Sequential diagnosis is a very useful strategy for system-level fault identification because of its lower cost of hardware.In this paper,the characterization of sequentially t-diagnosable system is given,and a tmivers...Sequential diagnosis is a very useful strategy for system-level fault identification because of its lower cost of hardware.In this paper,the characterization of sequentially t-diagnosable system is given,and a tmiversal algorithm to seek faulty units in the system is developed.展开更多
Conditionally t-diagnosable and t-diagnosable are important in system level diagnosis. Therefore,it is valuable to identify whether the system is conditionally t-diagnosable or t-diagnosable and derive the correspondi...Conditionally t-diagnosable and t-diagnosable are important in system level diagnosis. Therefore,it is valuable to identify whether the system is conditionally t-diagnosable or t-diagnosable and derive the corresponding conditional diagnosability and diagnosability. In the paper,distinguishable measures of pairs of distinct faulty sets with a new perspective on establishing functions are focused.Applying distinguishable function and decision function,it is determined whether a system is conditionally t-diagnosable( or t-diagnosable) or not under the PMC( Preparata,Metze,and Chien)model directly. Based on the decision function,a novel conditional diagnosability algorithm under the PMC model is introduced which can calculate conditional diagnosability rapidly.展开更多
With the popularization of network applications and multiprocessor systems, dependability of systems has drawn considerable attention. This paper presents a new technique of node grouping for system-level fault diagno...With the popularization of network applications and multiprocessor systems, dependability of systems has drawn considerable attention. This paper presents a new technique of node grouping for system-level fault diagnosis to simplify the complexity of large system di-agnosis. The technique transforms a complicated system to a group network, where each group may consist of many nodes that are either fault-free or faulty. It is proven that the transformation leads to a unique group network to ease system diagnosis. Then it studies systematically one-step t-faults diagnosis problem based on node grouping by means of the concept of hide-pendent point sets and gives a simple sufficient and necessary condition. The paper presents a diagnosis procedure for t-diagnosable systems. Furthermore, an efficient probabilistic diagnosis algorithm for practical applications is proposed based on the belief that most of the nodes in a system are fault-free. The result of software simulation shows that the probabilistic diagnosis provides high probability of correct diagnosis and low diagnosis cost, and is suitable for systems of any kind of topology.展开更多
文摘Sequential diagnosis is a very useful strategy for system-level fault identification because of its lower cost of hardware.In this paper,the characterization of sequentially t-diagnosable system is given,and a tmiversal algorithm to seek faulty units in the system is developed.
基金Supported by the National Natural Science Foundation of China(No.61562046)Science and Technology Project of Jiangxi Provincial Education Department(No.GJJ150777,GJJ160742)
文摘Conditionally t-diagnosable and t-diagnosable are important in system level diagnosis. Therefore,it is valuable to identify whether the system is conditionally t-diagnosable or t-diagnosable and derive the corresponding conditional diagnosability and diagnosability. In the paper,distinguishable measures of pairs of distinct faulty sets with a new perspective on establishing functions are focused.Applying distinguishable function and decision function,it is determined whether a system is conditionally t-diagnosable( or t-diagnosable) or not under the PMC( Preparata,Metze,and Chien)model directly. Based on the decision function,a novel conditional diagnosability algorithm under the PMC model is introduced which can calculate conditional diagnosability rapidly.
基金the National Natural Science Foundation of China under the pants No.69973016 and No.69733010.
文摘With the popularization of network applications and multiprocessor systems, dependability of systems has drawn considerable attention. This paper presents a new technique of node grouping for system-level fault diagnosis to simplify the complexity of large system di-agnosis. The technique transforms a complicated system to a group network, where each group may consist of many nodes that are either fault-free or faulty. It is proven that the transformation leads to a unique group network to ease system diagnosis. Then it studies systematically one-step t-faults diagnosis problem based on node grouping by means of the concept of hide-pendent point sets and gives a simple sufficient and necessary condition. The paper presents a diagnosis procedure for t-diagnosable systems. Furthermore, an efficient probabilistic diagnosis algorithm for practical applications is proposed based on the belief that most of the nodes in a system are fault-free. The result of software simulation shows that the probabilistic diagnosis provides high probability of correct diagnosis and low diagnosis cost, and is suitable for systems of any kind of topology.
