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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

Active Publication Date: 2021-08-20
北京赛博联物科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the past, it was some low-frequency data, and the amount of data was not very large
Intelligentization requires more sensitive perception, and the perceived information contains a large amount of detailed information, which means a large amount of data. If all the data related to the health and working conditions of the equipment are sent to The cloud will inevitably cause the resources of the cloud data storage server to be tight, and will cause the useful data on the health and working conditions of the diagnostic equipment to be submerged in the massive data, making the server a slow and shrinking simple storage device

Method used

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

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0154] In view of the above problems, this embodiment provides a device status monitoring method based on edge-cloud collaboration, which captures device operation information including characteristic parameters such as current ripples, and cooperates with edge-side computing, cloud storage, and autonomous learning to monitor device status. monitor.

[0155] Such as figure 1 shown, and also refer to figure 2 The data flow diagram of the device status monitoring method based on edge-cloud collaboration is shown. The device status monitoring method based on edge-cloud collaboration includes steps:

[0156] Step S1): Collect the operation information of at least one device, the operation information includes at least one of current, voltage, vibration, noise, temperature, strain, and attitude.

[0157] In the prior art, PLC or ammeter is used for collection, usually a point is collected periodically, or an average value is obtained for a period of time. These methods have info...

Embodiment 2

[0265] Industrial artificial intelligence requires big data for autonomous learning. However, if all data is collected and sent to the cloud big data center through the industrial Internet of Things, the amount of data is too large, and massive data is a huge burden for cloud transmission, storage, and calculation. . If the results of simple calculations are only sent to the cloud, although the amount of data is reduced, there is no raw data of specific events, so it is impossible to form sample data for autonomous learning.

[0266] This embodiment provides a monitoring system corresponding to the edge-cloud collaboration-based device status monitoring method of the embodiment.

[0267] Such as Figure 6-1 As shown, a device status monitoring system based on edge-cloud collaboration includes an edge side 1, a cloud 2, and a terminal 3. The terminal 3 can be a mobile phone 31 or a computer 32, for example.

[0268] The edge side 1 includes a data acquisition unit 11, a data ...

Embodiment 3

[0321] This embodiment provides a distributed storage medium, which stores a plurality of instructions, which can be set in different location spaces or areas according to different processing functions, including:

[0322] Set on the edge side, suitable for being loaded and executed by the processor:

[0323] Collect the operating information of at least one piece of equipment, including at least one of current, voltage, vibration, noise, temperature, strain, and attitude; among them, at least one piece of equipment is the same type of equipment or different types of equipment in the same workspace , or the same type of equipment or different types of equipment in different workspaces;

[0324] Process and cache the collected running information;

[0325] Perform feature extraction on the cached operating information, and the feature parameters obtained by feature extraction include: at least one of amplitude, peak value, action time, frequency component or combined calculat...

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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.

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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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B19/05
CPCG05B19/058G05B2219/14006
Inventor 张颖华
Owner 北京赛博联物科技有限公司