CN104005074B - Magnesium-based material biological composite coating controllable-degradation rate control method - Google Patents
Magnesium-based material biological composite coating controllable-degradation rate control method Download PDFInfo
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- arc oxidation
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Abstract
The invention discloses a magnesium-based material biological composite coating controllable-degradation rate control method. The method realizes preparation of composite coatings having different degradation rates by change of micro-arc oxidation technological parameters, and realizes network training by the technological parameter and degradation rate respectively as an input layer and an output layer and by a BP artificial neural network optimized by a genetic algorithm thereby acquiring a prediction model having a small error.
Description
(1) technical field
The present invention relates to the controlled Forecasting Methodology of degradation rate of a kind of differential arc oxidation biological composite coating, particular by adopting
The measurable of coating degradation speed is realized with the BP artificial neural network of genetic algorithm optimization.
(2) background technology
From the nineties in 20th century, the study hotspot of et al. Ke bio-medical material starts to be turned by Biostatic shaped material
Becoming degradation material, degradable magnesium alloy has been described as being a kind of revolutionary metallic biomaterial America and Europe.Magnesium alloy is made
Tempting application prospect is had for biological adsorbable bone section implants material.But, usual bone implanting part need to maintain in vivo
Time in 12 to 18 weeks also keeps enough intensity, until damaged tissues recovery from illness.Magnesium alloy implant material is contained within chlorine at human body
Can degrade rapidly in the corrosive medium of ion, be allowed to maintain time enough and premature failure, its Pitting corrosion behavior is also possible to
The inflammatory reaction that induction local organization is serious；Too high magnesium ion concentration also can cause bone morphogenetic protein (BMP-2) to secrete
Excess, activates osteoclast, causes bone resorption phenomenon.The current technology being used for improving corrosion stability of magnesium alloy is mainly surface modification skill
Art, and its effect is notable.At present the clinical embedded material needed the initial stage of implantation can in human body environment corrosion-resistant, keep
Enough intensity, and degrade with controlled speed during completing function, absorbed by human body or metabolism after degraded.
But the degradation rate of the magnesium alloy implant material after surface modification is unknowable, how to ensure magnesium alloy implant material
Do not degraded in advance after implanting human body, be the most all a difficult problem.Therefore, it is necessary to realize magnesium alloy implant material is dropped
Solve speed it is contemplated that.But the efficiency being obtained related data by numerous and diverse experiment is the lowest, it is unfavorable for the formation of industrialization.Closely
Nian Lai, the Predicting Technique that appears as of the neutral net with nonlinearity and the strongest adaptive learning ability brings new think of
Think, during neutral net is used for prediction work in recent years and achieve certain effect.So, change by combining Mg alloy surface
Property technology and neutral net, thus obtain the degradation rate Forecasting Methodology of a kind of surface modification mg-based material, for bio-medical
The application of metal implantation instrument and development have landmark significance.
(3) summary of the invention
The shortcoming that the controlled degradation of the mg-based material surface biological composite coating of present invention prior art to be overcome is the best,
The controllable degradation rate control method of a kind of mg-based material biological composite coating is provided.
The present invention uses BP artificial neural network to carry out matching lot of experimental data, obtains a reliable degradation rate prediction
Model.So can reduce the data removing to obtain degradation rate by numerous and diverse experiment, beneficially industrialization.
The technical solution used in the present invention is:
(1) the differential arc oxidation biology utilizing micro-arc oxidation and electrophoretic deposition to prepare controlled degradation at Mg alloy surface is multiple
Close coating；
(2) preparation of differential arc oxidation coating: selecting with sodium silicate, sodium fluoride and sodium hydroxide is main electrolyte group
Point, under the micro-arc oxidation process parameter set, prepare differential arc oxidation coating at Mg alloy surface；
(3) preparation of differential arc oxidation biological composite coating: with differential arc oxidation coating sample for the pending sample of electrophoretic deposition,
In the suspension as key component with sodium phosphate and hydroxyapatite (HA), set suitable electrophoretic deposition electrical quantity, to micro-
Arc oxide covering carries out electrophoretic deposition to prepare differential arc oxidation biological composite coating；
(4) described differential arc oxidation biological composite coating main body is differential arc oxidation coating, and differential arc oxidation coating is also compound painting
Layer antiseptical main part；Electrophoretic deposition coating mainly improves the biology performance of differential arc oxidation coating；
(5) in view of (4) Suo Shu, by changing the differential arc oxidation related process parameters i.e. anticorrosion energy of adjustable composite coating
Power, therefore can arrange different technological parameters to prepare the coating that degradation rate is different, reach controlled effect；
(6) affecting topmost three factors of differential arc oxidation coating degradation rate is: electric current density, process time and electricity
Solve liquid concentration.By changing these three parameter, the differential arc oxidation coating that degradation rate is different can be prepared, be coated with at differential arc oxidation
Carry out electrophoretic deposition on Ceng and prepare biological composite coating.The composite coating prepared is carried out the immersion in vitro experiment of SBF solution,
Obtain the degradation rate parameter of coating；
(7) selecting the 3-tier architecture BP neural net model establishing improved through genetic algorithm, input layer is three neurons, point
Not Wei electric current density, process time and three factors of concentration of electrolyte, output layer is a neuron, i.e. the degraded speed of coating
Rate；The number of hidden nodes determines according to simulation training and test result；
The whole process of described genetic algorithm:
71, first produce initial population, and colony is encoded；
72, colony being carried out fitness analysis, if meeting optimization principles directly export optimum individual and parameter, and tying
Bundle；Otherwise continue next step；
73, select individuality according to fitness, and retain the individuality of high fitness；
74, crossover operator acts on whole individuality, produces a new generation；
75, use mutation operator that the individuality in colony carries out structure variation adjustment, formed new individual；
76, the individuality after selection, intersection, mutation process becomes colony of future generation, repeats 2.
(8) using N (N >=50) group input layer experimental data and corresponding output layer experimental data as training sample, logical
Cross the negative gradient direction that the weights to network and threshold value change along network error to be adjusted, finally make network error reach minimum
Value or minima, thus obtain a minimum BP artificial neural-network control model of error rate.
The principle of the present invention:
The differential arc oxidation biological composite coating of controlled degradation is prepared based on differential arc oxidation coating, by adjusting the differential of the arc
Aoxidize three main technological parameters affecting coating degradation speed, the differential arc oxidation coating under different parameters can be obtained, at this
The electrophoretic deposition HA that a little differential arc oxidation coating surfaces are carried out under the same terms obtains biological composite coating, carries out composite coating
The immersion in vitro experiment of SBF solution, thus obtain the degradation rate of respective coatings.By differential arc oxidation three corresponding for this degradation rate
Parameter as input layer, carries out BP people as network output layer, differential arc oxidation three parameter as one group of training data, degradation rate
Artificial neural networks training and test, obtain a minimum BP Artificial Neural Network Prediction Model of error.This model is once set up,
In conjunction with differential arc oxidation system, as long as the input layer at model inputs three technological parameters of differential arc oxidation, i.e. can get under this parameter
The degradation rate of the differential arc oxidation coating of preparation.
Beneficial effects of the present invention major embodiment: use enough experimental datas to the BP people after being improved by genetic algorithm
Artificial neural networks model is trained, and obtains a minimum Controlling model of error；Any group of can be controlled by this model
Under differential arc oxidation three parameter, the degradation rate of the coating of preparation, decreases follow-up numerous and diverse experimental exploring, for bone implant material
Industrialization is laid a good foundation.
(4) accompanying drawing explanation
Fig. 1 genetic algorithm optimization BP artificial neural network schematic diagram；
Fig. 2 BP artificial neural network schematic diagram.
(5) detailed description of the invention
The present invention is described further below in conjunction with the accompanying drawings.
The technical solution used in the present invention is:
The controllable degradation rate control method of mg-based material biological composite coating, comprises the steps:
(1) the differential arc oxidation biology utilizing micro-arc oxidation and electrophoretic deposition to prepare controlled degradation at Mg alloy surface is multiple
Close coating；
(2) preparation of differential arc oxidation coating: selecting with sodium silicate, sodium fluoride and sodium hydroxide is main electrolyte group
Point, under the micro-arc oxidation process parameter set, prepare differential arc oxidation coating at Mg alloy surface；
(3) preparation of differential arc oxidation biological composite coating: with differential arc oxidation coating sample for the pending sample of electrophoretic deposition,
In the suspension as key component with sodium phosphate and hydroxyapatite (HA), set suitable electrophoretic deposition electrical quantity, to micro-
Arc oxide covering carries out electrophoretic deposition to prepare differential arc oxidation biological composite coating；
(4) described differential arc oxidation biological composite coating main body is differential arc oxidation coating, and differential arc oxidation coating is also compound painting
Layer antiseptical main part；Electrophoretic deposition coating mainly improves the biology performance of differential arc oxidation coating；
(5) in view of (4) Suo Shu, by changing the differential arc oxidation related process parameters i.e. anticorrosion energy of adjustable composite coating
Power, therefore can arrange different technological parameters to prepare the coating that degradation rate is different, reach controlled effect；
(6) affecting topmost three factors of differential arc oxidation coating degradation rate is: electric current density, process time and electricity
Solve liquid concentration.By changing these three parameter, the differential arc oxidation coating that degradation rate is different can be prepared, be coated with at differential arc oxidation
Carry out electrophoretic deposition on Ceng and prepare biological composite coating.The composite coating prepared is carried out the immersion in vitro experiment of SBF solution,
Obtain the degradation rate parameter of coating；
(7) selecting the 3-tier architecture BP neural net model establishing improved through genetic algorithm, input layer is three neurons, point
Not Wei electric current density, process time and three factors of concentration of electrolyte, output layer is a neuron, i.e. the degraded speed of coating
Rate；The number of hidden nodes determines according to simulation training and test result；
The whole process of described genetic algorithm:
71, first produce initial population, and colony is encoded；
72, colony being carried out fitness analysis, if meeting optimization principles directly export optimum individual and parameter, and tying
Bundle；Otherwise continue next step；
73, select individuality according to fitness, and retain the individuality of high fitness；
74, crossover operator acts on whole individuality, produces a new generation；
75, use mutation operator that the individuality in colony carries out structure variation adjustment, formed new individual；
76, the individuality after selection, intersection, mutation process becomes colony of future generation, repeats 2.
(8) using N (N >=50) group input layer experimental data and corresponding output layer experimental data as training sample, logical
Cross the negative gradient direction that the weights to network and threshold value change along network error to be adjusted, finally make network error reach minimum
Value or minima, thus obtain a minimum BP artificial neural-network control model of error rate.
Micro-arc oxidation and electrophoretic deposition is utilized to prepare differential arc oxidation biological composite coating.
Concentration of electrolyte forms: the Na of 1.75A g/L2SiO3·10H2The NaF of O, A g/L, NaOH solution regulation electrolyte
PH value, using deionized water as solvent.
Electrophoretic deposition liquid forms: Na3PO410.0g/L, HA nano powder (100nm) 3.0g/L, 3ml/L ethylene glycol, deionization
Water is as solvent.Use magnetic stirrer 1h, be then aged 6h, using the upper strata anionic turbid solution after ageing as electrophoresis
Deposition liquid.
(1) in the micro-arc oxidation electrolyte prepared, carry out differential arc oxidation experiment, use DC pulse differential arc oxidation dress
Putting, differential arc oxidation electrical quantity is: the differential arc oxidation time is B min, electric current density CA/dm2, dutycycle is 37.5%, electrolyte
Temperature is 20 DEG C.Process terminate after by sample natural drying, it is thus achieved that arc differential oxide ceramic coating.Differential arc oxidation coating sample is made
For the pending sample of electrophoretic deposition, using the pulse power, under conditions of voltage is 350V, electrophoretic deposition processes 10min.Process
Complete rear natural drying, the sample obtained is differential arc oxidation biological composite coating sample.
(2) use the differential arc oxidation biological composite coating prepared as sample, carry out external in the SBF solution of 37 DEG C
Immersion test.The average degradation rate D in soaking the time limit of testing coating.
SBF solution final concentration consists of (solvent is deionized water)
(3) Fig. 2 is seen: using concentration of electrolyte A, process time B and the electric current density C input parameter as input layer,
Using average degradation rate D as output parameter.Use as depicted through the BP artificial neural network of genetic algorithm optimization (Fig. 1)
Model carries out network training, by constantly adjusting weights and threshold values, improves training precision to reduce the error of forecast model.
(4) whole training process is through iteration repeatedly so that training error reaches target error or following.
(5) by using BP Artificial Neural Network Prediction Model, can reach to make under known micro-arc oxidation process parameter
The degradation rate of standby differential arc oxidation biological composite coating is controlled, thus reach coating degradation speed controlled.
Claims (1)
1. the controllable degradation rate control method of mg-based material biological composite coating, comprises the steps:
(1) micro-arc oxidation and electrophoretic deposition is utilized to prepare the compound painting of differential arc oxidation biology of controlled degradation at Mg alloy surface
Layer；
The preparation of differential arc oxidation coating: selecting with sodium silicate, sodium fluoride and sodium hydroxide is main electrolyte component, is setting
Micro-arc oxidation process parameter under, prepare differential arc oxidation coating at Mg alloy surface；
The preparation of differential arc oxidation biological composite coating: with differential arc oxidation coating sample for the pending sample of electrophoretic deposition, with phosphorus
In acid sodium and suspension that hydroxyapatite (HA) is key component, set suitable electrophoretic deposition electrical quantity, to differential arc oxidation
Coating carries out electrophoretic deposition to prepare differential arc oxidation biological composite coating；
Described differential arc oxidation biological composite coating main body is differential arc oxidation coating, and differential arc oxidation coating is also composite coating antiseptical
Main part；Electrophoretic deposition coating mainly improves the biology performance of differential arc oxidation coating；
By changing the differential arc oxidation related process parameters i.e. antiseptic power of adjustable composite coating, therefore can arrange different
Technological parameter prepares the coating that degradation rate is different, reaches controlled effect；
(2) affecting topmost three factors of differential arc oxidation coating degradation rate is: electric current density, process time and electrolyte
Concentration；By changing these three parameter, the differential arc oxidation coating that degradation rate is different can be prepared, on differential arc oxidation coating
Carry out electrophoretic deposition and prepare biological composite coating；The composite coating prepared is carried out the immersion in vitro experiment of SBF solution, obtains
The degradation rate parameter of coating；
(3) selecting the 3-tier architecture BP neural net model establishing improved through genetic algorithm, input layer is three neurons, is respectively
Electric current density, process time and three factors of concentration of electrolyte, output layer is a neuron, the i.e. degradation rate of coating；
The number of hidden nodes determines according to simulation training and test result；
The whole process of described genetic algorithm:
31, first produce initial population, and colony is encoded；
32, colony being carried out fitness analysis, if meeting optimization principles directly export optimum individual and parameter, and terminating；
Otherwise continue next step；
33, select individuality according to fitness, and retain the individuality of high fitness；
34, crossover operator acts on whole individuality, produces a new generation；
35, use mutation operator that the individuality in colony carries out structure variation adjustment, formed new individual；
36, the individuality after selection, intersection, mutation process becomes colony of future generation, repeats 32；
(4) using N group input layer experimental data and corresponding output layer experimental data as training sample, by the power to network
The negative gradient direction that value and threshold value change along network error is adjusted, and finally makes network error reach minimum or minima,
Thus obtain a minimum BP artificial neural-network control model of error rate, N >=50.
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| CN105862107B (en) * | 2016-05-26 | 2018-01-23 | 浙江工业大学 | The method that composite biological coating is prepared on magnesium alloy differential arc oxidation coating |
| CN111593279A (en) * | 2020-05-26 | 2020-08-28 | 浙江工业大学 | Method for controlling degradation rate of medical magnesium-based material composite biological coating |
| CN113981502A (en) * | 2021-10-29 | 2022-01-28 | 大连海事大学 | Aluminum alloy surface corrosion-resistant antifriction composite coating and preparation method thereof |
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| US6981423B1 (en) * | 2002-04-09 | 2006-01-03 | Rockwell Automation Technologies, Inc. | System and method for sensing torque on a rotating shaft |
| CN101539781A (en) * | 2009-04-22 | 2009-09-23 | 北京中冶设备研究设计总院有限公司 | Electrogalvanizing zinc coating thickness BP neural network control method and application in PLC thereof |
| CN102902257A (en) * | 2012-10-30 | 2013-01-30 | 威水星空（北京）环境技术有限公司 | Sewage treatment process optimization and energy-saving control system and method |
| CN103194782A (en) * | 2013-04-11 | 2013-07-10 | 浙江工业大学 | Method for preparing magnesium-based ceramic coating by micro-arc oxidation-electrophoretic deposition |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6981423B1 (en) * | 2002-04-09 | 2006-01-03 | Rockwell Automation Technologies, Inc. | System and method for sensing torque on a rotating shaft |
| CN101539781A (en) * | 2009-04-22 | 2009-09-23 | 北京中冶设备研究设计总院有限公司 | Electrogalvanizing zinc coating thickness BP neural network control method and application in PLC thereof |
| CN102902257A (en) * | 2012-10-30 | 2013-01-30 | 威水星空（北京）环境技术有限公司 | Sewage treatment process optimization and energy-saving control system and method |
| CN103194782A (en) * | 2013-04-11 | 2013-07-10 | 浙江工业大学 | Method for preparing magnesium-based ceramic coating by micro-arc oxidation-electrophoretic deposition |
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