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Method for predicting steam yield of steam boiler based on data mining

A technology of steam boiler and data mining, which is applied in electric digital data processing, design optimization/simulation, instruments, etc. It can solve the problems of low accuracy, long training period, and dependence on experience, so as to reduce dimensionality, save training time, The effect of high prediction accuracy

Pending Publication Date: 2021-06-04
QINGDAO HONGJIN E COMMERCE CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a method for predicting the steam output of steam boilers based on data mining, which solves the problems that the existing prediction methods rely too much on experience, have a long training period, and have low accuracy

Method used

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  • Method for predicting steam yield of steam boiler based on data mining
  • Method for predicting steam yield of steam boiler based on data mining
  • Method for predicting steam yield of steam boiler based on data mining

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Embodiment

[0024] A method for predicting the steam volume of a gas-fired steam boiler based on data mining. The specific implementation steps are as follows:

[0025] S1. Data acquisition

[0026] The production data of steam volume is selected from Fushide oil / gas steam boilers. The production data include ignition pressure, flameout pressure, steam pressure, steam temperature, boiler internal temperature, boiler feed water temperature, boiler return water temperature, boiler return water pressure, natural gas flow, Feed water pump speed, return water pump speed and steam flow. All the above data are collected every 1 second through the programmable controller PLC, collecting 72-96 hours of operation data.

[0027] The dataset is randomly divided into two parts, the first part dataset 1 has 4000 data points for training and developing predictive models through data mining algorithms, and the other part dataset 2 has 1000 data points for testing The predictive performance of the expor...

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Abstract

The invention discloses a method for predicting the steam yield of a steam boiler based on data mining, and relates to the technical field of steam yield production of gas steam boilers. According to the method, the steam generation process is analyzed, the data of the sensor of the steam boiler is taken as the basis, the steam yield prediction model is established by adopting the data mining algorithm, and the model can well predict the steam yield. According to the method, model parameters are selected by using a boosting-tree algorithm, a steam yield prediction model is established by using a fusion model of adaptive weight, and the performance of the prediction model is comprehensively tested and evaluated on the basis of five evaluation indexes. The input data is simplified, the data training time is saved, and the prediction precision is high.

Description

technical field [0001] The invention relates to the technical field of steam production of gas-fired steam boilers, in particular to a method for predicting steam production of steam boilers based on data mining. Background technique [0002] Gas steam boiler refers to a steam boiler that uses gas combustion to heat. The vertical steam boiler adopts the method of placing the burner below, with a two-pass structure, sufficient fuel combustion, stable boiler operation and less space occupation. At the same time, a spoiler is inserted in the smoke pipe to slow down the smoke exhaust speed, increase the heat transfer, and the boiler has high thermal efficiency. Reduce user costs; the horizontal steam boiler is a shell-type full-wet backflow three-pass pyrotechnic tube structure, the flame burns in a small positive pressure in the large combustion chamber, fully stretched, the combustion heat load is low, and the combustion heat efficiency is high, which effectively reduces Exha...

Claims

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Application Information

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IPC IPC(8): G06F30/27G06F119/22
CPCG06F30/27G06F2119/22
Inventor 于忠清李琳
Owner QINGDAO HONGJIN E COMMERCE CO LTD