The satellite-based automatic identification system (AIS) receiver has to encounter the frequency offset caused by the Doppler effect and the oscillator instability. This paper proposes a non-coherent sequence detecti...The satellite-based automatic identification system (AIS) receiver has to encounter the frequency offset caused by the Doppler effect and the oscillator instability. This paper proposes a non-coherent sequence detection scheme for the satellite-based AIS signal transmitted over the white Gaussian noise channel. Based on the maximum likelihood estimation and a Viterbi decoder, the proposed scheme is capable of tolerating a frequency offset up to 5% of the symbol rate. The complexity of the proposed scheme is reduced by the state-complexity reduction, which is based on per-survivor processing. Simulation results prove that the proposed non-coherent sequence detection scheme has high robustness to frequency offset compared to the relative scheme when messages collision exists.展开更多
Aiming at the potential presence of mixing automatic identification system(AIS) signals,a new demodulation scheme was proposed for separating other interfering signals in satellite systems.The combined iterative cross...Aiming at the potential presence of mixing automatic identification system(AIS) signals,a new demodulation scheme was proposed for separating other interfering signals in satellite systems.The combined iterative cross-correlation demodulation scheme,referred to as CICCD,yielded a set of single short signals based on the prior information of AIS,after the frequency,code rate and modulation index were estimated.It demodulates the corresponding short codes according to the maximum peak of cross-correlation,which is simple and easy to implement.Numerical simulations show that the bit error rate of proposed algorithm improves by about 40% compared with existing ones,and about 3 dB beyond the standard AIS receiver.In addition,the proposed demodulation scheme shows the satisfying performance and engineering value in mixing AIS environment and can also perform well in low signal-to-noise conditions.展开更多
Here we present a simple yet effective gas chromatography-mass spectrometry(GC-MS)identification approach for the detection of heteroatom-containing compounds(HACCs)in petroleum fractions.The MS/AMDIS(Automated Mass S...Here we present a simple yet effective gas chromatography-mass spectrometry(GC-MS)identification approach for the detection of heteroatom-containing compounds(HACCs)in petroleum fractions.The MS/AMDIS(Automated Mass Spectral Deconvolution and Identification System)program was used to identify parts per million(ppm)HACC concentrations in petroleum fractions in place of traditional techniques(extraction and standard injection).Polycyclic aromatic sulfur heterocycles(S-PAHs)were used as model compounds to confirm the validity of the AMDIS identifiers,which were compared with extracted results using the off-line X-calibur software.AMDIS was able to identify ppm concentrations of S-PAHs in oil condensate.There was good agreement between experimental and AMDIS identification results for S-PAHs in oil condensate.AMDIS was also used to detect nitrogen-containing compounds(NCCs)and alkylphenols in oil condensate.Our results confirmed the presence of 2-methylbenzothiazole,carbazole,and 2,4-ditertbutyl phenol.In a crude oil sample,AMDIS identification of m/z=191 biomarkers wa s consistent with empirical results.Therefore,AMDIS can help to reduce the number of experimental steps in identification protocols.展开更多
A new reaction system to determine nonlinear chemical fingerprint(NCF)and its use in identification method based on double reaction system was researched.Panax ginsengs,such as ginseng,American ginseng and notoginseng...A new reaction system to determine nonlinear chemical fingerprint(NCF)and its use in identification method based on double reaction system was researched.Panax ginsengs,such as ginseng,American ginseng and notoginseng were identified by the method.The NCFs of the three samples of Panax ginsengs were determined through two nonlinear chemical systems,namely system 1 consisting of sample components,H2SO4,MnSO4,NaBrO3,acetone and the new system,system 2 consisting of sample components,H2SO4,(NH4)4Ce(SO4)2,NaBrO3 and citric acid.The comparison between the results determined through systems 1 and 2 shows that the speed to determine NCF through system 2 is much faster than that through system 1;for systems 1 and 2,the system similarities of the same kind of samples are≥98.09%and 99.78%,respectively,while those of different kinds of samples are≤63.04%and 86.34%,respectively.The results to identify the kinds of some samples by system similarity pattern show that both the accuracies of identification methods based on single system 1 and 2 are≥95.6%,and the average values are 97.1%and 96.3%,respectively;the accuracy of the method based on double system is≥97.8%,and the average accuracy is 99.3%.The accuracy of the method based on double system is higher than that based on any single system.展开更多
Including servo valve, hydraulic cylinder, mill and sensor and ignoring nonlinear factors, the linear dynamic model of hydraulic automatic gage control(HAGC) system of a temper rolling mill was theoretically derived. ...Including servo valve, hydraulic cylinder, mill and sensor and ignoring nonlinear factors, the linear dynamic model of hydraulic automatic gage control(HAGC) system of a temper rolling mill was theoretically derived. The order of the model is 4/4, and can be reduced to 2/2. Based on modulating functions method, utilizing numerical integration, we constructed the equivalent identification model of HAGC, and the least square estimation algorithm was established. The input and output data were acquired on line at temper rolling mill in Shangshai Baosteel Group Corporation, and the continuous time model of HAGC system was estimated with the proposed method. At different modulating window intervals, the estimated parameters changed remarkably. When the frequency bandwidth of modulating filter matches that of estimated system, the parameters can be estimated accurately. Finally, the dynamic model of the HAGC was obtained and validated based on the spectral analysis result.展开更多
This work is concerned with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method ...This work is concerned with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system. A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model. Next, a computationally efficient nonlinear model predictive control algorithm(MGPC) is developed to deal with constrained problem of MIMO system. The identification process and performance of MGPC are shown. Numerical results about a polymerization reactor validate the effectiveness of the proposed method and the comparisons show that MGPC has a better performance than QDMC and basic GPC.展开更多
Strategic management of equipment system develop-ment must attach importance to effective strategic risk manage-ment.Aiming at the identification of strategic risk of equipment system development,firstly,the source of...Strategic management of equipment system develop-ment must attach importance to effective strategic risk manage-ment.Aiming at the identification of strategic risk of equipment system development,firstly,the source of strategic risk of equip-ment system development is analyzed and classified.Based on this,a causal loop diagram of strategic risk of equipment sys-tem development based on system dynamics is established.The system dynamics analysis software Vensim PLE is used to carry out the risk influencing factors analysis,risk consequences ana-lysis,risk feedback loop identification and corresponding pre-control measures,and achieves a good risk identification effect.展开更多
Based on system identification theory and FWD testing data, the effect of thickness error on backcalculating pavement layer moduli is studied and the method of singular value decomposition (SVD) is presented to solve ...Based on system identification theory and FWD testing data, the effect of thickness error on backcalculating pavement layer moduli is studied and the method of singular value decomposition (SVD) is presented to solve the morbidity problem of sensitivity matrix in this paper.The results show that the thickness error has great effects on the backcalculated pavement layer moduli. The error of backcalculated moduli can be controlled within the range of ±15% by limiting the thickness error within the range of ±5%.展开更多
A higher-order cumulant-based weighted least square（HOCWLS） and a higher-order cumulant-based iterative least square（HOCILS） are derived for multiple inputs single output（MISO） errors-in-variables（EIV） systems...A higher-order cumulant-based weighted least square（HOCWLS） and a higher-order cumulant-based iterative least square（HOCILS） are derived for multiple inputs single output（MISO） errors-in-variables（EIV） systems from noisy input/output data. Whether the noises of the input/output of the system are white or colored, the proposed algorithms can be insensitive to these noises and yield unbiased estimates. To realize adaptive parameter estimates, a higher-order cumulant-based recursive least square（HOCRLS） method is also studied. Convergence analysis of the HOCRLS is conducted by using the stochastic process theory and the stochastic martingale theory. It indicates that the parameter estimation error of HOCRLS consistently converges to zero under a generalized persistent excitation condition. The usefulness of the proposed algorithms is assessed through numerical simulations.展开更多
Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structur...Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structure by selecting important inputs of the system is studied. Firstly, a simplified two stage fuzzy curves method is proposed, which is employed to sort all possible inputs by their relevance with outputs, select the important input variables of the system and identify the structure.Secondly, in order to reduce the complexity of the model, the standard fuzzy c-means clustering algorithm and the recursive least squares algorithm are used to identify the premise parameters and conclusion parameters, respectively. Then, the effectiveness of IVS is verified by two well-known issues. Finally, the proposed identification method is applied to a realistic variable load pneumatic system. The simulation experiments indi cate that the IVS method in this paper has a positive influence on the approximation performance of the Takagi-Sugeno(T-S) fuzzy modeling.展开更多
The problem of how to identify the piecewise affine system is studied in this paper, where this considered piecewise affine system is a special nonlinear system. The reason why it is not easy to identify this piecewis...The problem of how to identify the piecewise affine system is studied in this paper, where this considered piecewise affine system is a special nonlinear system. The reason why it is not easy to identify this piecewise affine system is that each separated region and each unknown parameter vector are all needed to be determined simultaneously. Then, firstly, in order to achieve the identification goal, a multi-class classification process is proposed to determine each separated region. As the proposed multi-class classification process is the same with the classical data clustering strategy, the multi-class classification process can combine the first order algorithm of convex optimization, while achieving the goal of the classification process. Secondly, a zonotope parameter identification algorithm is used to construct a set, which contains the unknown parameter vector. In this zonotope parameter identification algorithm, the strict probabilistic description about the external noise is relaxed, and each unknown parameter vector is also identified. Furthermore, this constructed set is consistent with the measured output and the given bound corresponding to the noise. Thirdly, a sufficient condition about guaranteeing our derived zonotope not growing unbounded with iterations is formulated as an explicit linear matrix inequality. Finally, the effectiveness of this zonotope parameter identification algorithm is proven through a simulation example.展开更多
A dynamic genetic algorithms based on numeric encoding is proposed and its application in system identification is discussed. Simulation shows that the introduction of both numeric encoding and dynamic mutation can ef...A dynamic genetic algorithms based on numeric encoding is proposed and its application in system identification is discussed. Simulation shows that the introduction of both numeric encoding and dynamic mutation can effectively improve the accuracy and speed of searching for the optimum. It also show that the improved Genetic algorithm can identify time delay and parameters of the plant at the same time and converge to globle optimization.展开更多
The observation error model of the underwater acous-tic positioning system is an important factor to influence the positioning accuracy of the underwater target.For the position inconsistency error caused by consideri...The observation error model of the underwater acous-tic positioning system is an important factor to influence the positioning accuracy of the underwater target.For the position inconsistency error caused by considering the underwater tar-get as a mass point,as well as the observation system error,the traditional error model best estimation trajectory(EMBET)with little observed data and too many parameters can lead to the ill-condition of the parameter model.In this paper,a multi-station fusion system error model based on the optimal polynomial con-straint is constructed,and the corresponding observation sys-tem error identification based on improved spectral clustering is designed.Firstly,the reduced parameter unified modeling for the underwater target position parameters and the system error is achieved through the polynomial optimization.Then a multi-sta-tion non-oriented graph network is established,which can address the problem of the inaccurate identification for the sys-tem errors.Moreover,the similarity matrix of the spectral cluster-ing is improved,and the iterative identification for the system errors based on the improved spectral clustering is proposed.Finally,the comprehensive measured data of long baseline lake test and sea test show that the proposed method can accu-rately identify the system errors,and moreover can improve the positioning accuracy for the underwater target positioning.展开更多
Aimed at the problem of classification of non-hydrocarbons of crude oil, the theoretical standpoint that the polarity of a compound depends on the whole structure and composition of molecule instead of a kind of heter...Aimed at the problem of classification of non-hydrocarbons of crude oil, the theoretical standpoint that the polarity of a compound depends on the whole structure and composition of molecule instead of a kind of heteroatom or its functional group was presented. A method was established for the systematically structural identification of nitric compounds in crude oil. The pre-fractionation of a crude oil sample into 7 fractions was performed by di- adsorption column chromatography with neutral aluminum oxide and silica gel. Subsequently, the individual components were obtained by using capillary column gas chromatography, and the types of compounds were detected by a mass spectrometer. In combination with a chemometric resolution, the compounds of fraction were further identified. This method can relieve the difficulty of classical analysis in identifying those species with very low contents or without being completely separated. The structures of 168 nitric compounds in a crude oil sample were determined by this method.展开更多
In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis...In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning actuator.The static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,respectively.This model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is proposed.Experimental results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 ms.In the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 Hz.The proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.展开更多
Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint featur...Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint features to a data-driven technique and fur-ther reduces the adaptability of the technique to other datasets. To address this issue, the mechanism how the phase noise of high-frequency oscillators and the nonlinearity of power ampli-fiers affect the kurtosis of communication signals is investigated. Mathematical models are derived for intentional modulation (IM) and unintentional modulation (UIM). Analysis indicates that the phase noise of high-frequency oscillators and the nonlinearity of power amplifiers affect the kurtosis frequency and amplitude, respectively. A novel SEI method based on frequency and ampli-tude of the signal kurtosis (FA-SK) is further proposed. Simula-tion and real-world experiments validate theoretical analysis and also confirm the efficiency and effectiveness of the proposed method.展开更多
Modern warfare demands weapons capable of penetrating substantial structures,which presents sig-nificant challenges to the reliability of the electronic devices that are crucial to the weapon's perfor-mance.Due to...Modern warfare demands weapons capable of penetrating substantial structures,which presents sig-nificant challenges to the reliability of the electronic devices that are crucial to the weapon's perfor-mance.Due to miniaturization of electronic components,it is challenging to directly measure or numerically predict the mechanical response of small-sized critical interconnections in board-level packaging structures to ensure the mechanical reliability of electronic devices in projectiles under harsh working conditions.To address this issue,an indirect measurement method using the Bayesian regularization-based load identification was proposed in this study based on finite element(FE)pre-dictions to estimate the load applied on critical interconnections of board-level packaging structures during the process of projectile penetration.For predicting the high-strain-rate penetration process,an FE model was established with elasto-plastic constitutive models of the representative packaging ma-terials(that is,solder material and epoxy molding compound)in which material constitutive parameters were calibrated against the experimental results by using the split-Hopkinson pressure bar.As the impact-induced dynamic bending of the printed circuit board resulted in an alternating tensile-compressive loading on the solder joints during penetration,the corner solder joints in the edge re-gions experience the highest S11 and strain,making them more prone to failure.Based on FE predictions at different structural scales,an improved Bayesian method based on augmented Tikhonov regulariza-tion was theoretically proposed to address the issues of ill-posed matrix inversion and noise sensitivity in the load identification at the critical solder joints.By incorporating a wavelet thresholding technique,the method resolves the problem of poor load identification accuracy at high noise levels.The proposed method achieves satisfactorily small relative errors and high correlation coefficients in identifying the mechanical response of local interconnections in board-level packaging structures,while significantly balancing the smoothness of response curves with the accuracy of peak identification.At medium and low noise levels,the relative error is less than 6%,while it is less than 10%at high noise levels.The proposed method provides an effective indirect approach for the boundary conditions of localized solder joints during the projectile penetration process,and its philosophy can be readily extended to other scenarios of multiscale analysis for highly nonlinear materials and structures under extreme loading conditions.展开更多
A novel coronavirus, severe acute respiratory syndrome (SA RS)-associated coronavirus (SARS-CoV), has been identified as the causal agent of SARS. Spike (S) protein is a major structural glycoprotein of the SARS virus...A novel coronavirus, severe acute respiratory syndrome (SA RS)-associated coronavirus (SARS-CoV), has been identified as the causal agent of SARS. Spike (S) protein is a major structural glycoprotein of the SARS virus and a potential target for SARS-specific cell-mediated immune responses. A pa nel of S protein-derived peptides was tested for their binding affinity to HLA -A *0201 molecules. Peptides with high affinity for HLA-A *0201 were then as se ssed for their capacity to elicit specific immune responses mediated by cytotoxi c T lymphocytes (CTLs) both in vivo, in HLA-A2.1/K b transgenic mice, a nd in vitro, from peripheral blood lymphocytes (PBLs) harvested from healthy HLA-A 2.1 + donors. SARS-CoV protein-derived peptide-1 (SSp-1 RLNEVAKNL), induced pepti de-specific CTLs both in vivo (transgenic mice) and in vitro (human PBL s), which specifically released interferon-gamma (IFN-gamma) upon stimulation with SSp-1-pulsed autologous dendritic cells (DCs) or T2 cells. SSp-1-specif ic CTLs also lysed major histocompatibility complex (MHC)-matched tumor cell lines engineered to express S proteins. HLA-A *0201-SSp-1 tetramer staining re vealed the presence of significant populations of SSp-1-specific CTLs in SSp- 1-induced CD8 + T cells. We propose that the newly identified epitope SSp-1 w ill help in the characterization of virus control mechanisms and immunopathology in SARS-CoV infection, and may be relevant to the development of immunotherape utic approaches for SARS.展开更多
A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibratio...A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibration drilling based on the fuzzy least squares(FLS)-support vector machine(SVM) was developed, in which the fuzzy membership function was set by using linear distance, and its parameters, such as penalty factor and kernel parameter, were optimized by using adaptive genetic algorithm. And FLS-SVM identification on rock and soil parameters for vibration drilling was made by changing the input/output data from single freedom degree model of drilling bit-rock. The results of identification simulation and resonance column experiment show that relative error of natural frequency for some hard sand from identification simulation and resonance column experiment is 1.1% and the identification precision based on the fuzzy least squares-support vector machine is high.展开更多
文摘The satellite-based automatic identification system (AIS) receiver has to encounter the frequency offset caused by the Doppler effect and the oscillator instability. This paper proposes a non-coherent sequence detection scheme for the satellite-based AIS signal transmitted over the white Gaussian noise channel. Based on the maximum likelihood estimation and a Viterbi decoder, the proposed scheme is capable of tolerating a frequency offset up to 5% of the symbol rate. The complexity of the proposed scheme is reduced by the state-complexity reduction, which is based on per-survivor processing. Simulation results prove that the proposed non-coherent sequence detection scheme has high robustness to frequency offset compared to the relative scheme when messages collision exists.
基金Project(9140C860304) supported by the National Defense Key Laboratory Foundation of China
文摘Aiming at the potential presence of mixing automatic identification system(AIS) signals,a new demodulation scheme was proposed for separating other interfering signals in satellite systems.The combined iterative cross-correlation demodulation scheme,referred to as CICCD,yielded a set of single short signals based on the prior information of AIS,after the frequency,code rate and modulation index were estimated.It demodulates the corresponding short codes according to the maximum peak of cross-correlation,which is simple and easy to implement.Numerical simulations show that the bit error rate of proposed algorithm improves by about 40% compared with existing ones,and about 3 dB beyond the standard AIS receiver.In addition,the proposed demodulation scheme shows the satisfying performance and engineering value in mixing AIS environment and can also perform well in low signal-to-noise conditions.
文摘Here we present a simple yet effective gas chromatography-mass spectrometry(GC-MS)identification approach for the detection of heteroatom-containing compounds(HACCs)in petroleum fractions.The MS/AMDIS(Automated Mass Spectral Deconvolution and Identification System)program was used to identify parts per million(ppm)HACC concentrations in petroleum fractions in place of traditional techniques(extraction and standard injection).Polycyclic aromatic sulfur heterocycles(S-PAHs)were used as model compounds to confirm the validity of the AMDIS identifiers,which were compared with extracted results using the off-line X-calibur software.AMDIS was able to identify ppm concentrations of S-PAHs in oil condensate.There was good agreement between experimental and AMDIS identification results for S-PAHs in oil condensate.AMDIS was also used to detect nitrogen-containing compounds(NCCs)and alkylphenols in oil condensate.Our results confirmed the presence of 2-methylbenzothiazole,carbazole,and 2,4-ditertbutyl phenol.In a crude oil sample,AMDIS identification of m/z=191 biomarkers wa s consistent with empirical results.Therefore,AMDIS can help to reduce the number of experimental steps in identification protocols.
基金Project(61533021)supported by the National Natural Science Foundation of ChinaProject(R201706)supported by Hunan Food Pharmaceutical,China
文摘A new reaction system to determine nonlinear chemical fingerprint(NCF)and its use in identification method based on double reaction system was researched.Panax ginsengs,such as ginseng,American ginseng and notoginseng were identified by the method.The NCFs of the three samples of Panax ginsengs were determined through two nonlinear chemical systems,namely system 1 consisting of sample components,H2SO4,MnSO4,NaBrO3,acetone and the new system,system 2 consisting of sample components,H2SO4,(NH4)4Ce(SO4)2,NaBrO3 and citric acid.The comparison between the results determined through systems 1 and 2 shows that the speed to determine NCF through system 2 is much faster than that through system 1;for systems 1 and 2,the system similarities of the same kind of samples are≥98.09%and 99.78%,respectively,while those of different kinds of samples are≤63.04%and 86.34%,respectively.The results to identify the kinds of some samples by system similarity pattern show that both the accuracies of identification methods based on single system 1 and 2 are≥95.6%,and the average values are 97.1%and 96.3%,respectively;the accuracy of the method based on double system is≥97.8%,and the average accuracy is 99.3%.The accuracy of the method based on double system is higher than that based on any single system.
文摘Including servo valve, hydraulic cylinder, mill and sensor and ignoring nonlinear factors, the linear dynamic model of hydraulic automatic gage control(HAGC) system of a temper rolling mill was theoretically derived. The order of the model is 4/4, and can be reduced to 2/2. Based on modulating functions method, utilizing numerical integration, we constructed the equivalent identification model of HAGC, and the least square estimation algorithm was established. The input and output data were acquired on line at temper rolling mill in Shangshai Baosteel Group Corporation, and the continuous time model of HAGC system was estimated with the proposed method. At different modulating window intervals, the estimated parameters changed remarkably. When the frequency bandwidth of modulating filter matches that of estimated system, the parameters can be estimated accurately. Finally, the dynamic model of the HAGC was obtained and validated based on the spectral analysis result.
基金Projects(61573052,61273132)supported by the National Natural Science Foundation of China
文摘This work is concerned with identification and nonlinear predictive control method for MIMO Hammerstein systems with constraints. Firstly, an identification method based on steady-state responses and sub-model method is introduced to MIMO Hammerstein system. A modified version of artificial bee colony algorithm is proposed to improve the prediction ability of Hammerstein model. Next, a computationally efficient nonlinear model predictive control algorithm(MGPC) is developed to deal with constrained problem of MIMO system. The identification process and performance of MGPC are shown. Numerical results about a polymerization reactor validate the effectiveness of the proposed method and the comparisons show that MGPC has a better performance than QDMC and basic GPC.
文摘Strategic management of equipment system develop-ment must attach importance to effective strategic risk manage-ment.Aiming at the identification of strategic risk of equipment system development,firstly,the source of strategic risk of equip-ment system development is analyzed and classified.Based on this,a causal loop diagram of strategic risk of equipment sys-tem development based on system dynamics is established.The system dynamics analysis software Vensim PLE is used to carry out the risk influencing factors analysis,risk consequences ana-lysis,risk feedback loop identification and corresponding pre-control measures,and achieves a good risk identification effect.
文摘Based on system identification theory and FWD testing data, the effect of thickness error on backcalculating pavement layer moduli is studied and the method of singular value decomposition (SVD) is presented to solve the morbidity problem of sensitivity matrix in this paper.The results show that the thickness error has great effects on the backcalculated pavement layer moduli. The error of backcalculated moduli can be controlled within the range of ±15% by limiting the thickness error within the range of ±5%.
基金supported by the National High Technology Researchand Development Program of China(863 Program)(2012AA121602)the Preliminary Research Program of the General Armament Department of China(51322050202)
文摘A higher-order cumulant-based weighted least square（HOCWLS） and a higher-order cumulant-based iterative least square（HOCILS） are derived for multiple inputs single output（MISO） errors-in-variables（EIV） systems from noisy input/output data. Whether the noises of the input/output of the system are white or colored, the proposed algorithms can be insensitive to these noises and yield unbiased estimates. To realize adaptive parameter estimates, a higher-order cumulant-based recursive least square（HOCRLS） method is also studied. Convergence analysis of the HOCRLS is conducted by using the stochastic process theory and the stochastic martingale theory. It indicates that the parameter estimation error of HOCRLS consistently converges to zero under a generalized persistent excitation condition. The usefulness of the proposed algorithms is assessed through numerical simulations.
基金This work was supported by the Natural Science Foundation of Hebei Province(F2019203505).
文摘Input variables selection(IVS) is proved to be pivotal in nonlinear dynamic system modeling. In order to optimize the model of the nonlinear dynamic system, a fuzzy modeling method for determining the premise structure by selecting important inputs of the system is studied. Firstly, a simplified two stage fuzzy curves method is proposed, which is employed to sort all possible inputs by their relevance with outputs, select the important input variables of the system and identify the structure.Secondly, in order to reduce the complexity of the model, the standard fuzzy c-means clustering algorithm and the recursive least squares algorithm are used to identify the premise parameters and conclusion parameters, respectively. Then, the effectiveness of IVS is verified by two well-known issues. Finally, the proposed identification method is applied to a realistic variable load pneumatic system. The simulation experiments indi cate that the IVS method in this paper has a positive influence on the approximation performance of the Takagi-Sugeno(T-S) fuzzy modeling.
文摘The problem of how to identify the piecewise affine system is studied in this paper, where this considered piecewise affine system is a special nonlinear system. The reason why it is not easy to identify this piecewise affine system is that each separated region and each unknown parameter vector are all needed to be determined simultaneously. Then, firstly, in order to achieve the identification goal, a multi-class classification process is proposed to determine each separated region. As the proposed multi-class classification process is the same with the classical data clustering strategy, the multi-class classification process can combine the first order algorithm of convex optimization, while achieving the goal of the classification process. Secondly, a zonotope parameter identification algorithm is used to construct a set, which contains the unknown parameter vector. In this zonotope parameter identification algorithm, the strict probabilistic description about the external noise is relaxed, and each unknown parameter vector is also identified. Furthermore, this constructed set is consistent with the measured output and the given bound corresponding to the noise. Thirdly, a sufficient condition about guaranteeing our derived zonotope not growing unbounded with iterations is formulated as an explicit linear matrix inequality. Finally, the effectiveness of this zonotope parameter identification algorithm is proven through a simulation example.
文摘A dynamic genetic algorithms based on numeric encoding is proposed and its application in system identification is discussed. Simulation shows that the introduction of both numeric encoding and dynamic mutation can effectively improve the accuracy and speed of searching for the optimum. It also show that the improved Genetic algorithm can identify time delay and parameters of the plant at the same time and converge to globle optimization.
基金This work was supported by the National Natural Science Foundation of China(61903086,61903366,62001115)the Natural Science Foundation of Hunan Province(2019JJ50745,2020JJ4280,2021JJ40133)the Fundamentals and Basic of Applications Research Foundation of Guangdong Province(2019A1515110136).
文摘The observation error model of the underwater acous-tic positioning system is an important factor to influence the positioning accuracy of the underwater target.For the position inconsistency error caused by considering the underwater tar-get as a mass point,as well as the observation system error,the traditional error model best estimation trajectory(EMBET)with little observed data and too many parameters can lead to the ill-condition of the parameter model.In this paper,a multi-station fusion system error model based on the optimal polynomial con-straint is constructed,and the corresponding observation sys-tem error identification based on improved spectral clustering is designed.Firstly,the reduced parameter unified modeling for the underwater target position parameters and the system error is achieved through the polynomial optimization.Then a multi-sta-tion non-oriented graph network is established,which can address the problem of the inaccurate identification for the sys-tem errors.Moreover,the similarity matrix of the spectral cluster-ing is improved,and the iterative identification for the system errors based on the improved spectral clustering is proposed.Finally,the comprehensive measured data of long baseline lake test and sea test show that the proposed method can accu-rately identify the system errors,and moreover can improve the positioning accuracy for the underwater target positioning.
文摘Aimed at the problem of classification of non-hydrocarbons of crude oil, the theoretical standpoint that the polarity of a compound depends on the whole structure and composition of molecule instead of a kind of heteroatom or its functional group was presented. A method was established for the systematically structural identification of nitric compounds in crude oil. The pre-fractionation of a crude oil sample into 7 fractions was performed by di- adsorption column chromatography with neutral aluminum oxide and silica gel. Subsequently, the individual components were obtained by using capillary column gas chromatography, and the types of compounds were detected by a mass spectrometer. In combination with a chemometric resolution, the compounds of fraction were further identified. This method can relieve the difficulty of classical analysis in identifying those species with very low contents or without being completely separated. The structures of 168 nitric compounds in a crude oil sample were determined by this method.
文摘In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning actuator.The static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,respectively.This model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is proposed.Experimental results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 ms.In the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 Hz.The proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.
基金supported by the Youth Science and Technology Innovation Award of National University of Defense Technology (18/19-QNCXJ)the National Science Foundation of China (62271494)
文摘Extensive experiments suggest that kurtosis-based fingerprint features are effective for specific emitter identification (SEI). Nevertheless, the lack of mechanistic explanation restricts the use of fingerprint features to a data-driven technique and fur-ther reduces the adaptability of the technique to other datasets. To address this issue, the mechanism how the phase noise of high-frequency oscillators and the nonlinearity of power ampli-fiers affect the kurtosis of communication signals is investigated. Mathematical models are derived for intentional modulation (IM) and unintentional modulation (UIM). Analysis indicates that the phase noise of high-frequency oscillators and the nonlinearity of power amplifiers affect the kurtosis frequency and amplitude, respectively. A novel SEI method based on frequency and ampli-tude of the signal kurtosis (FA-SK) is further proposed. Simula-tion and real-world experiments validate theoretical analysis and also confirm the efficiency and effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant Nos.52475166,52175148)the Regional Collaboration Project of Shanxi Province(Grant No.202204041101044).
文摘Modern warfare demands weapons capable of penetrating substantial structures,which presents sig-nificant challenges to the reliability of the electronic devices that are crucial to the weapon's perfor-mance.Due to miniaturization of electronic components,it is challenging to directly measure or numerically predict the mechanical response of small-sized critical interconnections in board-level packaging structures to ensure the mechanical reliability of electronic devices in projectiles under harsh working conditions.To address this issue,an indirect measurement method using the Bayesian regularization-based load identification was proposed in this study based on finite element(FE)pre-dictions to estimate the load applied on critical interconnections of board-level packaging structures during the process of projectile penetration.For predicting the high-strain-rate penetration process,an FE model was established with elasto-plastic constitutive models of the representative packaging ma-terials(that is,solder material and epoxy molding compound)in which material constitutive parameters were calibrated against the experimental results by using the split-Hopkinson pressure bar.As the impact-induced dynamic bending of the printed circuit board resulted in an alternating tensile-compressive loading on the solder joints during penetration,the corner solder joints in the edge re-gions experience the highest S11 and strain,making them more prone to failure.Based on FE predictions at different structural scales,an improved Bayesian method based on augmented Tikhonov regulariza-tion was theoretically proposed to address the issues of ill-posed matrix inversion and noise sensitivity in the load identification at the critical solder joints.By incorporating a wavelet thresholding technique,the method resolves the problem of poor load identification accuracy at high noise levels.The proposed method achieves satisfactorily small relative errors and high correlation coefficients in identifying the mechanical response of local interconnections in board-level packaging structures,while significantly balancing the smoothness of response curves with the accuracy of peak identification.At medium and low noise levels,the relative error is less than 6%,while it is less than 10%at high noise levels.The proposed method provides an effective indirect approach for the boundary conditions of localized solder joints during the projectile penetration process,and its philosophy can be readily extended to other scenarios of multiscale analysis for highly nonlinear materials and structures under extreme loading conditions.
文摘A novel coronavirus, severe acute respiratory syndrome (SA RS)-associated coronavirus (SARS-CoV), has been identified as the causal agent of SARS. Spike (S) protein is a major structural glycoprotein of the SARS virus and a potential target for SARS-specific cell-mediated immune responses. A pa nel of S protein-derived peptides was tested for their binding affinity to HLA -A *0201 molecules. Peptides with high affinity for HLA-A *0201 were then as se ssed for their capacity to elicit specific immune responses mediated by cytotoxi c T lymphocytes (CTLs) both in vivo, in HLA-A2.1/K b transgenic mice, a nd in vitro, from peripheral blood lymphocytes (PBLs) harvested from healthy HLA-A 2.1 + donors. SARS-CoV protein-derived peptide-1 (SSp-1 RLNEVAKNL), induced pepti de-specific CTLs both in vivo (transgenic mice) and in vitro (human PBL s), which specifically released interferon-gamma (IFN-gamma) upon stimulation with SSp-1-pulsed autologous dendritic cells (DCs) or T2 cells. SSp-1-specif ic CTLs also lysed major histocompatibility complex (MHC)-matched tumor cell lines engineered to express S proteins. HLA-A *0201-SSp-1 tetramer staining re vealed the presence of significant populations of SSp-1-specific CTLs in SSp- 1-induced CD8 + T cells. We propose that the newly identified epitope SSp-1 w ill help in the characterization of virus control mechanisms and immunopathology in SARS-CoV infection, and may be relevant to the development of immunotherape utic approaches for SARS.
基金Project(2012BAK09B02-05) supported by the National Key Technology R&D Program of China during the Twelfth Five-year PeriodProject(51274250) supported by the National Natural Science Foundation of China
文摘A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibration drilling based on the fuzzy least squares(FLS)-support vector machine(SVM) was developed, in which the fuzzy membership function was set by using linear distance, and its parameters, such as penalty factor and kernel parameter, were optimized by using adaptive genetic algorithm. And FLS-SVM identification on rock and soil parameters for vibration drilling was made by changing the input/output data from single freedom degree model of drilling bit-rock. The results of identification simulation and resonance column experiment show that relative error of natural frequency for some hard sand from identification simulation and resonance column experiment is 1.1% and the identification precision based on the fuzzy least squares-support vector machine is high.
