Industrial equipment digital twinning construction maintenance method and system based on data driving

A data-driven, equipment technology, applied in the field of data-driven digital twin construction and maintenance of industrial equipment, can solve the problem that the digital twin cannot take into account the scope of application and efficiency, and achieves overcoming the difficulty of mechanism modeling, low resource occupation, and high efficiency. Effect

Pending Publication Date: 2022-04-08
INST OF AUTOMATION CHINESE ACAD OF SCI
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Problems solved by technology

[0006] In order to solve the above problems in the prior art, that is, the construction and maintenance process of digital twins cannot take into account the scope o

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  • Industrial equipment digital twinning construction maintenance method and system based on data driving

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[0044] The application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, not to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

[0045] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0046] The present invention provides a data-driven digital twin construction and maintenance method for industrial equipment, which can construct digital twins for complex equipment with many users and a long equipment maintenance period, and learn industrial equipment labeling data...

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Abstract

The invention belongs to the field of industrial equipment digital twinning, particularly relates to an industrial equipment digital twinning construction and maintenance method and system based on data driving, and aims to solve the problem that the application range and efficiency cannot be both considered in the construction and maintenance process of a digital twinning body. The method comprises the following steps: learning industrial equipment labeling data through a data-driven deep learning network to construct a digital twinborn body, and carrying out multi-modal fusion; carrying out multi-modal fusion model training on data of different enterprises through federal learning; new sample space distribution is continuously learned through lifelong learning, and the multi-modal fusion model is updated online; and carrying out industrial equipment health management through the model. According to the method, a complex equipment health management scene in which mechanism modeling is difficult, data sharing is difficult and new fault types continuously occur in a long-term operation and maintenance process in a real industrial scene can be overcome, and the digital twinborn body is vivid, robust, robust and credible.

Description

technical field [0001] The invention belongs to the field of digital twins of industrial equipment, and in particular relates to a data-driven digital twin construction and maintenance method, system and equipment for industrial equipment. Background technique [0002] The health management of the whole life cycle of industrial equipment is an inherent requirement of intelligent manufacturing. As the complexity of industrial equipment becomes higher and higher, the use environment and working conditions become more and more diverse. At the same time, the society has higher and higher requirements for the safe and healthy operation of industrial equipment. At the same time, with the continuous development of artificial intelligence deep learning, sensor technology, and digital twin concepts. The application of new technologies to improve the health management needs of industrial equipment is also becoming more and more intense. The full-cycle health management of industrial...

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Application Information

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IPC IPC(8): G06F30/27G06K9/62G06N3/04G06N3/08G06N5/02G06V10/80
Inventor 张腾飞张桂刚王健
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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