Verification and Validation of Rotating Machinery Using Digital Twin

Yasar Yanik, Stephen Ekwaro-Osire, João Paulo Dias, Edgard H. Porto, Diogo Alves, Tiago H Machado, Gregory Bregion Daniel, Helio Fiori de Castro, Katia Lucchesi Cavalca
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Abstract

Abstract Rotating machinery has extensive usage in industrial applications being either the main equipment (power plants) or auxiliary equipment (oil and gas exploitation). These are extremely complex systems that characteristically demand expensive maintenance programs, due to the high costs involved in an eventual shutdown. Consequently, critical faults diagnosis and prognosis are essential in the operation condition of those systems. Fault identification and classification criticality demand a robust verification of the codes and calculations, as well as a discerning validation of the numerical models used for rotating machinery. Hence, verification and validation (V&V) are an essential initial service for a digital twin (DT) so it may offer some advantages in this application. In this context, the following research question is proposed: Does V&V using DT improve data access and reduce the effort of data exchange? The following objectives are created to address the research question: perform a code verification, conduct the calculation verification, validate the models using two different validation approaches 1 and 2, and demonstrate easy access to asset data. For this study, two hydrodynamic bearings and a non-central disk were considered, representing a laboratory experimental setup. The validation metric requirement is promisingly satisfied for the disk and the bearings according to the validation approaches 1 and 2. Furthermore, validation approach 2 generates even more successful results than approach 1. Accurate estimation and reliable interpretation of the numerical model outcomes guarantee the DT application for future fault diagnosis and prognosis.
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基于数字孪生的旋转机械的验证与验证
旋转机械在工业应用中有着广泛的用途,无论是作为主要设备(发电厂)还是辅助设备(石油和天然气开采)。这些都是极其复杂的系统,由于最终关闭所涉及的高成本,通常需要昂贵的维护计划。因此,关键故障的诊断和预测对这些系统的运行状况至关重要。故障识别和分类临界要求对代码和计算进行强有力的验证,以及对用于旋转机械的数值模型进行识别验证。因此,验证和确认(V&V)是数字孪生(DT)的基本初始服务,因此它可能在此应用程序中提供一些优势。在此背景下,提出以下研究问题:使用DT的V&V是否改善了数据访问并减少了数据交换的工作量?创建以下目标是为了解决研究问题:执行代码验证,进行计算验证,使用两种不同的验证方法1和2验证模型,并演示对资产数据的轻松访问。在本研究中,考虑了两个流体动力轴承和一个非中心磁盘,代表了实验室的实验设置。根据验证方法1和2,可以很好地满足磁盘和轴承的验证度量要求。此外,验证方法2比方法1产生更成功的结果。数值模型结果的准确估计和可靠解释保证了DT在未来故障诊断和预测中的应用。
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来源期刊
CiteScore
5.20
自引率
13.60%
发文量
34
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