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Forecasting method for induction thermal deposition calcium-phosphate coating process on basis of neural network

A calcium-phosphorus coating and neural network technology, which is applied in the field of coating performance testing to expand research thinking, improve technical guidance, and enrich the knowledge base of process parameters.

Inactive Publication Date: 2014-04-23
SHANGHAI UNIV +1
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There are relatively few reports on neural network in the process prediction of calcium-phosphorus coating prepared by induction thermal deposition, but theoretically speaking, BP neural network can be used in the research of coating preparation process, but there is no relevant application of BP neural network at present. Related reports in the field of process evaluation and prediction of induction thermal deposition calcium phosphorus coating

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  • Forecasting method for induction thermal deposition calcium-phosphate coating process on basis of neural network
  • Forecasting method for induction thermal deposition calcium-phosphate coating process on basis of neural network
  • Forecasting method for induction thermal deposition calcium-phosphate coating process on basis of neural network

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Embodiment 1

[0028] In this example, see Figure 1 ~ Figure 3 , the process prediction method of induction thermal deposition calcium phosphorus coating based on neural network can be divided into the following five steps to realize:

[0029] a. Prepare calcium-phosphorus coatings by induction thermal deposition and collect test samples: Under laboratory conditions, induction thermal deposition is used to prepare calcium-phosphorus coatings on the surface of carbon / carbon composite materials, and the data during the experiment is recorded by the data acquisition device The three process parameters of time, frequency and temperature, as well as the corresponding coating deposition weight, organize the experimental data to form a test sample with 3 inputs and 1 output, that is, construct a 4×48 two-dimensional array as the test sample, and 48 represents a total of 48 sets of data , 4 represents that each set of data includes three input parameters and one output parameter, wherein time, freq...

Embodiment 2

[0035] This embodiment is basically the same as Embodiment 1, especially in that:

[0036] In this example, see Figure 7 ~ Figure 9 , the process prediction method of induction thermal deposition calcium phosphorus coating based on neural network can be divided into the following five steps to realize:

[0037] a. Utilize the induction thermal deposition method to prepare the calcium phosphorus coating, collect the test sample: same as embodiment one;

[0038] b. Utilize the test sample collected in the first step to fit the training sample: same as embodiment one;

[0039] c. set up BP neural network, utilize the training sample to train the network, and test the generalization ability of the network with the test sample: same as embodiment one;

[0040] d. Design the process parameters of the orthogonal level as the input parameters, and use the trained network simulation output parameters to construct the orthogonal samples: the same as the first embodiment;

[0041] e....

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Abstract

The invention discloses a forecasting method for an induction thermal deposition calcium-phosphate coating process on the basis of a neural network, which comprises the following steps of preparing a calcium-phosphate coating by utilizing an induction thermal deposition method and collecting a test sample; fitting out a training sample by the test sample; establishing the BP (Back Propagation) neural network, training the network by adopting a Levenberg-Marquardt algorithm and utilizing the training sample, and testing the generalization ability of the network by the test sample; designing orthogonal horizontal process parameters, using the orthogonal horizontal process parameters as input parameters, simulating output parameters by utilizing the trained network and constructing an orthogonal sample; and carrying out analyzing calculation on the obtained orthogonal sample and forecasting influence of the process parameters on the deposition process. According to the invention, the data mining ability of the neural network is successfully utilized and the relation between three process parameters of time, frequency and temperature of induction thermal deposition and the deposition rate is analyzed, so that design of the calcium-phosphate coating preparation process is effectively guided.

Description

technical field [0001] The present invention relates to a coating performance testing method, in particular to a coating process prediction method, and also relates to a neural network system analysis and application method, which is applied to the establishment of a process parameter knowledge base and the analysis of the impact of process parameters on the deposition process It has good technical guiding significance for experimental design and industrial application. Background technique [0002] HAp-coated C / C composites are a potential new generation of bone replacement and repair materials with broad application prospects. At present, the methods for preparing HAp coatings on the surface of C / C composites mainly include: plasma spraying method, coating sintering method, electrochemical method, alkali heat treatment method, bionic method and induction thermal deposition method. [0003] Experiments have proved that the induction thermal deposition method is simple, the...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N3/02
Inventor 白瑞成马花月林松李杰熊信柏张丹李爱军
Owner SHANGHAI UNIV
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