Neural-network-based enrichment process thermal monitoring method
A neural network and enrichment technology, applied in the field of thermal monitoring of the enrichment process based on neural network, can solve the problems that the enrichment process time cannot be accurately determined, and the enrichment process cannot be effectively described, so as to reduce exploratory resource consumption and experience Effects of Error, Efficiency Improvement and Accuracy
Inactive Publication Date: 2014-03-26
QINGDAO UNIV
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Problems solved by technology
At present, the enrichment process cannot be effectively described, and the enrichment process time cannot be accurately determined. According to empirical estimates, there may be a certain amount of idle or insufficient time, and excessive enrichment may cause additional and unknown errors source
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[0036] As mentioned above, the present invention provides a method for thermal monitoring of the enrichment process based on a neural network, which is used to describe and predict the enrichment process involved in the fields of analysis, separation, and purification. The content of the present invention is illustrated by the following examples combining enrichment and detection integrated calorimetric biosensors, without limiting the scope of the present invention.
[0037] The thermal monitoring method of the enrichment and detection integrated calorimetric biosensor enrichment process based on the neural network of the present invention comprises the following steps:
[0038] (1) Obtain the thermal monitoring signal of the enrichment process and its related influencing parameters as input variables.
[0039] The enrichment and detection integrated calorimetric biosensors are enriched and detected continuously in the same reactor. The present invention focuses on the enrich...
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The invention discloses a neural-network-based enrichment process thermal monitoring method, which comprises the following steps of: (1) acquiring an enrichment process thermal monitoring signal and related influencing parameters, which are used as variables; (2) building a neural network; (3) training and testing the neural network; and (4) describing and predicting the enrichment process by using the neural network. The neural network is a BP neural network based on L-M algorithm, which comprises an input layer, an intermediate layer and an output layer, wherein the input variables of the output layer are output thermal signals and corresponding relative positions of a plurality of temperature sensors and flow rate and eluting volume of an enriched solution sample; and the objective of the output layer is the concentration change rate of the enriched solution sample. The invention realizes quick, accurate and reliable description and prediction of the enrichment process, and can be used for describing, predicting and control the enrichment process involved in fields of analysis, separation, purification, and the like, with high efficiency and accuracy.
Description
technical field [0001] The invention relates to a thermal monitoring method for the enrichment process, in particular to a neural network-based thermal monitoring method for the enrichment process. Background technique [0002] Enrichment is widely used in analysis, separation, purification and other fields, especially in trace analysis. It is an important means to eliminate interference, reduce detection limit and improve analysis precision. The enrichment process can be described by the change trend of the concentration of the enriched sample liquid at the outlet of the enrichment column or enrichment bed, which can reflect the length of the enrichment mass transfer zone, determine the effective enrichment time and use it to control the progress of the enrichment process. [0003] The accurate description and prediction of the enrichment process is very beneficial to the optimization and control of the enrichment analysis, separation, purification and other processes. This...
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IPC IPC(8): G01N25/20
Inventor 郑艺华刘君王丽影
Owner QINGDAO UNIV