Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degrad...Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.展开更多
This study involved a comprehensive investigation aimed at achieving efficient multi-millijoule THz wave generation by exploiting the unique properties of cylindrical GaAs waveguides as effective mediators of the conv...This study involved a comprehensive investigation aimed at achieving efficient multi-millijoule THz wave generation by exploiting the unique properties of cylindrical GaAs waveguides as effective mediators of the conversion of laser energy into THz waves.Through meticulous investigation,valuable insights into optimizing THz generation processes for practical applications were unearthed.By investigating Hertz potentials,an eigen-value equation for the solutions of the guided modes(i.e.,eigenvalues)was found.The effects of various param-eters,including the effective mode index and the laser pulse power,on the electric field components of THz radia-tion,including the fundamental TE(transverse electric)and TM(transverse magnetic)modes,were evaluated.By analyzing these factors,this research elucidated the nuanced mechanisms governing THz wave generation within cylindrical GaAs waveguides,paving the way for refined methodologies and enhanced efficiency.The sig-nificance of cylindrical GaAs waveguides extends beyond their roles as mere facilitators of THz generation;their design and fabrication hold the key to unlocking the potential for compact and portable THz systems.This trans-formative capability not only amplifies the efficiency of THz generation but also broadens the horizons of practical applications.展开更多
To predict the remaining useful life(RUL) for a class of nonlinear multi-degradation systems, a method is presented. In the real industrial processes, systems are usually composed by several parts or components, and t...To predict the remaining useful life(RUL) for a class of nonlinear multi-degradation systems, a method is presented. In the real industrial processes, systems are usually composed by several parts or components, and these parts or components are working in the same environment, thus the degradations of these parts or components will be influenced by common factors. To describe such a phenomenon in degradations, a multi-degradation model with public noise is proposed. To identify the degradation states and the unknown parameters, an iterative estimation method is proposed by using the Kalman filter and the expectation maximization(EM) algorithm. Next, with known thresholds,the RUL of each degradation can be predicted by using the first hitting time(FHT). In addition, the RUL of the whole system can be obtained by a Copula function. Finally, a practical case is used to demonstrate the method proposed.展开更多
To explore a new evaluation method for spontaneous combustion tendency of different areas in sulfide ore heap, ore samples from a pyrite mine in China were taken as experimental materials, and the temperature variatio...To explore a new evaluation method for spontaneous combustion tendency of different areas in sulfide ore heap, ore samples from a pyrite mine in China were taken as experimental materials, and the temperature variations of the measuring points of simulated ore heap were measured. Combined with wavelet transform and nonlinear parameters extraction, a new method for spontaneous combustion tendency of different areas in sulfide ore heap based on nonlinear parameters was proposed and its reliability was verified by field test. The results indicate that temperature field evolution of the simulated ore heap presents significant spatial difference during self-heating process. Area with the maximum increasing extent of temperature in sulfide ore heap changes notably with the proceeding of self-heating reaction. Self-heating of sulfide ore heap is a chaotic evolution process, which means that it is feasible to evaluate spontaneous combustion tendency of different areas by nonlinear analysis method. There is a relatively strong correlation between the maximum Lyapunov exponent and spontaneous combustion tendency with the correlation coefficient of 0.9792. Furthermore, the sort of the maximum Lyapunov exponent is consistent with that of spontaneous combustion tendency. Therefore, spontaneous combustion tendency of different areas in sulfide ore heap can be evaluated by means of the maximum Lyapunov exponent method.展开更多
Nonlinearity and implicitness are common degradation features of the stochastic degradation equipment for prognostics.These features have an uncertain effect on the remaining useful life(RUL)prediction of the equipmen...Nonlinearity and implicitness are common degradation features of the stochastic degradation equipment for prognostics.These features have an uncertain effect on the remaining useful life(RUL)prediction of the equipment.The current data-driven RUL prediction method has not systematically studied the nonlinear hidden degradation modeling and the RUL distribution function.This paper uses the nonlinear Wiener process to build a dual nonlinear implicit degradation model.Based on the historical measured data of similar equipment,the maximum likelihood estimation algorithm is used to estimate the fixed coefficients and the prior distribution of a random coefficient.Using the on-site measured data of the target equipment,the posterior distribution of a random coefficient and actual degradation state are step-by-step updated based on Bayesian inference and the extended Kalman filtering algorithm.The analytical form of the RUL distribution function is derived based on the first hitting time distribution.Combined with the two case studies,the proposed method is verified to have certain advantages over the existing methods in the accuracy of prediction.展开更多
基金Projects(51475462,61374138,61370031)supported by the National Natural Science Foundation of China
文摘Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.
文摘This study involved a comprehensive investigation aimed at achieving efficient multi-millijoule THz wave generation by exploiting the unique properties of cylindrical GaAs waveguides as effective mediators of the conversion of laser energy into THz waves.Through meticulous investigation,valuable insights into optimizing THz generation processes for practical applications were unearthed.By investigating Hertz potentials,an eigen-value equation for the solutions of the guided modes(i.e.,eigenvalues)was found.The effects of various param-eters,including the effective mode index and the laser pulse power,on the electric field components of THz radia-tion,including the fundamental TE(transverse electric)and TM(transverse magnetic)modes,were evaluated.By analyzing these factors,this research elucidated the nuanced mechanisms governing THz wave generation within cylindrical GaAs waveguides,paving the way for refined methodologies and enhanced efficiency.The sig-nificance of cylindrical GaAs waveguides extends beyond their roles as mere facilitators of THz generation;their design and fabrication hold the key to unlocking the potential for compact and portable THz systems.This trans-formative capability not only amplifies the efficiency of THz generation but also broadens the horizons of practical applications.
基金supported by the National Natural Science Foundation of China(6129032461473164+1 种基金61490701)the Research Fund for the Taishan Scholar Project of Shandong Province of China(LZB2015-162)
文摘To predict the remaining useful life(RUL) for a class of nonlinear multi-degradation systems, a method is presented. In the real industrial processes, systems are usually composed by several parts or components, and these parts or components are working in the same environment, thus the degradations of these parts or components will be influenced by common factors. To describe such a phenomenon in degradations, a multi-degradation model with public noise is proposed. To identify the degradation states and the unknown parameters, an iterative estimation method is proposed by using the Kalman filter and the expectation maximization(EM) algorithm. Next, with known thresholds,the RUL of each degradation can be predicted by using the first hitting time(FHT). In addition, the RUL of the whole system can be obtained by a Copula function. Finally, a practical case is used to demonstrate the method proposed.
基金Projects(51304238,51534008)supported by the National Natural Science Foundation of ChinaProject(2015CX005)supported by Innovation Driven Plan of Central South University,China
文摘To explore a new evaluation method for spontaneous combustion tendency of different areas in sulfide ore heap, ore samples from a pyrite mine in China were taken as experimental materials, and the temperature variations of the measuring points of simulated ore heap were measured. Combined with wavelet transform and nonlinear parameters extraction, a new method for spontaneous combustion tendency of different areas in sulfide ore heap based on nonlinear parameters was proposed and its reliability was verified by field test. The results indicate that temperature field evolution of the simulated ore heap presents significant spatial difference during self-heating process. Area with the maximum increasing extent of temperature in sulfide ore heap changes notably with the proceeding of self-heating reaction. Self-heating of sulfide ore heap is a chaotic evolution process, which means that it is feasible to evaluate spontaneous combustion tendency of different areas by nonlinear analysis method. There is a relatively strong correlation between the maximum Lyapunov exponent and spontaneous combustion tendency with the correlation coefficient of 0.9792. Furthermore, the sort of the maximum Lyapunov exponent is consistent with that of spontaneous combustion tendency. Therefore, spontaneous combustion tendency of different areas in sulfide ore heap can be evaluated by means of the maximum Lyapunov exponent method.
基金supported by the National Defense Foundation of China(7160118371901216)the China Postdoctoral Science Foundation(2017M623415)
文摘Nonlinearity and implicitness are common degradation features of the stochastic degradation equipment for prognostics.These features have an uncertain effect on the remaining useful life(RUL)prediction of the equipment.The current data-driven RUL prediction method has not systematically studied the nonlinear hidden degradation modeling and the RUL distribution function.This paper uses the nonlinear Wiener process to build a dual nonlinear implicit degradation model.Based on the historical measured data of similar equipment,the maximum likelihood estimation algorithm is used to estimate the fixed coefficients and the prior distribution of a random coefficient.Using the on-site measured data of the target equipment,the posterior distribution of a random coefficient and actual degradation state are step-by-step updated based on Bayesian inference and the extended Kalman filtering algorithm.The analytical form of the RUL distribution function is derived based on the first hitting time distribution.Combined with the two case studies,the proposed method is verified to have certain advantages over the existing methods in the accuracy of prediction.
