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1. 发明授权

US5544308A Method for automating the development and execution of diagnostic reasoning software in products and processes 失效
标题翻译：自动化诊断推理软件在产品和过程中的开发和执行的方法
公开(公告)号：US5544308A
公开(公告)日：1996-08-06
申请号：US284382
申请日：1994-08-02
申请人： Gerard J. Giordano , Gregory deMare , Betsy Longendorfer , Michael N. Granieri , John P. Giordano , Mary E. Nolan , Ford Levy
发明人： Gerard J. Giordano , Gregory deMare , Betsy Longendorfer , Michael N. Granieri , John P. Giordano , Mary E. Nolan , Ford Levy
IPC分类号： G06F11/25 , G06C15/00 , G06F11/00
CPC分类号： G06F11/2257 , Y10S706/912
摘要： A method for automated diagnosis of faults in a system containing repairable parts is performed by selecting a set of faults representing all known failures which can occur among the parts of the system, characterized by symptom data representing the expected passing or failing results for tests applied at selected test locations in the system, generating a fault/symptom matrix of the set of faults mapped to the expected passing and failing results for the selected test locations, then performing actual tests one or more test locations and correlating the actual passing or failing test results to the fault/symptom matrix in order to identify a suspect list of faults. Additional tests may be performed until the suspect list cannot be reduced further. For efficiency, the tests are selected according to which have most diagnostic significance. The design data for the parts of the system are captured and the fault/symptom matrix is preprocessed for diagnostic efficiency and speed during run time. The diagnostic method can be implemented on a single microchip and embedded in a system for on-line diagnosis during system operation, for equipment testing, or even operator training.
摘要翻译：通过选择一组故障来执行包含可修复部件的系统中的故障的自动诊断的方法，该组故障表示可在系统的各部分之间发生的所有已知故障，其特征在于，表示对应用的测试的预期通过或失败结果的症状数据在系统中选定的测试位置，生成映射到所选测试位置的预期传递和失败结果的故障集的故障/症状矩阵，然后执行实际测试一个或多个测试位置，并将实际通过或失败的测试结果相关联到故障/症状矩阵，以便识别可疑的故障列表。可以执行其他测试，直到可疑列表不能进一步减少。为了效率，根据这些测试选择具有最大的诊断意义。捕获系统部件的设计数据，并在运行时间内对故障/症状矩阵进行预处理，以提高诊断效率和速度。该诊断方法可以在单个微芯片上实现，并嵌入系统中进行在线诊断，用于设备测试，甚至操作人员培训。

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