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Fault diagnosis method, device and equipment and storage medium

A technology of fault diagnosis and fault diagnosis model, which is applied in the field of equipment and storage media, devices, and fault diagnosis methods, and can solve problems such as low diagnostic efficiency, achieve accurate diagnosis, reduce low accuracy rate, and solve low fault diagnosis efficiency.

Pending Publication Date: 2021-04-06
SHANGHAI MUNICIPAL ELECTRIC POWER CO +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Embodiments of the present invention provide a fault diagnosis method, device, device, and storage medium, so as to solve the problem of low diagnosis efficiency during the fault diagnosis process of the edge side equipment of the Internet of Things

Method used

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  • Fault diagnosis method, device and equipment and storage medium
  • Fault diagnosis method, device and equipment and storage medium
  • Fault diagnosis method, device and equipment and storage medium

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0067] figure 1 It is a flow chart of a fault diagnosis method provided by Embodiment 1 of the present invention. This embodiment is applicable to the situation of diagnosing the fault of the edge side equipment of the power Internet of Things. This method can be executed by the fault diagnosis device in the embodiment of the present invention. The device can be implemented in software and / or hardware, such as figure 1 As shown, the method specifically includes the following steps:

[0068] S110. Acquire fault data of edge-side devices.

[0069] Specifically, the manner of acquiring the fault data of the edge-side device may be to collect the fault data of the edge-side device through a sensor.

[0070] Optionally, the sensor is used to collect the fault data of the edge-side equipment, and the fault data is stored in the sensor cache after being time stamped.

[0071] Specifically, multiple sensors are used to collect the fault data of the edge side equipment of the electr...

Embodiment 2

[0077] figure 2 It is a flowchart of a fault diagnosis method in Embodiment 2 of the present invention. This embodiment is optimized based on the above embodiment. In this embodiment, the missing fault data is completed to obtain the fault data to be diagnosed, including : Obtain the test sequence containing the missing fault data and the sample sequence of the complete fault data; complete the missing fault data in the test sequence according to the sample sequence to obtain the completed test sequence; if the sample sequence and the complete If the matching degree of the completed test sequence is the best match, the completed test sequence is used as the fault data to be diagnosed.

[0078] Such as figure 2 As shown, the method of this embodiment specifically includes the following steps:

[0079] S210. Acquire fault data of edge-side devices.

[0080] S220. Obtain a test sequence containing missing fault data and a sample sequence of complementary fault data.

[0081...

Embodiment 3

[0119] image 3 It is a schematic structural diagram of a fault diagnosis device provided by Embodiment 3 of the present invention. This embodiment is applicable to the fault diagnosis of the edge side equipment of the electric power Internet of Things. The device can be realized by software and / or hardware, and the device can be integrated in any device that provides the function of fault diagnosis, such as image 3 As shown, the device for fault diagnosis specifically includes: an acquisition module 310 , a completion module 320 and a diagnosis module 330 .

[0120] Wherein, the obtaining module 310 is used to obtain the fault data of the edge side device;

[0121] The completion module 320 is used to complete the missing fault data to obtain the fault data to be diagnosed;

[0122] The diagnostic module 330 is configured to process the fault data to be diagnosed through a fault diagnosis model to obtain a fault category, the fault diagnosis model is obtained by iterativel...

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Abstract

The invention discloses a fault diagnosis method, device and equipment and a storage medium. The method comprises the following steps of: acquiring fault data of edge side equipment; complementing the missing fault data to obtain to-be-diagnosed fault data; and processing the to-be-diagnosed fault data through a fault diagnosis model to obtain a fault category, the fault diagnosis model being obtained by iteratively training a to-be-trained fault diagnosis model through a training sample set, the training sample set comprising a fault data sample and a fault category corresponding to the fault data sample. Through the fault diagnosis method, device and equipment and storage medium provided by the technical schemes of the invention, the problem of acquired data loss can be solved, the problems of low equipment fault diagnosis accuracy and low efficiency are effectively solved by adjusting the weight of each decision tree in the fault diagnosis model, and the fault category of the edge side equipment of an electric power Internet of Things is efficiently and accurately diagnosed.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of fault diagnosis, and in particular, to a fault diagnosis method, device, equipment, and storage medium. Background technique [0002] The Internet of Things is an intelligent network based on the development of network technology, database technology and communication technology. With the advancement of the construction of the power Internet of Things, various types of smart sensors have been added to the terminal equipment side of the power grid, and the amount of edge-side data collected by the sensors has shown an exponential growth. [0003] In the traditional power Internet of Things scenario, the fault diagnosis method of edge-side equipment is usually to upload the edge-side data to the cloud data center, and use cloud computing resources to analyze and diagnose the fault of edge-side equipment. However, this traditional diagnosis method has the following bottlenecks: First, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06Q50/06
CPCG06Q50/06G06F18/24323G06F18/214
Inventor 李大伟宋纯贺陈晓露俞睿默李姝周晓鹂贾耕涛于诗矛
Owner SHANGHAI MUNICIPAL ELECTRIC POWER CO
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