• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.5
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• pp.417-425
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• 2006

This paper presents a new speed sensorless vector control scheme of Spindle Induction Motors(SIM) which can be successfully applied to at any speed including even zero speed. The proposed sensorless vector control of SIM uses rotor flux estimator with a variable bandwidth. This approach is based on the Closed-Loop Rotor Flux Observer(CLRFO) which includes a variable bandwidth of the PI controller. For low speed operation, the bandwidth of CLRFO has a variable bandwidth structure according to the estimated rotor velocity. The experimental results show the satisfactory operation of the proposed sensorless algorithm.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.499-505
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• 2018

Time delay estimation between two acoustic sensors is widely used in room acoustics and sonar for target position estimation, tracking and synchronization. A cross-correlation based method is representative for the time delay estimation. However, this method does not have enough consideration for the noise added to the receiving acoustic sensors. This paper proposes a new time delay estimation method considering the added noise on the receiver acoustic sensors. From comparing with the existing GCC (Generalized Cross Correlation) method, and adaptive eigen decomposition method, we show that the proposed method outperforms other methods for a colored signal source in the white Gaussian noise condition.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.73-74
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• 2023

본 논문에서는 음향센서를 기반으로 한 지하시설물 화재 위험감지 방법을 제안하였다. 음향센서는 진동이나 광센서처럼 접촉식이 아니기 때문에 결로가 발생하고 있는 취약구간에 설치하여 보다 효율적으로 활용이 가능하고 지하시설물 내부에 설치된 기기나 장비들과 상호작용하거나 간섭하지 않기 때문에 안전하게 관리가 가능하다. 이러한 특징으로 지하 시설물에서 내 통행이 불편하여 관리하기 힘든 구간이나 결로가 많아 화재안전에 주의가 필요한 곳에 설치하여 전기스파크 발생 감지를통해 재난이 발생하기 이전 화재위험을 감지하는 방법론 중 하나가 될 수 있다. 제안하는 방법은 음향 센서를 통해 지하공동구 안에서 발생하는 소리들을 수집하고 일정한 길이의 시간 단위 프레임들로 분할한 후 분석하여 전기스파크의 특징 벡터를 도출한다. 전기스파크 감지 모델로는 전기스파크 신호의 지역적 특성을 포착할 수 있도록 2D-CNN 구조를 사용하며 모델에서 출력된 전기 스파크 발생 예측확률을 분할된 단위 프레임 따라 계산하여 융합한다. 이로 인해 높은 정확도의 전기스파크 감지 정밀도를 얻을 수 있으며, 이는 전기 스파크에 의한 화재 이벤트 감지 있어서 효과적인 센싱 기술임을 알 수 있다.

• Journal of KIISE
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• v.42 no.8
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• pp.1031-1038
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• 2015

The recent emergence of smart phones, wearable devices, and even the IoT concept made it possible for various objects to interact one another anytime and anywhere. Among many of such smart services, a smart home service typically requires a large number of sensors to recognize the residents' activities. For this reason, the ideas on activity recognition using the data obtained from those sensors are actively discussed and studied these days. Furthermore, plenty of sensors are installed in order to recognize activities and analyze their patterns via data mining techniques. However, if many of these sensors should be installed for IoT smart home service, it raises the issue of cost and energy consumption. In this paper, we proposed a new method for reducing the number of sensors for activity recognition in a smart environment, which utilizes the principal component analysis and clustering techniques, and also show the effect of improvement in terms of the activity recognition by the proposed method.

• Journal of IKEEE
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• v.23 no.2
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• pp.543-551
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• 2019

Permanent Magnet Synchronous Motors(PMSMs) have a wider range of applications due to their high output density and high efficiency. PMSMs are used not only in high-power density, high-performance motor-driven systems such as vehicle and robots, but also in systems where cost-cutting is very important, such as washing machines, air conditioners and refrigerators. To reduce costs, position sensorless control is required, which is generally difficult to be used under conditions of starting the motor. Thus, the I-F speed control that rotates the current vector at any speed in the starting procedure should be used at first, and then the sensorless speed control could be applied after PMSM rotates above a certain speed. Speed control performance in I-F speed control and sensorless speed control is very important. And more speed control performance should be maintained even in the transient in which the two control techniques are changed. In this paper, the speed controller transition method from I-F speed control to sensorless speed control of permanent magnet synchronous motor is proposed. Experiments were carried out on the washing machine drive system to verify the performance of the proposed technique.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.64-69
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• 2015

Place awareness is an essential for location-based services that are widely provided to smartphone users. However, traditional GPS-based methods are only valid outdoors where the GPS signal is strong and also require symbolic place information of the physical location. In this paper, environmental sounds and images are used to recognize important aspects of each place. The proposed method extracts feature vectors from visual, auditory and location data recorded by a smartphone with built-in camera, microphone and GPS sensors modules. The heterogeneous feature vectors were then learned by an ensemble learning method that learns each group of feature vectors for each classifier respectively and votes to produce the highest weighted result. The proposed method is evaluated for place recognition using a data group of 3000 samples in six places and the experimental results show a remarkably improved recognition accuracy when using all kinds of sensory data comparing to results using data from a single sensor or audio-visual integrated data only.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.27-33
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• 2010

In this study, we conducted the classification experiments with GMM (Gaussian Mixture Model) from combining the extracted features by using microphone, Gyro sensor and Acceleration sensor in 9 different environment types. Existing studies of Context Aware wanted to recognize the Environment situation mainly using the Environment sound data with microphone, but there was limitation of reflecting recognition owing to structural characteristics of Environment sound which are composed of various noises combination. Hence we proposed the additional application methods which added Gyro sensor and Acceleration sensor data in order to reflect recognition agent's movement feature. According to the experimental results, the method combining Acceleration sensor data with the data of existing Environment sound feature improves the recognition performance by more than 5%, when compared with existing methods of getting only Environment sound feature data from the Microphone.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.159-167
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• 2006

Lipreading has been suggested as one of the methods to improve the performance of speech recognition in noisy environment. However, existing methods are developed and implemented only in software. This paper suggests a hardware design for real-time lipreading. For real-time processing and feasible implementation, we decompose the lipreading system into three parts; image acquisition module, feature vector extraction module, and recognition module. Image acquisition module capture input image by using CMOS image sensor. The feature vector extraction module extracts feature vector from the input image by using parallel block matching algorithm. The parallel block matching algorithm is coded and simulated for FPGA circuit. Recognition module uses HMM based recognition algorithm. The recognition algorithm is coded and simulated by using DSP chip. The simulation results show that a real-time lipreading system can be implemented in hardware.

• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.158-164
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• 2017

Typical hydrophones in line array sensors for early detection of covert underwater targets can measure only sound-pressure-magnitude with the limitation of being unable to identify the direction of an incoming wave. In this study, a thickness shear mode vibrator was proposed as the main component of an inertia type vector hydrophone to measure both magnitude and direction of acoustic signals from targets. The equation to analyze the output voltage of the vibrator to an external force was derived, and the validity of the equation was verified through finite element analysis of a PMN-PT single crystal vibrator. The analysis results from this study will be utilized in the future for the design of inertia type vector hydrophones made of thickness shear vibrators.

• Journal of Navigation and Port Research
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• v.38 no.5
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• pp.457-462
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• 2014

Indoor-positioning systems are useful to various applications. Navigation system is one of the most popular applications, which needs the information of directions of nodes' movements. Specifically the applications should get the information in real-time to properly show the current moving position of a node. In this paper, simple vector-based algorithms are proposed to compute amount and direction of changes of azimuth of mobile nodes' heading directions using existing indoor positioning systems in indoor environments where azimuth sensors do not work properly. Previous algorithms calculate the azimuth changes by too many steps of topology-based formula. The algorithms proposed in this paper get the amount of changes of azimuth by simple formula based on vector, and determine the direction of changes by the sign of value of simple formula based on the previous movement of nodes. The algorithms are much simpler and less error-prone than previous ones, and then they can detect changes in many location-based applications as well. The performance of the algorithms is proved logically and mathematically.