EPLA电-气转换阀的退化预测

Jinjun Lu, Mengling Wu, Gang Niu, Liujing Xiong
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引用次数: 0

摘要

随着预测与健康管理(PHM)技术的不断发展,在新兴工业信息化和工业智能化的驱动下,数字孪生技术已成为智能制造和智能维护领域的新兴研究热点。针对EPLA电-气转换阀(EP阀)PHM存在故障数据丢失、物理特性复杂、失效机理未知等问题,提出了一种基于数字孪生(DT)技术的EP阀退化预测方案。该程序主要分为三个部分:物理实体模块、虚拟仿真模块和退化预测模块。首先,本文通过对EP阀电磁铁的加速降解试验,获得了DT工艺所需的物理实体信息,并对电磁铁的失效机理进行了探讨。然后,通过EP阀虚拟仿真建模和动态退化仿真,获得DT工艺所需的模型仿真信息。最后,提出了物理实体信息与模型仿真信息之间的信息交互方法,为退化预测提供了理论依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Degradation Prediction of EPLA Electro-Pneumatic Changeover Valve
With the continuous development of Prognostic and Health Management (PHM) technology, driven by emerging industrial information and industrial intelligence, digital twin technology has become an emerging research hotspot in the field of smart manufacturing and smart maintenance. Aiming at problems such as the loss of fault data, complex physics, and unknown failure mechanism in the PHM of EPLA electro-pneumatic changeover valve (EP valve), this paper proposes an EP valve degradation prediction scheme based on digital twin (DT) technology. The program is mainly divided into three parts: physical entity module, virtual simulation module and degradation prediction module. First, this article obtains the physical entity information required by the DT process through the accelerated degradation test of the EP valve electromagnet, and discusses the failure mechanism of the electromagnet. Then, this paper obtains the model simulation information needed by the DT process through EP valve virtual simulation modeling and dynamic degradation simulation. Finally, this paper proposes an information interaction method between physical entity information and model simulation information, which provides a theoretical basis for degradation prediction.
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