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Circumferential current field testing system with TMR sensor array for non-contact detection and estimation of cracks on power plant piping

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SENSORS AND ACTUATORS A-PHYSICAL 2017年 263卷 542-553页

作者： Yuan, Xin'an Li, Wei Chen, Guoming Yin, Xiaokang Ge, Jiuhao China Univ Petr East China Ctr Offshore Equipment Safety Technol Qingdao 266580 Peoples R China

Piping is a critical component in power plant, which is subject to surface thermal fatigue cracks. Due to the high temperature and the presence of coatings, conventional non-destructive testing methods are unsuitable to detect the thermal fatigue cracks on power plant piping. This paper presents a novel circumferential current field testing system for the non-contact detection and estimation of cracks on power plant piping. A 3D dynamic finite element method model is developed to obtain the characteristic signals and optimize the inducing frequency. The circumferential uniform current field testing system with tunnel magneto resistance (TMR) sensor array is set up and the crack detection experiments are carried out. The results show that the circumferential current field testing system with TMR, sensor array can achieve non-contact, visual and efficient detection of cracks on power plant piping in a one pass scan. The depth and length of cracks can be estimated by the proposed calibration method. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Circumferential current field testing TMR detection and estimation Cracks Power plant piping

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Development of a model for detection and estimation of depth of shallow buried non-metallic landmine at microwave X-band frequency

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PROGRESS IN ELECTROMAGNETICS RESEARCH-PIER 2008年 79卷 225-250页

作者： Tiwari, K. C. Singh, D. Arora, M. K. Indian Inst Technol Dept Civil Engn Roorkee 247665 Uttar Pradesh India Indian Inst Technol Dept Elect & Comp Engn Roorkee 247665 Uttar Pradesh India

detection and estimation of depth of shallow buried landmines using microwave remote sensing is a complex and computationally intensive task. Despite a lot of research to correctly locate and identify the buried landmines, and to estimate its depth using microwave remote sensing data which is essential for demining with minimal risk, a lot of uncertainties still exist. Therefore in this paper, an extensive study using a ground based X-band scatterometer for detection of shallow buried landmine and estimation of its depth has been carried out. An experimental setup consisting of a ground based scatterometer operating in microwave X-band(10 GHz, 3 cm) has been used to generate backscatter data in a grid of 24 x 24 and a series of experiments under laboratory conditions conducted using dummy landmines (without explosives) buried to different depths up to 10 cm in dry smooth sand. It is difficult to detect the buried landmine by visual inspection of the raw data;therefore a novel approach by fusion of image processing techniques with electromagnetic (EM) analysis has been evolved for detection and estimation of depth of the landmine. The raw data generated through the experiments was processed through a series of image processing steps and a region of interest segmented using Otsu and maximum entropy based thresholding methods for further processing. A detection figure test has been proposed at this stage to reduce false alarms. Genetic algorithm (GA) with an electromagnetic (EM) model fusion has been proposed to estimate the depth after segmenting a suspected region containing the mine. The main advantage of the proposed model is that it does not have any requirement of separate training and test data set to train the optimizer and validate the results. Analyses of the results indicate that it is possible to segment suspected region of interest containing the landmines in data obtained in microwave X-band using either of the two thresholding methods. The depth of burie

关键词： .remote sensing backscatter depths explosives scatterometer using microwave detection and estimation IIT Roorkee buried landmines

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Optimal quadratic detection and estimation using generalized joint signal representations

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 1996年第12期44卷 3031-3043页

作者： Sayeed, AM Jones, DL UNIV ILLINOIS COORDINATED SCI LAB URBANA IL 61801 USA

Time-frequency analysis has recently undergone significant advances in two main directions: statistically optimized methods that extend the scope of tine-frequency-based techniques from merely exploratory data analysis to more quantitative application and generalized joint signal representations that extend time-frequency-based methods to a richer class of nonstationary signals. This paper fuses the two advances by developing optimal detection and estimation techniques based on generalized joint signal representations. By generalizing the statistical methods developed for time-frequency representations to arbitrary joint signal representations, this paper develops a unified theory applicable to a wide variety of problems in nonstationary statistical signal processing.

关键词： .estimation techniques TFR undergone time-frequency representations nonstationary signals exploratory data optimal detection detection and estimation Optimal Quadratic Generalized Joint Signal

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Optimal fault detection and estimation: a unified scheme and least squares solutions

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IFAC-PapersOnLine 2018年第24期51卷 465-472页

作者： Ding, S.X. University of Duisburg-Essen Duisburg47057 Germany

The motivation and the objective of this work are to approach fault detection and estimation issues in a unified framework. It is demonstrated that least squares techniques can be applied to solve basic fault detection and estimation problems for static and dynamic, statistic/stochastic and deterministic, linear and nonlinear processes. The solutions are optimum in the sense of maximizing fault detectability with false alarm rate lower than a predefined level. © 2018

关键词： Fault detection estimation Factorization detection and estimation False alarm rate Inner outer factorization Least squares estimation Least squares solutions Least squares techniques Nonlinear process Unified framework

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LFM Signal detection and estimation Based On Sparse Representation 49

LFM Signal Detection and Estimation Based On Sparse Represen...

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49th Annual Conference on Information Sciences and Systems (CISS)

作者： Joneidi, Mohsen Zaeemzadeh, Alireza Rezaeifar, Shideh Abavisani, Mahdi Rahnavard, Nazanin Univ Cent Florida Dept Elect Engn & Comp Sci Orlando FL 32816 USA Ferdowsi Univ Mashhad Dept Elect Engn Mashhad Iran

ISBN: (纸本)9781479984282

This paper presents a novel approach for detection and estimation of fundamental parameters of linear frequency modulation (LFM) signals, i.e., the initial frequency and Chirp rate. The proposed approach is based on sparse representation of noisy input signals over two specific dictionaries, each designed for finding a parameter of LFM signal. Moreover, an iterative framework is proposed for simultaneous sparse representation over the two dictionaries. Experimental results demonstrate that the presented method is comparable with the optimum transform for LFM signal estimation, Wigner-Hough, and furthermore, has significantly higher speed.

关键词： LFM signals detection and estimation sparse coding parametric dictionary

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A Novel Imaging-Based Target detection and Parameter estimation Scheme for Airborne Multichannel Circular Stripmap SAR

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2023年 61卷

作者： Song, Chong Wang, Bingnan Xiang, Maosheng Shi, Ruihua Dong, Qinghai Wang, Zhongqi Wang, Yachao Sun, Xiaofan Song, Lukai Chinese Acad Sci Aerosp Informat Res Inst Natl Key Lab Microwave Imaging Technol Beijing 100094 Peoples R China Univ Chinese Acad Sci Sch Elect Elect & Commun Engn Beijing 100049 Peoples R China Beijing Inst Spacecraft Syst Engn Beijing 100094 Peoples R China Shandong Prov Inst Land Surveying & Mapping Qingdao 250102 Shandong Peoples R China

Airborne multichannel circular stripmap synthetic aperture radar (CSSAR)-ground moving target indication (GMTI) has drawn increasing attention in wide-area surveillance, reconnaissance, and traffic monitoring due to its short revisit times. In this article, a novel scheme for CSSAR-GMTI systems is proposed to offer high-resolution focusing of moving targets and enable efficient detection and accurate parameter estimation, which are ensured by integrating moving target imaging with a space-time adaptive processing (STAP) clutter suppression step. The presented scheme develops a target imaging algorithm that forms SAR images focused on a particular 2-D motion parameter to maximize target signal energy and recover its high resolution. Moreover, benefiting from the suitable phase compensation designed in the 2-D frequency domain, moving targets can finally be properly focused in the SAR image without displacement, and their parameters can be uniquely determined. Experiments on an emulated radar dataset are conducted to validate the effectiveness of the proposed scheme.

关键词： Radar imaging Imaging Clutter Radar polarimetry Synthetic aperture radar Training data Radar cross-sections Circular stripmap synthetic aperture radar (CSSAR) detection and estimation ground moving target indication (GMTI)

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PDF approximations to estimation and detection in time-correlated alpha-stable channels

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SIGNAL PROCESSING 2017年 133卷 97-106页

作者： Hashemifard, Zeinab Amindavar, Hamidreza Amirkabir Univ Technol Dept Elect Engn Tehran Iran

This paper considers the estimation and detection problems for statistically dependent heavy-tailed signals with no closed-form probability density function (PDF). We propose two parametric PDF approximations for symmetric alpha-stable (S alpha S) distribution to be utilized in approaches based on the Maximum likelihood (ML) criterion. The nonlinear least square (LS) and curve fitting are used to compute parameters of the slew formulations which are functions of the characteristic exponent. Moreover, we study binary signal detection in channels with time-dependent heavy-tailed noise modeled by SaS distribution and first order autoregressive (AR(1)) process. Using the novel PDF approximations in the ML estimator, an algorithm for model parameters estimation of the noise is initially developed. Then, new suboptimal receivers are designed through the use of the new PDF formulations and parameter estimates. Numerical results demonstrate the superiority of the proposed approximations over the existing formulations, and also good accuracy for the estimation algorithm. Additionally, it is shown that the proposed detectors operate near optimal receiver and also outperform the other suboptimal detectors, especially when a is small.

关键词： detection and estimation Sub-optimum detector Alpha-stable distribution Approximation Impulsive noise

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Hyperbolic frequency modulated signal analysis using Mellin transform

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SIGNAL PROCESSING 2025年 234卷

作者： Zhang, Liang Du, Qinglei Peng, Ruihui Zhang, Xiangyu Chen, Hui Air Force Early Warning Acad Wuhan 430019 Peoples R China Harbin Engn Univ Harbin 266000 Peoples R China Naval Aviat Univ Qingdao 266041 Peoples R China

Hyperbolic frequency modulated (HFM) signal, an optimal Doppler tolerant waveform, has widespread application in radar and sonar. Interestingly, the theoretical waveform is very close to those actually used by bats. For the problems of detection and estimation of the HFM signal, an analysis method in the scale domain is proposed, firstly searching the peaks in a delay-scale matrix obtained by calculating Mellin transform (MT) of the signal with different artificial delays, and then estimating signal parameters, according to peak position. To find the peaks, a constant false alarm rate (CFAR) detector commonly used in radar signal processing is employed. Since MT is a linear transform, the multi-component HFM signal can be analyzed by the proposed method. In addition, the computational complexity is not very high, as MT can be numerically implemented by the fast Fourier transform. Using the simulated HFM signals and the bat echolocation call, the detection and estimation performance of the proposed method is fully verified.

关键词： Hyperbolic frequency modulated signal detection and estimation Mellin transform Fast Fourier transform Zero-padding Bat echolocation call

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Power Factor estimation of Distributed Energy Resources Using Voltage Magnitude Measurements

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Journal of Modern Power Systems and Clean Energy 2021年第4期9卷 859-869页

作者： Samuel Talkington Santiago Grijalva Matthew J.Reno School of Electrical and Computer Engineering Georgia Institute of TechnologyAtlantaGA 30318USA Electric Power Systems Research Department Sandia National LaboratoriesAlbuquerqueNM 87123USA

This paper presents a new method for the estimation of the injection state and power factor of distributed energy resources (DERs) using voltage magnitude measurements only. A physics-based linear model is used to develop estimation heuristics for net injections of real and reactive power at a set of buses under study, allowing a distribution engineer to form a robust estimate for the operating state and the power factor of the DER at those buses. The method demonstrates and exploits a mathematical distinction between the voltage sensitivity signatures of real and reactive power injections for a fixed power system model. Case studies on various test feeders for a model of the distribution circuit and statistical analyses are presented to demonstrate the validity of the estimation method. The results of this paper can be used to improve the limited information about inverter parameters and operating state during renewable planning, which helps mitigate the uncertainty inherent in their integration.

关键词： Decentralized power system control detection and estimation power factor sparse approximation

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Oil spill detection: imaging system modeling and advanced image processing using optimized SDC algorithm

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SIGNAL IMAGE AND VIDEO PROCESSING 2014年第8期8卷 1405-1419页

作者： Etellisi, Ehab A. Deng, Yiming Univ Colorado Dept Elect Engn Denver CO 80217 USA Univ Colorado Dept Bioengn Denver CO 80217 USA Univ Colorado Colorado Translat Res Imaging Ctr Denver CO 80217 USA

Oil spill on the sea surface might happen without any previous caution and is seen relatively often. Efficient and effective oil spill monitoring and detection can reduce response time, minimize remediation costs and limit dangerous impacts to the environment. An innovative satellite-based oil pollution detection framework is demonstrated in this paper, including satellite imaging system modeling-communication link configuration, noise model for image transmission and preprocessing. Finally, an optimized sequential detection of change-based image object detection algorithm is proposed to detect oil spill on the ocean surface from the enhanced remote sensing data. Moderate resolution imaging spectroradiometer images of the Gulf of Mexico accident from NASA between May and June 2010 are adopted for testing in our framework. The results of this research show that the proposed algorithms can effectively distinguish the spill covering vast areas of the marine environment even with severe additive noise and have good separation properties against complex signatures, such as the vicinity to the irregular coast or foggy and cloudy weather conditions.

关键词： Oil spill detection Sequential detection of change Satellite imaging systems detection and estimation

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