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source separation of Diesel Engine Vibration Based on the Empirical Mode Decomposition and Independent Component Analysis

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Chinese Journal of Mechanical Engineering 2012年第3期25卷 557-563页

作者： DU Xianfeng LI Zhijun BI Fengrong ZHANG Junhong WANG Xia SHAO Kang State Key Laboratory of Engines Tianjin UniversityTianjin 300072China

Vibration signals from diesel engine contain many different components mainly caused by combustion and mechanism operations,several blind source separation techniques are available for decomposing the signal into its components in the case of multichannel measurements,such as independent component analysis（ICA）.However,the source separation of vibration signal from single-channel is *** order to study the source separation from single-channel signal for the purpose of source extraction,the combination method of empirical mode decomposition（EMD） and ICA is proposed in diesel engine signal *** performance of the described methods of EMD-wavelet and EMD-ICA in vibration signal application is compared,and the results show that EMD-ICA method outperforms the other,and overcomes the drawback of ICA in the case of single-channel *** independent source signal components can be separated and identified effectively from one-channel measurement by ***,EMD-ICA improves the extraction and identification abilities of source signals from diesel engine vibration measurements.

关键词： empirical mode decomposition independent component analysis source separation single-channel signal

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Determination of urine-derived odorous compounds in a source separation sanitation system

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Journal of Environmental Sciences 2017年第2期29卷 240-249页

作者： Bianxia Liu Apostolos Giannis Ailu Chen Jiefeng Zhang Victor W.C.Chang Jing-Yuan Wang .Residues and Resource Reclamation Centre(R3C) Nanyang Environment and Water Research InstituteNanyang Technological University1 Cleantech LoopCleanTech OneSingapore 637141Singapore School of Civil and Environmental Engineering Nanyang Technological University50 Nanyang AvenueSingapore 639798Singapore

source separation sanitation systems have attracted more and more attention ***, separate urine collection and treatment could induce odor issues, especially in large scale application. In order to avoid such issues, it is necessary to monitor the odor related compounds that might be generated during urine storage. This study investigated the odorous compounds that emitted from source-separated human urine under different hydrolysis conditions. Batch experiments were conducted to investigate the effect of temperature, stale/fresh urine ratio and urine dilution on odor emissions. It was found that ammonia, dimethyl disulfide, allyl methyl sulfide and 4-heptanone were the main odorous compounds generated from human urine, with headspace concentrations hundreds of times higher than their respective odor thresholds. Furthermore, the high temperature accelerated urine hydrolysis and liquid–gas mass transfer, resulting a remarkable increase of odor emissions from the urine solution. The addition of stale urine enhanced urine hydrolysis and expedited odor emissions. On the contrary, diluted urine emitted less odorous compounds ascribed to reduced concentrations of odorant precursors. In addition,this study quantified the odor emissions and revealed the constraints of urine source separation in real-world applications. To address the odor issue, several control strategies are recommended for odor mitigation or elimination from an engineering perspective.

关键词： Odor emissions Volatile organic compounds(VOCs) Urine hydrolysis source separation Gas chromatography mass spectrometry(GC–MS)

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Novel blind source separation algorithm using Gaussian mixture density function

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Journal of Systems Engineering and Electronics 2004年第4期15卷 710-715页

作者： KongWei YangJie ZhouYue InstituteofImageProcessing&PatternRecognition ShanghaiJiaotongUniversityShanghai200030P.R.China

The blind source separation (BSS) is an important task for numerous applications in signal processing, communications and array processing. But for many complex sources blind separation algorithms are not efficient because the probability distribution of the sources cannot be estimated accurately. So in this paper, to justify the ME(maximum enteropy) approach, the relation between the ME and the MMI(minimum mutual information) is elucidated first. Then a novel algorithm that uses Gaussian mixture density to approximate the probability distribution of the sources is presented based on the ME approach. The experiment of the BSS of ship-radiated noise demonstrates that the proposed algorithm is valid and efficient.

关键词： Noise Entropy Mutual information source separation Vectors Algorithm design and analysis Transforms

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Non-Negative Minimum Volume Factorization (NMVF) for Hyperspectral Images (HSI) Unmixing: A Hybrid Approach

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Computers, Materials & Continua 2022年第11期73卷 3705-3720页

作者： Kriti Mahajan Urvashi Garg Nitin Mittal Yunyoung Nam Byeong-Gwon Kang Mohamed Abouhawwash Department of Computer Science and Engineering Chandigarh UniversityPunjab140413India Skill Faculty of Science and Technology Shri Vishwakarma Skill UniversityPalwal121102India Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)College of EngineeringMichigan State UniversityEast LansingMI48824USA

Spectral unmixing is essential for exploitation of remotely senseddata of Hyperspectral Images (HSI). It amounts to the identification of a position of spectral signatures that are pure and therefore called end members andtheir matching fractional, draft rules abundances for every pixel in HSI. Thispaper aims to unmix hyperspectral data using the minimal volume methodof elementary scrutiny. Moreover, the problem of optimization is solved bythe implementation of the sequence of small problems that are constrainedquadratically. The hard constraint in the final step for the abundance fractionis then replaced with a loss function of hinge type that accounts for outlinersand noise. Existing algorithms focus on estimating the endmembers (Ems)enumeration in a sight, discerning of spectral signs of EMs, besides assessmentof fractional profusion for every EM in every pixel of a sight. Nevertheless, allthe stages are performed by only a few algorithms in the process of hyperspectral unmixing. Therefore, the Non-negative Minimum Volume Factorization(NMVF) algorithm is further extended by fusing it with the nonnegativematrix of robust collaborative factorization that aims to perform all the threeunmixing chain steps for hyperspectral images. The major contributions ofthis article are in this manner: (A) it performs Simplex analysis of minimum volume for hyperspectral images with unsupervised linear unmixing isemployed. (B) The simplex analysis method is configured with an exaggeratedform of the elementary which is delivered by vertical component analysis(VCA). (C) The inflating factor is chosen carefully inactivating the constraintsin a large majority for relating to the source fractions abundance that speedsup the algorithm. (D) The final step is making simplex analysis method robustto outliners as well as noise that replaces the profusion element positivity hardrestraint by a hinge kind soft restraint, preserving the local minima havinggood quality. (E) The matrix factorizati

关键词： Hyperspectral Imaging minimum volume simplex source separation end member extraction non-negative minimum volume factorization(NMVF) endmembers(EMs)

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Blind separation of sources in nonlinear convolved mixture based on a novel network

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Journal of Systems Engineering and Electronics 2004年第4期15卷 497-501页

作者： HuYing YangJie Shenli InstituteofImageProcessingandPatternRecognition ShanghaiJiaotongUniversityShanghai200030P.R.China

Blind separation of independent sources from their nonlinear convoluted mixtures is a more realistic problem than from linear ones. A solution to this problem based on the Entropy Maximization principle is presented. First we propose a novel two-layer network as the de-mixing system to separate sources in nonlinear convolved mixture. In output layer of our network we use feedback network architecture to cope with convoluted mixtures. Then we derive learning algorithms for the two-layer network by maximizing the information entropy. Based on the comparison of the computer simulation results, it can be concluded that the proposed algorithm has a better nonlinear convolved blind signal separation effect than the H.H. Y's algorithm.

关键词： Entropy Delay Algorithm design and analysis Signal processing algorithms source separation Atmospheric modeling

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Empirical Study on Factors Influencing Residents’ Behavior of Separating Household Wastes at source

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Chinese Journal of Population,Resources and Environment 2007年第2期5卷 20-27页

作者： Murray Haight School of Planning Environmental Studies University of Waterloo Waterloo Canada

source separation is the basic premise for making effective use of household wastes. In eight cities of China, how- ever, several pilot projects of source separation finally failed because of the poor participation rate of residents. In order to solve this problem, identifying those factors that influence residents’ behavior of source separation becomes crucial. By means of questionnaire survey, we conducted descriptive analysis and ex- ploratory factor analysis. The results show that trouble-feeling, moral notion, environment protection, public education, environment value and knowledge deficiency are the main factors that play an important role for residents in deciding to separate their household wastes. Also, according to the contribution percentage of the six main factors to the total behavior of source separation, their influencing power is analyzed, which will provide suggestions on household waste management for policy makers and decision makers in China.

关键词： source separation influencing factors behavior household waste management

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A New Method for Obtaining the Heart Sound Signals source Components

A New Method for Obtaining the Heart Sound Signals Source Co...

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第30届中国控制与决策会议

作者： Cheng Xiefeng Dai Shicheng Li Yunyi Shan Xu Liu Jia College of Electronic Science and engineering Nanjing University of Posts and Telecommunications

This paper introduces a new method which using synchronized acquisition of four-channel heart sounds to acquire a heart sound signal source. First of all, we introduces the generation mechanism of heart sounds in detail, and puts forward that the heart sound signals have the characteristics of "time-sharing". Then, according to the basic characteristics of heart sound transmission in the thoracic cavity, we model the mathematical process of heart sound transmission in the thoracic, and propose a mathematical model about heart sound transmission. Finally, according to the mathematical characteristics of the model and the main feature of time-sharing in the heart sound signal, we propose a source separation method for the four-channel heart sound signal in order to obtain the source of heart sounds. The purpose of this algorithm is to eliminate the interaction between simultaneous acquisition of four-channel heart sound signal, which makes the acquired heart sound signal show the characteristics of time difference, energy concentration and low frequency of the spectrum so that we can obtain the source composition of heart sound signal. The experimental results show that the algorithm used in this paper can better obtain single heart sound source components, and single heart sound source components include four major components of the first heart sound（S1）, the A and P components of the second heart sound（S2）, which have a positive meaning in analyzing the original composition and production mechanism of the heart sound.

关键词： Heart sounds source components Time-sharing generation source separation

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