In the present investigation, the relation of pre-ageing temperature and pre-ageing time to mechanical properties was studied, and a model was established to predict the mechanical properties of AA6005 Al alloy. Compa...In the present investigation, the relation of pre-ageing temperature and pre-ageing time to mechanical properties was studied, and a model was established to predict the mechanical properties of AA6005 Al alloy. Compared with the experimental results, the deviation of the proposed model was limited to 8.1%, which showed reasonable accuracy of forecasting. It was found that the performance of AA6005 alloy was better at higher pre-ageing temperature with shorter pre-ageing time than that at T6 temper. The microstructure of the alloy was observed by transmission electron microscopy, and the results showed that high dislocation density and precipitate density existed at 160 ℃ and 200 ℃ pre-ageing, which were in good agreement with the model.展开更多
It is difficult to detect the anomalies whose matching relationship among some data attributes is very different from others’ in a dataset. Aiming at this problem, an approach based on wavelet analysis for detecting ...It is difficult to detect the anomalies whose matching relationship among some data attributes is very different from others’ in a dataset. Aiming at this problem, an approach based on wavelet analysis for detecting and amending anomalous samples was proposed. Taking full advantage of wavelet analysis’ properties of multi-resolution and local analysis, this approach is able to detect and amend anomalous samples effectively. To realize the rapid numeric computation of wavelet translation for a discrete sequence, a modified algorithm based on Newton-Cores formula was also proposed. The experimental result shows that the approach is feasible with good result and good practicality.展开更多
The predictive model of surface roughness of the spiral bevel gear (SBG) tooth based on the least square support vector machine (LSSVM) was proposed.A nonlinear LSSVM model with radial basis function (RBF) kernel was ...The predictive model of surface roughness of the spiral bevel gear (SBG) tooth based on the least square support vector machine (LSSVM) was proposed.A nonlinear LSSVM model with radial basis function (RBF) kernel was presented and then the experimental setup of PECF system was established.The Taguchi method was introduced to assess the effect of finishing parameters on the gear tooth surface roughness,and the training data was also obtained through experiments.The comparison between the predicted values and the experimental values under the same conditions was carried out.The results show that the predicted values are found to be approximately consistent with the experimental values.The mean absolute percent error (MAPE) is 2.43% for the surface roughness and 2.61% for the applied voltage.展开更多
基金Projects(51575539, U1837207) supported by the National Natural Science Foundation of ChinaProject(2020RC2002)supported by the Science and Technology Innovation Program of Hunan Province,ChinaProject(2021JJ40774)supported by Natural Science Foundation of Hunan Province,China。
文摘In the present investigation, the relation of pre-ageing temperature and pre-ageing time to mechanical properties was studied, and a model was established to predict the mechanical properties of AA6005 Al alloy. Compared with the experimental results, the deviation of the proposed model was limited to 8.1%, which showed reasonable accuracy of forecasting. It was found that the performance of AA6005 alloy was better at higher pre-ageing temperature with shorter pre-ageing time than that at T6 temper. The microstructure of the alloy was observed by transmission electron microscopy, and the results showed that high dislocation density and precipitate density existed at 160 ℃ and 200 ℃ pre-ageing, which were in good agreement with the model.
基金Project(50374079) supported by the National Natural Science Foundation of China
文摘It is difficult to detect the anomalies whose matching relationship among some data attributes is very different from others’ in a dataset. Aiming at this problem, an approach based on wavelet analysis for detecting and amending anomalous samples was proposed. Taking full advantage of wavelet analysis’ properties of multi-resolution and local analysis, this approach is able to detect and amend anomalous samples effectively. To realize the rapid numeric computation of wavelet translation for a discrete sequence, a modified algorithm based on Newton-Cores formula was also proposed. The experimental result shows that the approach is feasible with good result and good practicality.
基金Project(90923022) supported by the National Natural Science Foundation of ChinaProject(2009220022) supported by Liaoning Science and Technology Foundation,China
文摘The predictive model of surface roughness of the spiral bevel gear (SBG) tooth based on the least square support vector machine (LSSVM) was proposed.A nonlinear LSSVM model with radial basis function (RBF) kernel was presented and then the experimental setup of PECF system was established.The Taguchi method was introduced to assess the effect of finishing parameters on the gear tooth surface roughness,and the training data was also obtained through experiments.The comparison between the predicted values and the experimental values under the same conditions was carried out.The results show that the predicted values are found to be approximately consistent with the experimental values.The mean absolute percent error (MAPE) is 2.43% for the surface roughness and 2.61% for the applied voltage.
