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Industrial sequential data missing filling method based on sectional state displaying

A sequence data and sequence technology, which is applied in the filling field of missing industrial sequence data, to achieve the effect of fast running speed and high precision

Active Publication Date: 2013-08-14
DALIAN UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

At present, there is still a lack of an effective method that can simultaneously solve the three problems shown above

Method used

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  • Industrial sequential data missing filling method based on sectional state displaying
  • Industrial sequential data missing filling method based on sectional state displaying
  • Industrial sequential data missing filling method based on sectional state displaying

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Embodiment Construction

[0020] In order to better understand the technical solution of the present invention, the present invention takes the lack of energy sequence data of metallurgical enterprises as an example, and describes the implementation of the present invention in detail in conjunction with the accompanying drawings. There are many types of energy sequence data in metallurgical enterprises, and different energy data present different characteristics, such as data with quasi-periodic characteristics and large data fluctuations, see Figure 2 (a) blast furnace gas intake flow data; with a relatively fixed For periodic data, see Figure 2(b) blast furnace gas flow data for coke oven usage; for data without obvious regularity, see Figure 2(c) blast furnace gas consumption for hot rolling users. The present invention divides different types of energy sequence data at different intervals, so that each sequence division can be represented by the same feature quantity, that is, the sequence form, and...

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Abstract

The invention relates to an industrial sequential data missing filling method based on sectional state displaying. The industrial sequential data missing filling method includes: firstly, separating to-be-filled target sequences in a non-equidistant manner, displaying states for the separated sequences through three characteristic quantities including amplitude level, variation tendency and wave magnitude, and then establishing a method for computing a similarity factor of state displaying, searching similar sequences by the computed similarity factor, and finally utilizing a machine learning method to train the similar sequences of the to-be-filled sequences so as to establish a data missing filling model to fill the missing data sequences. The industrial sequential data missing filling method can fill missing sequential data caused by data storage or transmission fault and the like in an industrial process, can further complete monitoring data, and can improve data reliability so as to provide guarantees to data based optimization, control and scheduling operation realized in the industrial process.

Description

technical field [0001] The invention belongs to the field of information technology, and relates to sequence non-equidistant segmentation, sequence shape representation, similar sequence search and echo state network modeling theory, and is a filling method for missing industrial sequence data based on segmented state representation. The present invention utilizes the existing historical data of the industrial site, first performs non-equidistant segmentation on the target sequence to be filled, and then expresses the shape of the segmented sequence through the three characteristic quantities of amplitude level, change trend and fluctuation size, and further calculates the sequence shape Represent the similarity coefficient, use the calculated similarity coefficient to find similar sequences, and finally use the machine learning method to establish a data missing filling model to realize the filling of missing data sequences. Thereby effectively guaranteeing the integrity and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 刘颖赵珺盛春阳徐世坤王伟
Owner DALIAN UNIV OF TECH
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