Time difference model-based soft measurement modeling method

A time difference and modeling method technology, applied in CAD numerical modeling, special data processing applications, instruments, etc., can solve problems such as spending a lot of time, reducing factory operating efficiency, and offsetting.

Inactive Publication Date: 2018-09-28
NANJING FORESTRY UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, most methods do not consider the time-lag of the modeling data when establishing the soft sensor model.
In fact, because the process variables obtained by online instruments usually imply a long measurement cycle and analysis time, and the aging of the measuring instruments leads to problems such as drift and offset of the measured variable data, which makes the soft sensor modeling we use The data are affected so that the built model cannot accurately explain the process characteristics of the variable
In addition, for the parameter model, as time goes by, the process variable data will change dynamically. If the parameters cannot be adjusted accordingly, the model will not be applied normally, but it will take a lot of time in the process of parameter adjustment. and reduce plant operating efficiency

Method used

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  • Time difference model-based soft measurement modeling method

Examples

Experimental program
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Embodiment 1

[0129] The sewage data is taken from the sewage test data of a sewage treatment plant. The data includes 8 variables and a total of 356 days of sample data, such as figure 2 , image 3 shown. figure 2 It is influent suspended solids (SS), influent biological oxygen demand (BOD), influent chemical oxygen demand, influent total nitrogen (TN), influent total phosphorus (TP), effluent COD and effluent TN; image 3 is the total flow of sewage influent (Q).

[0130] The above algorithm is simulated by MATLAB, and the present invention is further described in detail:

[0131] Step 1: Perform time difference processing on the collected 356-day measurement data. The latter 120 samples are used as the test set of the model to test the predictive ability of the model. The input variables of the model are total flow of sewage influent, suspended solids in influent, biological oxygen demand in influent, chemical oxygen demand in influent, total nitrogen and total phosphorus in influe...

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Abstract

The invention discloses a time difference model-based soft measurement modeling method. The method can be used for complicated industrial processes with nonlinearity, time lag, time variance, multi-variable coupling and other characteristics. The method comprises the following steps of: training and learning time differences of input data and output data so as to obtain difference recombination data, and carrying out data prediction by taking the difference recombination data as an input of a soft measurement model; and constructing a time difference-based soft measurement model to predict a response variable, and evaluating the prediction ability of the model. Through carrying out modeling prediction on practical sewage treatment data, a time difference model is capable of well processingdrift of input and output variables in the process so as to obtain implicit variable time lag information and dynamic information in the data; and the time difference-based soft measurement model iscapable of improving the prediction ability and generalization ability of the model, and is more suitable for complicated and variant wastewater treatment processes.

Description

technical field [0001] The invention relates to a soft-sensing modeling method for effluent indicators in the sewage treatment process, in particular to a soft-sensing modeling method based on a time difference correlation vector machine and typical correlation analysis. technical background [0002] Different industries have different attitudes and motives for control. In recent years, with the enhancement of people's awareness of environmental protection, the sewage treatment industry has the same advanced control as other heavy industries. And due to the unique characteristics of sewage treatment itself, for example, compared with most industrial processes, the daily water quality and quantity of sewage treatment plants fluctuate greatly; wastewater must be treated and discharged up to standard, unlike other industrial production that can be "returned to the factory" for treatment; because The content of pollutants in sewage may be very small, and the sensor is difficult ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50
CPCG06F2111/10G06F30/20
Inventor 刘鸿斌宋留杨冲
Owner NANJING FORESTRY UNIV
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