A novel detection method of support vector machine （SVM） based on fractal dimension of signals is presented. And models of SVM are made based on nugget size defects of spot welding. Classification using these traine...A novel detection method of support vector machine （SVM） based on fractal dimension of signals is presented. And models of SVM are made based on nugget size defects of spot welding. Classification using these trained SVM models is done to signals of spot welding. It is shown from effect of different SVM models that these models with different inputs. In detection of defects, these models with inputs including sound signal have a high percentage of accuracy, the detection accuracy of these models with inputs including voltage signal will reduce. So the SVM models based on fractal dimensions of sound are some optimal nondestructive detection ones. At last a comparison between SVM detection model and ANNS detection model is researched which indicates that SVM is a more effective measure than Artificial neural networks in detection of nugget size defects during spot welding.展开更多
The acoustic emission signal of aluminum alloys spot welding includes the information of forming nugget and is one of the important parameters in the quality control. Due to the nonlinearity of the signals, classic Eu...The acoustic emission signal of aluminum alloys spot welding includes the information of forming nugget and is one of the important parameters in the quality control. Due to the nonlinearity of the signals, classic Euclidean geometry can not be applied to depict exactly. The fractal theory is implemented to quantitatively describe the characteristics of the acoustic emission signals. The experiment and calculation results show that the box counting dimension of acoustic emission signal, between 1 and 2, are distinctive from different nugget areas in AC spot welding. It is proved that box counting dimension is an effective characteristic parameter to evaluate spot welding quality. In addition, fractal theory can also be applied in other spot welding parameters, such as voltage, current, electrode force and so on, for the purpose of recognizing the spot welding quality.展开更多
The relation between acoustic emission signal and nugget during aluminum alloy spot welding was investigated in order to evaluate spot welding quality. Due to the nonlinearity of the signals, fractal theory was utiliz...The relation between acoustic emission signal and nugget during aluminum alloy spot welding was investigated in order to evaluate spot welding quality. Due to the nonlinearity of the signals, fractal theory was utilized to quantitatively describe the characteristics of the signals instead of classical Euclidean geometry which cannot describe the acoustic emission signal accurately. Through experiments and computing, the box counting dimension is found distinct from other acoustic emission signals and is a better approach to discriminating weld nugget stages. Results show that fractal dimensions increase from 1.51 to 1.78,and they are related to nugget areas added from non-fusion to over-heated nugget. And the box counting dimension can effectively evaluate the quality of the nugget in the spot welding and can be aoolied with current, displace, and other soot welding parameters.展开更多
Based on the judgement of fractional Br ow nian motion, this paper analyzes the radial rotating error of a precision rotor. The results indicate that the rotating error motion of the precision rot or is characterized...Based on the judgement of fractional Br ow nian motion, this paper analyzes the radial rotating error of a precision rotor. The results indicate that the rotating error motion of the precision rot or is characterized by basic fractional Brownian motions, i.e. randomicity, non -sequencity, and self-simulation insinuation to some extent. Also, this paper calculates the fractal box counting dimension of radial rotating error and judges that the rotor error motion is of stability, indicating that the motion range of the future track of the axes is relatively stable.展开更多
基金supported by National Natural Science Foundation of China (No.50575159)Science Foundation of Ministry of Education of China (No.106049)+1 种基金Doctoral Foundation of Ministry of Education of China (No.20060056058)and Tianjin Municipal Natural Science Foundation of China (No.06YFJMJC03400).
文摘A novel detection method of support vector machine （SVM） based on fractal dimension of signals is presented. And models of SVM are made based on nugget size defects of spot welding. Classification using these trained SVM models is done to signals of spot welding. It is shown from effect of different SVM models that these models with different inputs. In detection of defects, these models with inputs including sound signal have a high percentage of accuracy, the detection accuracy of these models with inputs including voltage signal will reduce. So the SVM models based on fractal dimensions of sound are some optimal nondestructive detection ones. At last a comparison between SVM detection model and ANNS detection model is researched which indicates that SVM is a more effective measure than Artificial neural networks in detection of nugget size defects during spot welding.
基金This research was supported by National Natural Science Foundation of China( No50575159)project of Chinese Ministry ofEducation(No106049, 20060056058)Natural Science Foundation of Tianjin (06YFJMJC03400)
文摘The acoustic emission signal of aluminum alloys spot welding includes the information of forming nugget and is one of the important parameters in the quality control. Due to the nonlinearity of the signals, classic Euclidean geometry can not be applied to depict exactly. The fractal theory is implemented to quantitatively describe the characteristics of the acoustic emission signals. The experiment and calculation results show that the box counting dimension of acoustic emission signal, between 1 and 2, are distinctive from different nugget areas in AC spot welding. It is proved that box counting dimension is an effective characteristic parameter to evaluate spot welding quality. In addition, fractal theory can also be applied in other spot welding parameters, such as voltage, current, electrode force and so on, for the purpose of recognizing the spot welding quality.
基金Supported by National Natural Science Foundation of China(No.50575159)Ministry of Education of China(No.20060056058 ,No.106049)Natural Science Foundation of Tianjin(No.06YFJMJC03400) .
文摘The relation between acoustic emission signal and nugget during aluminum alloy spot welding was investigated in order to evaluate spot welding quality. Due to the nonlinearity of the signals, fractal theory was utilized to quantitatively describe the characteristics of the signals instead of classical Euclidean geometry which cannot describe the acoustic emission signal accurately. Through experiments and computing, the box counting dimension is found distinct from other acoustic emission signals and is a better approach to discriminating weld nugget stages. Results show that fractal dimensions increase from 1.51 to 1.78,and they are related to nugget areas added from non-fusion to over-heated nugget. And the box counting dimension can effectively evaluate the quality of the nugget in the spot welding and can be aoolied with current, displace, and other soot welding parameters.
文摘Based on the judgement of fractional Br ow nian motion, this paper analyzes the radial rotating error of a precision rotor. The results indicate that the rotating error motion of the precision rot or is characterized by basic fractional Brownian motions, i.e. randomicity, non -sequencity, and self-simulation insinuation to some extent. Also, this paper calculates the fractal box counting dimension of radial rotating error and judges that the rotor error motion is of stability, indicating that the motion range of the future track of the axes is relatively stable.
