• Title/Summary/Keyword: Noise Parameter

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Analysis of drilling performance and shape for granite according to operating parameters of waterjet nozzles (복수의 워터젯 노즐 운용변수에 따른 화강암 천공성능 및 형상 분석)

  • Park, Jun-Sik;Cha, Hyun-Jong;Hong, Eun-Soo;Jun, Hyung-Woo;Oh, Tae-Min
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.23 no.6
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    • pp.589-604
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    • 2021
  • Waterjets for rocks have various advantages of the non-contact and eco-friendly excavation using only water and abrasive. To overcome the problems (e.g., dust and noise occurrence) of the conventional drilling methods, waterjet excavation methods are broadly used. It is advantageous to operate a couple of nozzles in order to increase the waterjet excavation efficiency. When multiple nozzles are used, it is essential to analyze the excavation performance and shape according to the nozzle operation method. In this study, nozzle angle, horizontal distance between nozzles, and standoff distance were defined as nozzle operating parameters and the excavation performance and shape were analyzed. As a result of the experiment, when the nozzle angle and standoff distance are increased, the excavation depth is decreased and the effective depth tends to be increased. In addition, based on the experimental results, the excavation shape criteria required for nozzle insertion were proposed and optimal nozzle operating parameters were derived according to the criteria. This study result is expected to be used as useful basic research in the future development of multiple waterjet nozzles for rock drilling.

Development of smart car intelligent wheel hub bearing embedded system using predictive diagnosis algorithm

  • Sam-Taek Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.1-8
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    • 2023
  • If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.

Effect of Sample Preparation on Predicting Chemical Composition and Fermentation Parameters in Italian ryegrass Silages by Near Infrared Spectroscopy (시료 전처리 방법이 근적외선분광법을 이용한 이탈리안 라이그라스 사일리지의 화학적 조성분 및 발효품질 평가에 미치는 영향)

  • Park, Hyung Soo;Lee, Sang Hoon;Choi, Ki Choon;Lim, Young Chul;Kim, Jong Gun;Seo, Sung;Jo, Kyu Chea
    • Journal of Animal Environmental Science
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    • v.18 no.3
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    • pp.257-266
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    • 2012
  • Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid, accurate method of evaluating some chemical constituents in cereal and dired animal forages. Analysis of forage quality by NIRS usually involves dry grinding samples. Costs might be reduced if samples could be analyzed without drying or grinding. The objective of this study was to investigate effect of sample preparations on prediction ability of chemical composition and fermentation parameter for Italian ryegrass silages by NIRS. A population of 147 Italian ryegrass silages representing a wide range in chemical parameters were used in this investigation. Samples were scanned at 1nm intervals over the wavelength range 680-2500 nm and the optical data recorded as log 1/Reflectance (log 1/R) and scanned in oven-dried grinding and fresh ungrinding condition. The spectral data were regressed against a range of chemical parameters using partial least squares (PLS) multivariate analysis in conjunction with four spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV) and maximizing the correlation coefficient of cross validation (${R^2}_{CV}$). The results of this study show that NIRS predicted the chemical parameters with high degree of accuracy in oven-dried grinding treatment except for moisture contents. Prediction accuracy of the moisture contents was better for fresh ungrinding treatment (SECV 1.37%, $R^2$ 0.96) than for oven-dried grinding treatments (SECV 4.31%, $R^2$ 0.68). Although the statistical indexes for accuracy of the prediction were the lower in fresh ungrinding treatment, fresh treatment may be acceptable when processing is costly or when some changes in component due to the processing are expected. Results of this experiment showed the possibility of NIRS method to predict the chemical composition and fermentation parameter of Italian ryegrass silages as routine analysis method in feeding value evaluation and for farmer advice.

Application of Dynamic Reaction Cell - Inductively Coupled Plasma Mass Spectrometry for the Determination of Calcium by Isotope Dilution Method (반응셀 유도결합플라스마 질량분석분석기를 이용한 칼슘 동위원소비율의 측정과 동위원소희석법의 적용)

  • Suh, Jungkee;Yim, Yonghyeon;Hwang, Euijin;Lee, Sanghak
    • Analytical Science and Technology
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    • v.15 no.5
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    • pp.417-426
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    • 2002
  • Inductively Coupled Plasma Dynamic Reaction Cell Quadrupole Mass Spectrometry (ICP-DRC-QMS) was characterized for the detection of the six naturally occurring calcium isotopes. The effect of the operating conditions of the DRC system was studied to get the best signal-to-noise ratio. This experiment shows that the potentially interfering ions such as $Ar^+$, ${CO_2}^+$, ${NO_2}^+$, $CNO^+$ at the calcium masses m/z 40, 42, 43, 44 and 48 were removed by flowing $NH_3$ gas at the rate of 0.7 mL/min $NH_3$ as reactive cell gas in the DRC with a RPq value (rejection parameter) of 0.6. The limits of detection for $^{40}Ca$, $^{42}Ca$, $^{43}Ca$, $^{44}Ca$, and $^{48}Ca$ were 1, 29, 169, 34, and 15 pg/mL, respectively. This method was applied to the determination of calcium in synthetic food digest samples (CCQM-P13) provided by LGC for international comparison. The isotope dilution method was used for the determination of calcium in the samples. The uncertainty evaluation was performed according to the ISO/GUM and EURACHEM guidelines. The determined mean concentration and its expanded uncertainty of calcium was ($66.4{\pm}1.2$) mg/kg. In order to assess our method, two reference samples, Riverine Water reference sample (NRCC SLRS-3) and Trace Elements in Water reference sample (NIST SRM 1643d), were analyzed.

Comparative assessment and uncertainty analysis of ensemble-based hydrologic data assimilation using airGRdatassim (airGRdatassim을 이용한 앙상블 기반 수문자료동화 기법의 비교 및 불확실성 평가)

  • Lee, Garim;Lee, Songhee;Kim, Bomi;Woo, Dong Kook;Noh, Seong Jin
    • Journal of Korea Water Resources Association
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    • v.55 no.10
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    • pp.761-774
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    • 2022
  • Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.

Evaluation for Optimization of CT Dose Reduction Methods in PET/CT (PET/CT 검사 시 CT 피폭선량 감소 방법들의 최적화 평가)

  • Do, Yong Ho;Lee, Hong Jae;Kim, Jin Eui
    • The Korean Journal of Nuclear Medicine Technology
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    • v.19 no.2
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    • pp.55-62
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    • 2015
  • Purpose Various methods for reducing radiation exposure have been continuously being developed. The aim of this study is to evaluate effectiveness of dose reduction, image quality and PET SUV changes by applying combination of automatic exposure dose(AEC), automated dose-optimized selection of X-ray tube voltage(CAREkV) and sinogram affirmed iterative reconstruction(SAFIRE) which can be controled by user. Materials and Methods Torso, AAPM CT performance and IEC body phantom images were acquired using biograph mCT64, (Siemens, Germany) PET/CT scanner. Standard CT condition was 120 kV, 40 mAs. Radiation exposure and noise were evaluated by applying AEC, CAREkV(120 kV, 40 mAs) and SAFIRE(120 kV, 25 mAs) with torso phantom compare to standard CT condition. And torso, AAPM and IEC phantom images were acquired with combination of 3 methods in condition of 120 kV, 25 mAs to evaluate radiation exposure, noise, spatial resolution and SUV changes. Results When applying AEC, CTDIvol and DLP were decreased by 50.52% and 50.62% compare to images which is not applying AEC. mAs was increased by 61.5% to compensate image quality according to decreasing 20 kV when applying CAREkV. However, CTDIvol and DLP were decreased by 6.2% and 5.5%. When reference mAs was the lower and strength was the higher, reduction of radiation exposure rate was the bigger. Mean SD and DLP were decreased by 2.2% and 38% when applying SAFIRE even though mAs was decreased by 37.5%(from 40 mAs to 25 mAs). Combination of 3 methods test, SD decreased by 5.17% and there was no significant differences in spatial resolution. And mean SD and DLP were decreased by 6.7% and 36.9% compare to 120 kV, 40 mAs with AEC. For SUV test, there was no statistical differences(P>0.05). Conclusion Combination of 3 methods shows dose reduction effect without degrading image quality and SUV changes. To reduce radiation exposure in PET/CT study, continuous effort is needed by optimizing various dose reduction methods.

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Comparison of Algorithms for Generating Parametric Image of Cerebral Blood Flow Using ${H_2}^{15}O$ PET Positron Emission Tomography (${H_2}^{15}O$ PET을 이용한 뇌혈류 파라메트릭 영상 구성을 위한 알고리즘 비교)

  • Lee, Jae-Sung;Lee, Dong-Soo;Park, Kwang-Suk;Chung, June-Key;Lee, Myung-Chul
    • The Korean Journal of Nuclear Medicine
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    • v.37 no.5
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    • pp.288-300
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    • 2003
  • Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.

A Development of Automatic Lineament Extraction Algorithm from Landsat TM images for Geological Applications (지질학적 활용을 위한 Landsat TM 자료의 자동화된 선구조 추출 알고리즘의 개발)

  • 원중선;김상완;민경덕;이영훈
    • Korean Journal of Remote Sensing
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    • v.14 no.2
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    • pp.175-195
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    • 1998
  • Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.

Estimate and Analysis of Planetary Boundary Layer Height (PBLH) using a Mobile Lidar Vehicle system (이동형 차량탑재 라이다 시스템을 활용한 경계층고도 산출 및 분석)

  • Nam, Hyoung-Gu;Choi, Won;Kim, Yoo-Jun;Shim, Jae-Kwan;Choi, Byoung-Choel;Kim, Byung-Gon
    • Korean Journal of Remote Sensing
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    • v.32 no.3
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    • pp.307-321
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    • 2016
  • Planetary Boundary Layer Height (PBLH) is a major input parameter for weather forecasting and atmosphere diffusion models. In order to estimate the sub-grid scale variability of PBLH, we need to monitor PBLH data with high spatio-temporal resolution. Accordingly, we introduce a LIdar observation VEhicle (LIVE), and analyze PBLH derived from the lidar loaded in LIVE. PBLH estimated from LIVE shows high correlations with those estimated from both WRF model ($R^2=0.68$) and radiosonde ($R^2=0.72$). However, PBLH from lidar tend to be overestimated in comparison with those from both WRF and radiosonde because lidar appears to detect height of Residual Layer (RL) as PBLH which is overall below near the overlap height (< 300 m). PBLH from lidar with 10 min time resolution shows typical diurnal variation since it grows up after sunrise and reaches the maximum after 2 hours of sun culmination. The average growth rate of PBLH during the analysis period (2014/06/26 ~ 30) is 1.79 (-2.9 ~ 5.7) m $min^{-1}$. In addition, the lidar signal measured from moving LIVE shows that there is very low noise in comparison with that from the stationary observation. The PBLH from LIVE is 1065 m, similar to the value (1150 m) derived from the radiosonde launched at Sokcho. This study suggests that LIVE can observe continuous and reliable PBLH with high resolution in both stationary and mobile systems.

The Evaluation of Reconstructed Images in 3D OSEM According to Iteration and Subset Number (3D OSEM 재구성 법에서 반복연산(Iteration) 횟수와 부분집합(Subset) 개수 변경에 따른 영상의 질 평가)

  • Kim, Dong-Seok;Kim, Seong-Hwan;Shim, Dong-Oh;Yoo, Hee-Jae
    • The Korean Journal of Nuclear Medicine Technology
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    • v.15 no.1
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    • pp.17-24
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    • 2011
  • Purpose: Presently in the nuclear medicine field, the high-speed image reconstruction algorithm like the OSEM algorithm is widely used as the alternative of the filtered back projection method due to the rapid development and application of the digital computer. There is no to relate and if it applies the optimal parameter be clearly determined. In this research, the quality change of the Jaszczak phantom experiment and brain SPECT patient data according to the iteration times and subset number change try to be been put through and analyzed in 3D OSEM reconstruction method of applying 3D beam modeling. Materials and Methods: Patient data from August, 2010 studied and analyzed against 5 patients implementing the brain SPECT until september, 2010 in the nuclear medicine department of ASAN medical center. The phantom image used the mixed Jaszczak phantom equally and obtained the water and 99mTc (500 MBq) in the dual head gamma camera Symbia T2 of Siemens. When reconstructing each image altogether with patient data and phantom data, we changed iteration number as 1, 4, 8, 12, 24 and 30 times and subset number as 2, 4, 8, 16 and 32 times. We reconstructed in reconstructed each image, the variation coefficient for guessing about noise of images and image contrast, FWHM were produced and compared. Results: In patients and phantom experiment data, a contrast and spatial resolution of an image showed the tendency to increase linearly altogether according to the increment of the iteration times and subset number but the variation coefficient did not show the tendency to be improved according to the increase of two parameters. In the comparison according to the scan time, the image contrast and FWHM showed altogether the result of being linearly improved according to the iteration times and subset number increase in projection per 10, 20 and 30 second image but the variation coefficient did not show the tendency to be improved. Conclusion: The linear relationship of the image contrast improved in 3D OSEM reconstruction method image of applying 3D beam modeling through this experiment like the existing 1D and 2D OSEM reconfiguration method according to the iteration times and subset number increase could be confirmed. However, this is simple phantom experiment and the result of obtaining by the some patients limited range and the various variables can be existed. So for generalizing this based on this results of this experiment, there is the excessiveness and the evaluation about 3D OSEM reconfiguration method should be additionally made through experiments after this.

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