| As we know, diagnostic systems constructed using traditional expert system approaches have many shortcomings, such as knowledge collected in completeness, system dependent on knowledge,and the difficulties of the acquisition of necessary diagnostic knowledge from experts etc. Model-based diagnosis is a new reasoning technique of intelligent diagnosis to overcome the shortcomings of traditional diagnostic methods model-based diagnostic method employ the model of the internal structure and behavior model of system, this method is strongly device independent,at the same time,this approach can be less costly to use.For example,the mode is given when product is designed and manufacturing at first;this mended model of product is use to that model of product. At the same time, the designing and exploitation cycle of product are shorten. Model-based diagnosis is attracted by many researchers in 1980s because of advantages and actual value. It has been an active branch in the area of artificial intelligence until 1990s. Two representative logical methods of model-based diagnosis are consistency-based diagnosis and abductive diagnosis. Consistency- based diagnosis deal with normal behavior models of system, and abductive diagnosis deal with faulty behavior models of system. No matter what it is , model representation of high efficiency is important to improve efficiency of diagnosis when we deal with complicated device. Hierarchical model-based diagnosis is put forward based on above two diagnosis methods. It's basic idea is hierarchical representation to diagnose by abstraction. The new system of abstraction have been obtained only contains finite components of abstract level. But when the components of abstraction level is elaborated to the detail levels, Candidates are made in relation to abstract levels. Such can reduce the search space of diagnosis system in order to improve diagnosis efficiency.We studied the work of "Mozetic", in which he defined three typical behavior abstraction operators mainly, including refinement/ collapse of values, introduction/deletion variables, eleboration/ simplification of mapping, and defined to model representation of detail levels in the diagnoses system which is mapped to abstraction level. The faults are isolated one level at a time by hierarohical diagnoses. At the same time, consistency condition is introduced . The first is restriction of incompleteness given a detailed level mapping m the condition, it prohibits cases where an x with an abstraction is mapped to a y without an abstraction; the second is preservation for mapping, which basically says that diagnosis which are impossible at the abstract level(where the search space is smaller)are impossible at the detailed level as well. Restriction of imcompleteness and impossible diagnoses are filtered by consistency condition in the process of diagnosis. Based on hierarohyical representation, restriction of imcompleteness and impossible diagnoses are filtered by consistency condition in the process of diagnosis, and searching space is reduced. Moreover, model representation is defined that any state of diagnoses system is mapped to observation of input and output system, which is different from consistency-based diagnoses and abductive diagnoses. We implement the algorithm using Borland Jbuider and tested it on or gate of circuit.Diagnoses system is represented hierarchically by abstraction in order to reduce the number of component of abstracted level and eliminate impossible diagnoses in detailed level by consistency condition to reduce diagnostic costs. But it is a kind of static , single,and fixed technics of hierarchical representation, which make no use of the set of currently available observations so that the efficiency of hierarchical diagnoses is not high. Such as,when the most abstraction level is not the top level but certain middle level and level 0.The level 0 is the worst condition (which is the same as general diagnoses efficiency.) We improve Mozetic's algorithm by structure abstractio...
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