• Title/Summary/Keyword: Detection Status

Search Result 869, Processing Time 0.025 seconds

Fault Detection of Propeller of an Overactuated Unmanned Surface Vehicle based on Convolutional Neural Network (합성곱신경망을 활용한 과구동기 시스템을 가지는 소형 무인선의 추진기 고장 감지)

  • Baek, Seung-dae;Woo, Joo-hyun
    • Journal of the Society of Naval Architects of Korea
    • /
    • v.59 no.2
    • /
    • pp.125-133
    • /
    • 2022
  • This paper proposes a fault detection method for a Unmanned Surface Vehicle (USV) with overactuated system. Current status information for fault detection is expressed as a scalogram image. The scalogram image is obtained by wavelet-transforming the USV's control input and sensor information. The fault detection scheme is based on Convolutional Neural Network (CNN) algorithm. The previously generated scalogram data was transferred learning to GoogLeNet algorithm. The data are generated as scalogram images in real time, and fault is detected through a learning model. The result of fault detection is very robust and highly accurate.

A Study on Diagnosis of The Energized Status of 22.9kV Multigrounded Underground Power Cable (22.9kV 다중 접지 지중 전력 케이블의 가압 상태 진단에 관한 기초 연구)

  • Kim, Chang-Gyo;Hong, Jin-Su;Jeong, Yeong-Ho
    • The Transactions of the Korean Institute of Electrical Engineers C
    • /
    • v.48 no.10
    • /
    • pp.699-703
    • /
    • 1999
  • An experimental study to identify the energized status of the 22.9kV underground power cable by the detection of vibration has been performed. We have derived that there exists vibration at double the line frequency in live cables by electromagnetic force. The relative amplitudes of the cable vibration according to the energized status of the cable were calculated by computer simulation. The cable vibration can also be picked up by accelerometer. A prototype was tested on the underground distribution system in Chonan substation, KEPCO. Comparison between simulation results and field test results was performed. The results showed that the energized status of the calble can be identified by measuring the vibration of the cable using accelerometer.

  • PDF

International Caries Detection and Assessment System (ICDAS) (최신 치아우식 진단기준 : International Caries Detection and Assessment System (ICDAS))

  • Choi, Youn-Hee
    • The Journal of the Korean dental association
    • /
    • v.49 no.8
    • /
    • pp.451-460
    • /
    • 2011
  • Dental caries has been widely prevalent with presence of cavitation on teeth. For the last several decades, the prevalence of dental caries in developed countries has rapidly decreased so there has been needed a new and detailed diagnostic guideline to differentiate the severity of dental caries, especially for early status of caries. The cariology specifically requires the development of an integrated definition of dental caries and uniform systems for measuring the caries process in the fields of clinical diagnosis and treatment, epidemiological researches, and dental education and so forth. The international Caries Detection and Assessment System (ICDAS) optically measures the enamel surface changes and potential histological depth of carious lesions by relying on surface characteristics of teeth. ICDAS is a visual classification system that was developed to diagnose the subtle changes of enamel surface, predict the progress direction of early caries, allow standardized data collection in relation to caries in different settings, and to enable better comparison of oral health between countries worldwide and research studies.

A Comparative Study on Collision Detection Algorithms based on Joint Torque Sensor using Machine Learning (기계학습을 이용한 Joint Torque Sensor 기반의 충돌 감지 알고리즘 비교 연구)

  • Jo, Seonghyeon;Kwon, Wookyong
    • The Journal of Korea Robotics Society
    • /
    • v.15 no.2
    • /
    • pp.169-176
    • /
    • 2020
  • This paper studied the collision detection of robot manipulators for safe collaboration in human-robot interaction. Based on sensor-based collision detection, external torque is detached from subtracting robot dynamics. To detect collision using joint torque sensor data, a comparative study was conducted using data-based machine learning algorithm. Data was collected from the actual 3 degree-of-freedom (DOF) robot manipulator, and the data was labeled by threshold and handwork. Using support vector machine (SVM), decision tree and k-nearest neighbors KNN method, we derive the optimal parameters of each algorithm and compare the collision classification performance. The simulation results are analyzed for each method, and we confirmed that by an optimal collision status detection model with high prediction accuracy.

Ultrasonic detection properties for partial discharge at the premolded joint of a 23kV cable (23kV급 조립형 케이블 접속재에서 부분방전 신호의 초음파 검출특성)

  • Lee, Woo-Young;Ryoo, Hee-Suk;Sun, Jong-Ho;Kim, Sang-Jun;Song, Il-Gun;Kim, Joo-Yong
    • Proceedings of the KIEE Conference
    • /
    • 1996.07c
    • /
    • pp.1907-1909
    • /
    • 1996
  • In this paper, ultrsonic detection properties at a premolde joint utilized in a 23kV cables are studied. In a experiment a artificial defect within a joint and a measuring system are builded for generating discharges, gathering data about a detection properties, respectively. The experiment results show that one point detection is not allowed for monitoring a global status of a joint discharges and a detection sensitivity is less than 100pC. And also the attenuation and wave speed at the material of joint insulator are obtained.

  • PDF

Development of a Drowsiness Detection System using Machine Vision (머신 비젼을 이용한 졸음 감지 시스템 개발)

  • Kang, Su Min;Huh, Kyung Moo
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.22 no.4
    • /
    • pp.266-270
    • /
    • 2016
  • In this paper, we propose a technique of drowsiness detection using machine vision. The drowsiness of vehicle driver is often the primary cause of motor vehicle accidents. Therefore, the checking of eye images for detecting drowsiness status of driver is critical for preventing these accidents. In our suggested method, we analyze the changes of histogram and edge of eye region images which are acquired using CCD camera. We developed a drowsiness detection system using the histogram and edge change information. The experimental results show that our proposed method enhances the accuracy of detecting drowsiness nearly to 98%, and can be used for preventing vehicle accidents due to the drowsiness of drivers.

Fault Prediction Based on Unbalanced Current Detection of Three Phase Heater and Selection of the Protective Device (3상 히터의 불평형전류 검출에 의한 결함예측 및 보호장치의 선정)

  • Lee, Mun Hyung;Jung, Jae Hee
    • Journal of the Korean Society of Safety
    • /
    • v.30 no.1
    • /
    • pp.28-33
    • /
    • 2015
  • Three phase heaters in 7 buildings of 2 sites were examined for precise diagnosis. The sample size was 626. Precise examinations of current and the heater wiring status revealed contact failures and arcs in equipments that had CUF larger than 10%. Contact failures and arcs may cause electrical fire. Therefore, the correlation between the CUF and the imperfections in heater equipment and its wiring was analyzed for three phase heaters. In addition, the protection devices used for detection of heater imperfections were found to be unsuitable for the purpose. Current status of the protection devices was analyzed, and suggestions for improvements were made for new standards of the protection device selection.

A study on remote monitoring system for tower Parking facility (엘리베이터식 주차설비 원격감시시스템 구현)

  • Lee, W.T.;Lee, J.J.;Kim, K.H.;Cha, J.S.;Jeong, Y.K.
    • Proceedings of the KIEE Conference
    • /
    • 1999.07g
    • /
    • pp.3206-3208
    • /
    • 1999
  • This paper describes the remote fault monitoring system for tower parking facilities. This system consists of central station, remote monitoring equipments and communication equipments. The central station is developed under client-server architecture which composed a DB server, a fault detection client, a status collection client and a A/S client. And the remote monitoring systems are connected to central station by LAN using RAS(Remote Access Service) which is constructed PSTN(Public Switched Telephone Network). This system offers real-time fault detection and status data acquisition of tower parking system.

  • PDF

The Status Quo and Future of Software Regression Bug Discovery via Fuzz Testing (퍼즈 테스팅을 통한 소프트웨어 회귀 버그 탐색 기법의 동향과 전망)

  • Lee, Gwangmu;Lee, Byoungyoung
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.31 no.5
    • /
    • pp.911-917
    • /
    • 2021
  • As software gets an increasing amount of patches, lots of software bugs are increasingly caused by such software patches, collectively known as regression bugs. To proactively detect the regressions bugs, both industry and academia are actively searching for a way to augment fuzz testing, one of the most popular automatic bug detection techniques. In this paper, we investigate the status quo of the studies on augmenting fuzz testing for regression bug detection and, based on the limitations of current proposals, provide an outlook of the relevant research.

Development of Camera Monitoring System for Detecting the Opening Status of Saemangeum Sluice Gate (새만금 갑문 개폐 자동 영상 관측 시스템 개발)

  • Kim, Tae-Rim;Park, Jong-Jib;Jang, Seong-Woo
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.14 no.1
    • /
    • pp.73-83
    • /
    • 2011
  • The opening status of Saemangeum sluice gate is an important factor to the coastal water qualities near Saemangeum dikes. The sluice gate opening information is important in analysing current velocity and water quality data measured at the Saemanguem observation tower as well as in determining boundary conditions of numerical simulation for coastal environment outside Saemangeum dikes. This study establishes unmanned camera monitoring system on Saemangeum observation tower using mini notebook and digital camera, and extracts information on the opening status from images automatically. Images are analysed using variance difference of images together with edge detection techniques in order to get correct information.