Sewage treatment process soft measurement method based on extreme gradient lifting algorithm

A technology of sewage treatment and soft measurement, applied in the direction of design optimization/simulation, etc., can solve problems such as difficult online measurement

Pending Publication Date: 2020-03-24
JIANGNAN UNIV
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Problems solved by technology

[0005] Aiming at the problem that the important indicator in the sewage treatment process: water ammonia nitrogen concentration is difficult to measure online, the present invention provides a soft-sensing method for sewage treatment process based on the extreme gradient lifting algorithm
Firstly, aiming at the problem of missing values ​​in the collected data of industrial processes, the proximity algorithm model is used to fill the missing values; secondly, the extreme gradient boosting algorithm is used for soft sensor modeling; finally, the grid search method is used to adjust the seven parameters of the model, so that Get a more accurate soft sensor model

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  • Sewage treatment process soft measurement method based on extreme gradient lifting algorithm
  • Sewage treatment process soft measurement method based on extreme gradient lifting algorithm
  • Sewage treatment process soft measurement method based on extreme gradient lifting algorithm

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Embodiment

[0071] Using a soft-sensing modeling method for sewage treatment process based on extreme gradient promotion proposed by the present invention, 8 production batches are taken, the cycle of each batch of data is 14 days, the sampling interval is 15 minutes, and each batch has 1344 sets of data , a total of 10752 sets of sewage treatment process data, each batch represents a complete sewage treatment process, of which 6 batches are used as training data sets for soft sensor modeling A i is a 1×4-dimensional row vector, a set of input quantities for soft sensor modeling samples, is A i The output of the corresponding soft sensor modeling sample, i=1,2,...,8064; 2 batches are used as the test data set of soft sensor modeling {(B 1 ,y 1 ),(B 2 ,y 2 ),…,(B 2688 ,y 2688 )}, B i is a 1×4-dimensional row vector, as a set of input quantities of soft sensor modeling samples, y i is B i Corresponding soft sensor sample output, i=1,2,...,2688. The specific implementation is as...

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Abstract

The invention provides a sewage treatment process soft measurement method based on an extreme gradient lifting algorithm, and belongs to the field of industrial sewage treatment process soft measurement modeling and application. Firstly, for the problem that missing values exist in data collected in the industrial process, a proximity algorithm model is adopted for missing value filling; secondly,soft measurement modeling is performed by using an extreme gradient boosting algorithm; and finally, seven parameters of the model are adjusted by using a grid search method, so that a more accuratesoft measurement model is obtained. The method can improve the prediction precision of the effluent ammonia nitrogen concentration in the sewage treatment process.

Description

technical field [0001] The invention belongs to the field of soft-sensing modeling and application in industrial sewage treatment process, and in particular relates to a soft-sensing method for concentration of effluent water quality parameters in sewage treatment process based on extreme gradient lifting algorithm. Background technique [0002] With the progress and development of the social economy, the pollution of the water environment by human beings is increasing day by day, and the efficient treatment of sewage has become more and more important for sustainable development. The concentration of ammonia nitrogen in water quality parameters is an important indicator to measure whether the water quality meets the national discharge standards. However, the current determination method for the concentration of ammonia nitrogen in water quality is cumbersome to operate, and the real-time performance is not high. Therefore, it is usually necessary to study the soft-sensing m...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/20
Inventor 潘丰李畅
Owner JIANGNAN UNIV
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