Study on the Internal Pipeline Inspection Devices with Energy Acquisition Methods

Wang Ming-Xu,차인수,Wang Yue,Bei Lei,최홍준,정경환,김동묵,김봄,오승아,Ye In Cheol,유일준 한국에너지학회 2023 에너지공학 Vol.32 No.1

The pipeline conveying natural gas must be regularly inspected by the detection device, and the cracks and corrosion condition inside the pipeline should be detected. Generally, the detection device consists of three parts: drive part, detection part and energy part. Since pipeline transportation is long-distance transportation and cannot realize wired detection, the energy part needs to provide enough electric energy for the detection part to meet the energy consumption of the detection part. The method of obtaining energy for the energy part is very important. In this paper, the energy part is studied, and an efficient energy part is designed. By analyzing the change law of the positive pressure on the inner wall of the energy acquisition wheel on the pipeline, the corresponding torque and power changes are obtained when the detector moves at different speeds. Through the test platform system, the output power of the energy part at different speeds is collected, and the accuracy of the theoretical calculation is verified.

적정 에너지 베이스라인 구축을 위한 하이브리드 모델 기반 이상값 검출 알고리즘

이태규(Lee, Tae-Kyu),김정욱(Kim, Jeong-Uk) 한국건축친환경설비학회 2024 한국건축친환경설비학회 논문집 Vol.18 No.2

This study explores the importance of establishing an appropriate energy baseline for the energy management of buildings and building complexes. The energy baseline serves as a benchmark for assessing a building’s energy consumption and accurately measuring the effects of energy-saving measures. With many buildings using energy inefficiently, accurately setting an energy baseline presents challenges. This research emphasizes the necessity of continuously monitoring a building’s energy consumption to establish a sustainable energy management strategy. The proper setting and management of an energy baseline play a crucial role in assessing the effectiveness of energy demand management projects. The study demonstrates that the energy baseline varies according to energy consumption behavior, revealing up to a 28% daily discrepancy in estimated energy baseline through the detection of anomaly data. These findings suggest difficulties in accurately determining an energy baseline, yet underline the need for appropriate criteria for judgment and the significance of constructing a proper baseline for accurately calculating the energy-saving effects from a demand management perspective. Future research aims to develop additional algorithms for analyzing energy consumption behavior and detecting anomalous data.

무선에너지하비스팅 시스템을 위한 효율적인 스펙트럼 센싱 기법

황유민,신요안,김동인,김진영 사단법인 한국위성정보통신학회 2017 한국위성정보통신학회논문지 Vol.12 No.4

스펙트럼 센싱은 인지무선 (cognitive radio) 시스템을 동작시키기 위한 주요한 기법이며 인지무선 시스템을 통해 최근 주목받고있는 무선에너지하비스팅 시스템에 에너지 하비스팅 효율을 개선할 수 있다. 최근 스펙트럼 센싱을 위한 다양한 기술이 연구되었는데, 그 중에서 가장 널리 쓰이고 있는 에너지 검출 (energy detection) 기술이 있다. 그러나 2차 유저 (secondary user; SU) 가 주파수페이딩 (frequency fading) 및 쉐도잉 (shadowing)에 의해 영향을 받을 수 있기 때문에, 에너지 검출은 실제 무선 통신에서 숨겨진단말기 문제 (hidden terminal problem)를 갖는다. 협력 스펙트럼 센싱 (cooperative spectrum sensing)은 SU의 공간적 다양성을이용하여 이 문제를 해결할 수 있습니다. 그러나 다중 보조를 처리하여 데이터를 증가시키는 문제가 있기 때문에 우리는 적응형스펙트럼 센싱 알고리즘을 사용하는 시스템 모델을 제안하고 성능을 시뮬레이션 한다. 이 알고리즘은 기본 사용자 (primary user; PU)의 수신 신호의 신호 대 잡음비 (signal to Noise Ratio; SNR)에 따라 단일 에너지 검출과 협동 에너지 사이의 감지 방법을 선택하는 방법을 이용한다. 시뮬레이션 결과를 통해 적응형 스펙트럼 센싱이 인지무선 시스템에서 더 효율적이라는 것을 확인한다. Spectrum sensing is a critical functionality of Cognitive Radio(CR) systems and the CR systems can be applied to RF energy harvesting systems to improve an energy harvesting rate. There are number of spectrum sensing techniques. One of techniques is energy detection. Energy detection is the simplest detection method and is the most commonly used. But, energy detection has a hidden terminal problem in real wireless communication, because of secondary user (SU) can be affected by frequency fading and shadowing. Cooperative spectrum sensing can solve this problem using spatial diversity of SUs. But it has a problem of increasing data by processing multiple secondary. So, we propose the system model using adaptive spectrum sensing algorithm and system model is simulated. This algorithm chooses sensing method between single energy sensing and cooperative energy according to the received signal's Signal to Noise Ratio (SNR) from Primary User (PU). The simulation result shows that adaptive spectrum sensing has an efficiency and improvement in CR systems.

이동물체 탐지 및 추적을 위한 에너지 보정 스네이크(ECS) 알고리즘의 실험 및 평가

윤희병,양성실 한국정보처리학회 2009 정보처리학회논문지. 소프트웨어 및 데이터 공학 Vol.16 No.4

Active Contour Model, that is, Snake algorithm is effective for detection and tracking the objects. However, this algorithm has some drawbacks; numerous parameters must be designed(weighting factors, iteration steps, etc.), a reasonable initialization must be available and moreover suffers from numerical instability. Therefore we propose a novel Energy Corrected Snake(ECS) algorithm which improved on external energy of Snake algorithm for detection and tracking the moving object more effectively. The proposed algorithm uses the difference image, getting when the object is moving. It copies four direction images from the difference image and performs the accumulating compute to erasing image noise, so that it gets external energy steadily. Then external energy united with contour that is computed by internal energy. Consequently we can detect and track the moving object more speedily and easily. To show the effectiveness of the proposed algorithm, we experiment on 3 situations. The experimental results showed that the proposed algorithm outperformed by 6~9% of detection rate and 6~11% of tracker detection rate compared with the Snake algorithm. 능동 윤곽선 모델, 즉 스네이크 알고리즘은 물체 탐지 및 추적에 사용되는 유용한 알고리즘이다. 그러나 이 알고리즘은 요소별 가중치 부여 및 반복단계 시 많은 변수가 필요하고, 초기화 애로 및 계산상 불안정성 등의 단점이 있다. 따라서 본 논문에서는 이러한 단점을 개선하여 보다 효과적인 이동물체 탐지 및 추적을 위해 기존 스네이크 알고리즘의 외부 에너지를 개선한 새로운 에너지 보정 스네이크(ECS) 알고리즘을 제안한다. 이를 위해 이동물체 이동 시 획득한 차영상 이미지를 4개의 방향성 이미지로 복사하고 각 이미지 픽셀에 대해 누적 연산 후 에너지 강화배열 내 저장 및 노이즈 제거를 통해 안정적인 이미지, 즉 외부 에너지를 획득한다. 또한 별도로 계산된 내부 에너지를 통해 얻어진 윤곽선(contour)을 외부 에너지에 병합함으로써 빠르고 쉬운 이동물체 탐지 및 추적이 가능하다. 제안한 알고리즘의 효용성을 확인하기 위해 3가지 상황을 대상으로 실험하였다. 실험 결과, 제안한 알고리즘이 기존 스네이크 알고리즘에 비해 탐지율은 평균 6~9%, 추적율은 6~11% 정도의 향상을 보였다.

Dynamic radionuclide identification using energy weighted algorithm with commercialized radiation portal monitor based on plastic scintillators

Lee, Hyun Cheol,Choi, Hyun Joon,Koo, Bon Tack,Choi, Chang-Il,Park, Chang Su,Kim, Hong-Suk,Min, Chul Hee Pergamon 2020 Radiation physics and chemistry Vol.170 No.-

<P><B>Abstract</B></P> <P>A radiation portal monitoring (RPM) system, which detects illegal radioactive materials at ports or airports, mainly consists of plastic scintillators made of polyvinyl toluene with poor energy resolution. Therefore, it is difficult to expect accurate nuclide analysis. Hence, in this study, we validated an energy weighted algorithm proposed in a previous study by identifying the energy weighted spectra of dynamic <SUP>137</SUP>Cs, <SUP>60</SUP>Co, <SUP>226</SUP>Ra, and <SUP>238</SUP>U using a commercialized RPM. The spectrum data in the static and dynamic conditions of all the sources were measured using a sedan vehicle. The peak detection of <SUP>137</SUP>Cs and <SUP>60</SUP>Co according to the measurement distance and source speed was evaluated and compared with that identified using a NaI(Tl)-based RPM. Even at the source speeds of 5 and 10 km/h, the peak of the energy weighted spectrum was successfully detected. In particular, when <SUP>137</SUP>Cs and <SUP>60</SUP>Co over 70 μCi were moved at 30 km/h, all the peaks were detected within the designated peak detection range. The experiment presented in this study is a methodological analysis, however, the energy weighted algorithm can be applied in primary RPM inspection.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Energy weighted algorithm was applied to a commercialized RPM system. </LI> <LI> Energy weighted spectra of dynamic gamma sources were evaluated. </LI> <LI> Nuclides were successfully identified using plastic scintillators. </LI> </UL> </P>

2022 개정 과학과 교육과정에 나타나는 에너지 관련 성취기준에 대한 네트워크 분석

조헌국,노현아,최재혁 에너지기후변화교육학회 2023 에너지기후변화교육 Vol.13 No.2

This study focused on investigating the features of achievement standards relevant to the concept of energy presented in the 2022 revised national curriculum of science and examining the pedagogical implications for implementing energy education according to the revised curriculum. Thirty-four energy standards were extracted from various science subjects comprising 471 standards, and the network characteristics are compared according to school grades and the fields of science. The results show that most of the relevant standards are dealt with in high schools, with a large proportion linked to physics; however, the subject of earth science does not explicitly include the concept of energy. The result of different types of centralities based on a part-of-speech tagger revealed that the achievement standards are mainly categorized into three areas: procedural skills, such as explanation, investigation, and argumentation; energy-centered components, such as energy forms, transfer, and application; and scientific concepts, such as physical motions and chemical reactions. In this study, clusters of network graphs are examined through community detection, and the networks comprise eight themes. Energy-centered components are widely tackled across the school level. In particular, conceptual and domain-specific contents increased from the primary to secondary level. Based on these findings, we suggest several implications for implementing energy education aligned with the 2022 revised national curriculum of science. 본 연구는 2022 개정 과학과 교육과정에서의 에너지와 관련된 성취기준의 서술을 학교급 및 학문 영역별에 따른 특징을 분석하여 에너지 관련 교육에 대한 시사점을 제공하고자 수행하였다. 이에 공통 및 선택 중심 교육과정의 과학과 21개 과목 471개 성취기준 중 에너지와 관련된 성취기준 34개를 추출하였으며, 이를 네트워크 분석을 활용해 학교급이나 학문 영역에 따른 특징을 분석하였다. 연구 결과, 에너지와 관련된 내용은 대부분 고등학교 수준이었고, 학문 영역으로는 물리학에 치중되어 있었고, 지구과학의 경우에는 명시적으로 포함된 성취기준이 존재하지 않았다. 성취기준을 구성하는 주요어의 여러 가지 중심성 지수를 살펴보면 설명, 이해, 조사, 논증 등 과정⋅기능적 측면과 에너지의 전환, 활용, 과정 등의 에너지의 흐름과 형태 등에 대한 내용적 요소, 물리적 운동과 화학반응 등의 물리적, 화학적 맥락에서의 에너지에 대한 학습으로 크게 구분됨을 알 수 있다. 커뮤니티 탐지를 중심으로 언어 네트워크의 범주를 분석한 결과 생명 현상 및 생태계에서의 에너지, 지속가능 발전 측면에서의 에너지, 열에너지 및 전기에너지, 지구 및 태양계에서의 에너지, 양자 수준의 에너지, 일상제품 속 에너지와 원리, 물리적 운동에서의 에너지, 자원으로서의 에너지 등 8가지로 구분되었다. 학교급에 따른 성취기준의 특징을 서로 비교하면 초등학교에서 중학교, 고등학교 공통적으로 에너지의 종류나 전환, 이용 등 일생상활과 관련된 측면에서의 에너지에 대한 사용과 실천 등을 다루며, 학교급이 올라갈수록 물리적 운동, 화학반응, 생명현상과 물질대사 등 개념적 맥락에서의 에너지 교육이 점점 증가하였다. 이와 같은 연구 결과를 토대로 2022 개정 과학과 교육과정 도입에 따른 에너지 교육을 위한 시사점을 제공하였다.

Energy-efficient intrusion detection system for secure acoustic communication in under water sensor networks

N. Nithiyanandam,C. Mahesh,S.P. Raja,S. Jeyapriyanga,T. Selva Banu Priya 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.6

Under Water Sensor Networks (UWSN) has gained attraction among various communities for its potential applications like acoustic monitoring, 3D mapping, tsunami detection, oil spill monitoring, and target tracking. Unlike terrestrial sensor networks, it performs an acoustic mode of communication to carry out collaborative tasks. Typically, surface sink nodes are deployed for aggregating acoustic phenomena collected from the underwater sensors through the multi-hop path. In this context, UWSN is constrained by factors such as lower bandwidth, high propagation delay, and limited battery power. Also, the vulnerabilities to compromise the aquatic environment are in growing numbers. The paper proposes an Energy-Efficient standalone Intrusion Detection System (EEIDS) to entail the acoustic environment against malicious attacks and improve the network lifetime. In EEIDS, attributes such as node ID, residual energy, and depth value are verified for forwarding the data packets in a secured path and stabilizing the nodes' energy levels. Initially, for each node, three agents are modeled to perform the assigned responsibilities. For instance, ID agent verifies the node's authentication of the node, EN agent checks for the residual energy of the node, and D agent substantiates the depth value of each node. Next, the classification of normal and malevolent nodes is performed by determining the score for each node. Furthermore, the proposed system utilizes the sheep-flock heredity algorithm to validate the input attributes using the optimized probability values stored in the training dataset. This assists in finding out the best-fit motes in the UWSN. Significantly, the proposed system detects and isolates the malicious nodes with tampered credentials and nodes with lower residual energy in minimal time. The parameters such as the time taken for malicious node detection, network lifetime, energy consumption, and delivery ratio are investigated using simulation tools. Comparison results show that the proposed EEIDS outperforms the existing acoustic security systems.

Energy Detection Based Sensing for Secure Cognitive Spectrum Sharing in the Presence of Primary User Emulation Attack

Salem, Fatty M.,Ibrahim, Maged H.,Ibrahim, I.I. The Institute of Electronics and Information Engin 2013 IEIE Transactions on Smart Processing & Computing Vol.2 No.6

Spectrum sensing, as a fundamental functionality of Cognitive Radio (CR), enables Secondary Users (SUs) to monitor the spectrum and detect spectrum holes that could be used. Recently, the security issues of Cognitive Radio Networks (CRNs) have attracted increasing research attention. As one of the attacks against CRNs, a Primary User Emulation (PUE) attack compromises the spectrum sensing of CR, where an attacker monopolizes the spectrum holes by impersonating the Primary User (PU) to prevent SUs from accessing the idle frequency bands. Energy detection is often used to sense the spectrum in CRNs, but the presence of PUE attack has not been considered. This study examined the effect of PUE attack on the performance of energy detection-based spectrum sensing technique. In the proposed protocol, the stationary helper nodes (HNs) are deployed in multiple stages and distributed over the coverage area of the PUs to deliver spectrum status information to the next stage of HNs and to SUs. On the other hand, the first stage of HNs is also responsible for inferring the existence of the PU based on the energy detection technique. In addition, this system provides the detection threshold under the constraints imposed on the probabilities of a miss detection and false alarm.

수동 소나 쌍을 이용한 에너지 인식 분산탐지 체계의 설계 및 성능 분석

도주환(Joo-Hwan Do),김송근(Song-Geun Kim),홍순목(Sun-Mog Hong) 대한전자공학회 2009 電子工學會論文誌-SP (Signal processing) Vol.46 No.4

이 논문에서는 한 쌍의 수동 광대역 소나로 구성된 병렬구조 분산센서망에 적용할 수 있는 에너지 인식 분산탐지 체계의 설계 및 성능분석에 대해 검토한다. 이 분산탐지기는 융합규칙으로 AND 규칙과 OR 규칙을 사용하였다. 이 경우 각 센서노드의 문턱값 규칙은 전체 분산센서망의 탐지확률을 최대로 하는 UMP(uniformly most powerful)임을 증명하였다. 그리고 소나 체계에서 오경보에 의해 발생하는 에너지 비용을 제한 조건으로 주었을 때, 탐지확률을 최대화하는 센서노드의 최적 문턱값이 갖는 특성을 이론적으로 검토하였다. 나아가 신호 강도, 에너지 비용에 대한 제한조건, 센서노드 사이의 간격등이 탐지성능에 미치는 영향을 수치실험을 통해 분석하였다. In this paper, optimum design of energy-aware distributed detection is considered for a parallel sensor network system consisting of a fusion center and two passive sonar nodes. AND rule and OR rule are employed as the fusion rules of the sensor network. For the fusion rules, it is shown that a threshold rule of each sensor node has uniformly most powerful properties. Optimum threshold for each sensor is investigated that maximizes the probability of detection under a constraint on energy consumption due to false alarms. It is also investigated through numerical experiments how signal strength, an energy constraint, and the distance between two sensor nodes affect the system detection performances.

준지도 이상탐지를 위한 다층 홉필드 신경망

곽봉,김동국 한국디지털콘텐츠학회 2023 한국디지털콘텐츠학회논문지 Vol.24 No.11

This study proposes a multi-layer Hopfield neural network (MHNN) for semi-supervised anomaly detection. MHNN comprises the structure of a modern continuous Hopfield network (MCHN), which is an energy-based model, and is extended so that the energy function has a multi-layer neural network. The energy function of MHNN is used as a detection criterion for anomaly detection. We present the gradient-based parameter update methods for MHNN training, using contrastive divergence and score matching. To evaluate the proposed technique, semi-supervised anomaly detection experiments were conducted using ECG, UNSW and Fashion MNIST/MNIST. The proposed MHNN showed a higher F1-score than the single-layer MCHN and conventional energy-based techniques. Consequently, we indicate that the proposed MHNN is a highly effective energy-based model for anomaly detection.