• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.71.5-71
• /
• 2001

This paper presents the vibration control of a flexible intelligent beam with added mass. The materials which is a glass fiber reinforced(GFR) thermoplastic composite is employed to achieve vibration characteristics according to added mass induced end of composite beam. In the experiments of forced vibration control, the -controller are employed to achieve vibration suppression in forced vibration situations. Also, in the controller design, 1st and 2nd´s natural frequencies are considered in the modeling, because robust control theory which has robustness to structured uncertainty is adopted to suppress the vibration. By designing a controller using mu-synthesis, robust performance against measurement noise, various modeling.

• Structural Engineering and Mechanics
• /
• v.34 no.1
• /
• pp.1-14
• /
• 2010

The innovative intelligent fuzzy weighted input estimation method which efficiently and robustly estimates the unknown time-varying input force in on-line is presented in this paper. The algorithm includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. To directly synthesize the Kalman filter with the estimator, this work presents an efficient robust forgetting zone, which is capable of providing a reasonable compromise between the tracking capability and the flexibility against noises. The capability of this inverse method are demonstrated in the input force estimation cases of the plate structure system. The proposed algorithm is further compared by alternating between the constant and adaptive weighting factors. The results show that this method has the properties of faster convergence in the initial response, better target tracking capability, and more effective noise and measurement bias reduction.

• ETRI Journal
• /
• v.43 no.5
• /
• pp.881-890
• /
• 2021

Photoplethysmography (PPG) is a noninvasive technique that can be used to conveniently measure heart rate (HR) and thus obtain relevant health-related information. However, developing an automated PPG system is difficult, because its waveforms are susceptible to motion artifacts and between-patient variation, making its interpretation difficult. We use deep neural network (DNN) filters to mimic the cognitive ability of a human expert who can distinguish the features of PPG altered by noise from various sources. Systolic (S), onset (O), and first derivative peaks (W) are recognized by three different DNN filters. In addition, the boundaries of uninformative regions caused by artifacts are identified by two different filters. The algorithm reliably derives the HR and presents recognition scores for the S, O, and W peaks and artifacts with only a 0.7-s delay. In the evaluation using data from 11 patients obtained from PhysioNet, the algorithm yields 8643 (86.12%) reliable HR measurements from a total of 10 036 heartbeats, including some with uninformative data resulting from arrhythmias and artifacts.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.24 no.2
• /
• pp.92-98
• /
• 2019

Accurate estimation of motor parameters is required in some motor control applications. For example, the value of stator resistance is required for stator flux-oriented control mostly used in doubly fed induction generator systems. Stator resistance is not a constant value and continuously changes due to the rise in temperature during motor operation. Estimation errors degrade the control performance. Hence, this study proposes a simple stator resistance estimation method. In this scheme, the differential components of voltage and current values are used to eliminate the dead-time effect, and Kalman filter algorithm is applied to reduce the error according to measurement noise. Simulation and experimental results obtained with a permanent magnet motor show the validity of the proposed algorithm.

• Journal of Information Processing Systems
• /
• v.15 no.1
• /
• pp.169-180
• /
• 2019

Transmitting visual information over a broadcasting network is not only prone to a copyright violation but also is a forgery. Authenticating such information and protecting its authorship rights call for more advanced data encoding. To this end, electronic watermarking is often adopted to embed inscriptive signature in imaging data. Most existing watermarking methods while focusing on robustness against degradation remain lacking of measurement against security loophole in which the encrypting scheme once discovered may be recreated by an unauthorized party. This could reveal the underlying signature which may potentially be replaced or forged. This paper therefore proposes a novel digital watermarking scheme in temporal-frequency domain. Unlike other typical wavelet based watermarking, the proposed scheme employed the Lorenz chaotic map to specify embedding positions. Effectively making this is not only a formidable method to decrypt but also a stronger will against deterministic attacks. Simulation report herein highlights its strength to withstand spatial and frequent adulterations, e.g., lossy compression, filtering, zooming and noise.

• Journal of Power Electronics
• /
• v.19 no.2
• /
• pp.443-453
• /
• 2019

As the core component of transmission systems, converters are very prone to failure. To improve the accuracy of fault diagnosis for wind power converters, a fault feature extraction method combined with a wavelet transform and compressed sensing theory is proposed. In addition, an improved AdaBoost-SVM is used to diagnose wind power converters. The three-phase output current signal is selected as the research object and is processed by the wavelet transform to reduce the signal noise. The wavelet approximation coefficients are dimensionality reduced to obtain measurement signals based on the theory of compressive sensing. A sparse vector is obtained by the orthogonal matching pursuit algorithm, and then the fault feature vector is extracted. The fault feature vectors are input to the improved AdaBoost-SVM classifier to realize fault diagnosis. Simulation results show that this method can effectively realize the fault diagnosis of the power transistors in converters and improve the precision of fault diagnosis.

• Current Optics and Photonics
• /
• v.3 no.3
• /
• pp.204-209
• /
• 2019

In an optical interferometer that uses sinusoidal modulation and quadrature detection, the amplitude and offset of the interference signal vary with time, even without considering system noise. As a result, the circular Lissajous figure becomes elliptical, with wide lines. We propose and experimentally demonstrate a method for compensating quadrature detection error, based on digital signal processing to deal with scaling and fitting. In scaling, fluctuations in the amplitudes of in-phase and quadrature signals are compensated, and the scaled signals are fitted to a Lissajous unit circle. To do so, we scale the average fluctuation, remove the offset, and fit the ellipse to a unit circle. Our measurements of a target moving with uniform velocity show that we reduce quadrature detection error from 5 to 2 nanometers.

• Journal of the Semiconductor & Display Technology
• /
• v.20 no.3
• /
• pp.103-107
• /
• 2021

In this paper, a capacitive water level sensor for boilers was developed. In order to accurately monitor the water level in a high-temperature boiler that generates a lot of precipitates, the occurrence of precipitates on the surface of the water level sensor should be small, and a sensor capable of measuring even if the sensor surface is somewhat contaminated is required. The capacitive water level sensor has a structure in which one of the two electrodes is insulated with Teflon coating, and the stainless steel package of the water level sensor is brought into contact with the water tank so that the entire water tank becomes another electrode of the water level sensor. A C-V converter that converts the capacitance change of the capacitive water level sensor into a voltage change was developed and integrated with the water level sensor to minimize noise. The performance of the developed capacitive water level sensor was evaluated through measurement.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1994.06a
• /
• pp.848-853
• /
• 1994

This paper describes the concept and basic technique of measuring torsional operational deflection shapes using a laser-based torsional vibration meter, a dual-channel FFT analyzer and operational deflection shapes software running on a PC. Torsional Operational Deflection Shapes (TODS) is defined similar to ODS (Operational Deflection Shapes), with the exception the TODS designates the operational deflection shapes of structures vibrating in a rotational, or angular, degree of freedom. Thus the TODS measurements can be applied to rotating shafts and the results of such a measurement are shown. In some cases it may be great benefit to apply order tracking and/or synchronous time domain averaging techniques in order to avoid smearing and reduce noise problems.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.45.2-45
• /
• 2001

In case that the perfect model following conditions are not satisfied in the system, a perfect model-following controller is difficult to apply to the system. To deal with this problem, in this paper, a robust imperfect stable model-following controller is designed by combining time delay controller and sliding mode controller based on the concept of two degrees of freedom(2-DOF) controller design method. The experimental dynamic modeling of the commercial overhead crane with capacity of two tons is carried out. To remove the noise of the measuring signals from the swing angle measurement device and estimate the state of the swing angles of the transported object at each time instant, realtime tracker is designed using Kalman filter. The performance of the designed robust controller is tested through the commercial overhead. The experimental results show that the designed controller is robust and applicable to real systems.