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Study On CO2 Hardening Alkalinity Phenolic Resin Performance Based On Artificial Neural Networks

Posted on:2010-07-03Degree:MasterType:Thesis
Country:ChinaCandidate:Q SunFull Text:PDF
GTID:2121360272499593Subject:Materials Processing Engineering
Abstract/Summary:PDF Full Text Request
Casting industry has a decisive influence on the national economic development. As the casting industry developing to the scale and sophistication of the production process, the request about sand binder is getting higher and higher. As CO2 hardening alkaline phenolic resin is synthesized by a cumbersome process, the neural network model and the combination of traditional experiments and computer application are used to optimize CO2 hardening alkaline phenolic resin synthesize process. This method can improve the performance of sand moulds and save test materials use.Artificial neural network has started the rapid development as a non-linear science from the end of the 1980s. Artificial neural network from the experimental data through self-learning automatic access to a unique mathematical model of the superiority of its people without pre-set formula to the form, but in the experimental data based on a limited, iterative calculations, we can get a experimental data reflect the inherent law of the mathematical model .Neural network excels at dealing with the problems with unobvious regulation and too many variable components.The synthesis principle of CO2 hardening alkaline phenolic resin was analyzed first in this paper, a certain amount of experiments were carried on after comprehending the synthesize process, so enough data for neural network model study and verification were prepared. In accordance with the function and characteristic of artificial neural networks technology, used the antipropagation algorithm (the BP algorithm) to establish the reflection phenolics synthesis craft and the performance neural network model. In the training process, to speed up the network study speed and avoid the network shaking fiercely, an additional momentum method was used to improve the BP algorithm. And the BP neural network model was established finally. Simultaneously, the CO2 hardening alkalinity phenolics cementing agent's flying into a rage quantity, defeated and dispersed shop characteristics and so on nature were also taken to carry on deeper tests, which proved the CO2 hardening alkalinity phenolics cementing agent's superiority further.. Finally the efficient analysis about the CO2 hardening alkalinity phenolics cementing agent was made, indicating that it has prominent production use value and economic efficiency as a kind of casting cementing agent.
Keywords/Search Tags:Alkaline Phenol-aldehyde Resin, Artificial Neural Networks, BP Algorithm, Process Optimiza
PDF Full Text Request
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