Intelligent diagnosis method and device based on ensemble learning framework, equipment and medium

A technology of intelligent diagnosis and integrated learning, applied in the direction of integrated learning, measuring devices, instruments, etc., can solve the problems of continuous update and expansion of the fault knowledge base, poor actual fault diagnosis, and a large number of calibration system equipment, etc., to achieve rich data types, The effect of improving the accuracy of fault diagnosis and fast operation speed

Pending Publication Date: 2021-03-16
泽恩科技有限公司
View PDF0 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In actual production, the application effect of the expert system in the fault diagnosis of the verification system is not good. On the one hand, the verification system involves a lot of equipment, and the cause of the fault is not all caused by a single problem, but often a combination of multiple situations. The fault knowledge base It needs to be continuously updated and expanded; on the other hand, the fault diagnosis of the verification system mostly uses the method of comparing the equipment measurement point data with the preset threshold value. The size of the threshold value setting is not based on the change of the variable factors associated with it. However, most of the adjustments are determined through expert experience and remain unchanged for a long time, lacking objectivity
[0004] For the above-mentioned related technologies, the inventor believes that there is a defect that the actual fault diagnosis is not good. Therefore, the fault diagnosis method of the metrological verification automation system needs to be further improved

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Intelligent diagnosis method and device based on ensemble learning framework, equipment and medium
  • Intelligent diagnosis method and device based on ensemble learning framework, equipment and medium
  • Intelligent diagnosis method and device based on ensemble learning framework, equipment and medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0060] In this example, if figure 1 As shown, the application discloses a method for intelligent diagnosis based on an integrated learning framework, comprising the following steps:

[0061] S10: Collect multi-source operating data of the automatic system for metrological verification of the target, and preprocess the multi-source operating data to obtain a corresponding failure data sample set.

[0062] In this embodiment, the target metrology verification automatic system is the verification system to be diagnosed; the failure data sample set refers to the data sample set whose operation state is the failure state in the multi-source operation data.

[0063] Specifically, the collection sources of multi-source operation data include the FDB database of the target metering and verification automation line, the line body monitoring software, and the operation data generated by various sensors. In this embodiment, the multi-source operation data includes multiple data types. T...

Embodiment 2

[0146] In an embodiment, an intelligent diagnosis device based on an integrated learning framework is provided, and the intelligent diagnosis device based on the integrated learning framework corresponds to the intelligent diagnosis method based on the integrated learning framework in the above-mentioned embodiments. Such as Figure 6 As shown, the intelligent diagnosis device based on the integrated learning framework includes a data acquisition module 10 , a data readable processing module 20 , a model training module 30 and a real-time diagnosis prediction module 40 . The detailed description of each functional module is as follows:

[0147] The data acquisition module 10 is used to collect the multi-source operating data of the automatic system for measuring and verifying the target, and preprocess the multi-source operating data to obtain the corresponding failure data sample set;

[0148] A data-readable processing module 20, configured to construct a target data set re...

Embodiment 3

[0171] In one embodiment, a computer device is provided, the computer device may be a server, and its internal structure diagram may be as follows Figure 7 shown. The computer device includes a processor, memory, network interface and database connected by a system bus. Wherein, the processor of the computer device is used to provide calculation and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs and databases. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used to store multi-source operation data, fault data sample set, target data set, online operation data and other intermediate processing data. The network interface of the computer device is used to communicate with an external termin...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to an intelligent diagnosis diagnosis method and device based on an ensemble learning framework, equipment and a medium, and the method comprises the steps of collecting multi-source operation data of a target metrological verification automatic system, and carrying out the preprocessing of the multi-source operation data to obtain a corresponding fault data sample set; constructing a readable target data set of a preset fault diagnosis model according to the fault data sample set, wherein the preset fault diagnosis model adopts an XGBoost model, training the XGBoost model according to the target data set, and taking the corresponding XGBoost model after training as a target fault diagnosis model; and acquiring online operation data of the target metrological verification automatic system in real time, and analyzing the online operation data according to the target fault diagnosis model to predict the fault condition of the target metrological verification automatic system. According to the invention, the fault condition of the metrological verification automatic system can be accurately predicted on line in real time, and the fault diagnosis efficiency and accuracy are improved.

Description

technical field [0001] The present invention relates to the technical field of power metering diagnosis, in particular to an intelligent diagnosis method, device, equipment and medium based on an integrated learning framework. Background technique [0002] With the continuous deepening of electric power information construction and the development of smart grid and artificial intelligence technology, the demand for intelligent metering equipment is increasing day by day, which makes the metering verification components tend to be automated, standardized and process-oriented. Promotion, people rely more and more on the verification assembly line. Once the verification line fails, the verification work errors and losses caused are several times or even dozens of times the labor cost. Therefore, it is important to do a good job in fault warning and quickly locate faults Realize the guarantee of full automation and intelligence. [0003] At present, the mainstream method of ver...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N20/20G01R31/00G01D21/02
CPCG06N20/20G01R31/00G01D21/02G06F18/2148G06F18/241
Inventor 何春平
Owner 泽恩科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap