• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.11
• /
• pp.218-226
• /
• 1998

In this study a neural network based expert system designed to diagnose operating status of a rotating spindle system supported by ball bearings was introduced. In order to facilitate practical failure situations, five exemplary abnormal status was fabricated. Out of several possible data source locations, seven most effective spots were chosen and proven to be the most successful in predicting single and multiple abnormalities. Increased signal strength was measured around where abnormality was embedded. Signal mea-surement locations producing high prediction rate were also classified. Even though multiple abnormalities were hard to be decoupled into their individual causes, proposed diagnostic system was somewhat effective in predicting such cases under certain combination of sensor locations. Among several abnormal operating conditions, highest prediction rate can be expected when signal is spoiled by the failure or damage in outer race. Proposed diagnostic system was again proven to be the most effective system in analyzing and ranking the importance of data sources.

• Journal of Biomedical Engineering Research
• /
• v.16 no.4
• /
• pp.555-561
• /
• 1995

In this paper, the O-Ring Measurement System (O-R MS) has been designed to supplement such subectivity and apply to the diagnosis by constitution. A single chip microprocessor of Intel MCS-51 family has been used to control the O-R MS and process data with real time, and the O-R MS could measure the minute muscular strength, expanded width between fingers, and time of the measurement. Therefore the objective constitutional diagnosis is possible by the O-R MS. As a clinical testing for estimating credibility of O-R MS, the acupuncture points representing the constitution has been stimulated using a semiconductor laser stimulator and measure the muscular strength by the O-R MS. The result of clinical testing has been shown that the constitutional diagnosis with the O-R MS is proved highly precision of 96% and it is expected that the O-R MS can be used practically for the objective constitutional diagnosis.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.674-679
• /
• 1987

Process failures can occur at any time during operation, so a continuous effort of fault detection, diagsis, and correction is required. Expert system paridigm has been regarded as a promising approach to real time process supervisory control especially to fault diagnosis. The most important aspects of fault diagnostic expert systems(FDES) are the problem-solving inference strategy and knowledge organizations. The necessity of FDES, the nature of diagnostic knowledge, the representation of knowledge, and the inference mechanism of FDES, et al. are described, which are announced by previous researchers. And the existing FDES are categorized and critically reviewed in this work.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.18 no.34
• /
• pp.25-33
• /
• 1995

An expert system DESPRESS is developed to diagnose the fault of press by using CBR technique. In this paper, we describes the subjects for development of the system. DESPRESS deals compositly with perceptive symptoms, functional abnormalities, lamp signals and gage values, and then outputs fault parts and fault status for the press. The expert system can be used to prevent occurance of unexpected fault and minimize break times for failures.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.23 no.54
• /
• pp.155-165
• /
• 2000

The fault diagnosis is a systematic and unified method to find based on the observing data resulting in noises. This paper presents the fault prediction and diagnosis using fuzzy expert system technique to manipulate the uncertainties efficiently in predictive perspective. We apply a fuzzy event tree analysis to the computer system, and build up the fault prediction and diagnosis using fuzzy expert system that predicts and diagnoses the error of the system in the advance of error.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.18 no.2
• /
• pp.323-338
• /
• 1994

This paper outlines a framework for performing intelligent sensor validation for a diagnostic expert system while reasoning under uncertainty. The emphasis is on the algorithmic preprocess technique. A companion paper focusses on heuristic post-processing. Sensor validation plays a vital role in the ability of the overall system to correctly detemine the state of a plant monitored by imperfect sensors. Especially, several theoretical developments were made in understanding uncertain sensory data in statistical aspect. Uncertain information in sensory values is represented through probability assignments on three discrete states, "high", "normal", and "low", and additional sensor confidence measures in Algorithmic Sv.Upper and lower warning limits are generated from the historical learning sets, which represents the borderlines for heat rate degradation generated in the Algorithmic SV initiates a historic data base for better reference in future use. All the information generated in the Algorithmic SV initiate a session to differentiate the sensor fault from the process fault and to make an inference on the system performance. This framework for a diagnostic expert system with sensor validation and reasonig under uncertainty applies in HEATXPRT$^{TM}$, a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.13 no.9
• /
• pp.703-712
• /
• 2003

This paper suggests a fuzzy expert system for fault diagnosis of rotating machinery, based on modulated databases. In the proposed system, alarm and trip levels are set based on ISO, considering operating condition, machinery type and maintenance history. Input signals for diagnosis, such as sub-and super-harmonic components of vibration and mean value, are normalized from 0 to 1 under the threshold level and otherwise equal to one so that chronic faults slightly below the threshold level can be monitored. The database for diagnosis consists of two modules: the well-known Sohre's chart module and if-then type rules. The Sohre's chart is utilized for the most common problems of high-speed turbomachinery, while the rule-based module, which was collected from many papers and reports, is for diagnosing peculiar faults according to the type of machinery. To infer the results from two modules, a fuzzy operation of Yager sum was adopted. Using a simulator constructed in laboratory, experimental verification was performed for the cases of unbalance and resonance which were intended. The experimental results show that the proposed fuzzy expert system has feasibility in practical diagnosis of rotating machinery.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.05a
• /
• pp.303-312
• /
• 2003

This paper suggests a fuzzy expert system for fault diagnosis of rotating machinery, based on modulated databases. In the proposed system, alarm and trip levels are set based on ISO, considering operating condition, machinery type and maintenance history. Input signals for diagnosis, such as sub- and super-harmonic components of vibration and mean value, are normalized from 0 to 1 under the threshold level and otherwise equal to one so that chronic faults slightly below the threshold level can be monitored. The database for diagnosis consists of two modules: the well-known Sohre's chart module and if-then type rules. The Sohre's chart is utilized for the most common problems of high-speed turbomachinery, while the rule-based module, which was collected from many papers and reports, is for diagnosing peculiar faults according to the type of machinery. To infer the results from two modules, a fuzzy operation of Yager sum was adopted. Using a simulator constructed in laboratory, experimental verification was performed for the cases of resonance and housing looseness which were intended. The experimental results show that the proposed fuzzy expert system has feasibility in practical diagnosis of rotating machinery.

• The Journal of Korean Association of Computer Education
• /
• v.5 no.2
• /
• pp.39-48
• /
• 2002

It is general that the ICAI(Intelligent Computer Assisted Instruction) consists of 4 modules. Export module, Teacher module, Student module and Interface module. In each module construction, there should be some rules to control strategies efficiently and systematically that are related to the texts and assessment instruments, assessment results and evaluation, feedback, etc. It is necessary to use a method to classify the curriculum into sections with units and to represent the identified relationships between them. These relationships are available to all the process of learning, assessment, evaluation and feedback. In this paper, we propose the method to represent these units and relationships as a graph. In addition, we implement an internet-based courseware authoring tool to support the environment in which several expert can construct concurrently the courseware with cooperation between them.

• Journal of The Korean Association of Information Education
• /
• v.21 no.6
• /
• pp.675-690
• /
• 2017

Preparing the 4th industrial revolution age, a diagnostic assessment management system which can collect nationwide data has been implemented and utilized for the development of the evidence-based educational policy. This study aims to develop heuristics to help to improve usability of such systems, which are utilized by primary and middle school community including teachers and students in the nationwide. To achieve the objective, previous studies related to the development of heuristics in the educational contexts as well as basic heuristics from Nielsen were reviewed, and usability problems of the web-based diagnostic-supplement system being currently utilized, as a sample system, were analyzed. Then, the first version of heuristics was developed. The developed heuristics were validated and revised through 2 rounds of the delphi methods with 15 experts. This study has an implication with preparing foundations on improving usability of such diagnostic assessment management system utilized by school community at the nationwide in educational contexts.