基于机液联合仿真模型的闸门启闭机故障注入及诊断研究

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振动与冲击 ›› 2024, Vol. 43 ›› Issue (13) : 198-209.

论文

李浩宇1，徐平2，铁瑛1，黄建章1

作者信息 +

Fault injection and diagnosis of gate hoist based on mechanical-hydraulic joint simulation model

LI Haoyu1, XU Ping2, TIE Ying1, HUANG Jianzhang1

Author information +

文章历史 +

摘要

为了对含故障特征的弧形闸门系统运行信号进行评估和故障诊断研究，基于某弧形闸门实验平台检测数据，建立弧形闸门启闭机构的机液联合仿真模型，进行模型相似度分析和修正。通过基于闸门实时开度反馈信号闸门状态控制策略对闸门进行工作状态的控制，提高了仿真效率和稳定性，获得更符合实际的状态特征。在模型中注入液压系统与机械系统故障，分析故障对闸门运行信号产生的影响。为了充分体现故障特征信息，选取多个信号进行融合并调整权重分配，基于加权多通道数据融合方法解决了故障识别精度波动大的问题，为了提高网络模型的泛化能力，在网络模型中加入残差结构进行优化，基于迁移学习的卷积神经网络解决了故障识别精度低的问题。结果表明，构建的模型可以表现出弧形闸门工作过程中重要信号比如压力、流量、振动等信号特征的动态变化；使用改进后的加权多通道数据融合的基于残差结构优化的神经网络准确率达到了97.17%。

Abstract

For evaluating the operating signal and fault diagnosis of the radial gate system with fault characteristics, based on the test data of a radial gate, a mechanical-hydraulic joint simulation model was established, the model similarity was analyzed and modified. Control the working status of the gate through a gate state control strategy based on real-time gate opening feedback signal，the simulation efficiency and stability were improved, more realistic state characteristics were obtained. Many faults were injected into the model to analyze the impact of faults on the gate. For reflecting the fault characteristic information, several signals were selected for fusion and weight distribution were adjusted, the problem of large fluctuations in fault identification accuracy was solved. For improving the generalization ability of network models, adding residual structure to the network model for optimization, the problem of low fault identification accuracy was solved. The results show that the model can show the dynamic changes of important signals such as pressure, flow and vibration; the accuracy of the neural network based on residual structure optimization using the improved weighted multi-channel data fusion is 97.17%.

导出引用

李浩宇1，徐平2，铁瑛1，黄建章1. 基于机液联合仿真模型的闸门启闭机故障注入及诊断研究[J]. 振动与冲击, 2024, 43(13): 198-209

LI Haoyu1, XU Ping2, TIE Ying1, HUANG Jianzhang1. Fault injection and diagnosis of gate hoist based on mechanical-hydraulic joint simulation model[J]. Journal of Vibration and Shock, 2024, 43(13): 198-209

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