• Journal of the Korean Society for Precision Engineering
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• v.16 no.9
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• pp.62-67
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• 1999

In milling, cutting tool ins directly attached to spindle and this tells that spindle can provide very useful information on the cutting tool condition such as wear or breakage. Since spindle is rotating at a high speed, measuring spindle velocity using a noncontacting measurement system gives the best information which can be obtained. Due to the force applied to spindle through cutting tool, velocity of spindle changes. And any change in cutting tool condition affects cutting force and consequently spindle vibration. With the intent of continuously monitoring cutting tool condition in intermittent machining operations in a benign manner, a noncontacting velocity measurement system using a laser Doppler velocimeter was assembled to measure spindle torsional vibration. Spindle vibration was measured and analysis of it in the frequency domain yielded a measure which corresponded to amount of cutting tool wear in milling.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.518-524
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• 2011

This paper presents a study on the calibration of accelerometer data in the gyroscope free inertial navigation system(GFINS) using fuzzy inference system(FIS). The conventional INS(inertial navigation system) which can measure yaw rate and linear velocity using inertial sensors as the gyroscope and accelerometer. However, the INS is difficult to design as small size and low power because it uses the gyroscope. To solve the problem, the GFINS which does not have the gyroscope have been studied actively. However, the GFINS has cumulative error problem still. Hence, this paper proposes Fuzzy-GFINS which can calibrate the data of an accelerometer using FIS consists of two inputs that are ratio between linear velocity of the autonomous ground vehicle(AGV) and the accelerometer and ratio between linear velocity of the encoders and the accelerometer. To evaluate the proposed Fuzzy-GFINS, we made the AGV with Mecanum wheels and applied the proposed Fuzzy-GFINS. In experimental result, we verified that the proposed method can calibrate effectively data of the accelerometer in the GFINS.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.3
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• pp.237-244
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• 2024

An Attitude and Heading Reference System (AHRS) provides the attitude of a vehicle with a constant velocity using an Inertial Measurement Unit (IMU) and a magnetometer. In this case, in order to avoid the disadvantage of a gyroscope, an AHRS using a Gyro-Free IMU (GF-IMU) that is composed of only accelerometers may be considered instead of the gyroscopes. In this paper, a design method of an AHRS using a GF-IMU is proposed. The proposed AHRS consists of roll and pitch calculation, yaw calculation, angular acceleration and angular velocity calculation, attitude calculation, and a Kalman filter. In particular, since the angular velocity cannot be measured from a gyroscope, the angular acceleration is obtained from the accelerometer output, and the angular velocity is calculated by integrating it. In order to show the usefulness of the proposed method, a performance evaluation was carried out. The performance evaluation results show that the attitude estimation performance of the proposed AHRS is similar to that of the conventional AHRS.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.71-81
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• 2022

In order for electro-optical tracking system (EOTS) to have accurate target coordinate, accurate navigation results are required. If an integrated navigation system is configured using an inertial measurement unit (IMU) of EOTS and the vehicle's navigation results, navigation results with high rate can be obtained. Due to the time-delay of the navigation results of the vehicle in the EOTS and scale factor errors of the EOTS IMU in high-speed and high dynamic operation of the vehicle, it is much more difficult to have accurate navigation results. In this paper, an integrated navigation system of EOTS which compensates time-delay and scale factor error is proposed. The proposed integrated navigation system consists of vehicle's navigation system which provides time-delayed navigation results, an EOTS IMU, an inertial navigation system (INS), an augmented Kalman filter and integration Kalman filter. The augmented Kalman filter outputs navigation results, in which the time-delay of the vehicle's navigation results is compensated. The integration Kalman filter estimates position, velocity, attitude error of the EOTS INS and accelerometer bias, accelerometer scale factor error, gyro bias and gyro scale factor error from the difference between the output of the augmented Kalman filter and the navigation result of the EOTS INS. In order to check performance of the proposed integrated navigation system, simulations for output data of a measurement generator and land vehicle experiments were performed. The performance evaluation results show that the proposed integrated navigation system provides more accurate navigation results.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.2
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• pp.117-124
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• 2020

In this paper, the symmetric position drift of the integration approach in pedestrian dead reckoning (PDR) system with dual foot-mounted IMU is analyzed. The PDR system that uses the inertial sensor attached to the shoe is called the IA-based PDR system. Since this system is designed based on the inertial navigation system (INS), it has the same characteristics as the error of the INS, then zero-velocity update (ZUPT) is used to correct this error. However, an error that cannot be compensated perfectly by ZUPT exists, and the trend of the position error is the symmetric direction along the side of the shoe(left, right foot) with the IMU attached. The symmetric position error along the side of the shoe gradually increases with walking. In this paper, we analyze the causes of symmetric position drift and show the results. It suggests the possibility of factors other than the error factors that are generally considered in the PDR system based on the integration approach.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.1247-1249
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• 1993

In this paper, NUDFET(NonUniformly Doped Field Effect Transistor) is presented as an alternative which offers the possibility of reducing the power necessary to operate switching circuits without a substantial loss in speed. The purpose of this NUDFET is to modify the electric field profile in order to cause carrier velocity saturation to occur at a lower voltage than it would occur in the uniformly doped device of the same channel length. The more MESFET and NUDFET circuits are realized, the more accurate model ins the performance of these devices become required. Analytic model ins was replaced by numerical analysis because of the complexity of device configuration. In this paper, FEM is selected because of simpler local mesh refinement and smaller computer memory than FDM. For accurate analysis, this paper has applied the Scharfetter-Gummel(S-G) Scheme and seven-point Gaussian Quadrature rule to assembly of the finite-element stiffness matrices and right-hand side vector of the semiconductor equations.

• Journal of Ocean Engineering and Technology
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• v.30 no.5
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• pp.367-373
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• 2016

This paper describes the development of a navigation HILS (hardware in the loop simulation) system for an integrated navigation performance analysis of a large diameter unmanned underwater vehicle (LDUUV). The HILS system was used for the performance analysis of the LDUUV. When a conventional HILS system is used, it is not possible to calculate the velocity and position using an inertial navigation system (INS). To cope with this problem, an external acceleration was generated. To evaluate the proposed method, we compare the results of a Monte Carlo simulation and navigation HILS experiment.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.239-247
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• 2022

The existing studies on the localization in the GNSS (Global Navigation Satellite System) denied environment usually exploit low-cost MEMS IMU (Micro Electro Mechanical Systems Inertial Measurement Unit) sensors to replace the GNSS signals. However, the navigation system still requires GNSS signals for the normal environment. This paper presents an integrated GNSS/INS (Inertial Navigation System) navigation system which combines GNSS and multiple IMU sensors using extended Kalman filter in partially GNSS-denied environments. The position and velocity of the INS and GNSS are used as the inputs to the integrated navigation system. The Mahalanobis distance is used for novelty detection to detect the outlier of GNSS measurements. When the abnormality is detected in GNSS signals, GNSS data is excluded from the fusion process. The performance of the proposed method is evaluated using MATLAB/Simulink. The simulation results show that the proposed algorithm can achieve a higher degree of positioning accuracy in the partially GNSS-denied environment.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.209-215
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• 2022

As intelligent autonomous driving vehicle development has become a big topic around the world, accurate reference dynamics estimation has been more important than before. Current systems generally use speed and heading information sensed from a distant point as a vehicle reference dynamic, however, the dynamics between different points are not same especially during rotating motions. In order to estimate properly estimate the reference dynamics from the information such as velocity and heading sensed at a point distant from the reference point such as center of gravity, this study proposes estimating reference dynamics from any location in the vehicle by combining the Bicycle and Ackermann models. A test system was constructed by implementing multiple GNSS/INS equipment on an Robot Operating System (ROS) and an actual car. Angle and speed errors of 10° and 0.2 m/s have been reduced to 0.2° and 0.06 m/s after applying the suggested method.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.50-56
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• 2023

INS(Inertial Navigation System) calculates navigation information using a vehicle's acceleration and angular velocity without the outside information. However, when navigation is performed for a long time, navigation error gradually diverges and the performance decreases. To enhance INS's performance, the rotation of inertial measurement unit is developed to compensate error sources of inertial sensors, which is called RINS(Rotational Inertial Navigation System). This paper analyzes the influence of several errors for dual-axis RINS and the shows the results using simulation.