For high reliability and long life systems, system pass/fail data are often rare. Integrating lower-level data, such as data drawn from the subsystem or component pass/fail testing,the Bayesian analysis can improve th...For high reliability and long life systems, system pass/fail data are often rare. Integrating lower-level data, such as data drawn from the subsystem or component pass/fail testing,the Bayesian analysis can improve the precision of the system reliability assessment. If the multi-level pass/fail data are overlapping,one challenging problem for the Bayesian analysis is to develop a likelihood function. Since the computation burden of the existing methods makes them infeasible for multi-component systems, this paper proposes an improved Bayesian approach for the system reliability assessment in light of overlapping data. This approach includes three steps： fristly searching for feasible paths based on the binary decision diagram, then screening feasible points based on space partition and constraint decomposition, and finally simplifying the likelihood function. An example of a satellite rolling control system demonstrates the feasibility and the efficiency of the proposed approach.展开更多
Similarity measure design on non-overlapped data was carried out and compared with the case of overlapped data.Unconsistant feature of similarity on overlapped data to non-overlapped data was provided by example.By th...Similarity measure design on non-overlapped data was carried out and compared with the case of overlapped data.Unconsistant feature of similarity on overlapped data to non-overlapped data was provided by example.By the artificial data illustration,it was proved that the conventional similarity measure was not proper to calculate the similarity measure of the non-overlapped case.To overcome the unbalance problem,similarity measure on non-overlapped data was obtained by considering neighbor information.Hence,different approaches to design similarity measure were proposed and proved by consideration of neighbor information.With the example of artificial data,similarity measure calculation was carried out.Similarity measure extension to intuitionistic fuzzy sets(IFSs)containing uncertainty named hesitance was also followed.展开更多
Simultaneous localization and mapping(SLAM)is widely used in many robot applications to acquire the unknown environment's map and the robots location.Graph-based SLAM is demonstrated to be effective in large-scale...Simultaneous localization and mapping(SLAM)is widely used in many robot applications to acquire the unknown environment's map and the robots location.Graph-based SLAM is demonstrated to be effective in large-scale scenarios,and it intuitively performs the SLAM as a pose graph.But because of the high data overlap rate,traditional graph-based SLAM is not efficient in some respects,such as real time performance and memory usage.To reduce1 data overlap rate,a graph-based SLAM with distributed submap strategy(DSS)is presented.In its front-end,submap based scan matching is processed and loop closing detection is conducted.Moreover in its back-end,pose graph is updated for global optimization and submap merging.From a series of experiments,it is demonstrated that graph-based SLAM with DSS reduces 51.79%data overlap rate,decreases 39.70%runtime and 24.60%memory usage.The advantages over other low overlap rate method is also proved in runtime,memory usage,accuracy and robustness performance.展开更多
基金supported by the National Natural Science Foundation of China(61304218)
文摘For high reliability and long life systems, system pass/fail data are often rare. Integrating lower-level data, such as data drawn from the subsystem or component pass/fail testing,the Bayesian analysis can improve the precision of the system reliability assessment. If the multi-level pass/fail data are overlapping,one challenging problem for the Bayesian analysis is to develop a likelihood function. Since the computation burden of the existing methods makes them infeasible for multi-component systems, this paper proposes an improved Bayesian approach for the system reliability assessment in light of overlapping data. This approach includes three steps： fristly searching for feasible paths based on the binary decision diagram, then screening feasible points based on space partition and constraint decomposition, and finally simplifying the likelihood function. An example of a satellite rolling control system demonstrates the feasibility and the efficiency of the proposed approach.
文摘Similarity measure design on non-overlapped data was carried out and compared with the case of overlapped data.Unconsistant feature of similarity on overlapped data to non-overlapped data was provided by example.By the artificial data illustration,it was proved that the conventional similarity measure was not proper to calculate the similarity measure of the non-overlapped case.To overcome the unbalance problem,similarity measure on non-overlapped data was obtained by considering neighbor information.Hence,different approaches to design similarity measure were proposed and proved by consideration of neighbor information.With the example of artificial data,similarity measure calculation was carried out.Similarity measure extension to intuitionistic fuzzy sets(IFSs)containing uncertainty named hesitance was also followed.
基金the Project Fund for Key Discipline of the Shanghai Municipal Education Commission(No.J50104)the Major State Basic Research Development Program of China(No.2017YFB0403500)。
文摘Simultaneous localization and mapping(SLAM)is widely used in many robot applications to acquire the unknown environment's map and the robots location.Graph-based SLAM is demonstrated to be effective in large-scale scenarios,and it intuitively performs the SLAM as a pose graph.But because of the high data overlap rate,traditional graph-based SLAM is not efficient in some respects,such as real time performance and memory usage.To reduce1 data overlap rate,a graph-based SLAM with distributed submap strategy(DSS)is presented.In its front-end,submap based scan matching is processed and loop closing detection is conducted.Moreover in its back-end,pose graph is updated for global optimization and submap merging.From a series of experiments,it is demonstrated that graph-based SLAM with DSS reduces 51.79%data overlap rate,decreases 39.70%runtime and 24.60%memory usage.The advantages over other low overlap rate method is also proved in runtime,memory usage,accuracy and robustness performance.
