• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.988-990
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• 1999

Using neural network approach, the diagnosis of faults in industrial process that requires observing multiple data simultaneously are studied in this paper. Two-stage diagnosis is proposed as the basic structure. The first stage detects the dynamic trend of each measurements and the second stage diagnosis the faults. This paper makes up for the disadvantage of neural about unknown faults. The potential of this approach is demonstrated in simulation using a model of tank reactor.

• Proceedings of the KIEE Conference
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• 2003.07e
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• pp.113-116
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• 2003

BiCMOS circuit consist of CMOS part which constructs logic function, and bipolar part which drives output load. In this paper, proposes a method for efficiently generating test pattern which detect faults in BiCMOS circuits. In proposed method, BiCMOS circuit is divided into pull-up part and pull-down part, using structural property of BiCMOS circuit, and we generate test pattern using set theory for efficiently detecting faults which occured each divided blocks.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.314-316
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• 1993

In this paper, a method to detect and diagnose faults in Automated Manufacturing Systems(AMS) is proposed. In AMS, it is necessary to monitor the process-status. The detection and diagnosis of faults are often difficult in monitoring level with given passive data. We propose the model-based monitoring system for faults detection and diagnosis using Petri Nets to model AMS efficiently and easily. Simulation results show the validity of proposed method with example of Reverse Mill Process in Automated Mill Lines.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.127.1-127
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• 2001

In this paper we propose an input/output model based fault diagnosis method to detect and isolate single faults in the robot arm control system. The proposed algorithm is functionally composed of three main parts-parameter estimation, fault detection, and isolation, When a change in the system occurs, the errors between the system output and the estimated output cross a predetermined threshold, and once a fault in the system is detected, and in this zone the estimated parameters are transferred to the fault classifier by ART2(adaptive resonance theory 2) neural network for fault isolation. Since ART2 neural network is an unsupervised neural network fault classifier does not require the knowledge of all possible faults to isolate the faults occurred in the system. Simulations are carried out to evaluate the performance of the proposed ...

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.399-405
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• 2008

Recently, robot technology is actively going on progress to the field of various services such as home care, medical care, entertainment, and etc. Because these service robots are in use nearby person, they need to be operated safely even though hardware and software faults occur. This paper proposes a Fault-Tolerant middleware for a robot system, which has following two characteristics: supporting of heterogeneous network interface and processing of software components and network faults. The Fault-Tolerant middleware consists of a Service Layer(SL), a Network Adaptation Layer(NAL), a Network Interface Layer(NIL), a Operating System ion Layer(OSAL), and a Fault-Tolerant Manager(FTM). Especially, the Fault-Tolerant Manager consists of 4 components: Monitor, Fault Detector, Fault Notifier, and Fault Recover to detect and recover the faults effectively. This paper implements and tests the proposed middleware. Some experiment results show that the proposed Fault-Tolerant middleware is working well.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.233-238
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• 2000

CNC machine tool is assembled by central processor, PLC(Programmable Logic Controller), and actuator. The sequential control of machine generally controlled by a PLC. The main fault occured at PLC in 3 control parts. In LC faults, operational fault is charged over 70%. This paper describes diagnosis model and data processing for remote monitoring and diagnosis system in machine tools with open architecture controller. Two diagnostic models based on the ladder diagram. Logical Diagnosis Model(LDM), Sequential Diagnosis Model(SDM), are proposed. Data processing structure is proposed ST(Structured Text) based on IEC1131-3. The faults from CNC are received message form open architecture controller and faults from PLC are gathered by sequential data.. To do this, CNC and PLC's logical and sequential data is constructed database.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.6
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• pp.619-623
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• 2008

As higher reliability and accuracy on production facilities are required to detect incipient faults, a diagnostic system for predictive maintenance of the facility is highly recommended. In this paper, it presents a study on the application of vibration signals to diagnose faults for a rotating machinery using the Mahalanobis distance-Taguchi system. RMS, crest factor and Kurtosis that is known as the statistical methods and the spectrum analysis are used to diagnose faults as parameters of Mahalanobis distance.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.7
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• pp.759-766
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• 1988

the effect of heat treatment in oxygen ambient on the nucleation and growth of oxidation induced stacking faults(OSF) in n-type(100)silicon wafer has been investigated. The growth of OSF is determind as a function of oxygen concentration in silicon wafer, heat treatment time and temperature, and the activation energy for the growth of OSF can be obtained from the growth kinetics. The activation energies are respectively 2.66 eV for dry oxidation and 2.37 eV for wet oxidation. In this paper, we have also studied the structural feature of OSF with the comparison of optical microscopic morphology and crystalline structure.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.1-9
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• 1994

This paper analyzes the faults and their mechanism of CMOS ICs using IDDQ testing technique and evalutes the reliability of the chips that fail this test. It is implemented by the three testing phases, initial test, burn-in and life test. Each testing phase includes the parametric test, functional test, IDDQ test and propagation delay test. It is shown that the short faults such as gate-oxide short, bridging can be only detected by IDDQ testing technique and the number of test patterns for this test technique is very few. After first burn-in, the IDDQ of some test chips is decreased, which is increased in conventional studies and in subsequent burn-in, the IDDQ of all test chips is stabilized. It is verified that the resistive short faults exist in the test chips and it is deteriorated with time and causes the logic fault. Also, the new testing technique which can easily detect the rsistive short fault is proposed.

• Journal of the Korean Society for Railway
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• v.9 no.6 s.37
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• pp.725-731
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• 2006

Hot Standby sparing system detecting faults by using software, and being tolerant any faults by using Hardware Redundancy is difficult to perform quantitative reliability prediction and to detect real time faults. Therefore, this paper designs Hot Standby sparing system using hardware basis self checking logic in order to overcome this problem. It also performs failure mode analysis of Hot Standby sparing system with designed self checking logic by using FMEA (Failure Mode Effect Analysis), and identifies reliability assessment of the controller designed by quantifying the numbers of failure development by using FTA (Fault Tree Analysis)