基于数字孪生优化技术的智能电网中智能生产和配电线路系统的分析与开发

Q4 Engineering Measurement Sensors Pub Date : 2024-07-03 DOI:10.1016/j.measen.2024.101272
Thangaraja Arumugam , Nitin Kundlik Kamble , Venkataramana Guntreddi , N. Vishnu Sakravarthy , S. Shanthi , Sivakumar Ponnusamy
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引用次数: 0

摘要

数字孪生(DT)被定义为通过实时数据集表现的对象的虚拟演示。DT 通过人工智能来提高决策技术。DT 包括模拟、合并、观察、分析和保存等过程。DT 只是物理结构的精确再现。通过实时分析,DT 可用于发现和评估问题。在现实世界中存在之前,对物体进行事先分析和评估非常重要。这些数字孪生有助于生产线系统的制造和实施。DT 包括生产线的工位划分和装配过程操作条件所需的时间。这些系统的集成可降低总体成本参数。采用物理模拟模型可在降低成本的同时获得更高的性能。在优化过程中使用了带有遗传算法的人工神经网络,以实现使用数字双胞胎的生产线系统。
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Analysis and development of smart production and distribution line system in smart grid based on optimization techniques involving digital twin

The term Digital Twin (DT) is defined as the virtual demonstration of an object that is represented through real-time datasets. DT is done through artificial intelligence to enhance decision-making techniques. DT includes the process of simulation, amalgamation, observation, analysis, and conservation. The DT is simply the exact reproduction of the physical structures. DT is used in the identification and evaluation of problems through real-time analysis. It is important to have prior analysis and evaluation of the object before existing in the real world. These digital twins help in the manufacturing and implementation of the production line system. DT includes the production line with the station division and the hours needed for the operating conditions for the assembly process. The systems are integrated to reduce the overall cost parameter. The physical simulation model is employed to obtain higher performance with reduced cost. An artificial neural network with a genetic algorithm is used for the optimization process to achieve a production line system using digital twins.

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来源期刊
Measurement Sensors
Measurement Sensors Engineering-Industrial and Manufacturing Engineering
CiteScore
3.10
自引率
0.00%
发文量
184
审稿时长
56 days
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