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18th International Offshore and Polar Engineering Conference (ISOPE 2008)

作者： Maheshwari, Himanshu Ruf, Wolfgang Walters, Dave 2H Offshore Inc Houston TX USA

ISBN: (纸本)9781880653708

Riser integrity monitoring provides critical performance data during day to day operation and in extreme events. In-situ integrity monitoring improves the understanding of the complex riser behavior leading to enhancement of design practices. The paper discusses a range of methodologies for offshore riser monitoring. A review of existing and planned monitoring programs is provided with particular focus on the level of success achieved. Monitoring instrumentation and applications are discussed from the "fit for purpose" perspective, highlighting the monitoring objectives, reliability requirements and offshore operations. The paper also describes data processing methods used for screening and evaluating the collected data. The differences amongst standalone, hardwired, and acoustic data processing and further analysis of the monitoring data are discussed. Hardwired methods are focused on providing information that are relevant for making operational decisions at offshore facilities during day to day activities. Additional onshore data processing is focusing on providing information that can be used in the continuous effort to better understand riser response. In summary, the paper discusses the relative benefits and potential problems associated with hardwired, stand-alone and acoustic monitoring systems in adding value to the integrity management of deepwater risers.

关键词： Riser monitoring structural monitoring data processing methods

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Construction of a Simulation Evaluation System for Physical Education and Analysis of data processing methods

Construction of a Simulation Evaluation System for Physical ...

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作者： Li, Jianhui Aba Teachers College Sichuan Province Wenchuan623000 China

In the era of big data, the rapid advancements in information technology have made the excavation and analysis of data resources crucial for various industries. Within this context, physical education (PE) plays a pivotal role in fostering students’ physical fitness and resilient willpower. Establishing an effec-tive evaluation system and enhancing data analysis techniques hold significant importance in elevating teaching quality and fostering the holistic development of students. This article introduces a PE evaluation framework that leverages big data analysis. By developing a PE simulation evaluation system, it enables the comprehensive collection, purification, interpretation, and feedback of sports-related data. Utilizing visualization technology, the analysis outcomes are presented in a user-friendly manner, thereby aiding teachers in making informed teaching deci-sions and bolstering the optimization of sports teaching practices in universities. Experimental findings reveal that this system can significantly enhance the quality of PE instruction, assist students in gaining a deeper understanding of their PE learning progress, and spark their interest and motivation in learning. Addition-ally, it provides teachers with an expanded arsenal of teaching resources and tools, promoting personalized teaching and boosting teaching efficacy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： data processing methods Physical Education Simulation Evaluation System

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The Comparison and Improvement of data processing methods in Video Quality Subjective Assessment

The Comparison and Improvement of Data Processing Methods in...

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International Congress on Image and Signal processing

作者： Shuang Yang Yifan Wang Fang Meng Xiuhua Jiang Hao Liu Inf. Eng. Sch. Commun. Univ. of China Beijing China

ISBN: (纸本)9781479958368

data screening applied in video quality subjective assessment is helpful to remove abnormal observers and ensure the precision and effectiveness of the results. This paper firstly introduces two main data-processing methods, which are recommended in ITU-R BT.500 and ITU-R BT.1788 respectively, and then proposes an improved data-processing method, which is used to eliminate observers whose score trends are inconsistent with the overall trend in the first stage and then eliminate observers with too many outliers. Finally we analyze the applicability of those data-processing methods and verify the effectiveness of the improved method.

关键词： data compression data handling observers video coding video signal processing ITU-R BT.1788 ITU-R BT.500 abnormal observer removal data processing methods data screening data-processing method video communications video compression video quality evaluation video quality subjective assessment video transmission Correlation Correlation coefficient Market research Observers Quality assessment Standards Video recording Pearson correlation coefficient Spearman rank correlation coefficient subjective assessment video quality

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Switching data-processing methods in a control loop: Trade-off between delay and probability of data acquisition

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IFAC-PapersOnLine 2016年第22期49卷 274-279页

作者： van Horssen, E.P. Antunes, D. Heemels, W.P.M.H. Control System Technology Group Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands

Many control applications, such as vision-based control, require data-processing methods to distill sensor information. This data-processing introduces several undesired effects in the control loop, such as delays, the probability of not acquiring information, and measurement inaccuracies. Often, these effects obey a trade-off. For example, the probability of acquiring control-relevant information, related to the probability of data-loss, is typically higher if a larger delay is allowed. While a single processing method with a reasonable trade-off is typically selected, we propose instead a solution to switch between data-processing methods with different delays and corresponding data-loss probabilities. We prove that the proposed method achieves a better LQG-type performance when compared to the individual methods. A simulation considering a second-order system illustrates the advantages of the proposed method. © 2016

关键词： data handling data acquisition data processing Delay control systems Economic and social effects Probability Time delay Control applications data processing methods Information loss Optimal controls Second order systemss Self triggered controls Switched system Vision based control

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Energy calibration based on ridge lines in scatter plots

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JOURNAL OF INSTRUMENTATION 2025年第4期20卷

作者： Li, Shuo Lyu, Xudong Li, Xinyu Huazhong Univ Sci & Technol Dept Biomed Engn Wuhan Hubei Peoples R China Raycan Technol Co Ltd Suzhou Jiangsu Peoples R China

In applications such as PET and proton therapy monitoring, MVT and TOT methods have played a significant role. However, these methods face issues such as energy nonlinearity and inconsistent performance across different energy ranges. The challenge of investigating and resolving these issues has become urgent. This paper proposes a nonlinear calibration framework based on a 3D energy spectrum surface and diffusion equations, significantly improving the energy resolution and calibration accuracy of high-energy radiation detection systems. To address this challenge, this work establishes a foundation using the joint probability density surface of the acquisition system's input and output energies, along with the probability density and energy transfer equation. From this foundation, a transfer equation describing the energy input-output relationship is derived, and subsequently, a ridge line equation is developed for energy calibration. This approach results in an improvement in linearity from -5.11%, obtained via empirical scatter plot fitting, to -1.18%.

关键词： data processing methods Performance of High Energy Physics Detectors data acquisition concepts Electronic detector readout concepts (solid-state)

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Nanosecond hardware regression trees in FPGA at the LHC

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NUCLEAR INSTRUMENTS & methods IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2025年 1072卷

作者： Serhiayenka, Pavel Roche, Stephen T. Carlson, Benjamin T. Hong, Tae Min Univ Pittsburgh Dept Phys & Astron Pittsburgh PA 15260 USA St Louis Univ Sch Med St Louis MO USA Westmont Coll Dept Phys & Engn Santa Barbara CA USA

We present a generic parallel implementation of the decision tree-based machine learning (ML) method in hardware description language (HDL) on field programmable gate arrays (FPGA). A regression problem in high energy physics at the Large Hadron Collider (LHC) is considered: the estimation of the magnitude of missing transverse momentum using boosted decision trees (BDT). A forest of twenty decision trees each with a maximum depth often using eight input variables of 16-bit precision is executed with a latency of less than 10 ns using O(0.1%) resources on Xilinx UltraScale+ VU9P - approximately ten times faster and five times smaller compared to similar designs using high level synthesis (HLS) - without the use of digital signal processors (DSP) while eliminating the use of block RAM (BRAM). We also demonstrate a potential application in the estimation of muon momentum for ATLAS RPC at the High-Luminosity LHC (HL-LHC).

关键词： data processing methods data reduction methods Digital electronic circuits Trigger algorithms Trigger concepts and systems (hardware and software)

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Edge detection and depth evaluation of CFRP internal delamination defects based on differential image frequency domain preprocessing

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JOURNAL OF INSTRUMENTATION 2025年第1期20卷

作者： Zhou, Guangyu Fu, Yu Zhang, Zhijie Yin, Wuliang North Univ China Sch Instrument & Elect 3 Xueyuan Rd Taiyuan Peoples R China Shanxi Open Univ Inst Technol 108 Qianfeng north Rd Taiyuan Peoples R China Univ Manchester Sch Elect & Elect Engn Oxford Rd Manchester M13 9PL England

Carbon fiber reinforced polymers (CFRP) are widely used in fields such as aviation and aerospace. However, subtle defects can significantly impact the material's service life, making defect detection a critical priority. This paper presents a method for detecting delamination defects in carbon fiber reinforced composites (CFRP) using line laser infrared thermography. A preprocessing approach combining differential thermography and frequency-domain filtering is proposed to effectively eliminate the trailing artifacts caused by line laser scanning, resulting in defect feature images with an improved signal-to-noise ratio. Utilizing the preprocessed frequency-domain magnitude image data, an improved Fuzzy C-Means clustering segmentation algorithm is developed, achieving high-precision edge detection of layered defects with an average accuracy of 95.0%. Furthermore, defect depth classification based on the frequency-domain magnitude data is performed using the K-Nearest Neighbor (KNN) algorithm, yielding an average accuracy of 98.8%. These results validate the effectiveness of the proposed algorithms for defect edge detection and depth assessment.

关键词： data processing methods Detection of defects Image processing Lasers

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Spectrum analysis for identification of nuclides at radiological crime scene

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JOURNAL OF INSTRUMENTATION 2025年第3期20卷 C03004-C03004页

作者： Kaissas, I. Themistokleous, I. Karafasoulis, K. Xanthos, S. Kyriakis, A. Aristotle Univ Thessaloniki Fac Engn Sch Elect & Comp Engn Thessaloniki 54124 Greece Hellen Army Acad Div Nat Sci & Applicat Vari Attikis 16673 Greece Int Hellen Univ Dept Ind Engn & Management Thessaloniki 57400 Greece Natl Ctr Sci Res Demokritos Inst Nucl & Particle Phys Aghia Paraskevi 15341 Greece

Gamma-ray spectroscopy is an essential technique for identifying the composition of radioactive materials. This work presents a detailed algorithm for analysing gamma-ray spectra, focusing on peak detection, energy calibration, efficiency calibration and nuclide identification. The algorithm includes a systematic approach to match observed peaks with known nuclides, following a peak detection method, efficiency and energy calibration methods. The algorithm attempts to provide spectral analysis and nuclides identification on-site with portable spectroscopic devices. Therefore, it is tested with portable HPGe and CZT detectors demonstrating its ability to reliably identify isotopes in complex spectra, derived by multi radioactive sources identification scenarios. A conventional energy calibration is performed on the spectrum data to convert channels to energy values. Additional calibration is performed to adjust the height of the photopeaks, considering the efficiency curve of each detector. The algorithm identifies possible nuclides associated with each peak by searching for nuclides within a specified range of energy interval, minimum half-life, and minimum fraction yield of the photopeak. The matching process involves comparing photopeaks of the spectrum under investigation with a complete dataset of energies of gamma-rays and their emitters. To exclude false positive identifications of nuclides, a criterion considers a certain number of the most intense gamma-ray energies that each possible nuclide emits and investigates whether these energies are correlated with the photopeaks. In addition, another criterion checks the height of the photopeaks based on their fraction yield. The algorithm attempts to offer a solution for field applications, enhancing radiological crime-scene investigations and environmental monitoring.

关键词： data processing methods Spectrometers gamma-spectroscopy Nuclide identification Nuclear security

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Simulated near-field radioactive source localization in 3D with Coded Aperture and Convolutional Neural Networks

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JOURNAL OF INSTRUMENTATION 2025年第1期20卷

作者： Karafasoulis, K. Kaissas, I. Papadimitropoulos, C. Potiriadis, K. Lambropoulos, C. P. Hellen Army Acad Dept Nat Sci & Applicat Evelpidon Ave Vari Attikis 16673 Greece Aristotle Univ Thessaloniki Fac Engn Dept Elect & Comp Engn Egnatia 54124 Thessaloniki Greece Natl & Kapodistrian Univ Athens Dept Aerosp Sci & Technol Psachna Evia 34400 Greece Greek Atom Energy Commiss Patriarxou Grigoriou & Neapoleos Aghia Paraskevi Greece

Coded Aperture 7-cameras have been extensively used in applications ranging from astrophysics to nuclear medicine for imaging radioactive source distributions. These devices allow the identification of the direction of 7-emitters by analyzing the shadow patterns projected onto pixelated detectors. In this work, we propose a novel approach based on Convolutional Neural Networks (CNNs) for accurately localizing radioactive sources in 3D using one coded aperture gamma camera. The CNN is trained using simulated shadowgrams generated by a custom simulation tool, with sources placed at various positions within the near-field, ranging from 20 cm to 120 cm from the detector. Unlike previous methods that focused on estimating angular coordinates, our model also accurately estimates the distance of the source, achieving a distance estimation accuracy of 10 mm, in addition to determining the polar and azimuthal angles. This capability is particularly relevant for medical imaging applications, where precise localization of radioactive sources is crucial. The results of our study demonstrate the potential of CNN-based algorithms in improving the accuracy and reliability of single-detector systems in near-field radioactive source localization.

关键词： data processing methods Gamma camera, SPECT, PET PET/CT, coronary CT angiography (CTA) Image reconstruction in medical imaging Medical-image reconstruction methods and algorithms, computer-aided software

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Feature extraction on the TRD readout FPGA with HLS in the mCBM experiment

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JOURNAL OF INSTRUMENTATION 2025年第3期20卷 C03047-C03047页

作者： Schledt, D. Blume, C. Kebschull, U. Goethe Univ Frankfurt Max Von Laue Str 1 D-60438 Frankfurt Germany

The CBM experiment uses a free streaming DAQ with interaction rates up to 10MHz resulting in data rates, which exceed storage capabilities, necessitating online processing. The SPADIC ASIC of the CBM-TRD provides hit messages with oscilloscope-like sampling of the detector data, encoding valuable information. To speed up data unpacking and computing time, feature extraction is moved to the readout FPGA. In the mCBM experiment this approach is tested, demonstrating the benefits of HLS and C++ template programming for algorithm development. Results show resolution improvements and significant reductions in data volume and unpacking speed at the computing cluster.

关键词： data processing methods data acquisition concepts Digital signal processing (DSP) Pattern recognition, cluster finding, calibration and fitting methods

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