Soft measurement method and device for total phosphorus in effluent of agricultural sewage facilities based on artificial neural network

A technology of artificial neural network and effluent total phosphorus, applied in the direction of measuring devices, neural learning methods, biological neural network models, etc., can solve problems such as large quantities, achieve accurate prediction, improve reaction speed, avoid real-time and accurate detection poor sex effect

Active Publication Date: 2022-04-05
ZHEJIANG UNIV
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Therefore, the number of permutations and combinations of its indicators will be extremely large, and it cannot be selected through a limited number of experiments.

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  • Soft measurement method and device for total phosphorus in effluent of agricultural sewage facilities based on artificial neural network
  • Soft measurement method and device for total phosphorus in effluent of agricultural sewage facilities based on artificial neural network
  • Soft measurement method and device for total phosphorus in effluent of agricultural sewage facilities based on artificial neural network

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Embodiment Construction

[0030] The present invention will be further elaborated and illustrated below in conjunction with the accompanying drawings and specific embodiments. The technical features of the various implementations in the present invention can be combined accordingly on the premise that there is no conflict with each other.

[0031] The present invention constructs a soft measurement device for total phosphorus in the effluent of agricultural sewage facilities based on artificial neural network, wherein the agricultural sewage facilities are running A 2 O process or contain A 2 The rural domestic sewage treatment facility of the combination process of O, the soft sensor device includes the following components:

[0032] On-site condition monitoring equipment, including conductivity electrodes installed at the water inlet of rural domestic sewage treatment facilities to be predicted, A 2 O The dissolved oxygen electrode in the aerobic tank of the process and the pH electrode, conductivi...

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Abstract

The invention discloses a method and device for soft measurement of total phosphorus in effluent of agricultural sewage facilities based on an artificial neural network, belonging to the fields of water quality monitoring, artificial intelligence and the like. The prediction device first installs the operating state parameters of the electrode collection facilities such as influent conductivity, effluent conductivity, effluent turbidity, effluent pH, and aerobic pool DO in rural domestic sewage treatment facilities of different process types, and then uses the artificial intelligence embedded in the online data platform. Neural Network Prediction of Total Phosphorus Concentration in Facility Effluent. The relevant results show that the device and method have a good fitting effect and promotion value for the total phosphorus concentration in the effluent of the facility.

Description

technical field [0001] The invention belongs to the field of water quality monitoring, and in particular relates to a method and device for soft measurement of total phosphorus in effluent of agricultural sewage facilities based on an artificial neural network. Background technique [0002] Total phosphorus is one of the main monitoring indicators for the effluent quality of rural domestic sewage treatment facilities in my country. The current detection methods for total phosphorus are mainly manual sampling by operation and maintenance personnel and laboratory chemical detection. Although the measurement accuracy of this method is high, due to the scattered and large number of rural domestic sewage treatment facilities in my country, some prefecture-level cities already contain tens of thousands of rural domestic sewage treatment facilities, and the use of traditional chemical methods obviously requires a lot of manpower and material resources For operation and maintenance....

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01N27/00G06N3/08G06N3/04
CPCG01N27/00G06N3/084G06N3/04
Inventor 梁志伟林强罗安程张研
Owner ZHEJIANG UNIV
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