Ideas from engineering have helped the understanding of biological organisms for thousands of years. However, the mechanical aspects of biological materials and structures can, if properly interpreted and analysed, le...Ideas from engineering have helped the understanding of biological organisms for thousands of years. However, the mechanical aspects of biological materials and structures can, if properly interpreted and analysed, lead to a deeper understanding of the biology of organisms. Such an approach, although always current in some form, is nevertheless subject to the vagaries of fashion and the availability of analytical techniques. At present we are in a period of upturn. Areas of interest are deployable structures (applications in aerospace), palaeontology (how little do we need to know in order to create a credible biosphere) and food science (we need a rational approach to the mechanics of food).展开更多
This paper investigates the vibration characteristics of diesel engine cylinder heads by means of the time series method. With the concept of "Assumed System",the vibration transfer function of real cylinder...This paper investigates the vibration characteristics of diesel engine cylinder heads by means of the time series method. With the concept of "Assumed System",the vibration transfer function of real cylinder head structures is established using the autoregressive-moving average models(ARMA models) of cylinder head surface vibration signals. Then this transfer function is successfully used to reconstruct the gas pressure trace inside the cylinder from measured cylinder head vibration signals. This offers an effective means for diesel engine cylinder pressure detection and condition monitoring.展开更多
Time series are an important object of study in sciences, engineering and business, especially in cases where it is expected to know, predict and optimize behaviors. In this context, we intend to show the feasibility ...Time series are an important object of study in sciences, engineering and business, especially in cases where it is expected to know, predict and optimize behaviors. In this context, we intend to show the feasibility of using artificial neural networks in the study of several time series in an engineering course, especially those that have no overt behavior or are not able to be modeled mathematically in a simple way and have direct application in the education of future engineers.展开更多
With the development of the integration of aviation safety and artificial intelligence,research on the combination of risk assessment and artificial intelligence is particularly important in the field of risk manageme...With the development of the integration of aviation safety and artificial intelligence,research on the combination of risk assessment and artificial intelligence is particularly important in the field of risk management,but searching for an efficient and accurate risk assessment algorithm has become a challenge for the civil aviation industry.Therefore,an improved risk assessment algorithm(PS-AE-LSTM)based on long short-term memory network(LSTM)with autoencoder(AE)is proposed for the various supervised deep learning algorithms in flight safety that cannot adequately address the problem of the quality on risk level labels.Firstly,based on the normal distribution characteristics of flight data,a probability severity(PS)model is established to enhance the quality of risk assessment labels.Secondly,autoencoder is introduced to reconstruct the flight parameter data to improve the data quality.Finally,utilizing the time-series nature of flight data,a long and short-termmemory network is used to classify the risk level and improve the accuracy of risk assessment.Thus,a risk assessment experimentwas conducted to analyze a fleet landing phase dataset using the PS-AE-LSTMalgorithm to assess the risk level associated with aircraft hard landing events.The results show that the proposed algorithm achieves an accuracy of 86.45%compared with seven baseline models and has excellent risk assessment capability.展开更多
Current structural analysis software programs offer few if any applicable device-specifi c hysteresis rules or nonlinear elements to simulate the precise mechanical behavior of a multiple friction pendulum system(MFPS...Current structural analysis software programs offer few if any applicable device-specifi c hysteresis rules or nonlinear elements to simulate the precise mechanical behavior of a multiple friction pendulum system(MFPS) with numerous sliding interfaces.Based on the concept of subsystems,an equivalent series system that adopts existing nonlinear elements with parameters systematically calculated and mathematically proven through rigorous derivations is proposed.The aim is to simulate the characteristics of sliding motions for an MFPS isolation system with numerous concave sliding interfaces without prior knowledge of detailed information on the mobilized forces at various sliding stages.An MFPS with numerous concave sliding interfaces and one articulated or rigid slider located between these interfaces is divided into two subsystems: the fi rst represents the concave sliding interfaces above the slider,and the second represents those below the slider.The equivalent series system for the entire system is then obtained by connecting those for each subsystem in series.The equivalent series system is validated by comparing numerical results for an MFPS with four sliding interfaces obtained from the proposed method with those from a previous study by Fenz and Constantinou.Furthermore,these numerical results demonstrate that an MFPS isolator with numerous concave sliding interfaces,which may have any number of sliding interfaces,is a good isolation device to protect structures from earthquake damage through appropriate designs with controllable mechanisms.展开更多
In recent years, with the rapid development of sensing technology and deployment of various Internet of Everything devices, it becomes a crucial and practical challenge to enable real-time search queries for objects, ...In recent years, with the rapid development of sensing technology and deployment of various Internet of Everything devices, it becomes a crucial and practical challenge to enable real-time search queries for objects, data, and services in the Internet of Everything. Moreover, such efficient query processing techniques can provide strong facilitate the research on Internet of Everything security issues. By looking into the unique characteristics in the IoE application environment, such as high heterogeneity, high dynamics, and distributed, we develop a novel search engine model, and build a dynamic prediction model of the IoE sensor time series to meet the real-time requirements for the Internet of Everything search environment. We validated the accuracy and effectiveness of the dynamic prediction model using a public sensor dataset from Intel Lab.展开更多
In order to study the hydrodynamic characteristics of the karst aquifers in northern China,time series analyses(correlation and spectral analysis in addition with hydrograph recession analysis)are applied on Baotu Spr...In order to study the hydrodynamic characteristics of the karst aquifers in northern China,time series analyses(correlation and spectral analysis in addition with hydrograph recession analysis)are applied on Baotu Spring and Heihu Spring in Jinan karst spring system,a typical karst spring system in northern China.Results show that the auto-correlation coefficient of spring water level reaches the value of 0.2 after 123 days and 117 days for Baotu Spring and Heihu Spring,respectively.The regulation time obtained from the simple spectral density function in the same period is 187 days and 175 days for Baotu Spring and Heihu Spring.The auto-correlation coefficient of spring water level reaches the value of 0.2 in 34-82 days,and regulation time ranges among 40-59 days for every single hydrological year.The delay time between precipitation and spring water level obtained from cross correlation function is around 56 days for the period of 2012-2019,and varies among 30-79 days for every single hydrological year.In addition,the spectral bands in cross amplitude functions and gain functions are small with 0.02,and the values in the coherence functions are small.All these behaviors illustrate that Jinan karst spring system has a strong memory effect,large storage capacity,noticeable regulation effect,and time series analysis is a useful tool for studying the hydrodynamic characteristics of karst spring system in northern China.展开更多
Traditional studies on integrated statistical process control and engineering process control (SPC-EPC) are based on linear autoregressive integrated moving average (ARIMA) time series models to describe the dynamic n...Traditional studies on integrated statistical process control and engineering process control (SPC-EPC) are based on linear autoregressive integrated moving average (ARIMA) time series models to describe the dynamic noise of the system.However,linear models sometimes are unable to model complex nonlinear autocorrelation.To solve this problem,this paper presents an integrated SPC-EPC method based on smooth transition autoregressive (STAR) time series model,and builds a minimum mean squared error (MMSE) controller as well as an integrated SPC-EPC control system.The performance of this method for checking the trend and sustained shift is analyzed.The simulation results indicate that this integrated SPC-EPC control method based on STAR model is effective in controlling complex nonlinear systems.展开更多
Electrostatic monitoring technology of particle charging information can facilitate online monitoring of aero-engine,which effectively enhances engine fault diagnosis and health managements.Unlike traditional engine s...Electrostatic monitoring technology of particle charging information can facilitate online monitoring of aero-engine,which effectively enhances engine fault diagnosis and health managements.Unlike traditional engine state monitoring technologies,aircraft engine monitoring by gas path electrostatic monitoring not only covers the predicted information source itself,but also detects the information that can provide an early warnings for initial fault states through gas path charging levels.This paper establishes a non-stationary time sequence change-point model for anomaly recognition of electrostatic signals based on change-point theory combined with difference method of non-stationary time series.Finally,electrostatic induction data were utilized by the engine life test for a particular aircraft to validate the proposed algorithm.The results indicate that the activity level and the event rate were0.5—0.8(nc)and 50%,respectively,which were far greater than 4—12(pc)and 0—4% under normal working conditions of the engine.展开更多
基于基波磁通补偿的串联混合型有源电力滤波器(active power filter,APF)应用于高电压、大容量的谐波抑制场合时,受变压器励磁支路谐波电压的影响,逆变器不能等效为基波电流源,其输出电流将含有大量的谐波,从而影响滤波效果。以逆变...基于基波磁通补偿的串联混合型有源电力滤波器(active power filter,APF)应用于高电压、大容量的谐波抑制场合时,受变压器励磁支路谐波电压的影响,逆变器不能等效为基波电流源,其输出电流将含有大量的谐波,从而影响滤波效果。以逆变器为核心,推导出在励磁支路谐波压降影响下的串联变压器的谐波等效阻抗。并以此为基础,从理论上分析励磁电感和变比对串联变压器谐波等效阻抗和APF滤波效果的影响。仿真结果验证了理论分析的正确性。最后,针对广东某厂10kV、1MVA电力负荷,研制一套基于基波磁通补偿的串联混合型有源滤波器工程样机,取得非常好的滤波效果。展开更多
Condition-based maintenance based on fault prediction has been widely concerned by the industry. Most of the contributions on fault prediction are based on various sensor data and mathematical models of the equipment....Condition-based maintenance based on fault prediction has been widely concerned by the industry. Most of the contributions on fault prediction are based on various sensor data and mathematical models of the equipment. The complexity of the model and data signal is the key factor affecting the practicability of the model. In addition, even for the same type and batch of equipment, the manufacturing process, operation environment and other factors also affect the model parameters. In this paper, a series event model is conducted to predict the fault of marine diesel engines. Numerical example illustrates that the proposed event model is feasible.展开更多
Spatiotemporal residual noise in terrestrial earth observation products,often caused by unfavorable atmospheric conditions,impedes their broad applications.Most users prefer to use gap-filled remote sensing products w...Spatiotemporal residual noise in terrestrial earth observation products,often caused by unfavorable atmospheric conditions,impedes their broad applications.Most users prefer to use gap-filled remote sensing products with time series reconstruction(TSR)algorithms.Applying currently available implementations of TSR to large-volume datasets is time-consuming and challenging for non-professional users with limited computation or storage resources.This study introduces a new open-source software package entitled‘HANTS-GEE’that implements a well-known and robust TSR algorithm,i.e.Harmonic ANalysis of Time Series(HANTS),on the Google Earth Engine(GEE)platform for scalable reconstruction of terrestrial earth observation data.Reconstruction tasks can be conducted on user-defined spatiotemporal extents when raw datasets are available on GEE.According to site-based and regional-based case evaluation,the new tool can effectively eliminate cloud contamination in the time series of earth observation data.Compared with traditional PC-based HANTS implementation,the HANTS-GEE provides quite consistent reconstruction results for most terrestrial vegetated sites.The HANTS-GEE can provide scalable reconstruction services with accelerated processing speed and reduced internet data transmission volume,promoting algorithm usage by much broader user communities.To our knowledge,the software package is thefirst tool to support full-stack TSR processing for popular open-access satellite sensors on cloud platforms.展开更多
文摘Ideas from engineering have helped the understanding of biological organisms for thousands of years. However, the mechanical aspects of biological materials and structures can, if properly interpreted and analysed, lead to a deeper understanding of the biology of organisms. Such an approach, although always current in some form, is nevertheless subject to the vagaries of fashion and the availability of analytical techniques. At present we are in a period of upturn. Areas of interest are deployable structures (applications in aerospace), palaeontology (how little do we need to know in order to create a credible biosphere) and food science (we need a rational approach to the mechanics of food).
基金Supported by the Shanghai Municipal Education Commission Foundation under Grant No. 06FZ039.
文摘This paper investigates the vibration characteristics of diesel engine cylinder heads by means of the time series method. With the concept of "Assumed System",the vibration transfer function of real cylinder head structures is established using the autoregressive-moving average models(ARMA models) of cylinder head surface vibration signals. Then this transfer function is successfully used to reconstruct the gas pressure trace inside the cylinder from measured cylinder head vibration signals. This offers an effective means for diesel engine cylinder pressure detection and condition monitoring.
文摘Time series are an important object of study in sciences, engineering and business, especially in cases where it is expected to know, predict and optimize behaviors. In this context, we intend to show the feasibility of using artificial neural networks in the study of several time series in an engineering course, especially those that have no overt behavior or are not able to be modeled mathematically in a simple way and have direct application in the education of future engineers.
基金the National Natural Science Foundation of China(U2033213)the Fundamental Research Funds for the Central Universities(FZ2021ZZ01,FZ2022ZX50).
文摘With the development of the integration of aviation safety and artificial intelligence,research on the combination of risk assessment and artificial intelligence is particularly important in the field of risk management,but searching for an efficient and accurate risk assessment algorithm has become a challenge for the civil aviation industry.Therefore,an improved risk assessment algorithm(PS-AE-LSTM)based on long short-term memory network(LSTM)with autoencoder(AE)is proposed for the various supervised deep learning algorithms in flight safety that cannot adequately address the problem of the quality on risk level labels.Firstly,based on the normal distribution characteristics of flight data,a probability severity(PS)model is established to enhance the quality of risk assessment labels.Secondly,autoencoder is introduced to reconstruct the flight parameter data to improve the data quality.Finally,utilizing the time-series nature of flight data,a long and short-termmemory network is used to classify the risk level and improve the accuracy of risk assessment.Thus,a risk assessment experimentwas conducted to analyze a fleet landing phase dataset using the PS-AE-LSTMalgorithm to assess the risk level associated with aircraft hard landing events.The results show that the proposed algorithm achieves an accuracy of 86.45%compared with seven baseline models and has excellent risk assessment capability.
文摘Current structural analysis software programs offer few if any applicable device-specifi c hysteresis rules or nonlinear elements to simulate the precise mechanical behavior of a multiple friction pendulum system(MFPS) with numerous sliding interfaces.Based on the concept of subsystems,an equivalent series system that adopts existing nonlinear elements with parameters systematically calculated and mathematically proven through rigorous derivations is proposed.The aim is to simulate the characteristics of sliding motions for an MFPS isolation system with numerous concave sliding interfaces without prior knowledge of detailed information on the mobilized forces at various sliding stages.An MFPS with numerous concave sliding interfaces and one articulated or rigid slider located between these interfaces is divided into two subsystems: the fi rst represents the concave sliding interfaces above the slider,and the second represents those below the slider.The equivalent series system for the entire system is then obtained by connecting those for each subsystem in series.The equivalent series system is validated by comparing numerical results for an MFPS with four sliding interfaces obtained from the proposed method with those from a previous study by Fenz and Constantinou.Furthermore,these numerical results demonstrate that an MFPS isolator with numerous concave sliding interfaces,which may have any number of sliding interfaces,is a good isolation device to protect structures from earthquake damage through appropriate designs with controllable mechanisms.
基金supported by the National Natural Science Foundation of China under NO.61572153, NO. 61702220, NO. 61702223, and NO. U1636215the National Key research and Development Plan (Grant No. 2018YFB0803504)
文摘In recent years, with the rapid development of sensing technology and deployment of various Internet of Everything devices, it becomes a crucial and practical challenge to enable real-time search queries for objects, data, and services in the Internet of Everything. Moreover, such efficient query processing techniques can provide strong facilitate the research on Internet of Everything security issues. By looking into the unique characteristics in the IoE application environment, such as high heterogeneity, high dynamics, and distributed, we develop a novel search engine model, and build a dynamic prediction model of the IoE sensor time series to meet the real-time requirements for the Internet of Everything search environment. We validated the accuracy and effectiveness of the dynamic prediction model using a public sensor dataset from Intel Lab.
基金This study is supported by the geological survey project:National Glacier and Desertification Remote Sensing Geological Survey(DD20190515)Youth Innovation Fund of China Aero Geophysical Prospecting and Remote Sensing Center for Natural Resources(2020YFL18).
文摘In order to study the hydrodynamic characteristics of the karst aquifers in northern China,time series analyses(correlation and spectral analysis in addition with hydrograph recession analysis)are applied on Baotu Spring and Heihu Spring in Jinan karst spring system,a typical karst spring system in northern China.Results show that the auto-correlation coefficient of spring water level reaches the value of 0.2 after 123 days and 117 days for Baotu Spring and Heihu Spring,respectively.The regulation time obtained from the simple spectral density function in the same period is 187 days and 175 days for Baotu Spring and Heihu Spring.The auto-correlation coefficient of spring water level reaches the value of 0.2 in 34-82 days,and regulation time ranges among 40-59 days for every single hydrological year.The delay time between precipitation and spring water level obtained from cross correlation function is around 56 days for the period of 2012-2019,and varies among 30-79 days for every single hydrological year.In addition,the spectral bands in cross amplitude functions and gain functions are small with 0.02,and the values in the coherence functions are small.All these behaviors illustrate that Jinan karst spring system has a strong memory effect,large storage capacity,noticeable regulation effect,and time series analysis is a useful tool for studying the hydrodynamic characteristics of karst spring system in northern China.
基金Supported by National Natural Science Foundation of China (No. 70931004)
文摘Traditional studies on integrated statistical process control and engineering process control (SPC-EPC) are based on linear autoregressive integrated moving average (ARIMA) time series models to describe the dynamic noise of the system.However,linear models sometimes are unable to model complex nonlinear autocorrelation.To solve this problem,this paper presents an integrated SPC-EPC method based on smooth transition autoregressive (STAR) time series model,and builds a minimum mean squared error (MMSE) controller as well as an integrated SPC-EPC control system.The performance of this method for checking the trend and sustained shift is analyzed.The simulation results indicate that this integrated SPC-EPC control method based on STAR model is effective in controlling complex nonlinear systems.
基金supported by the Initial Scientific Research Fund (No.2015QD02S)the Foundation Research Funds for the Central Universities (No.3122016A004, 3122017027)
文摘Electrostatic monitoring technology of particle charging information can facilitate online monitoring of aero-engine,which effectively enhances engine fault diagnosis and health managements.Unlike traditional engine state monitoring technologies,aircraft engine monitoring by gas path electrostatic monitoring not only covers the predicted information source itself,but also detects the information that can provide an early warnings for initial fault states through gas path charging levels.This paper establishes a non-stationary time sequence change-point model for anomaly recognition of electrostatic signals based on change-point theory combined with difference method of non-stationary time series.Finally,electrostatic induction data were utilized by the engine life test for a particular aircraft to validate the proposed algorithm.The results indicate that the activity level and the event rate were0.5—0.8(nc)and 50%,respectively,which were far greater than 4—12(pc)and 0—4% under normal working conditions of the engine.
文摘基于基波磁通补偿的串联混合型有源电力滤波器(active power filter,APF)应用于高电压、大容量的谐波抑制场合时,受变压器励磁支路谐波电压的影响,逆变器不能等效为基波电流源,其输出电流将含有大量的谐波,从而影响滤波效果。以逆变器为核心,推导出在励磁支路谐波压降影响下的串联变压器的谐波等效阻抗。并以此为基础,从理论上分析励磁电感和变比对串联变压器谐波等效阻抗和APF滤波效果的影响。仿真结果验证了理论分析的正确性。最后,针对广东某厂10kV、1MVA电力负荷,研制一套基于基波磁通补偿的串联混合型有源滤波器工程样机,取得非常好的滤波效果。
文摘Condition-based maintenance based on fault prediction has been widely concerned by the industry. Most of the contributions on fault prediction are based on various sensor data and mathematical models of the equipment. The complexity of the model and data signal is the key factor affecting the practicability of the model. In addition, even for the same type and batch of equipment, the manufacturing process, operation environment and other factors also affect the model parameters. In this paper, a series event model is conducted to predict the fault of marine diesel engines. Numerical example illustrates that the proposed event model is feasible.
基金supported by the National Natural Science Foundation of China(grant number 42171371 and No.41701492)Massimo Menenti acknowledges the support of the MOST High Level Foreign Expert program(grant number G2022055010L)the Chinese Academy of Sciences President s International Fellowship Initiative(grant number 2020VTA0001).
文摘Spatiotemporal residual noise in terrestrial earth observation products,often caused by unfavorable atmospheric conditions,impedes their broad applications.Most users prefer to use gap-filled remote sensing products with time series reconstruction(TSR)algorithms.Applying currently available implementations of TSR to large-volume datasets is time-consuming and challenging for non-professional users with limited computation or storage resources.This study introduces a new open-source software package entitled‘HANTS-GEE’that implements a well-known and robust TSR algorithm,i.e.Harmonic ANalysis of Time Series(HANTS),on the Google Earth Engine(GEE)platform for scalable reconstruction of terrestrial earth observation data.Reconstruction tasks can be conducted on user-defined spatiotemporal extents when raw datasets are available on GEE.According to site-based and regional-based case evaluation,the new tool can effectively eliminate cloud contamination in the time series of earth observation data.Compared with traditional PC-based HANTS implementation,the HANTS-GEE provides quite consistent reconstruction results for most terrestrial vegetated sites.The HANTS-GEE can provide scalable reconstruction services with accelerated processing speed and reduced internet data transmission volume,promoting algorithm usage by much broader user communities.To our knowledge,the software package is thefirst tool to support full-stack TSR processing for popular open-access satellite sensors on cloud platforms.