Accurate test effectiveness estimation for analogue and mixed-signal Systems on a Chip (SoCs) is currently prohibitive in the design environment. One of the factors that sky rockets fault simulation costs is the numbe...Accurate test effectiveness estimation for analogue and mixed-signal Systems on a Chip (SoCs) is currently prohibitive in the design environment. One of the factors that sky rockets fault simulation costs is the number of structural faults which need to be simulated at circuit-level. The purpose of this paper is to propose a novel fault list compression technique by defining a stratified fault list, build with a set of “representative” faults, one per stratum. Criteria to partition the fault list in strata, and to identify representative faults are presented and discussed. A fault representativeness metric is proposed, based on an error probability. The proposed methodology allows different tradeoffs between fault list compression and fault representation accuracy. These tradeoffs may be optimized for each test preparation phase. The fault representativeness vs. fault list compression tradeoff is evaluated with an industrial case study—a DC-DC (switched buck converter). Although the methodology is presented in this paper using a very simple fault model, it may be easily extended to be used with more elaborate fault models. The proposed technique is a significant contribution to make mixed-signal fault simulation cost-effective as part of the production test preparation.展开更多
A new identification method of neuro-uzzy Hammerstein model based on probability density function(PDF) is presented,which is different from the idea that mean squared error(MSE) is employed as the index function in tr...A new identification method of neuro-uzzy Hammerstein model based on probability density function(PDF) is presented,which is different from the idea that mean squared error(MSE) is employed as the index function in traditional identification methods.Firstly,a neuro-fuzzy based Hammerstein model is constructed to describe the nonlinearity of Hammerstein process without any prior process knowledge.Secondly,a kind of special test signal is used to separate the link parts of the Hammerstein model.More specifically,the conception of PDF is introduced to solve the identification problem of the neuro-fuzzy Hammerstein model.The antecedent parameters are estimated by a clustering algorithm,while the consequent parameters of the model are identified by designing a virtual PDF control system in which the PDF of the modeling error is estimated and controlled to converge to the target.The proposed method not only guarantees the accuracy of the model but also dominates the spatial distribution of PDF of the model error to improve the generalization ability of the model.Simulated results show the effectiveness of the proposed method.展开更多
针对通用测试系统对系统统一模型的迫切需求以及目前ATE(AutomaticTest Equipment)模型化设计的不足,基于信号建立了一套完整、有效的ATE系统模型.此模型将ATE系统的硬件资源以及UUT(Unit Under Test)均进行了模型化处理.提出了基于TFF(...针对通用测试系统对系统统一模型的迫切需求以及目前ATE(AutomaticTest Equipment)模型化设计的不足,基于信号建立了一套完整、有效的ATE系统模型.此模型将ATE系统的硬件资源以及UUT(Unit Under Test)均进行了模型化处理.提出了基于TFF(Test Foundation Framework)的基本信号模型;提出了完全基于信号的仪器驱动模型;提出了基于测试与诊断相结合思想的UUT模型;提出了基于模型间信息共享的思想和路径以逻辑开关描述思想的路径模型.该模型体系为系统资源配置、仪器可互换、测试程序自动生成以及故障诊断提供了强有力的模型基础,从而大大加快了ATE的设计过程,从很大程度上降低了开发成本.展开更多
文摘Accurate test effectiveness estimation for analogue and mixed-signal Systems on a Chip (SoCs) is currently prohibitive in the design environment. One of the factors that sky rockets fault simulation costs is the number of structural faults which need to be simulated at circuit-level. The purpose of this paper is to propose a novel fault list compression technique by defining a stratified fault list, build with a set of “representative” faults, one per stratum. Criteria to partition the fault list in strata, and to identify representative faults are presented and discussed. A fault representativeness metric is proposed, based on an error probability. The proposed methodology allows different tradeoffs between fault list compression and fault representation accuracy. These tradeoffs may be optimized for each test preparation phase. The fault representativeness vs. fault list compression tradeoff is evaluated with an industrial case study—a DC-DC (switched buck converter). Although the methodology is presented in this paper using a very simple fault model, it may be easily extended to be used with more elaborate fault models. The proposed technique is a significant contribution to make mixed-signal fault simulation cost-effective as part of the production test preparation.
基金National Natural Science Foundation of China(No.61374044)Shanghai Municipal Science and Technology Commission,China(No.15510722100)+2 种基金Shanghai Municipal Education Commission,China(No.14ZZ088)Shanghai Talent Development Plan,ChinaShanghai Baoshan Science and Technology Commission,China(No.bkw2013120)
文摘A new identification method of neuro-uzzy Hammerstein model based on probability density function(PDF) is presented,which is different from the idea that mean squared error(MSE) is employed as the index function in traditional identification methods.Firstly,a neuro-fuzzy based Hammerstein model is constructed to describe the nonlinearity of Hammerstein process without any prior process knowledge.Secondly,a kind of special test signal is used to separate the link parts of the Hammerstein model.More specifically,the conception of PDF is introduced to solve the identification problem of the neuro-fuzzy Hammerstein model.The antecedent parameters are estimated by a clustering algorithm,while the consequent parameters of the model are identified by designing a virtual PDF control system in which the PDF of the modeling error is estimated and controlled to converge to the target.The proposed method not only guarantees the accuracy of the model but also dominates the spatial distribution of PDF of the model error to improve the generalization ability of the model.Simulated results show the effectiveness of the proposed method.
文摘针对通用测试系统对系统统一模型的迫切需求以及目前ATE(AutomaticTest Equipment)模型化设计的不足,基于信号建立了一套完整、有效的ATE系统模型.此模型将ATE系统的硬件资源以及UUT(Unit Under Test)均进行了模型化处理.提出了基于TFF(Test Foundation Framework)的基本信号模型;提出了完全基于信号的仪器驱动模型;提出了基于测试与诊断相结合思想的UUT模型;提出了基于模型间信息共享的思想和路径以逻辑开关描述思想的路径模型.该模型体系为系统资源配置、仪器可互换、测试程序自动生成以及故障诊断提供了强有力的模型基础,从而大大加快了ATE的设计过程,从很大程度上降低了开发成本.
