Method and device for detecting equipment health based on joint learning

A testing equipment and health technology, which is applied in the field of testing equipment health based on joint learning, can solve problems such as operational risks, waste of resources, and inability to detect and maintain equipment, and achieve the effect of solving testing and maintenance.

Pending Publication Date: 2022-03-01
ENNEW ICOME INTERNET TECH CO LTD
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Problems solved by technology

[0004] In view of this, the embodiments of the present disclosure provide a method and device for detecting equipment health based on joint learning, so as to solve the problems of operation risk and waste of resources caused by the inability to timely and accurately detect and maintain equipment in the prior art

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Embodiment Construction

[0027] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and techniques are presented for a thorough understanding of the embodiments of the present disclosure. It will be apparent, however, to one skilled in the art that the present disclosure may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present disclosure with unnecessary detail.

[0028] Federated learning refers to the comprehensive utilization of various AI (Artificial Intelligence, artificial intelligence) technologies under the premise of ensuring data security and user privacy, and joint multi-party cooperation to jointly mine data value and promote new intelligent business models and models based on joint modeling. Federated learning has at least the followi...

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Abstract

The invention provides an equipment health detection method and device based on joint learning. The method comprises the following steps: responding to device data of a target device with a detection demand sent by a participant in the joint learning architecture; extracting key feature data in the equipment data sent by the participants according to the detection requirements of the participants; compressing key feature data in the equipment data according to the attribute information of the target equipment; establishing an equipment health trend curve by using key feature data in the compressed equipment data; matching the equipment data of the target equipment with values on the equipment health trend curve; and determining the health state of the predicted target equipment according to a matching result of the equipment data of the target equipment and the values on the trend curve. According to the method and the device, the problems of operation risk and resource waste caused by incapability of timely and accurately detecting and maintaining the equipment in the prior art are solved.

Description

technical field [0001] The present disclosure relates to the field of energy technology, and in particular to a method and device for detecting equipment health based on joint learning. Background technique [0002] With the vigorous development of the energy industry, there are more and more applications of related energy equipment. This requires extensive maintenance of energy equipment. At present, the existing technology for the maintenance and maintenance of energy equipment is: to regularly check or maintain the equipment by manually setting the detection time, which causes a great waste of human resources and the manual detection is inaccurate and incomplete. [0003] How to carry out accurate and timely equipment maintenance and testing methods has become an urgent problem to be solved. Contents of the invention [0004] In view of this, the embodiments of the present disclosure provide a method and device for detecting equipment health based on federated learnin...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/00G06Q10/06G06K9/62G06N3/08
CPCG06Q10/20G06Q10/06315G06Q10/0639G06F18/22
Inventor 徐少龙张燧金成浩马家琳
Owner ENNEW ICOME INTERNET TECH CO LTD
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