A Method for Predicting Remaining Life of Heat Meter Based on Data Fusion of Multiple Degraded Samples

A technology of degradation data and life prediction, which is applied in the field of equipment safety, can solve the problem of low life prediction accuracy of heat meters, achieve the effect of facilitating subsequent data analysis and reducing training time

Active Publication Date: 2019-12-24
XI AN JIAOTONG UNIV
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a method for predicting the remaining life of a heat meter based on the fusion of multi-degraded sample data to solve the problem of life prediction of a heat meter based on a large number of actual case data of performance degradation. The problem of low precision

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
  • A Method for Predicting Remaining Life of Heat Meter Based on Data Fusion of Multiple Degraded Samples
  • A Method for Predicting Remaining Life of Heat Meter Based on Data Fusion of Multiple Degraded Samples
  • A Method for Predicting Remaining Life of Heat Meter Based on Data Fusion of Multiple Degraded Samples

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051] Degradation Index (DI) is a reference established for studying equipment performance degradation to quantitatively describe the degree of performance degradation, and is widely used in the fields of equipment performance degradation and remaining life prediction.

[0052] Support Vector Machine (SVM) is a powerful tool developed under the statistical learning theory system to realize the principle of structural risk minimization. It mainly realizes the principle of structural risk minimization by keeping the empirical risk value fixed and minimizing the confidence range. It is suitable for Learn from small samples. SVM is mainly used in the field of pattern recognition (classification), while Support Vector Regression (SVR) is extended on the basis of SVM theory. As a regression algorithm with known results, it has been widely used in the field of prediction. Applications.

[0053] One-class support vector machine (One-class SVM) is developed on the basis of SVM theory...

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 a method for predicting the residual lives of heat meters based on multiple degradation sample data fusion. The method comprises the steps that performance degradation data ofeach heat meter are obtained, a performance degradation index-residual life sequence set R of the N heat meters is established, and the performance degradation index-residual life sequence set R of the N heat meters is clustered by using a One-class SVM; and a regression model between degradation indexes and the residual lives are established by using the SVR, by utilizing the performance degradation data of the to-be-predicted heat meters at the current time and combining the regression model, the residual lives rul of the to-be-predicted heat meters at the current time are determined, and thus the residual lives of the heat meters are predicted. The analysis result of the method for predicting the residual lives of the heat meters is reliable, improving of the reliability of the heat meters can be promoted, and the reference means can be provided for quality verification of the heat meters in China.

Description

technical field [0001] The invention belongs to the technical field of equipment safety, and in particular relates to a method for predicting the remaining life of a heat meter based on data fusion of multiple degraded samples. Background technique [0002] As a measuring instrument, the heat meter is the basis for accurate measurement of the heating system. The performance change of the heat meter not only affects its own service life, but also has a great impact on the heat metering system in which it is located. Improving the prediction accuracy of the remaining life of the heat meter can not only ensure the long-term stable operation of the heat meter during use, but also further clarify the problems existing in the heat meter, and then take corresponding improvement measures to improve the reliability of the heat meter and promote the heat dissipation. The improvement of meter reliability can also provide a reference for the quality verification of heat meters in my cou...

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 Patents(China)
IPC IPC(8): G01K19/00
CPCG01K19/00
Inventor 姜洪权高建民高智勇王荣喜周涛刘东程梁泽明
Owner XI AN JIAOTONG UNIV
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