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ABSTRACTAs
ABSTRACT
As a common building material,the concrete durability has always been the focus of our attention.According to survey,concrete building in our country of northeast,north and northwest areas have been seriously affected by the freeze-thaw damage.The frost resistance has become an important indicator in measuring concrete durability[11.Prior to actual application,the related tests of checking frost resistance is needed.After several
examinations,we Call select the specimens which can meet the construction standards.
Although foreign equipment has a high performance,the cost is high at the same time- Domestic equipment has a lower price,but mostly simple structure and low intelligence on
the other hand.The freeze.thaw testing machine designed in out subject based on
manufacturer standards of freeze.thaw test equipmentl2I,constructing the hardware system with the core of Atmega32.Combined with the PC software CO-development platform LabWindows/CVl,high degree of development of intelligent monitoring and control system which can realize the destination of accurate measurement,hardware structure rationalization and operation platform humanization jS here.
In addition,as the strong nonlinear mapping capabilities and adaptive learning and memory features of neural network has been taken into accounted.We will also build BP
neural network model to solve the problem of concrete frost performance-related index
(relative dynamic modulus of elasticity)forecasting.
Select the main factors(water.cement ratio,cement consumption,freezing and thawing times)as raw input data samples and relative dynamic elastic modulus as a single output to create the BP network model.After training,simulation and comparing with the actual measured values,we can judge the BP neural network we made can be used in practice or
not.
In combined with virtual instrument technology and neural network forecasting techniques,we use software to replace some of the hardware devices.In this wa
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