Research on Predicting the Stability of Partially Stabilized Zirconia Prepared by Microwave Heating Using SVM

2010 ◽  
Vol 146-147 ◽  
pp. 510-516
Author(s):  
Sheng Hui Guo ◽  
Li Jun Liu ◽  
Dong Bo Li ◽  
Jin Hui Peng ◽  
Li Bo Zhang ◽  
...  
Keyword(s):  
Microwave Heating ◽  
Influence Factors ◽  
Theory And Practice ◽  
Future Application ◽  
Support Vector ◽  
Stabilized Zirconia ◽  
Partially Stabilized Zirconia ◽  
Typical Data ◽  
Svm Model ◽  
The Stability

The stability is a key product performance index, which can directly determine the quality of the partially stabilized zirconia (PSZ), so how to predict the stability of PSZ accurately, quickly and easily in the preparation process is very important. In this paper, a new mathematical model to predict the stability of PSZ prepared by microwave heating was proposed, based on statistical theory (SLT) and support vector machine (SVM) theory, which relates the stability of PSZ and the influence factors, such as the holding temperature, rising rate of temperature, holding time, decreasing rate of temperature and hardening temperature. Typical data collected from 58 experiments were used for the training samples and test samples. Then testing and analyzing was done. The results showed that the SVM model is reasonable and it is accurate and reliable to predict the stability of the partially stabilized zirconia prepared by microwave heating by SVM model. Besides, multiple influence factors can be comprehensively considered in the SVM model, thus a new highly effective method for predicting the stability of PSZ prepared by microwave heating is provided for future application, which is of great significance to theory and practice.

Research on Predicting the Stability of Partially Stabilized Zirconia Based on SVM

2010 ◽  
Vol 146-147 ◽  
pp. 460-465 ◽  
Author(s):  
Sheng Hui Guo ◽  
Dong Bo Li ◽  
Li Jun Liu ◽  
Jin Hui Peng ◽  
Li Bo Zhang ◽  
...  
Keyword(s):  
Relative Error ◽  
Influence Factors ◽  
Commercial Application ◽  
Support Vector ◽  
Stabilized Zirconia ◽  
Partially Stabilized Zirconia ◽  
Typical Data ◽  
Svm Model ◽  
Commercial Process ◽  
The Stability

The stability is one most important product performance index, which can directly determine the quality of the partially stabilized zirconia (PSZ), and the stability of PSZ is always fluctuating in the commercial process, so how to accurately, quickly and easily predict the stability of PSZ in the preparation process is very important. In the present paper, a new mathematical model to predict the stability of PSZ was proposed, based on statistical theory (SLT) and support vector machine (SVM) theory, which relates the stability of PSZ and the influence factors, such as the holding temperature, rising rate of temperature, holding time, decreasing rate of temperature and hardening temperature. Typical data collected from commercial process were collected for the training samples and test samples. Then testing and analyzing was done. The results showed that the max relative error was 1.80%, the least relative error was 0%, and the average relative error was 0.58%. It is accurate and reliable to predict the stability of PSZ by SVM model. Besides, multiple influence factors can be comprehensively considered in the SVM model, thus a new highly effective method for predicting the stability of PSZ is provided for commercial application.

Support Vector Machine and its Predicting Stability of Partially Stabilized Zirconia by Microwave Heating Preparation

2011 ◽  
Vol 382 ◽  
pp. 281-288 ◽  
Author(s):  
Biao Yang ◽  
Wei Li ◽  
Li Jun Liu ◽  
Jin Hui Peng ◽  
Li Bo Zhang ◽  
...  
Keyword(s):  
Support Vector ◽  
Risk Minimization ◽  
Stabilized Zirconia ◽  
Partially Stabilized Zirconia ◽  
Modeling And Prediction ◽  
Vector Machines ◽  
Structural Risk ◽  
Learning Machine ◽  
The Stability ◽  
Promising Type

Support vector machines (SVMs) are a promising type of learning machine based on structural risk minimization and statistical learning theory, which can be divided into two categories: support vector classification (SVC) machines and support vector regression machines (SVR). The basic elements and algorithms of SVR machines are discussed. As modeling and prediction methods are introduced into the experiment of microwave preparing partially stabilized zirconia (PSZ) and built the stability prediction model, the better prediction accuracy and the better fitting results are verified and analyzed. This is conducted to elucidate the good generalization performance of SVMs, specially good for dealing with nonlinear data.

Application of Genetic Arithmetic and Support Vector Machine in Prediction of Compression Index of Clay

2013 ◽  
Vol 438-439 ◽  
pp. 1167-1170
Author(s):  
Xu Chao Shi ◽  
Ying Fei Gao
Keyword(s):  
Support Vector Machine ◽  
Influence Factors ◽  
Support Vector ◽  
Compression Index ◽  
Risk Minimization ◽  
Minimization Principle ◽  
Structural Risk Minimization Principle ◽  
Svm Model ◽  
Genetic Arithmetic ◽  
Practical Tool

The compression index is an important soil property that is essential to many geotechnical designs. As the determination of the compression index from consolidation tests is relatively time-consuming. Support Vector Machine (SVM) is a statistical learning theory based on a structural risk minimization principle that minimizes both error and weight terms. Considering the fact that parameters in SVM model are difficult to be decided, a genetic SVM was presented in which the parameters in SVM method are optimized by Genetic Algorithm (GA). Taking plasticity index, water content, void ration and density of soil as primary influence factors, the prediction model of compression index based on GA-SVM approach was obtained. The results of this study showed that the GA-SVM approach has the potential to be a practical tool for predicting compression index of soil.

An Improved Online SVM Algorithm for Overcoming the Influence of Muscle Fatigue in sEMG Based Human Machine Interaction

2014 ◽  
Vol 536-537 ◽  
pp. 1026-1031
Author(s):  
Jun Cai ◽  
Rui Liu
Keyword(s):  
Muscle Fatigue ◽  
Training Data ◽  
Support Vector ◽  
The Novel ◽  
Human Machine Interaction ◽  
Svm Algorithm ◽  
Svm Model ◽  
Novel Method ◽  
Machine Interface ◽  
The Stability

For the problem that the stability of surface Electromyographic EMG(sEMG) based human-machine interface(HMI) declines as the muscle fatigue takes place, an improved incremental training algorithm for online support vector machine(SVM) is proposed. This paper study the changes of sEMG when muscle fatigue occurs by the method of continuous wavelet transform, and then apply the improved online SVM for sEMG classification. The novel method adjusts the parameters of SVM model to adapt itself based on the changes of sEMG signals and the training data is conditionally selected and forgot. Experiment results show that the presented algorithm performs high modeling precision and training speed is increased. Furthermore, this method effectively overcomes the influence of muscle fatigue during long-term operating sEMG based HMI.

A Discrimination Method of Saturated Sand Liquefaction Possibility Based on Support Vector Machine

2014 ◽  
Vol 509 ◽  
pp. 38-43
Author(s):  
Zhong Jie Fan ◽  
Yan Qiu Leng ◽  
Yong Long Xu ◽  
Zheng Jiang Meng ◽  
Ji Wei Xu
Keyword(s):  
Support Vector Machine ◽  
Influence Factors ◽  
Kernel Functions ◽  
Small Sample ◽  
Support Vector ◽  
Saturated Sand ◽  
Risk Minimization ◽  
Sand Liquefaction ◽  
Discriminant Model ◽  
Svm Model

Based on the analysis of influence factors of saturated sand, this paper expounds the limitations of traditional evaluation of liquefaction, and introduces the criterion of support vector machine (SVM) based on the principle of structural risk minimization. According to the main influence factors of sand liquefaction, a SVM discriminant model of sand liquefaction with different kernel functions is established. Through studying small sample data, this model can establish nonlinear mapping relationship between influence factors and liquefaction type. On the basis of seismic data, a radial based kernel function is selected to predict sand liquefaction type. The research results show that the predicted magnitude is identical with the actual result, to prove that it is effective to apply this SVM model to evaluate the level of sand liquefaction.

Effect of SiCp Addition on Microstructure and Mechanical Properties of ZTA Ceramics by Microwave Sintering

2018 ◽  
Vol 281 ◽  
pp. 217-223 ◽  
Author(s):  
Yong Qiang Chen ◽  
Sai Li ◽  
Wei Li ◽  
Ting Ting Su ◽  
Bing Bing Fan ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Microwave Heating ◽  
Bending Strength ◽  
Microwave Sintering ◽  
Precipitation Method ◽  
Stabilized Zirconia ◽  
Oriented Growth ◽  
Directional Growth ◽  
Partially Stabilized Zirconia ◽  
Microstructure And Mechanical Properties

The effects of SiCp addition on the microstructure and mechanical properties of ZTA ceramics was investigated by microwave sintering. Partially stabilized zirconia（3Y-ZrO2）nanopowder containing SiCp was prepared by microwave pyrolysing precursor which was was achieved by co-precipitation method. The powders of alumina, yttria partially stabilized zirconia containing SiCp were mixed to prepare ZTA ceramics green body by die pressing and cold isostatic pressing and subsequently sintered at the range of 1350°C-1550°C for 30min by microwave. XRD revealed that 3Y-ZrO2/SiC powder contained more tetragonal phase than 3Y-ZrO2 powder which was also confirmed by SEM and particle size distribution. The phenomenon was because of SiCp forming the microwave heating spot that promoted pyrolysis progress when 3Y-ZrO2/SiC powder was prepared by microwave heating. Microstructure showed that the grain of ZTA ceramics had directional growth by microwave sintering. SiCp firstly absorbed microwave that made more uniform sintering of ZTA ceramics and caused local oriented growth of zirconia and alumina. Thus, the bending strength of ZTA ceramics was higher than ZTA without SiCp. The ladder type heating mode of microwave sintering ZTA ceramics reduced relatively sintering time by 20min due to the addition of SiCp.Introduction

A Study of Rhombohedral Phase in Y2 O3 -Partially Stabilized Zirconia

1986 ◽  
Vol 78 ◽  
Author(s):  
Jukishige Kitano ◽  
Y. Mori ◽  
A. Ishitani ◽  
T. Masaki
Keyword(s):  
Heat Treatment ◽  
Phase Transformation ◽  
Hot Isostatic Pressing ◽  
Tetragonal Zirconia ◽  
Rhombohedral Phase ◽  
X Ray Diffraction ◽  
Stabilized Zirconia ◽  
Partially Stabilized Zirconia ◽  
X Ray ◽  
The Stability

ABSTRACTTetragonal to rhombohedral phase transformation was studied by X-ray diffraction technique on the ground surfaces of tetragonal zirconia polycrystals (Y-TZP) and partially stabilized zirconia (Y-PSZ) with 2.0 to 5.0 mol% Y2 O3 contents prepared by hot isostatic pressing. The rhombohedral phase increased with increase of Y2 O3 content from 2.0 to 5.0 mol%, and also with the increase of HIPing temperature from 1400 to 1600°C. The stability of the phase was also studied with regard to the surface finish and annealing. The subsequent heat treatment of the samples was found to promote the reverse rhombohedral to tetragonal transformation.

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