We present a paradigmatic example of a feedbackcontrolled system: an electric motor with sensor and controller. Diagnosis of this system is performed based on a qualitative model that reflects deviations of parameters and behavior from a fixed reference state. The hypothesis that has been examined in this case study is that detection of behavior discrepancies does not necessarily require simulation of behavior, but can be done by checking (qualitative) states only. The qualitative models and the state-based diagnosis algorithm proved to establish a basis sufficient for fault detection and fault identification in the motor example. Some of the general preconditions for this are discussed.
In intelligent educational systems, assessment of what the learner is doing is a prerequisite for proper, knowledgeable guidance of the educational process. We propose to use existing techniques from the field of modelbased reasoning for this purpose. This paper describes how a modified version of GDF can be exploited in diagnosing a learner's problem solving behaviour. The problem solving task for the learner is structured prediction of behaviour. We present models of this problem solving knowledge that adhere to the representational requirements of model-based reasoning, and show how GDE-like diagnostic techniques can be employed to'determine those reasoning steps that the learner cannot have applied correctly given the observations. Our approach of diagnosing the learner's problem solving behaviour, rather than his or her misconceptions, induces an educational strategy that focusses on learning from errors and stimulates the learner's'self-repair' capabilities. Introduction One of the main bottlenecks in individualising education is the assessment and interpretation of the learner's problem solving behaviour, often referred to as cognitive diagnosis. As observed by Self, theories on modelbased diagnosis aim at providing general frameworks for diagnosis, and thus "if cognitive diagnosis is indeed a type of diagnosis..., it should be covered by these frameworks" (Self 1992). In this paper, this claim investigated by reusing existing ideas and techniques in the context educational systems. Based on an explicit model of the subject matter, we apply the 6DE paradigm (de Kleer & Williams 1987) to assess the learner's problem solving behaviour.
The automotive industry was the first to promote the development of applications of model-based systems technology on a broad scale and, as a result, has produced some of the most advanced prototypes and products. In this article, we illustrate the features and benefits of model-based systems and qualitative modeling by prototypes and application systems that were developed in the automotive industry to support on-board diagnosis, design for diagnosability, and failure modes and effects analysis. Car manufacturers and their suppliers face increasingly serious challenges particularly related to fault analysis and diagnosis during the life cycle of their products. On the one hand, the complexity and sophistication of vehicles is growing, so it is becoming harder to predict interactions between vehicle systems, especially when failures occur. On the other hand, legal regulations and the demand for safety impose strong requirements on the detection and identification of faults and the prevention of their effects on the environment or dangerous situations for passengers and other people.
The traditional reliability design methods are imperfect because the designed systems aim at fewer faults, but once a fault happens, the systems might hard fail. To solve this problem, we present a self-maintenance machine (SMM), one that can maintain its functions flexibly even though faults occur. To achieve the capabilities of diagnosing and repair planning, a model-based approach that uses qualitative physics was proposed. Regarding the repair-executing capability, control-type repair strategy was followed. A prototype of the SMM was developed, and it succeeded in maintaining its functions if the structure did not change. However, the prototype revealed the following problems when its reasoning system was used with a commercial product as embedded software: (1) poor performance of the reasoning system, (2) system size that was too large, (3) low adaptability to environmental changes, and (4) roughness of qualitative repair operations. To solve these problems, we proposed new reasoning method based on virtual cases and fuzzy qualitative values. This methodology is one of knowledge compilation, which gives better reasoning performance and can deal with real-world applications such as the SMM. By using this method, we finally developed a commercial photocopier that has self-maintainability and is more robust against faults. The commercial version has been supplied worldwide as a product of Mita Industrial Co., Ltd., since April 1994.
The state of the art in integrated circuit design is the use of special hardware description languages such as VHDL. Designs are programmed in VHDL and refined up to the point where the physical realization of the new circuit or board can be created automatically. Before that stage is reached, the designs are tested by simulating them and comparing their output to that prescribed by the specification. The task of circuit design therefore becomes primarily one of software development. A significant part of the design effort is taken up by detection of unacceptable deviations from this specification and the correction of such faults.