Research on practical and verifiable prediction methods for the service life of bearings plays a critical role in improving the reliability and safety of aircraft engines. The concept of grade-life （GL） is introduce...Research on practical and verifiable prediction methods for the service life of bearings plays a critical role in improving the reliability and safety of aircraft engines. The concept of grade-life （GL） is introduced to de- scribe the service life of bearings. A GL prognostic model for aircraft engine bearings is proposed based on sup- port vector machine （SVM） and fuzzy logic inference. Firstly, the mathematical model is discussed to predict the physics-based GL （PGL）. Then, the diagnostic estimation model based on SVM is presented in detail to predict the empirical GL （EPL）. Thirdly, a fuzzy logic inference is adopted to fuse two GL predicted results. Finally, the GL prognostic model is verified by the run-to-failure data acquired from an accelerated life test of an aircraft bearing. The results show that the model provides a more practical and reliable prediction for the service life of bearings.展开更多
A simple,stable and reliable virtual logic analyzer is presented. The logic analyzer had two modules:one was the test pattern generation module,the other was the logic monitoring module. Combining the two modules,one ...A simple,stable and reliable virtual logic analyzer is presented. The logic analyzer had two modules:one was the test pattern generation module,the other was the logic monitoring module. Combining the two modules,one is able to test a digital circuit automatically. The user interface of the logic analyzer was programmed with LabVIEW. Two Arduino UNO boards were used as the hardware targets to input and output the logic signals. The maximum pattern update rate was set to be 20 Hz. The maximum logic sampling rate was set to be 200 Hz. After twelve thousand cycles of exhaustive tests,the logic analyzer had a 100% accuracy. As a tutorial showing how to build virtual instruments with Arduino,the software detail is also explained in this article.展开更多
Identifying code has been widely used in man-machine verification to maintain network security.The challenge in engaging man-machine verification involves the correct classification of man and machine tracks.In this s...Identifying code has been widely used in man-machine verification to maintain network security.The challenge in engaging man-machine verification involves the correct classification of man and machine tracks.In this study,we propose a random forest(RF)model for man-machine verification based on the mouse movement trajectory dataset.We also compare the RF model with the baseline models(logistic regression and support vector machine)based on performance metrics such as precision,recall,false positive rates,false negative rates,F-measure,and weighted accuracy.The performance metrics of the RF model exceed those of the baseline models.展开更多
基金Supported by the China Postdoctoral Science Foundation(20100481500)~~
文摘Research on practical and verifiable prediction methods for the service life of bearings plays a critical role in improving the reliability and safety of aircraft engines. The concept of grade-life （GL） is introduced to de- scribe the service life of bearings. A GL prognostic model for aircraft engine bearings is proposed based on sup- port vector machine （SVM） and fuzzy logic inference. Firstly, the mathematical model is discussed to predict the physics-based GL （PGL）. Then, the diagnostic estimation model based on SVM is presented in detail to predict the empirical GL （EPL）. Thirdly, a fuzzy logic inference is adopted to fuse two GL predicted results. Finally, the GL prognostic model is verified by the run-to-failure data acquired from an accelerated life test of an aircraft bearing. The results show that the model provides a more practical and reliable prediction for the service life of bearings.
文摘A simple,stable and reliable virtual logic analyzer is presented. The logic analyzer had two modules:one was the test pattern generation module,the other was the logic monitoring module. Combining the two modules,one is able to test a digital circuit automatically. The user interface of the logic analyzer was programmed with LabVIEW. Two Arduino UNO boards were used as the hardware targets to input and output the logic signals. The maximum pattern update rate was set to be 20 Hz. The maximum logic sampling rate was set to be 200 Hz. After twelve thousand cycles of exhaustive tests,the logic analyzer had a 100% accuracy. As a tutorial showing how to build virtual instruments with Arduino,the software detail is also explained in this article.
基金Project supported by the National Natural Science Foundation of China(Nos.61673361 and 61422307)
文摘Identifying code has been widely used in man-machine verification to maintain network security.The challenge in engaging man-machine verification involves the correct classification of man and machine tracks.In this study,we propose a random forest(RF)model for man-machine verification based on the mouse movement trajectory dataset.We also compare the RF model with the baseline models(logistic regression and support vector machine)based on performance metrics such as precision,recall,false positive rates,false negative rates,F-measure,and weighted accuracy.The performance metrics of the RF model exceed those of the baseline models.
