Online biochemical oxygen demand (BOD) soft measurement method based on dynamic feedforward neural network

A technology of biochemical oxygen demand and neural network, which is applied in the field of online soft measurement of biochemical oxygen demand based on dynamic feedforward neural network, can solve the problem of time-consuming and laborious, unable to reflect the actual situation of sewage treatment in time, and difficult to achieve closed-loop sewage treatment process Control and other issues

Inactive Publication Date: 2013-01-16
LIAONING TECHNICAL UNIVERSITY
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Problems solved by technology

Among them, the water quality parameter BOD refers to the amount of oxygen required to decompose a unit of organic matter within a specified time. At present, most sewage treatment plants use the dilution inoculation method and the rapid measurement method of microbial sensors to measure the biochemical oxygen demand BOD in different types of water. The BOD analysis test is determined The period is generally 5 days, which cannot reflect the actual situation of sewage treatment in time, and cannot realize real-time measurement of BOD, which directly makes it difficult to achieve closed-loop control in the sewage treatment process
In addition, the number and content of pollutants in sewage are large and varied, which is a big challenge for detection
The development of process measuring instruments in the form of new hardware can directly solve the problem of variable and water quality parameter detection in various sewage treatment processes, but due to the complexity of organic matter in sewage, developing these sensors will be a time-consuming and laborious project.

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  • Online biochemical oxygen demand (BOD) soft measurement method based on dynamic feedforward neural network
  • Online biochemical oxygen demand (BOD) soft measurement method based on dynamic feedforward neural network
  • Online biochemical oxygen demand (BOD) soft measurement method based on dynamic feedforward neural network

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Embodiment Construction

[0082] Embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0083] In the present invention, the auxiliary variables selected for soft measurement of BOD are DO, SS, PH, and COD, wherein DO is the concentration of dissolved oxygen in the influent water quality of the aeration tank, SS is the concentration of suspended solids in the influent water quality of the aeration tank, and PH is the concentration of suspended solids in the influent water quality of the aeration tank. The pH of the water quality of the aeration tank, COD is the amount of oxygen required by the oxidized substances in the water quality of the aeration tank when it is oxidized by a chemical oxidant. Except for PH, which has no unit, the units of other auxiliary variables are mg / L;

[0084] The embodiment of the present invention adopts the water quality analysis data of a sewage treatment plant in 2010, and all the experimental data samples are...

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Abstract

The invention discloses an online biochemical oxygen demand (BOD) soft measurement method based on a dynamic feedforward neural network. The method comprises the following steps of: designing a dynamic feedforward neural network topological structure for BOD soft measurement of a sewage aeration tank, determining an input sample of the dynamic feedforward neural network, and performing online normalization processing on the input sample; calculating the variation condition of an ownership connection value connected with a hidden node in the neural network in each training process by employing a standardized data training neural network, judging the activeness of the hidden node, and splitting the hidden node with high activeness; judging the capacity of learning information of the hidden node by calculating the absolutely output variation condition of the hidden node in the training process, and deleting a hidden node without the learning capacity; adjusting parameters of the neural network; and determining the BOD of effluent of the aeration tank after the training process of the dynamic feedforward neural network is ended. The method has the advantages of high real-time property, high stability, high precision and high neural network generalization ability.

Description

technical field [0001] The invention belongs to the technical field of soft measurement of sewage water quality parameters, and in particular relates to an online soft measurement method for biochemical oxygen demand based on a dynamic feedforward neural network. Background technique [0002] In the "Outline of the Twelfth Five-Year Plan for National Economic and Social Development of the People's Republic of China", the State Council put forward the overall goal of the urban sewage treatment rate reaching 85%, and proposed to improve the sewage treatment rate and sewage discharge standards for the sewage treatment industry. Require. These requirements put forward higher requirements for the sewage treatment industry in terms of "quality" and "quantity". However, the actual operation status of my country's sewage treatment plants is not optimistic. According to the statistics of the environmental protection department, about 50% of the sewage treatment plants have insuffic...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/18G06N3/02
Inventor 张昭昭郭伟张美金
Owner LIAONING TECHNICAL UNIVERSITY
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