Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method for quickly screening steady-state condition data in large-scale process data

A technology of process data and steady-state working conditions, applied in other database retrieval, electronic digital data processing, other database retrieval based on metadata, etc.

Active Publication Date: 2017-08-01
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
View PDF9 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the sliding window method used in the prior art cannot adapt to the rapid

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
  • Method for quickly screening steady-state condition data in large-scale process data
  • Method for quickly screening steady-state condition data in large-scale process data
  • Method for quickly screening steady-state condition data in large-scale process data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0069] A method for quickly screening steady-state operating condition data in large-scale process data, comprising the following steps:

[0070] A. Initialization processing of steady-state data screening,

[0071] Perform data filtering on the data segment that needs to be filtered for steady-state working condition data,

[0072] According to the purpose of selecting data, the storage space with a length of n is selected as the sliding window, and the storage space is the minimum unit for judging the stability of the process data segment, wherein n represents the number of data contained in the sliding window,

[0073] According to the allowable deviation value α of a single data in a sliding window containing n data, calculate the threshold δ of the standard deviation of n data in the sliding window y ;

[0074] Calculate the mean value of n data at the starting position of the data segment as the initial value of the sliding window mean value

[0075] Calculate the s...

Embodiment 2

[0129] This embodiment is improved on the basis of Embodiment 1.

[0130] In step B, calculate the standard deviation σ of the data within the sliding window at time k+1 k+1 When the variance diff k+1 Make corrections. use diff k to diff k-n+1 The n variance data are fitted (k / 2k The rate of change of the slope at the diff k+1 The predicted value of diff′ k+1 , using diff k+1 with diff' k+1 Calculate the weighted average of σ k+1 . where diff' k+1 The weighting rate of is inversely proportional to the linearity of the fitted curve. by diff k+1 Correction can effectively reduce the interference of interference signals to the data screening process.

Embodiment 3

[0132] This embodiment is improved on the basis of Embodiment 2.

[0133]The system traverses the selected steady-state data segment ste, clusters the traversed data according to the density, and determines the abnormal data through the clustered local abnormal factors. According to the proportion of abnormal data detected, use diff k to diff k-n+1 The n variance data are fitted to the fitting curve for feedback correction. Through feedback correction, it is possible to improve the diff in Example 2 k+1 The accuracy with which the correction is made.

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 quickly screening steady-state condition data in large-scale process data. The method comprises the steps that A, steady-state data screening is initialized; B, a sliding window moves from a starting point to an ending point of data, a new data point enters the sliding window every time the sliding window moves, meanwhile, the starting point of the original data in the sliding window is abandoned, and a mean value and a standard deviation of the new data in the sliding window are calculated; C, the standard deviation of n pieces of new data contained in the sliding window is compared with a standard deviation threshold value delta y, and corresponding screening operation is performed according to the comparison result; and D, the data at the two ends of a selected steady-state data segment are deleted, and the calculation accuracy of a data steady-state value is improved. Through the method, defects in the prior art can be overcome, and the screening speed of the large-scale process data is increased.

Description

technical field [0001] The invention relates to the technical field of process data mining, in particular to a method for quickly screening steady-state working condition data in large-scale process data. Background technique [0002] In the process of process data model identification and parameter determination of system stable working conditions, it is necessary to apply the steady-state working condition data in the process data. For a large amount of process data, manual screening is time-consuming and laborious. Sliding window is a general data statistical processing method, which traverses data through a fixed-length window. For example, Chinese invention patent CN 103679218 B discloses a handwritten keyword detection method, which extracts the feature points of the text image to be detected by using a sliding window, and then compares it with the keyword feature library. However, the sliding window method used in the prior art cannot adapt to the rapid processing of...

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
IPC IPC(8): G06F17/30
CPCG06F16/907
Inventor 董泽尹二新
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com