With the Industry 4.0 era coming, modern chemical plants will be gradually transformed into smart factories, which sets higher requirements for fault detection and diagnosis(FDD) to enhance operation safety intelligen...With the Industry 4.0 era coming, modern chemical plants will be gradually transformed into smart factories, which sets higher requirements for fault detection and diagnosis(FDD) to enhance operation safety intelligence. In a typical chemical process, there are hundreds of process variables. Feature selection is a key to the efficiency and effectiveness of FDD. Even though artificial immune system has advantages in adaptation and independency on a large number of fault samples, antibody library construction used to be based on experience. It is not only time consuming, but also lack of scientific foundation in fault feature selection, which may deteriorate the FDD performance of the AIS. In this paper, a fault antibody feature selection optimization(FAFSO) algorithm is proposed based on genetic algorithm to optimize the fault antibody features and the antibody libraries' thresholds simultaneously. The performance of the proposed FAFSO algorithms is illustrated through the Tennessee Eastman benchmark problem.展开更多
Developing an efficient and robust lightweight graphic user interface （GUI） for industry process monitoring is always a challenging task. Current implementation methods for embedded GUI are with the matters of real-...Developing an efficient and robust lightweight graphic user interface （GUI） for industry process monitoring is always a challenging task. Current implementation methods for embedded GUI are with the matters of real-time processing and ergonomics performance. To address the issue, an embedded lightweight GUI component library design method based on quasar technology embedded （Qt/E） is proposed. First, an entity-relationship （E-R） model for the GUI library is developed to define the functional framework and data coupling relations. Second, a cross-compilation environment is constructed, and the QI/E shared library files are tailored to satisfy the requirements of embedded target systems. Third, by using the signal-slot communication interfaces, a message mapping mechanism that does not require a call-back pointer is developed, and the context switching performance is improved. According to the multi-thread method, the parallel task processing capabilities fbr data collection, calculation, and display are enhanced, and the real-time performance and robustness are guaranteed. Finally, the human-computer interaction process is optimized by a scrolling page method, and the ergonomics pertbrmance is verified by the industrial psychology methods Two numerical cases and five industrial experiments show that the proposed method can increase real-time read-write correction ratios by more than 26% and 29%, compared with Windows-CE-GUl and Android-GUl, respectively. The component library can be tailored to 900 KB and supports 12 hardware platforms. The average session switch time can be controlled within 0.6 s and six key indexes for ergonomics are verified by different industrial applications.展开更多
基金Supported by the National Natural Science Foundation of China(61433001)
文摘With the Industry 4.0 era coming, modern chemical plants will be gradually transformed into smart factories, which sets higher requirements for fault detection and diagnosis(FDD) to enhance operation safety intelligence. In a typical chemical process, there are hundreds of process variables. Feature selection is a key to the efficiency and effectiveness of FDD. Even though artificial immune system has advantages in adaptation and independency on a large number of fault samples, antibody library construction used to be based on experience. It is not only time consuming, but also lack of scientific foundation in fault feature selection, which may deteriorate the FDD performance of the AIS. In this paper, a fault antibody feature selection optimization(FAFSO) algorithm is proposed based on genetic algorithm to optimize the fault antibody features and the antibody libraries' thresholds simultaneously. The performance of the proposed FAFSO algorithms is illustrated through the Tennessee Eastman benchmark problem.
基金Project supported by the National Natural Science Foundation of China(Nos.51775501,51375446,U1509212,and 51405441)the Zhejiang Provincial Natural Science Foundation,China(No.LR16E050001)the Zhejiang Provincial Health Department Program,China(No.2015KYA067)
文摘Developing an efficient and robust lightweight graphic user interface （GUI） for industry process monitoring is always a challenging task. Current implementation methods for embedded GUI are with the matters of real-time processing and ergonomics performance. To address the issue, an embedded lightweight GUI component library design method based on quasar technology embedded （Qt/E） is proposed. First, an entity-relationship （E-R） model for the GUI library is developed to define the functional framework and data coupling relations. Second, a cross-compilation environment is constructed, and the QI/E shared library files are tailored to satisfy the requirements of embedded target systems. Third, by using the signal-slot communication interfaces, a message mapping mechanism that does not require a call-back pointer is developed, and the context switching performance is improved. According to the multi-thread method, the parallel task processing capabilities fbr data collection, calculation, and display are enhanced, and the real-time performance and robustness are guaranteed. Finally, the human-computer interaction process is optimized by a scrolling page method, and the ergonomics pertbrmance is verified by the industrial psychology methods Two numerical cases and five industrial experiments show that the proposed method can increase real-time read-write correction ratios by more than 26% and 29%, compared with Windows-CE-GUl and Android-GUl, respectively. The component library can be tailored to 900 KB and supports 12 hardware platforms. The average session switch time can be controlled within 0.6 s and six key indexes for ergonomics are verified by different industrial applications.
