• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1254-1258
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• 2003

One of the major factors that effect sensor performance is analog noise that added in a sensor signal such as voltage. In multi-axis force sensors, error sources may be classified mainly in two groups. One is structural error due to inaccuracy of sensor body. The other error source is noise signals existing in the sensed information. This paper presents a brief review about the principle of multi-axis force sensors, and then proposes a method that can reduce the effect of noise signal to sensor performance. The method is to convert analog voltage signal to digital numbers near sensor body and then to read these digital signals and conduct signal processing in the computer. By this way, we can eliminate a bad effect of electromagnetic wave emitted from computer and of 60 Hz noise emitted from AC source. The proposed method is investigated through experimental demonstration. The experimental results show that it improves S/N ratio of the sensor about 40 times in our experimental setup.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.334-339
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• 2019

In this study, we propose a compensation method of raw LiDAR data with noise and noise filtering for signal processing of LiDAR sensors during the development phase. The raw LiDAR data include constant errors generated by delays in transmitting and receiving signals, which can be resolved by LiDAR signal compensation. The signal compensation consists of two stage. First one is LiDAR sensor calibration for a compensation of geometric distortion. Second is walk error compensation. LiDAR data also include fluctuation and outlier noise, the latter of which is removed by data filtering. In this study, we compensate for the fluctuation by using the Kalman filter method, and we remove the outlier noise by applying a Gaussian weight function.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1677-1688
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• 2020

In the sodium-cooled fast reactor, the steam generator is a heat exchange device between sodium and water, which may cause leakage, resulting in a sodium-water reaction accident, which in turn affects the safe operation of the entire nuclear reactor. To this end, the electromagnetic vortex flowmeter is used to detect leakage of the steam generator and its signal processing method is studied in this paper. The hydraulic experiment was carried out by using water instead of liquid sodium, and the sensor output signal of the electromagnetic vortex flowmeter under different gas injection volumes was collected. The bubble noise signal is reflected by the base line of the sensor output signal. According to the relationship between the proportion of the bubble noise signal in the sensor output signal and the gas injection volume, a signal processing method based on the energy ratio calculation is proposed to detect whether the water contains bubbles. The gas injection experiment of liquid sodium was conducted to verify the effectiveness of the signal processing method in the detection of bubbles in sodium, and the minimum detectable leak rate of water in the steam generator was detected to be 0.2 g/s.

• Smart Structures and Systems
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• v.1 no.2
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• pp.185-215
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• 2005

Advanced signal processing techniques have been long introduced and widely used in structural health monitoring (SHM) and nondestructive evaluation (NDE). In our research, we applied several signal processing approaches for our embedded ultrasonic structural radar (EUSR) system to obtain improved damage detection results. The EUSR algorithm was developed to detect defects within a large area of a thin-plate specimen using a piezoelectric wafer active sensor (PWAS) array. In the EUSR, the discrete wavelet transform (DWT) was first applied for signal de-noising. Secondly, after constructing the EUSR data, the short-time Fourier transform (STFT) and continuous wavelet transform (CWT) were used for the time-frequency analysis. Then the results were compared thereafter. We eventually chose continuous wavelet transform to filter out from the original signal the component with the excitation signal's frequency. Third, cross correlation method and Hilbert transform were applied to A-scan signals to extract the time of flight (TOF) of the wave packets from the crack. Finally, the Hilbert transform was again applied to the EUSR data to extract the envelopes for final inspection result visualization. The EUSR system was implemented in LabVIEW. Several laboratory experiments have been conducted and have verified that, with the advanced signal processing approaches, the EUSR has enhanced damage detection ability.

• Journal of Sensor Science and Technology
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• v.29 no.2
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• pp.82-88
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• 2020

In this paper, we propose a complementary metal-oxide semiconductor (CMOS) binary image sensor with a gate/body-tied (GBT) p-channel metal-oxide-semiconductor field-effect transistor (PMOSFET)-type photodetector using a double-tail comparator for high-speed and low-power operations. The GBT photodetector is based on a PMOSFET tied with a floating gate (n+ polysilicon) and a body that amplifies the photocurrent generated by incident light. A double-tail comparator compares an input signal with a reference voltage and returns the output signal as either 0 or 1. The signal processing speed and power consumption of a double-tail comparator are superior over those of conventional comparator. Further, the use of a double-sampling circuit reduces the standard deviation of the output voltages. Therefore, the proposed CMOS binary image sensor using a double-tail comparator might have advantages, such as low power consumption and high signal processing speed. The proposed CMOS binary image sensor is designed and simulated using the standard 0.18 ㎛ CMOS process.

• Proceedings of the KWS Conference
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• 2005.11a
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• pp.144-146
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• 2005

Dual electromagnetic sensor is used for sensing the weld line. The sensor consists of excitation and two sensing coil wound over the ferro-magnetic core. By using the dual sensor, the effect of noise is minimized. It is based on the generation of eddy currents in the welding plate by passing current through the excitation coil. The sensor can be used to track the butt joints having no gap between them, where a vision based sensor fails to track. Sensor sensitivity depends on the number of coil turns, frequency of excitation, distance of a sensor from the work piece, diameter of core, etc. The whole system consists of a sensor, a signal processing board, a motion controller and a personnel computer (PC). The raw sensor signal is processed using the signal processing board. It consists of amplification, rectification, filtering, averaging, offset adjustment, etc. Based on sensor data, the motion controller adjusts the position of a welding torch.

• Journal of Sensor Science and Technology
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• v.32 no.4
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• pp.246-251
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• 2023

Internet of Things (IoT) systems process signals from various sensors using signal processing algorithms suitable for the signal characteristics. To analyze complex signals, these systems usually use signal processing algorithms in the frequency domain, such as fast Fourier transform (FFT), filtering, and short-time Fourier transform (STFT). In this study, we propose a multi-mode sensor signal processor (SSP) accelerator with an FFT-based hardware design. The FFT processor in the proposed SSP is designed with a radix-2 single-path delay feedback (R2SDF) pipeline architecture for high-speed operation. Moreover, based on this FFT processor, the proposed SSP can perform filtering and STFT operation. The proposed SSP is implemented on a field-programmable gate array (FPGA). By sharing the FFT processor for each algorithm, the required hardware resources are significantly reduced. The proposed SSP is implemented and verified on Xilinxh's Zynq Ultrascale+ MPSoC ZCU104 with 53,591 look-up tables (LUTs), 71,451 flip-flops (FFs), and 44 digital signal processors (DSPs). The FFT, filtering, and STFT algorithm implementations on the proposed SSP achieve 185x average acceleration.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.425-428
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• 2001

In this paper, FMCW radar signal processing technique for the vehicle detection system are studied. And FMCW radar sensor is used as a equipment for vehicle detection. To test the performance of developed algorithm, the evaluation of the algorithm is done by simulation for signal processing technique of vehicle detection system. RADAR signal of a driving vehicle is generated by using the Matlab. Distance and velocity of vehicles are calculated with developed a1gorithm. Also the signal processing procedure is done for the virtual data with FM-AM converted noise.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.52-57
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• 2024

To measure the vortex structures within the turbulent boundary layer, a hot-wire sensor was mounted on a stepper motor controller and moved to the designated measurement points. Near the surface within the flow field, the velocity is relatively slow, making the measurements highly sensitive to electromagnetic interference (EMI) during signal processing. This EMI primarily originates from the power supplies of computers and other electronic equipment. In our experimental setup, EMI was introduced into BNC cables connected to the hot-wire sensor from the powered stepper motor. When power was supplied to the motor controller to move the hot-wire sensor, EMI appeared on the oscilloscope screen. Consequently, unexpected noise was present in the data measured by the hot-wire sensor. To mitigate this and enhance the signal-to-noise ratio (SNR) during measurements, the connecting cables were shielded, and an old computer without EMI shielding was replaced.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2006.06a
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• pp.97-100
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• 2006

A sensor and measuring system were implemented to measure both uroflow and urophonography signal during urination for diagnose the BPH(benign prostatic hypertrophy). The implemented system was composed of the uroflow sensor using the load-cell, the urophonography measurement sensor so as stethoscope type, pre-processing part for sensors signal detection, amplifier and filter, system control parts and PC measurement program. A simulator of the lower urinary system that is experimental equipment implemented for evaluates the developed system. The two signals were measured using implemented system and analyzed these signal by means of time domain and frequency domain for extraction of the characteristic parameter which can most effectively reflected by the occlusion of the lower urinary system. Furthermore two signals were measured and analyzed with the subject of 5 healthy adult for clinical application possibility of the implemented system. As a result, the most influence bandwidth of effect according to occlusion of the lower urinary system is $253{\sim}282Hz$ of the urophonography signal.