Device status monitoring method, monitoring system and storage medium based on edge-cloud collaboration

A technology of equipment status and similar equipment, applied in general control systems, control/regulation systems, and program control in sequence/logic controllers, etc. question
CN112947290BActive Publication Date: 2021-08-20北京赛博联物科技有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
北京赛博联物科技有限公司
Publication Date
2021-08-20

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Abstract

The invention belongs to the technical field of equipment performance prediction, and relates to an equipment status monitoring method, a monitoring system and a storage medium based on edge-cloud collaboration. The method includes: collecting the operation information of at least one device; processing and caching the collected operation information; performing feature extraction on the cached operation information; including at least feature parameters and time stamps of data information corresponding to the extracted feature parameters , generate a data snapshot; transmit at least the index data set including the data snapshot, the device information corresponding to the data snapshot, and the event description to the database in the cloud and store it; The data layout of each level; the data layout of the corresponding index data set is displayed on the terminal communicating with the database. It can realize edge-cloud collaboration in the true sense, conduct comprehensive status monitoring on equipment, and improve the accuracy of equipment status evaluation and fault prediction.
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Description

technical field

[0001] The invention belongs to the technical field of equipment performance prediction, and in particular relates to an equipment status monitoring method based on edge-cloud collaboration, an equipment performance monitoring system based on edge-cloud collaboration, and a distributed storage medium. Background technique

[0002] Industrial manufacturing equipment is facing huge challenges in operation and maintenance. Unplanned downtime of equipment not only seriously affects manufacturing efficiency and quality, but also brings high maintenance costs to manufacturing companies. How to effectively and accurately maintain equipment has become an urgent problem to be overcome in the digital transformation of industrial manufacturing.

[0003] The predictive maintenance method is strongly recommended by the industry and is considered to be an effective means to deal with unexpected equipment downtime. Predictive maintenance is to monitor and evaluate the stat...

Claims

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