• Title/Summary/Keyword: Prediction of Frequency

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A Study on Prediction of Conducted EMI In PWM inverter fed Induction Motor Drive System (PWM 인버터-유도전동기 구동시스템의 전도노이즈 예측에 관한 연구)

  • 이진환;안정준;원충연;김영석;최세완
    • Proceedings of the KIPE Conference
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    • 1999.07a
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    • pp.367-372
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    • 1999
  • In this paper, an inverter fed induction motor drive system is analyed in order to predict the conducted interference. High frequency model for inverter, motor and system parasitic components are proposed. High frequency component allows time and frequency domain analysis to be performed with standard PSpice tool. The overall high frequency component and model are verified by comparing simulation and experimental result.

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A method for optimizing lifetime prediction of a storage device using the frequency of occurrence of defects in NAND flash memory (낸드 플래시 메모리의 불량 발생빈도를 이용한 저장장치의 수명 예측 최적화 방법)

  • Lee, Hyun-Seob
    • Journal of Internet of Things and Convergence
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    • v.7 no.4
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    • pp.9-14
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    • 2021
  • In computing systems that require high reliability, the method of predicting the lifetime of a storage device is one of the important factors for system management because it can maximize usability as well as data protection. The life of a solid state drive (SSD) that has recently been used as a storage device in several storage systems is linked to the life of the NAND flash memory that constitutes it. Therefore, in a storage system configured using an SSD, a method of accurately and efficiently predicting the lifespan of a NAND flash memory is required. In this paper, a method for optimizing the lifetime prediction of a flash memory-based storage device using the frequency of NAND flash memory failure is proposed. For this, we design a cost matrix to collect the frequency of defects that occur when processing data in units of Drive Writes Per Day (DWPD). In addition, a method of predicting the remaining cost to the slope where the life-long finish occurs using the Gradient Descent method is proposed. Finally, we proved the excellence of the proposed idea when any defect occurs with simulation.

Prediction on the Performance of Polymer-Based Mechanical Low-Pass Filters for High-G Accelerometers (고충격 가속도센서용 고분자 기반 기계식 저역통과필터의 성능 예측)

  • Sehwan Song;Junyong Jang;Youlim Lee;Hanseong Jo;Sang-Hee Yoon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.26 no.3
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    • pp.262-272
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    • 2023
  • A polymer-based mechanical low-pass filter(m-LPF) for high-g accelerometers makes it possible to remove high-frequency transient noises from acceleration signals, thus ensuring repeatable and reliable measurement on high-g acceleration. We establish a prediction model for performance of m-LPF by combining a fundamental vibration model with the fractional derivative standard linear solid(FD SLS) model describing the storage modulus and loss modulus of polymers. Here, the FD SLS model is modified to consider the effect of m-LPF shape factor (i.e., thickness) on storage modulus and loss modulus. The prediction accuracy is verified by comparing the displacement transmissibility(or cut-off frequency) estimated using our model with that measured from 3 kinds of polymers(polysulfide rubber(PSR), silicone rubber(SR), and polydimethylsiloxane(PDMS)). Our findings will contribute a significant growth of m-LPF for high-g accelerometers.

Fatigue Life Prediction of Sensor Pod for Aircraft Considering Aircraft Loads (비행체 하중을 고려한 항공기용 센서 포드의 피로수명 예측)

  • Cho, Jae Myung;Jang, Joon;Choi, Woo Chun;Bae, Jong In
    • Journal of Aerospace System Engineering
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    • v.13 no.3
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    • pp.32-39
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    • 2019
  • Sensor pods mounted on the exterior of the aircraft used for tactical missions should have a fatigue life based on the expected load spectrum during operation. For mission equipment such as the sensor pod, the frequency fatigue life prediction method which applies the dynamic vibration environment condition is preferred due to the efficiency of the analysis. In this paper, a fatigue life prediction method in the frequency domain where stress due to static and dynamic loads is synthesized based on the actual flight load spectrum is proposed. After comparison with the existing analysis method, the fatigue life of the proposed analysis method was predicted conservatively. The proposed sensor pods satisfy the requirements of the fatigue life.

Internet Roundtrip Delay Prediction Using the Maximum Entropy Principle

  • Liu, Peter Xiaoping;Meng, Max Q-H;Gu, Jason
    • Journal of Communications and Networks
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    • v.5 no.1
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    • pp.65-72
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    • 2003
  • Internet roundtrip delay/time (RTT) prediction plays an important role in detecting packet losses in reliable transport protocols for traditional web applications and determining proper transmission rates in many rate-based TCP-friendly protocols for Internet-based real-time applications. The widely adopted autoregressive and moving average (ARMA) model with fixed-parameters is shown to be insufficient for all scenarios due to its intrinsic limitation that it filters out all high-frequency components of RTT dynamics. In this paper, we introduce a novel parameter-varying RTT model for Internet roundtrip time prediction based on the information theory and the maximum entropy principle (MEP). Since the coefficients of the proposed RTT model are updated dynamically, the model is adaptive and it tracks RTT dynamics rapidly. The results of our experiments show that the MEP algorithm works better than the ARMA method in both RTT prediction and RTO estimation.

A simple formula for insertion loss prediction of large acoustical enclosures using statistical energy analysis method

  • Kim, Hyun-Sil;Kim, Jae-Seung;Lee, Seong-Hyun;Seo, Yun-Ho
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.6 no.4
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    • pp.894-903
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    • 2014
  • Insertion loss prediction of large acoustical enclosures using Statistical Energy Analysis (SEA) method is presented. The SEA model consists of three elements: sound field inside the enclosure, vibration energy of the enclosure panel, and sound field outside the enclosure. It is assumed that the space surrounding the enclosure is sufficiently large so that there is no energy flow from the outside to the wall panel or to air cavity inside the enclosure. The comparison of the predicted insertion loss to the measured data for typical large acoustical enclosures shows good agreements. It is found that if the critical frequency of the wall panel falls above the frequency region of interest, insertion loss is dominated by the sound transmission loss of the wall panel and averaged sound absorption coefficient inside the enclosure. However, if the critical frequency of the wall panel falls into the frequency region of interest, acoustic power from the sound radiation by the wall panel must be added to the acoustic power from transmission through the panel.

Prediction of Frequency Modulation of BPF Tonal Noise for Random Pitch Cross-Flow Fans by Unsteady Viscous Flow Computations (비정상 점성유동 해석에 의한 부등피치 횡류홴의 BPF 순음 주파수 변조 특성 예측)

  • Cho, Yong;Moon, Young J.
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.27 no.3
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    • pp.286-293
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    • 2003
  • The unsteady flow characteristics and associated blade tonal noise of a cross-flow fan are predicted by computational methods. The incompressible Navier-Stokes equations are time-accurately solved for obtaining the pressure fluctuations between the rotating blades and the stabilizer. and the sound pressure is predicted using Curie's equation. The discrete noise characteristics of three impellers with a uniform and two random pitch (type-A and -B) blades are compared by their SPL (Sound Pressure Level) spectra. and the frequency modulation characteristics of the BPF (Blade Passing Frequency) noise are discussed. Besides. a mathematical model is proposed for the prediction of discrete blade tonal noise and is validated with available experimental data. The fan performance is also compared with experimental data. indicating that the random pitch effect does not significantly alter the performance characteristics at ${\phi}$ 〉 0.4

Development of Traffic Accident Frequency Prediction Model in Urban Signalized Intersections with Fuzzy Reasoning and Neural Network Theories (퍼지 및 신경망이론을 이용한 도시부 신호교차로 교통사고예측모형 개발)

  • Kang, Young-Kyun;Kim, Jang-Wook;Lee, Soo-Il;Lee, Soo-Beom
    • International Journal of Highway Engineering
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    • v.13 no.1
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    • pp.69-77
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    • 2011
  • This study is to suggest a methodology to overcome the uncertainty and lack of reliability of data. The fuzzy reasoning model and the neural network model were developed in order to overcome the potential lack of reliability which may occur during the process of data collection. According to the result of comparison with the Poisson regression model, the suggested models showed better performance in the accuracy of the accident frequency prediction. It means that the more accurate accident frequency prediction model can be developed by the process of the uncertainty of raw data and the adjustment of errors in data by learning. Among the suggested models, the performance of the neural network model was better than that of the fuzzy reasoning model. The suggested models can evaluate the safety of signalized intersections in operation and/or planning, and ultimately contribute the reduction of accidents.