• Journal of the Korean Solar Energy Society
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• v.38 no.3
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• pp.21-28
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• 2018

The objects of PV (Photovoltaic) monitoring system is to reduce the loss of system and operation and maintenance costs. In case of PV plants with configured of centralized inverter type, only 1 PV module might be caused a large loss in the PV plant. For this reason, the monitoring technology of PV module-level that find out the location of the fault module and reduce the system losses is interested. In this paper, a fault diagnosis algorithm are proposed using thermal and electrical characteristics of PV modules under failure. In addition, the monitoring system applied with proposed algorithm was constructed. The wireless sensor using LoRa chip was designed to be able to connect with IoT device in the future. The characteristics of PV module by shading is not failure but it is treated as a temporary failure. In the monitoring system, it is possible to diagnose whether or not failure of bypass diode inside the junction box. The fault diagnosis algorithm are developed on considering a situation such as communication error of wireless sensor and empirical performance evaluation are currently conducting.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.633-639
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• 2001

This paper proposes a knowledge-based expert system. which is assembled into hardware organized with sensor module. AID converter, USB. data acquisition PC and software composed of monitoring and diagnosis module combined with a frame-based method using Sohre's chart and a rule-based method. Vibration signals using various sensors are acquired by AID converter. transferred into PC and processed to obtain a continuous monitoring of the machine status displayed into several plots. Through combining frame-base which covers wide vibration causes with rule-base which gives relatively specified diagnosis results, high accuracy of fault diagnosis can be guaranteed and knowledge base can be easily extended by adding new causes or symptoms. Some examples using experimental data show the good feasibility of the proposed algorithm for condition monitoring and diagnosis of industrial rotating machinery.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.4
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• pp.254-260
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• 2000

This paper deals with the development of fault tolerant control for a nonlinear boiler system with noise and disturbance. The MCMBPC(Multivariable Constrained Model Based Predictive Control) is adopted for the control of the specific boiler turbin model. The fault detection and diagnosis are accomplished with the Kalman filter and two bias estimators. Once a fault is detected, two Bias estimators are driven to estimate the fault and to discriminate Process fault and sensor fault. In this paper, a fault tolerant control scheme combining MCMBPC with a fault compensation method based on the bias estimator is proposed. The proposed scheme has been applied to the nonlinear boiler system and shown a satisfactory performance through some simulations.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.578-580
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• 1997

A new method of Fault Diagnosis in linear systems using unknown input observer design technique is presented. This method is based upon the fact that the structural uncertainties, actuator faults, and sensor faults of a linear system can be rewritten in unknown inputs. The proposed method can simultaneously estimate the state variables of an actual system, as well as the actuator and sensor faults.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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• pp.1758-1764
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• 2012

A large number of wire rope has been used in various inderstiries as Cranes and Elevators from expanding the scale of the industrial market. But now, the management of wire rope is used as manually operated by rope replacement from over time or after the accident.It is caused to major accidents as well as economic losses and personal injury. Therefore its time to need periodic fault diagnosis of wire rope or supply of real-time monitoring system. Currently, there are several methods has been reported for fault diagnosis method of the wire rope, to find out the feature point from extracting method is becoming more common compared to time wave and model-based system. This method has implemented a deterministic modeling like the observer and neural network through considering the state of the system as a deterministic signal. However, the out-put of real system has probability characteristics, and if it is used as a current method on this system, the performance will be decreased at the real time. And if the random noise is occurred from unstable measure/experiment environment in wire rope system, diagnostic criterion becomes unclear and accuracy of diagnosis becomes blurred. Thus, more sophisticated techniques are required rather than deterministic fault diagnosis algorithm. In this paper, we developed the fault diagnosis of the wire rope using probability density estimation techniques algorithm. At first, The steady-state wire rope fault signal detection is defined as the probability model through probability distribution estimate. Wire rope defects signal is detected by a hall sensor in real-time, it is estimated by proposed probability estimation algorithm. we judge whether wire rope has defection or not using the error value from comparing two probability distribution.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.457-466
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• 2021

This paper describes the design of model-based fault diagnosis software to apply to the propulsion system in tracked amphibious assault vehicle which consists of an engine, a transmission, a cooling system, and two waterjets. This software includes specific functions to detect the failures regarding sensor malfunctions, mechanical malfunctions, control errors, and communication errors. This software generates the proper malfunction codes which are classified as the warning and caution. In order to validate the fault diagnosis software, the manual and automatic test are performed using the test program with 32 test cases. Test results show that the designed fault diagnosis software is reliable and effective for applying to the propulsion system.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.2
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• pp.89-95
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• 2003

We consider a problem of application of analytical redundancy to engine synchronization process of spark ignition engines, which is critical to timing for every ECU process including ignition and injection. The engine synchronization process we consider here is performed using the pulse signal obtained by the revolution of crankshaft trigger wheel (CTW) coupled to crank shaft. We propose a discrete-time linear model for the signal, for which we construct FDI (Fault Detection & Isolation) system consisting residual generator and threshold based on linear observer.

• Proceedings of the SAREK Conference
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• 2005.11a
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• pp.241-246
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• 2005

The objective of this study is to develop a rule-based fault detection and diagnosis algorithm and an experimental verification using air handling unit. To develop an analytical algorithm which precisely detects a faulted component, energy equations at each control volume of AHU were applied. An experimental verification was conducted in the AHU at Green Building in KIER. In the experiment conducted in hot summer condition, the rule based FDD algorithm isolated a faulted sensor from HVAC components.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.9
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• pp.627-638
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• 2022

This paper discusses the utilization of fault-tolerant technology in the industry by analyzing the status of drone failures in the unmanned vehicle industry survey conducted in 2020. Based on the survey results of the domestic unmanned vehicle industry, we identify subsystems with high fault rates and high severity when faults occur. In addition, fault simulations of the identified subsystems are conducted to analyze the effect of the fault on the vehicles. After that, the fault diagnosis and fault compensation methods studied so far are reviewed, and research cases of the methods are examined. Moreover, the ways to apply it to actual fault cases in the unmanned vehicle industry are debated. Furthermore, based on the previous discussion, the fault-tolerant system is presented, and the consideration when designing the fault-tolerant system in the industry are studied.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.12
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• pp.201-209
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• 2009

In power plant operations, sensor values often exhibit erroneous values due to their failures or the intrusions of various noises. However, most of the power plant monitoring and fault diagnosis systems perform their tasks based on the assumptions that the collected sensor values are correct all the times. These assumptions, which are not valid, often lead to serious consequences such as power plant trips. In this paper, we propose a power plant sensor value validation technique that can utilize the relationships existing among the sensor values as the sensor redundancy. The proposed technique is applied to the flow meters installed along boiler feed water systems of a typical tubular type boiler thermal power plant and shows a good potential of future applications.