Transformer health prediction method based on digital twinning
A technology for health prediction and transformers, applied in transformer testing, nuclear methods, design optimization/simulation, etc., can solve the problems of insufficient virtual-real interaction, inaccurate PHM technology model, incomplete data, etc., and achieve the effect of improving its own operation efficiency
Pending Publication Date: 2021-04-20
JIANGSU UNIV OF SCI & TECH
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Problems solved by technology
[0004] The purpose of the present invention is to solve the problems of inaccurate models, incomplete data, and insufficient virtual-real interaction in the PHM technology used under the dynamic changes of the operating environment of the transformer.
Method used
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Embodiment
[0023] Embodiment: A transformer health prediction method, implemented based on digital twin technology. Such as figure 1 As shown, the method specifically includes the following steps:
[0024] Build a digital twin of a marine transformer:
[0025] Step 1. For the customized physical marine transformer, carry out signal acquisition, obtain the data used to characterize its operating state, and store it in the transformer data storage platform; the data used to characterize its operating state includes: the voltage of the marine transformer , current, temperature distribution, frequency, insulation detection, etc.
[0026] Step 2. For the structural material of the transformer to be predicted, establish a theoretical model for simulating the health of the transformer from the perspectives of electromagnetic mechanics and thermodynamics, and determine and verify the model that affects the health of the transformer in combination with the offline transformer health degradation...
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The invention relates to the technical field of marine equipment health degree prediction and particularly relates to a method for predicting the health of a marine transformer by using a digital twinning technology. The method comprises two parts of constructing a transformer digital twinning body and constructing a transformer health degree prediction model. By establishing a digital twin of a marine transformer, the health degradation tracks of the transformer under different working conditions are generated, and inconsistency of the transformer and changes of the environment and the working conditions can be effectively coped with. In combination with a machine learning model, a rapid transformer health prediction model can be established and updated regularly to cope with working conditions and environmental changes, and defects in the prior art are obviously overcome. Related difficulties of transformer fault prediction and positioning, low isolation capability, untimely equipment health degree management and the like in an original mode are solved, and meanwhile, the method has important significance for improving operation efficiency of the ship and exerting efficiency of related equipment of the ship.
Description
technical field [0001] The technical field of the present invention is designed to predict the health of marine equipment, specifically, a transformer health prediction method based on digital twins. Background technique [0002] As a large number of new ships adopting brand-new design concepts, advanced information technology, and new crafts are successively put into service in China, the complexity and technical requirements of their equipment have been greatly increased, and the frequency of failures of marine equipment will increase accordingly, and their maintenance requirements will also be greatly increased. Therefore, health prediction technology is one of the important technologies that ships rely on for normal navigation. Due to the development of sensing technology and Internet of Things technology, as well as the dynamic changes in the operating environment of complex equipment, the monitoring data volume of marine transformers has doubled accordingly, and presen...
Claims
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Login to View More IPC IPC(8): G06F30/27G06N20/10G01R31/62
Inventor 何祖军左文杰杨奕飞严志剑苏贞齐亮
Owner JIANGSU UNIV OF SCI & TECH