기계 장비의 진동 데이터는 필연적으로 노이즈를 포함하고 있다. 이러한 노이즈는 기계 장비의 유지보수를 진행하는데 악영향 을 끼친다. 그에 따라 데이터의 노이즈를 얼마나 효과적으로 제거해주냐에 따라 학습 모델의 성능을 좌우한다. 본 논문에서는 시계열 데 이터를 전처리 함에 있어 특성추출 과정을 포함하지 않는 Denoising Auto Encoder 기법을 활용하여 데이터의 노이즈를 제거했다. 또한 기계 신호 처리에 널리 사용되는 Wavelet Transform과 성능 비교를 진행했다. 성능비교는 고장 탐지율을 계산하여 진행했으며 보다 정확한 비교 를 위해 분류 성능 평가기준 중 하나인 F-1 Score를 계산하여 성능 비교를 진행했다. 고장을 탐지하는 과정에서는 One-Class SVM 기법을 활용하여 고장 데이터를 탐지했다. 성능 비교 결과 고장 진단율과 오차율 측면에서 Denoising Auto Encoder 기법이 Wavelet Transform 기법 에 비해 보다 좋은 성능을 나타냈다.

Recently, a study of prognosis and health management (PHM) was conducted to diagnose failure and predict the life of air craft engine parts using sensor data. PHM is a framework that provides individualized solutions for managing system health. This study predicted the remaining useful life (RUL) of aeroengine using degradation data collected by sensors provided by the IEEE 2008 PHM Conference Challenge. There are 218 engine sensor data that has initial wear and production deviations. It was difficult to determine the characteristics of the engine parts since the system and domain-specific information was not provided. Each engine has a different cycle, making it difficult to use time series models. Therefore, this analysis was performed using machine learning algorithms rather than statistical time series models. The machine learning algorithms used were a random forest, gradient boost tree analysis and XG boost. A sliding window was applied to develop RUL predictions. We compared model performance before and after applying the sliding window, and proposed a data preprocessing method to develop RUL predictions. The model was evaluated by R-square scores and root mean squares error (RMSE). It was shown that the XG boost model of the random split method using the sliding window preprocessing approach has the best predictive performance.

IWRAP 프로그램은 수로에서의 위험성을 평가하는데 유용한 프로그램이다. 그러나 이 프로그램의 기본 버전의 경우 AIS 데이터를 수집하는 기능이 포함되지 않아서, 더구나 베트남과 같은 개발도상국에서는 해상교통량 통계 데이터가 없는 실정이다. 사용자들은 수동으로 준비하여 입력하여야 한다. 이 연구는 IWRAP Mk2 프로그램 기본 버전을 사용하는데 있어 AIS 데이터를 전처리(pre-process) 할 수 있는 프로그램을 개발하고자 하였으며, 선박 형태, 선박 크기, 통과 시간 등으로 분류한 통항로에서의 선박 통항 척수 및 항로 배치와 같이 해역 내 해상교통에 관한 정보들을 사용자에게 제공하도록 고안되었다. 이렇게 개발된 통합 AIS 프로그램(Total AIS, TOAIS)은 베트남 Vung Tau 해역의 AIS 수집 데이터를 전처리할 수 있는지에 대하여 검증하였다. 그 결과, 통합 AIS 프로그램에서 전처리한 데이터를 이용한 IWRAP 프로그램은 베트남 해역의 위험성을 효율적으로 평가할 수 있었다.

In this paper, we introduce the performance evaluation and development of Raw VLBI Data Buffer(RVDB) system for the synchronized playback processing of observed data in Korea-Japan Joint VLBI Correlator(KJJVC). The high-speed correlation processing system is under development so that the radio data obtained with 8192 channels and 8 Gbps speed from 16 stations will be able to be processed. When the recorded data of each station are played to correlator, the time synchronization of each station is very important because the correlator should process the data obtained with same time and condition. There are many types of recorder systems in the East Asia VLBI Network (EAVN). Therefore it is required to prepare the special time synchronized playback processing system to synchronize the time tag of observed data. The developed RVDB system consists of Data Input Output(DIO), 10GbE switch, and Disk Data Buffer(DDB). It can record the data with maximum 2 Gbps speed, and can play back the data to correlator with nominal 2 Gbps speed. To enable to play back the data of different playback system to the correlator, we developed the high-speed time synchronized playback processing system. We carried out the experiments of playing back and correlation for gigabit correlator and VCS trial product so as to confirm the performance of developed time synchronized playback processing system. In case of online and offline playing back experiment for gigabit correlator, we confirmed that the online and offline correlation results were the same. In case of playing back experiment for VCS trial product, we verified that the wide band and narrow band correlation results were also the same. Through the playing back experiments of RVDB system, the effectiveness of developed RVDB system was verified. In this paper, the system design, construction and experimental results are shown briefly.

차량방호 안전시설에 대한 성능의 검증은 충돌시험의 가속도와 각속도 데이터를 사용하여 산정한 탑승자 안전지수를 평가하여 이루어진다. 탑승자 안전지수로는 THIV(Theoretical Head Impact Velocity), PHD(Post-impact Head Deceleration), ASI(Acceleration Severity Index), OIV(Occupant Impact Velocity)와 ORA(Occupant Ridedown Acceleration)가 있다. 탑승자 안전지수 계산에 상이한 데이터 처리과정과 수치절차의 적용이 가능하기 때문에 동일한 시험 데이터에 대하여 다양한 탑승자 안전지수값이 결정될 수 있어서 혼란이 초래되고 있는 실정이다. 이러한 문제를 해결하기 위하여 다양한 상세절차와 데이터 처리과정이 탑승자 안전지수에 미치는 영향을 조사하였다. 지침에 제시된 계측시간간격을 사용하여 차량충돌시험이 수행된다면 보간법과 수치적분방법은 THIV와 OIV 값에 영향을 크게 미치지 않았다. 그리고 PHD에 대한 10msec 이동평균방법과 데이터 처리과정의 영점보정은 탑승자 안전지수에 상당한 영향을 미치기 때문에 이에 관한 구체적인 방법이 지침에 규정되어야 한다.

In this paper, we introduce the performance test results of digital data processing system for KVN (Korean VLBI Network). The digital data processing system for KVN consists of DAS (Data Acquisition System) and high-speed recorder which called Mark5B system. DAS system performs the digitalization of analog radio signal through ADS-1000 gigabit sampler with 1 Gsps/2-bit and process the digital filtering of digital signal. Mark5B system records the output data of DFB (Digital Filter Bank) with about 1 Gbps. In this paper, we carried out the preliminary evaluation experiments of the KVN digital data processing system connected between DAS system and Mark5B with VSI (VLBI Standard Interface) interface which is designed for compatible in each VLBI system. We first performed all of the KVN digital data processing system connected by VSI interface in the world. In factory inspection phase, we found that the DAS system has a memory read/write error in DSM (Digital Spectrometer) by analyzing the recorded data in Mark5B system. We confirmed that the DSM memory error has been correctly solved by comparing DSM results with Mark5B results. The effectiveness of KVN digital data processing system has been verified through the preliminary experiments such as data transmission, recording with VSI interface connection and data analysis between DSM and Mark5B system. In future work, we will perform the real astronomical observation by using the KVN 21m radio telescopes so as to verify its stability and performance.

We developed a new program for automatic continuum normalization of Echelle spectrographic data. Using this algorithm, we have determined spectral continuum of almost BOES data. The first advantage of this algorithm is that we can save much time for continuum determination and normalization. The second advantage is that the result of this algorithm is very reliable for almost spectral type of spectrum. But this algorithm cannot be applied directly to the spectrum which has very strong and broad emission lines, for example Wolf-Rayet type spectrum. We implanted this algorithm to the program which was developed in the previous study. And we introduced more upgraded BOES data reduction program. This program has more convenient graphical user interface environment, so users can easily reduce BOES data. Lastly, we presented the result of study on line profile variation of magnetic Ap/Bp stars analyzed using this program.

In this paper, we describe the radio astronomical data processing system implementation using Mark5B and its development. KASI(Korea Astronomy and Space Science Institute) is constructing the KVN (Korean VLBI Network) until the end of 2007, which is the first VLBI(Very Long Baseline Interferometery) facility in Korea and dedicated for the mm-wave VLBI observation. KVN will adopt the DAS (Data Acquisition System) consisting of digital filter with various function and 1Gsps high-speed sampler to digitize the radio astronomical data for analyzing on the digital filter system. And the analyzed data will be recorded to recorder up to 1Gbps data rates. To test this, we have implemented the system which is able to process 1Gbps data rates and carried out the data recording experiment.