• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10b
• /
• pp.1216-1221
• /
• 1990

An algorithm for multiple fault diagnosis of linear dynamic systems is proposed. The algorithm is constructed by using of the geometric approach based on observation that, when the number of faulty units of the system is known, the set of faulty units can be differentiated from other sets by checking linear varieties in the measurement data space. It is further shown that the system with t number of faults can be diagnosed within (t+1) sample-time units if the input-output measurements are rich and that the algorithm can be used for diagnosis even when the number of faults is not known in advance.

• Journal of IKEEE
• /
• v.7 no.1 s.12
• /
• pp.107-118
• /
• 2003

In this paper, dynamic control model is formulated by considering the geometrical structure of the deaerator storage tank in nuclear power plant and input-output flow rate at steady state, and we describe fault detection and diagnosis (FDD) scheme based on the adaptive estimator. The performance and effectiveness of the proposed FDD scheme are evaluated by applying real operating data obtained from the YOUNGKWANG 3 & 4 FSAR.

• Proceedings of the KIEE Conference
• /
• 1999.11d
• /
• pp.1025-1027
• /
• 1999

Recently, many researches on a diagnosis of stator winding insulation of large generators are reported. They mostly utilize a trend analysis of Partial Discharge (PD). In this paper, a novel on-line monitoring system for an insulation diagnosis is proposed. This system obtains the parameters such as Maximum Partial Discharge Magnitude (QM), Normalized Quantity Number (NQN) and Dynamic Stagnation Voltage (DSV) by continuous on-line monitoring of winding insulation. It is capable of diagnosing the insulation condition by analyzing the trend of PD and utilizing the database built by the system.

• Advances in robotics research
• /
• v.2 no.1
• /
• pp.99-112
• /
• 2018

The main contribution of this work is the design of a field programmable gate array (FPGA) based ARX-Laguerre proportional-integral observation (PIO) system for fault detection and identification (FDI) in a multi-input, multi-output (MIMO) nonlinear uncertain dynamical robot manipulators. An ARX-Laguerre method was used in this study to dynamic modeling the robot manipulator in the presence of uncertainty and disturbance. To address the challenges of robustness, fault detection, isolation, and estimation the proposed FPGA-based PI observer was applied to the ARX-Laguerre robot model. The effectiveness and accuracy of FPGA based ARX-Laguerre PIO was tested by first three degrees of the freedom PUMA robot manipulator, yielding 6.3%, 10.73%, and 4.23%, average performance improvement for three types of faults (e.g., actuator fault, sensor faults, and composite fault), respectively.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.11a
• /
• pp.134-139
• /
• 2004

The correlation dimension of a nonlinear method for the diagnosis on the clearance of rotating machinery is introduced in this paper. The correlation dimension can provide some intrinsic information of an underlying dynamic system by reconstructing measured scalar time series. Vibration signals measured from a rotor with different operating conditions are analyzed using the correlation dimension. The results show that the correlation dimension method can identify the magnitude of the clearance of a rotor and the lubricating condition.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
• /
• 2004.06a
• /
• pp.62-67
• /
• 2004

• Proceedings of the Korean Nuclear Society Conference
• /
• 2004.05a
• /
• pp.219-219
• /
• 2004

• Proceedings of the Korean Nuclear Society Conference
• /
• 1999.10a
• /
• pp.101.2-101
• /
• 1999

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.10
• /
• pp.931-940
• /
• 2017

This paper describes a predictive fault diagnosis algorithm for autonomous vehicles based on a kinematic model that uses a sliding mode observer. To ensure the safety of autonomous vehicles, reliable information about the environment and vehicle dynamic states is required. A predictive algorithm that can interactively diagnose longitudinal environment and vehicle acceleration information is proposed in this paper to evaluate the reliability of sensors. To design the diagnosis algorithm, a longitudinal kinematic model is used based on a sliding mode observer. The reliability of the fault diagnosis algorithm can be ensured because the sliding mode observer utilized can reconstruct the relative acceleration despite faulty signals in the longitudinal environment information. Actual data based performance evaluations are conducted with various fault conditions for a reasonable performance evaluation of the predictive fault diagnosis algorithm presented in this paper. The evaluation results show that the proposed diagnosis algorithm can reasonably diagnose the faults in the longitudinal environment and acceleration information for all fault conditions.

• Transactions on Control, Automation and Systems Engineering
• /
• v.2 no.1
• /
• pp.24-30
• /
• 2000

The aim of this paper is to describe an advanced method of the fault diagnosis using Control Theory with reference to a crack detection, a new way to localize the crack position under influence of the plant disturbance and white measurement noise on a rotating shaft. As the first step, the shaft is physically modelled with a finite element method as usual and the dynamic mathematical model is derived from it using the Hamilton-principle and in this way the system is modelled by various subsystems. The equations of motions with a crack are established by the adaption of the local stiffness change through breathing and gaping[1] from the crack to the equation of motion with an undamaged shaft. This is supposed to be regarded as a reference system for the given system. Based on the fictitious model of the time behaviour induced from vibration phenomena measured at the bearings, a nonlinear state observer is designed in order to detect the crack on the shaft. This is the elementary NL-observer(EOB). Using the elementary observer, an Estimator(Observer Bank) is established and arranged at the certain position on the shaft. In case, a crack is found and its position is known, the procedure, fro the estimation of the depth is going to begin.