Supercharge Your Innovation With Domain-Expert AI Agents!

Electric energy metering equipment failure rate estimation method based on weighted nonlinear Bayesian

A technology of electric energy measurement equipment and failure rate, applied in computing, computer parts, instruments, etc., can solve problems such as the influence of the correctness of probabilistic methods and the difficulty in obtaining fault data.

Active Publication Date: 2019-11-01
HUNAN UNIV
View PDF8 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the difficulty in obtaining failure data of products in natural environments, reliability analysis generally belongs to the field of small samples
However, when there are outliers in the failure data, the correctness of the probabilistic method is easily affected

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
  • Electric energy metering equipment failure rate estimation method based on weighted nonlinear Bayesian
  • Electric energy metering equipment failure rate estimation method based on weighted nonlinear Bayesian
  • Electric energy metering equipment failure rate estimation method based on weighted nonlinear Bayesian

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0060] The present invention will be described in more detail below in conjunction with the accompanying drawings and embodiments.

[0061] Such as figure 1 Shown is the structural framework of the adopted method of the present invention, and concrete steps comprise:

[0062] Step 1, data collection and preprocessing;

[0063] Step 2, constructing a hybrid outlier discrimination method to discriminate the outlier data in the sample D;

[0064] First calculate the Pierman correlation coefficient between different environmental stress data and electric energy metering equipment, and then calculate the weighted kNN to obtain the outlier point z of the failure data oi The score of kNN(z oi ). Among them, weighted kNN uses weighted Euclidean distance when calculating the distance between data points, which is specifically defined as:

[0065]

[0066] Then use the contour coefficient and DBI to continuously optimize the appropriate parameter k of weighted kNN;

[0067] Ste...

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 discloses an electric energy metering equipment failure rate estimation method based on weighted nonlinear Bayesian. Reliable operation of electric energy metering equipment in a smart power grid is directly related to fair metering and power dispatching of electric energy. According to the technical scheme, the method comprises the steps that failure data and environmental stress data of the electric energy metering equipment are collected, a mixed abnormal value discrimination method based on a weighted kNN and a Shore Wiener criterion is adopted to discriminate data abnormal values according to sample set data, and weights of the abnormal values in the failure data are obtained; and a weighted nonlinear Bayesian model is established, the failure rate of the electric energymetering equipment is predicted and evaluated, and the reliability of the electric energy metering equipment is solved. The method achieves the estimation of the failure rate of the batch electric energy metering equipment, can be used for the quality evaluation and life prediction of the electric energy metering equipment, and provides suggestions and important references for the rotation, scheduling, bidding and storage of the equipment.

Description

technical field [0001] The invention belongs to the field of failure analysis and reliability prediction of electric energy metering equipment, in particular to a method for predicting the failure rate of electric energy metering equipment based on Weighted Nonlinear Bayesian (Weighted Nonlinear Bayesian, WBN). Background technique [0002] Electric energy metering equipment is the most important part of the power grid terminal, and the accurate measurement of electric energy is the guarantee and cornerstone of the healthy development of the smart grid. Especially in recent years, the goals of "Strong Smart Grid" and "Ubiquitous Power Internet of Things" proposed by my country have increased the reliability requirements of power equipment in typical environments. Commonly used electric energy metering equipment includes single-phase and three-phase smart energy meters and concentrators, etc. The electricity consumption, voltage and current information in the grid can be coll...

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): G06Q50/06G06K9/62G06F17/17
CPCG06Q50/06G06F17/17G06F18/24147Y04S10/50
Inventor 唐求邱伟滕召胜邱俊欧阳映彤覃玉红成达李宁
Owner HUNAN UNIV
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com