• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2582-2587
• /
• 2003

This paper proposes an application of sliding mode observer to the problem of fault detection and reconstruction for descriptor systems with both actuator and sensor faults. In detecting and reconstructing the faults simultaneously, first, we will consider the fault detection problem for sensor fault. The detection of sensor fault is achieved from the design of the matrix which eliminates the influence of actuator fault. Secondly, the sliding mode observer which adds the general full-order observer for descriptor system to feedforward injection map and feedforward compensation signal is designed, and through which the sensor fault is reconstructed. Finally, with the reconstructed sensor fault, and by eliminating differential term of the sensor fault, the actuator fault is detected and reconstructed.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.341-344
• /
• 1997

This paper presents a dynamics failure detection algorithm developed for the two-motor-driven electric vehicle system. The algorithm is based on the application of the fault detection filter. The fault detection includes the identification of sudden pressure drops of the two rear tires in driving axis and dynamics faults of the two inverter-motor-paired actuators An E.V. dynamics simulator is developed, which includes the modeling of the E.V. dynamics as well as the driving dynamics. The simulator, which allows the generation of various fault situations, is utilized in the verification of the developed fault detection algorithm. The results of the simulations are also presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1489-1492
• /
• 1997

To increase reliability and performance of an IMS(Intelligent Manufacturing System), fault tolerant control based on an accurate fault diagnosis is needed. In this paper, robot FDI(fault detection and identification) is proposed for IMS where the robot is controlled with state estimates of a nonlinear filter using a mathematical robot model. The Chi-square distribution is applied fault detection and fault size is estimated by a proposed bias filter. Performance of the proposed algorithm is tested by simulation for studies.

• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.5
• /
• pp.666-673
• /
• 1998

To increase reliability and performance of an IMS(Intelligent Manufacturing System), fault tolerant control based on an accurate fault diagnosis is needed. In this paper, robot FDI(fault detection and identification) is proposed for IMS where the robot is controlled with state estimates of a nonlinear filter using a mathematical robot model. The Chi-square test and GLR(General likelihood ratio) test are applied for fault detection and fault size is estimated by a proposed bias filter. Performance of the proposed algorithm is tested by simulation for studies.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.36 no.6
• /
• pp.430-436
• /
• 1987

A Detection filter that can be used for the Detection and Isolation of process faults is proposed by the use of fault vector modelling, and is applied to DC Motor fault detection. The proposed detection filter is a new one in a view point that its outputs are the estimates of fault variables(or linear combination of them) while all the existing filters estimate the state of process. By this properties, the process fault detection systems with this filter can be constructed in very simple structure. Besides the simplicity of structure and design procedure, the filter has an useful feature that various types of fault can be estimated via the filter by choosing appropriate fault models.

• Journal of KIISE:Software and Applications
• /
• v.37 no.7
• /
• pp.568-572
• /
• 2010

Self-healing is one of the techniques that assure dependability of mission-critical system. Self-healing consists of fault detection and fault recovery and fault detection is important first step that enables fault recovery but it causes overhead. We can detect fault based on model, the detection tasks that notify system's behavior and compare normal behavior model and system's behavior are heavy jobs. In this paper, we propose architecture-based multi-level self-adaptive monitoring method that complements model-based fault detection. The priority of fault detection per component is different in the software architecture. Because the seriousness and the frequency of fault per component are different. If the monitor is adapted to intensive to the component that has high priority of monitoring and loose to the component that has low priority of monitoring, the overhead can be decreased and the efficiency can be maintained. Because the environmental changes of software and the architectural changes bring the changes at the priority of fault detection, the monitor learns the changes of fault frequency and that is adapted to intensive to the component that has high priority of fault detection.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.11
• /
• pp.883-890
• /
• 2003

Two GOS (Generalized Observer Scheme) type Fault Detection Isolation Schemes (FDIS), employing the bank of unknown input functional observers (UIFO) as a residual generator, are proposed to make the practical use of the multiple observer based FDIS. The one is IFD (Instrument Fault Detection) scheme and the other is PFD (Process Fault Detection) scheme. A design method of UIFO is suggested for robust residual generation and reducing the size of the observer bank. Several design objectives that can be achieved by the FDI schemes and the design methods to meet the objectives are described. An IFD system is constructed for the Boeing 929 Jetfoil boat system to show the effectiveness of the propositions. Major contributions of this paper are two folds. Firstly, the proposed UIFO approaches considerably reduce the size of residual generator in the GOS type FDI systems. Secondly, the FDI schemes, in addition to the basic functions of the conventional observer-based FDI schemes, can reconstruct the failed signal or give the estimates of fault magnitude that can be used for compensating fault effects. The schemes are directly applicable to the design of a fault tolerant control systems.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.27 no.11
• /
• pp.587-595
• /
• 2015

In this study, fault symptoms were simulated and analyzed for a single-effect absorption chiller. The fault patterns of fault detection parameters were tabulated using the fault symptom simulation results. Fault detection and diagnosis by a process history-based method were performed for the in-situ experiment of a single-effect absorption chiller. Simulated fault modes for the in-situ experimental study are the decreases in cooling water and chilled water mass flow rates. Five no-fault reference models for fault detection of a single-effect absorption chiller were developed using fault-free steady-state data. A sensitivity analysis of fault detection using the normalized distance method was carried out with respect to fault progress. When mass flow rates of the cooling and chilled water decrease by more than 19.3% and 17.8%, respectively, the fault can be detected using the normalized distance method, and COP reductions are 6.8% and 4.7%, respectively, compared with normal operation performance. The pattern recognition method for fault diagnosis of a single-effect absorption chiller was found to indicate each failure mode accurately.

• Journal of Institute of Control, Robotics and Systems
• /
• v.18 no.12
• /
• pp.1090-1095
• /
• 2012

In this paper, we propose a model-based fault diagnosis method applied to vibration data. The fault detection is performed by comparing estimated parameters with normal parameters and deciding if the observed changes can be explained satisfactorily in terms of noise or undermodelling. The key feature of this method is that it accounts for the effects of noise and model mismatch. And we aslo design a classifier for the fault isolation by applying the multiclass SVM (Support Vector Machine) to the estimated parameters. The proposed fault detection and isolation methods are applied to an engine vibration data to show a good performance. The proposed fault detection method is compared with a signal-based fault detection method through a performance analysis.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.7 no.3 s.18
• /
• pp.140-148
• /
• 2004

Fault detection and isolation(FDI) and reconfigurable flight control system provide better survivability even though actuator faults occur. In this study, a new fault detection and isolation algorithm is proposed using fuzzy logic. When the FDI system detects the actuator fault, the fuzzy logic investigates the state variables to find which actuator has fault. Proposed fuzzy detection algorithm detect not only a single fault but also multiple faults. After detecting the fault, the reconfigurable flight control system begins operating for compensating the effects of the fault. A numerical simulation using six degree-of-freedom nonlinear aircraft model is performed to verity the performance of the proposed fault detection and isolation scheme.