• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.32.3-32
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• 2002

We analyze the effect of main inertial sensor errors such as, misalignment, scale factor error and bias on the performance of modified sequential probability ratio test (SPRT) for sequential fault detection and isolation (FDI). The inertial sensor errors cause the modified SPRT method to give false alarm. We use a two-stage KF to obtain a modified parity vector with which the inertial sensor errors can be removed and thus modified SPRT method can be used regardless of inertial sensor errors.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.487-490
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• 1995

This paper discisses the effects geometric errors on the measurement of error motions of rotor with the cylindrical capacitive displacement sensor. Analytic model of the measuring process with this sensor is derived and this model shows that the effect of geometric errors of sensor is larger than that of rator on the measurement of error motions of rotor. The computer simulation shows effect of periodic errors in this sensor on the measuring orbit.

• International Journal of Control, Automation, and Systems
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• v.2 no.4
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• pp.536-541
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• 2004

It is important to estimate and calibrate sensor errors in maintaining the performance level of SDINS. In this study, an estimation technique of fixed sensor errors for SDINS calibration is discussed. First, the fixed errors of gyros and accelerometers, excluding gyro biases are estimated by the navigation information of SDINS in multi-position. The SDINS with RLG includes flexure errors. In this study, the gyros flexures are out of consideration, but the proposed procedure selects certain positions and rotations in order to minimize the influence of flexures. Secondly, the influences of random walks, flexures and orientation errors are verified via numerical simulations. Thirdly, applying the previous estimated errors to SDINS, the estimation of gyro biases is conducted via the additional control signals of close-loop self-alignment. Lastly, the experiments illustrate that the extracted calibration parameters are available for the improvement of SDINS.

• Smart Structures and Systems
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• v.16 no.2
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• pp.329-345
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• 2015

As commonly known, sensor errors and faulty signals may potentially lead structures in vibration to catastrophic failures. This paper presents a new approach to deal with sensor errors/faults in vibration control of structures by using the Fault detection and isolation (FDI) technique. To demonstrate the effectiveness of the approach, a space truss structure with semi-active devices such as Magneto-Rheological (MR) damper is used as an example. To address the problem, a Linear Matrix Inequality (LMI) based fixed-order $H_{\infty}$ FDI filter is introduced and designed. Modeling errors are treated as uncertainties in the FDI filter design to verify the robustness of the proposed FDI filter. Furthermore, an innovative Fuzzy Fault Tolerant Controller (FFTC) has been developed for this space truss structure model to preserve the pre-specified performance in the presence of sensor errors or faults. Simulation results have demonstrated that the proposed FDI filter is capable of detecting and isolating sensor errors/faults and actuator faults e.g., accelerometers and MR dampers, and the proposed FFTC can maintain the structural vibration suppression in faulty conditions.

• Journal of the Korean Solar Energy Society
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• v.38 no.6
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• pp.65-72
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• 2018

Since data-driven building technologies have been widely applied to building energy systems, the accuracy of building sensors has more impacts on the building performance and system performance analysis. Various building sensors, however, can have typical errors including a random error (noise) and a systematic error (bias). The systematic error is indicated by the difference between the mean of measurements and their true value. It may occur due to the sensor's physical condition, measured phenomena, working environments inside the systems. Unfortunately, a conventional calibration method has limitations in calibrating the systematic errors because of the difference between working environments and calibration conditions. In such situations, a novel sensor calibration method is needed to handle various sensor errors, especially for systematic errors, in building energy systems having various thermodynamic environments. This study proposes a building sensor calibration method named Virtual In-situ Calibration (VIC) and shows how it is applied into a real building system and how it solves the sensor errors.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.513-518
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• 1987

In this paper the error equations of the SDINS aligned by the gyrocompass are derived considering that the alignment errors are correlated to the sensor errors. Also the navigation errors due to the correlated errors are simulated by this error equations. The simulations are performed by the covariance analysis method, assumed all the sensor errors are random constants. The simulation results show that while the INS maintains the alignment attitude the cancellation takes place between the correlated errors, but once the INS changes attitude this cancellation effect is perturbed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.672-676
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• 2004

In this paper, measuring system of 5 DOF motion errors are proposed using two capacitive type sensor, a straight edge and a laser interfoerometer. Yawing error and pitching error are measured using the laser interferometer, and rolling error is measured by the reversal method using a capacitive type sensor. Linear motion errors of horizontal and vertical direction are measured using the sequential two point method. In this case, influence of angular motion errors is compensated using the previously measured angular motion errors. In the horizontal direction, measuring accuracy is within 0.05 $\mu$m and 0.27 arcsec, and in the vertical direction, it is within 0.15 $\mu$m and 0.5 arcsec. From these results, it is confirmed that the proposed measureing system is very effective to the measurement of 5 DOF motion errors in the ultra precision feed tables.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.187-193
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• 2003

This paper presents an on-machine measurement method of flatness error fur surface machining processes. There are two kinds of on-machine measurement methods available to measure flatness errors in workpieces: i.e., surface scanning method and sensor scanning method. However, motion errors are often engaged in both methods. This paper proposes an idea to realize a measurement system of flatness errors and its rigorous application for estimation of motion errors of the positioning system. The measurement system is made by modifying the straightness measurement system, which consists of a laser, a CCD camera and processing system, a sensor head, and some optical units. The sensor head is composed of a retroreflector, a ball and ball socket, a linear motion guide unit and adjustable arms. The experimental .results show that the proposed method is useful to identify flatness errors of machined workpieces as well as motion errors of positioning systems.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.43-52
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• 1997

Ultrasonic sensors are widely employed in detecting range to a target by the virtue of their low cost and simplicity. However, the sensor's measurements are corrupted by systematic errors due mainly to the dependency of sound speed upon surrounding conditions and random errors of uncertain origin. In this paper, we present the results of research carried out to reduce these errors for increasing the reliability of an untrasonic sensor system to be used in orbotic or other automated system's range finding. The sensor system designed herein is in a peuliar structure having a reference target and two receivers. Echoes from a small reference target placed at a known distance are used for compensating the variations of sound speed according to the changes of sensing conditions. Unlike existing ones, the technique proposed can compensate the effects of temperature or any other physical parameters without an additional sensor dedicated to the compensation. The measurements by two redundantly employed receivers are fused to reduce random errors in a statistical sense. The correlation of the signals from the receivers sharing a hardware in part is considered in the fusion process. The methodology desicribed in this paepr is conceptually simple, easy to be implemented, and effetive to increase the accuracy of the sensor measurements as experimental results confirm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.536-564
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• 2019

Soft faults are inherent in wireless sensor networks (WSNs) due to external and internal errors. The failure of processes in a protocol stack are caused by errors on various layers. In this work, impact of errors and channel misbehavior on process execution is investigated to provide an error classification mechanism. Considering implementation of WSN protocol stack, inter-process correlations of stacked and peer layer processes are modeled. The proposed model is realized through local and global decision trees for fault diagnosis. A hybrid framework is proposed to implement local decision tree on sensor nodes and global decision tree on diagnostic cluster head. Local decision tree is employed to diagnose critical failures due to errors in stacked processes at node level. Global decision tree, diagnoses critical failures due to errors in peer layer processes at network level. The proposed model has been analyzed using fault tree analysis. The framework implementation has been done in Castalia. Simulation results validate the inter-process correlation model-based fault diagnosis. The hybrid framework distributes processing load on sensor nodes and diagnostic cluster head in a decentralized way, reducing communication overhead.