Fractional Differential Recognition Algorithm for Electrochemical Characteristic of Steel Concrete Structure Corrosion
A technology of fractional differentiation and steel-concrete structure, which is applied in the direction of electrical digital data processing, special data processing applications, calculations, etc., and can solve problems such as irreversible transformations
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Embodiment 1
[0036] Specifically, this method uses the fractional differential operator to calculate the corrosion electrochemical transfer function, and then controls the error between the calculated value and the experimental value, obtains the parameter value to be identified in the transfer function, and realizes the identification of the electrochemical state of steel corrosion .
[0037] The general electrochemical equivalent circuit R of steel bar corrosion in reinforced concrete structure is as follows c ((R ct Z w )Z CPE as an example.
[0038] (1)R c ((R ct Z w )Z CPE The establishment of the transfer function of the equivalent circuit
[0039]
[0040] Among them, G(jω)-admittance; I(jω) and U(jω) are respectively the excitation current and the corresponding voltage response, or the current response and the corresponding excitation voltage; R c - Concrete resistance; R ct -Resistance of steel bar corrosion electrochemical reaction at steel-concrete interface; Y OQ ...
Embodiment 2
[0060] Using Maltab language to realize the programming of the above theoretical algorithm, figure 1 The flow of algorithm writing is given. First, the corresponding transfer function is given according to the specific requirements. In this example, the general equivalent circuit R is given c ((R ct Z w )Z CPE Such as the transfer function of formula (1); secondly, the fractional differential operator is selected, in this example, the Grundwald-Letnikov differential operator of formula (8) is used; thirdly, the fractional differential operator is obtained under constant potential step excitation Current response calculation result I(c); Fourth, under the given initial parameter value, Matlab is used to perform nonlinear fitting on the calculation result I(c) to obtain each parameter value; Fifth, the premise of traversing each sampling point Next, calculate the error sum (9) formed by each sampling point, if the error (9) is greater than the control error, change the value...
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