• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1724-1725
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• 2007

This paper presents a fault detection and isolation(FDI) scheme for a nonlinear systems with a actuator and sensor faults. A residual generator based on the observer model generate the information for a fault detection. The proposed fault estimators are activated for a fault isolation and applied to estimate the time-varying lumped faults(model uncertainty + fault). but a fault estimator error dose not converge to zero since the derivative of lumped fault is not zero. Then the fuzzy neural network(FNN) is used to estimate the fault estimator error. Simulation results are presented to illustrate the effectiveness and the applicability of the approaches proposed.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.589-594
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• 1993

This paper presents a fault detection strategy that discriminates the faulty sensor and that detects the component fault using a bank of observers for the system in which sensor fault and component fault can occur simultaneously. Observers as many as the number of measurements are designed, and each observer uses measurements excluding sequentially one measurement, to estimate the state variables. The faulty sensor can be found out by comparing each state variable from different observer. Next, component fault can be detected by using measurements from the sensors excluding the faulty sensor. The suggested strategy is applied to a nonisothermal, series reaction with unknown reaction kinetics in a CSTR. This strategy is found out to perform well even in the case that the sensor and component fault occur simultaneously. Since each observer is designed to be independent of reaction kinetics, this strategy is not affected by the model uncertainty and nonlinearity of the reaction kinetics.

• Bulletin of the Korean Chemical Society
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• v.31 no.9
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• pp.2537-2541
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• 2010

We chose a fluorescent pentapeptide sensor (-CPGHE) containing a dansyl fluorophore as a model peptide and investigated whether the selectivity and sensitivity of the peptides for heavy and transition metal ions could be tuned by changing amino acid sequence. In this process, we developed a selective peptide sensor, Cp1-d (-HHPGE, $K_d\;=\;670\;nM$) for detection of $Zn^{2+}$ in 100% aqueous solution and a selective and sensitive peptide sensor, Cp1-e (-CCHPGE, $K_d\;=\;24\;nM$) for detection of $Cd^{2+}$ in 100% aqueous solution. Overall results indicate that the selectivity and sensitivity of the metallopeptide sensors to specific heavy and transition metal ions can be tuned by changing amino acid sequence.

• Journal of Electrochemical Science and Technology
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• v.14 no.3
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• pp.215-221
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• 2023

A rapid and environment-friendly electrochemical sensor to determine the chemical oxygen demand (COD) has been developed. The boron-doped diamond (BDD) thin-film electrode is employed as the anode, which fully oxidizes organic pollutants and provides a current response in proportion to the COD values of the sample solution. The BDD-based amperometric COD sensor is optimized in terms of the applied potential and the solution pH. At the optimized conditions, the COD sensor exhibits a linear range of 0 to 80 mg/L and the detection limit of 1.1 mg/L. Using a set of model organic compounds, the electrochemical COD sensor is compared with the conventional dichromate COD method. The result shows an excellent correlation between the two methods.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.140-152
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• 2017

This Paper is for A study of sensor fusion using Radar sensor and Vision sensor in moving object detection. Radar sensor has some problems to detect object. When the sensor moves by wind or that kind of thing, it can happen to detect wrong object like building or tress. And vision sensor is very useful for all area. And it is also used so much. but there are some weakness that is influenced easily by the light of the area, shaking of the sensor device, and weather and so on. So in this paper I want to suggest to fuse these sensor to detect object. Each sensor can fill the other's weakness, so this kind of sensor fusion makes object detection much powerful.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1117-1124
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• 2011

An integrated fault detection and isolation method is proposed in this paper. The main objective of this paper is development fault detection, isolation and diagnosis algorithm based on the DKF (Decentralized Kalman Filter) and the bank of IMM (Interacting Multiple Model) filters using penalty scalar for both partial and total faults and the outlier detection algorithm for preventing false alarm also included. The proposed FDI (Fault Detection and Isolation) scheme is developed in four phases. In the first phase, the outlier detection filter is designed to prevent false alarm as a pre-filter. In the second phases, two local filters and master filter are designed to detect sensor faults. In the third phases, the proposed FDI scheme checks sensor residual to isolate sensor faults and 11 EKFs actuator fault models are designed to detect wherever actuator faults occur. In the last phases, four filters are designed to identify the fault type which is either the total fault or partial fault. The developed scheme can deal with not only sensor and actuator faults, but also preventing false alarm. An important feature of the proposed FDI scheme can decreases fault isolation time and figure out not only fault detection and isolation but also fault type identification. To verify the proposed FDI algorithm performance, the Simulator is also developed under the Matlab/Simulink environment.

• Journal of IKEEE
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• v.13 no.3
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• pp.39-46
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• 2009

Wireless sensor networks consist of small, autonomous devices with wireless networking capabilities. In order to further increase the applicability in real world applications, minimizing energy consumption is one of the most critical issues. Therefore, accurate energy model is required for the evaluation of wireless sensor networks. In this paper we analyze the power consumption for wireless sensor networks. To develop the power consumption model, we have measured the power characteristics of commercial Kmote node based on TelosB platforms running TinyOS. Based on our model, the estimated lifetime of a battery powered sensor node can use about 6.9 months for application of human detection using PIR sensors. This result indicates that sensor nodes can be used in a monitoring system for elderly living alone.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.11a
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• pp.192-195
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• 2008

A sensor fault detection method for small turbo shaft engine considering multiple trim conditions is proposed. This engine is used in a helicopter. Firstly, under multiple trim conditions, we derive the linearized models from a nonlinear model which includes engine, rotor and feedback control loop. As a fault detection method, we adopt the Kalman filter based method. To keep continuity of estimates between the changes of trim conditions, we reconfigure the initial values of state variables at trim changes. We detect the faults with two steps that when the first filter does not alarm the faults for some sensors, the second filter is runned for other sensor. Via some simulations we show that the proposed method works well under multiple trim conditions.

• Composites Research
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• v.13 no.6
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• pp.47-54
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• 2000

One promising method for impact detection of composite structures is based on the use of piezopolymer thin fim (PVDf) sensor. In this paper, the relationship between the contact force and the signals of the attached strain gage and PVDF sensor to the composite plate subjected to low-velocity impact were derived. The relation for the open circuit and short circuit voltage of PVDF sensor was derived based on the equivalent circuit model of the piezoelectric sensor. The work was then extended to include experimental investigation into the use of short circuit voltage of PVDF sensor without using charge amplifier to detect low-velocity impact. The natural frequencies and damping ratio of the composite plate obtained from the vibration test were used to modify the analytical model and therefore the differences between measured and simulated signal of the modified analytical model in both forward and backward problem were considerably reduced. The reconstructed contact force and simulated sensor signals agreed well with the measured contact force, strain gage signal, and PVDF sensor singanl.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.17-24
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• 2006

We consider the sensor location problem (SLP) on a given sensor field. We present the sensor field as grid of points. There are several types of sensors which have different detection ranges and costs. If a sensor is placed in some point, the points inside of its detection range can be covered. The coverage ratio decreases with distance. The problem we consider in this thesis is called multiple-type differential coverage sensor location problem (MDSLP). MDSLP is more realistic than SLP. The coverage quantities of points are different with their distance form sensor location in MDSLP. The objective of MDSLP is to minimize total sensor costs while covering every sensor field. This problem is known as NP-hard. We propose a new integer programming formulation of the problem. In comparison with the previous models, the new model has a smaller number of constraints and variables. This problem has symmetric structure in its solutions. This group is used for pruning in the branch-and-bound tree. We solved this problem by branch-and-cut(B&C) approach. We tested our algorithm on about 60 instances with varying sizes.