
- 高压电器 2026年
- 作者机构：
  
  1.三峡大学电气与新能源学院，湖北宜昌 443002
  2.电工材料电气绝缘全国重点实验室，陕西西安 710049
- 作者简介：
  
  丁璨(1982—)，男，博士，讲师，主要从事高压开关电器的实验、仿真及理论计算。(E-mail：dingcan@ctgu.edu.cn)。
  刘佳宇(2001—), 男，硕士研究生，主要研究方向为高压电器的故障诊断。(E-mail：liujiayu@ctgu.edu.cn)。
- 基金信息：
  
  电工材料电气绝缘全国重点实验室开放课题项目资助(EIPE23211)
- DOI：
  中图分类号：
- 收稿：2025-02-13，
  
  修回：2025-03-09，
  
  录用：2025-04-27，
- 稿件说明：
移动端阅览
丁璨, 刘佳宇, 付博民, 等. 基于IDBO-GRU的电磁斥力操动机构故障诊断模型研究[J/OL]. 高压电器, 2026.

DING Can, LIU Jiayu, FU Bomin, et al. Fault Diagnosis Model of Electromagnetic Repulsive Actuator Mechanism Based on IDBO-GRU[J/OL]. High VoltageApparatus, 2026.
丁璨, 刘佳宇, 付博民, 等. 基于IDBO-GRU的电磁斥力操动机构故障诊断模型研究[J/OL]. 高压电器, 2026. DOI：

DING Can, LIU Jiayu, FU Bomin, et al. Fault Diagnosis Model of Electromagnetic Repulsive Actuator Mechanism Based on IDBO-GRU[J/OL]. High VoltageApparatus, 2026. DOI：

摘要

针对电磁斥力操动机构的机械故障诊断率偏低问题，文中提出了一种基于改进蜣螂优化算法(IDBO)优化门控循环单元神经网络（GRU）的故障诊断方法。首先，采用最大奇异值能量熵方法(EEMSE)对机构的分闸振动信号进行特征提取构建特征向量矩阵，并利用Lasso回归系数和皮尔逊相关系数对特征矩阵进行降维。然后，引入Chebyshev混沌映射、黄金正弦策略、位置更新动态权重系数对传统蜣螂优化算法(DBO)进行改进，并使用IDBO对GRU超参数优化，建立基于IDBO-GRU的电磁斥力操动机构故障诊断模型。最后，搭建实验平台对模型进行验证，结果表明，建立的故障诊断模型诊断精确度达到96.88％，相较于其它诊断模型具有更高准确率和更好稳定性，为电磁斥力操动机构的故障诊断提供了一种新的诊断模型。

Abstract

To address the problem of low mechanical fault diagnosis rate of electromagnetic repulsive actuator mechanism

the paper proposes a fault diagnosis method based on the Improved Dung Beetle Optimization (IDBO)algorithm to optimize the Gated Recurrent Unit (GRU)neural network

which firstly adopts the Energy Entropy of Maximum Singular Value (EEMSE) to construct the feature vector matrix for feature extraction of the slamming vibration signals of the mechanism

and then utilizes the Lasso regression coefficient and the Pearson correlation coefficient to reduce the dimension of the feature matrix.Then

Chebyshev chaotic mapping

golden sine strategy

and dynamic weight coefficients of position update are introduced to improve the traditional Dung Beetle Optimization (DBO)algorithm

and the hyperparameter optimization of GRU using IDBO is used to establish the fault diagnosis model of electromagnetic repulsive actuator mechanism based on IDBO-GRU.Finally

the experimental platform is built to verify the model

and the results show that the diagnostic accuracy of the established fault diagnosis model reaches 96.88%

which is higher in accuracy and better in stability than other diagnostic models

and provides a new diagnostic model for the fault diagnosis of the electromagnetic repulsive actuator.

关键词

Keywords

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