In recent decades,control performance monitoring(CPM)has experienced remarkable progress in research and industrial applications.While CPM research has been investigated using various benchmarks,the historical data be...In recent decades,control performance monitoring(CPM)has experienced remarkable progress in research and industrial applications.While CPM research has been investigated using various benchmarks,the historical data benchmark(HIS)has garnered the most attention due to its practicality and effectiveness.However,existing CPM reviews usually focus on the theoretical benchmark,and there is a lack of an in-depth review that thoroughly explores HIS-based methods.In this article,a comprehensive overview of HIS-based CPM is provided.First,we provide a novel static-dynamic perspective on data-level manifestations of control performance underlying typical controller capacities including regulation and servo:static and dynamic properties.The static property portrays time-independent variability in system output,and the dynamic property describes temporal behavior driven by closed-loop feedback.Accordingly,existing HIS-based CPM approaches and their intrinsic motivations are classified and analyzed from these two perspectives.Specifically,two mainstream solutions for CPM methods are summarized,including static analysis and dynamic analysis,which match data-driven techniques with actual controlling behavior.Furthermore,this paper also points out various opportunities and challenges faced in CPM for modern industry and provides promising directions in the context of artificial intelligence for inspiring future research.展开更多
A designed visual geometry group(VGG)-based convolutional neural network(CNN)model with small computational cost and high accuracy is utilized to monitor pulse amplitude modulation-based intensity modulation and direc...A designed visual geometry group(VGG)-based convolutional neural network(CNN)model with small computational cost and high accuracy is utilized to monitor pulse amplitude modulation-based intensity modulation and direct detection channel performance using eye diagram measurements.Experimental results show that the proposed technique can achieve a high accuracy in jointly monitoring modulation format,probabilistic shaping,roll-off factor,baud rate,optical signal-to-noise ratio,and chromatic dispersion.The designed VGG-based CNN model outperforms the other four traditional machine-learning methods in different scenarios.Furthermore,the multitask learning model combined with MobileNet CNN is designed to improve the flexibility of the network.Compared with the designed VGG-based CNN,the MobileNet-based MTL does not need to train all the classes,and it can simultaneously monitor single parameter or multiple parameters without sacrificing accuracy,indicating great potential in various monitoring scenarios.展开更多
A statistic-based benchmark was proposed for performance assessment and monitoring of model predic- tive control; the benchmark was straightforward and achievable by recording a set of output data only when the contro...A statistic-based benchmark was proposed for performance assessment and monitoring of model predic- tive control; the benchmark was straightforward and achievable by recording a set of output data only when the control performance was good according to the user’s selection. Principal component model was built and an auto- regressive moving average filter was identified to monitor the performance; an improved T2 statistic was selected as the performance monitor index. When performance changes were detected, diagnosis was done by model validation using recursive analysis and generalized likelihood ratio (GLR) method. This distinguished the fact that the per- formance change was due to plant model mismatch or due to disturbance term. Simulation was done about a heavy oil fractionator system and good results were obtained. The diagnosis result was helpful for the operator to improve the system performance.展开更多
Large-scale dense wavelength division multiplexing(DWDM)multi-channel performance monitoring is one of the indispensable technologies for the flexible optical networks.The existing Labelbased monitoring scheme require...Large-scale dense wavelength division multiplexing(DWDM)multi-channel performance monitoring is one of the indispensable technologies for the flexible optical networks.The existing Labelbased monitoring scheme requires expensive optical demultiplexing components/equipment to avoid the influence of stimulated Raman scattering(SRS),which is not only costly and bulky,but also could not monitor the wavelength channels simultaneously.In this paper,a low-cost,high-accuracy monitoring scheme based on Optical Label Method is proposed for DWDM networks,where the optical channel power and node identification(ID),as the main monitoring targets that both can indicate or evaluate the channel connection status,could be efficiently monitored.In the scheme,a novel digital signal processing(DSP)method of SRS mitigation is proposed and demonstrated,and an asynchronous code-division multiple access(A-CDMA)based digital label encoding and decoding method is adopted to distinguish the node ID so that channel initial added node can be accurately verified,thereby wavelength connection status can be reliably monitored by combining the channel power and node ID information.The simulation results show that each wavelength channel power and node ID can be accurately monitored only by low bandwidth photoelectric detector(PD)under the condition of 80 wavelengths and 10 spans at C-band.展开更多
Control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control sy...Control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities(e.g. valve stiction) present in most industrial control systems. In this work, a novel probability distribution distance based index is proposed to monitor the performance of non-linear control systems. The proposed method uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.展开更多
Learning Management System(LMS)is an application software that is used in automation,delivery,administration,tracking,and reporting of courses and programs in educational sector.The LMS which exploits machine learning...Learning Management System(LMS)is an application software that is used in automation,delivery,administration,tracking,and reporting of courses and programs in educational sector.The LMS which exploits machine learning(ML)has the ability of accessing user data and exploit it for improving the learning experience.The recently developed artificial intelligence(AI)and ML models helps to accomplish effective performance monitoring for LMS.Among the different processes involved in ML based LMS,feature selection and classification processesfind beneficial.In this motivation,this study introduces Glowworm-based Feature Selection with Machine Learning Enabled Performance Monitoring(GSO-MFWELM)technique for LMS.The key objective of the proposed GSO-MFWELM technique is to effectually monitor the performance in LMS.The pro-posed GSO-MFWELM technique involves GSO-based feature selection techni-que to select the optimal features.Besides,Weighted Extreme Learning Machine(WELM)model is applied for classification process whereas the parameters involved in WELM model are optimallyfine-tuned with the help of May-fly Optimization(MFO)algorithm.The design of GSO and MFO techniques result in reduced computation complexity and improved classification performance.The presented GSO-MFWELM technique was validated for its performance against benchmark dataset and the results were inspected under several aspects.The simulation results established the supremacy of GSO-MFWELM technique over recent approaches with the maximum classification accuracy of 0.9589.展开更多
Faults in rotating machine are difficult to detect and identify,especially when the system is complex and nonlinear.In order to solve this problem,a novel performance monitoring and fault diagnosis method based on ker...Faults in rotating machine are difficult to detect and identify,especially when the system is complex and nonlinear.In order to solve this problem,a novel performance monitoring and fault diagnosis method based on kernel generalized discriminant analysis(kernel GDA,KGDA)was proposed.Through KGDA,the data were mapped from the original space to the high-dimensional feature space.Then the statistic distance between normal data and test data was constructed to detect whether a fault was occurring.If a fault had occurred,similar analysis was used to identify the type of faults.The effectiveness of the proposed method was evaluated by simulation results of vibration signal fault dataset in the rotating machinery,which was scalable to different rotating machinery.展开更多
High performance control of an interactive process such as iron and steel plant relies on ability to honor safety and operational constraints;reduce the standard deviations of variables that need to be controlled(e.g....High performance control of an interactive process such as iron and steel plant relies on ability to honor safety and operational constraints;reduce the standard deviations of variables that need to be controlled(e.g.product quantity,quality );de-bottlenecking the process;and,maximize profitability or lower cost(e.g.energy savings, improve hot metal content).These objectives may be prioritized in this order,but can vary and are very difficult to achieve optimally through conventional control.A multivariable predictive controller solution,along with its extensive inferential sensor and built-in optimizer,provides online closed loop control and optimization for many interactive metal and mining processes to lower the energy cost,increase throughput,and optimize product quality and yield. Control loop performance is also a key factor to improve iron and steel plant automation and operation result; Honeywell CPM offers vender-independent product which provides monitoring,tuning,modeling of control loop and sustainable loop performance analysis and maintenance solution towards operation stability and energy saving.展开更多
This paper classifies and surveys different approaches proposed for performance monitoring, in particular the optical signal-to-noise ratio (OSNR) monitoring, in transparent reconfigurable WDM networks. Some considera...This paper classifies and surveys different approaches proposed for performance monitoring, in particular the optical signal-to-noise ratio (OSNR) monitoring, in transparent reconfigurable WDM networks. Some considerations for future monitoring schemes are discussed.展开更多
The mode of telecommunication network management is changing from“network oriented”to“subscriber oriented”.Aimed at enhancing subscribers’feeling,proactive performance monitoring(PPM)can enable a fast fault corre...The mode of telecommunication network management is changing from“network oriented”to“subscriber oriented”.Aimed at enhancing subscribers’feeling,proactive performance monitoring(PPM)can enable a fast fault correction by detecting anomalies designating performance degradation.In this paper,a novel anomaly detection approach is the proposed taking advantage of time series prediction and the associated confidence interval based on multiplicative autoregressive integrated moving average(ARIMA).Furthermore,under the assumption that the training residual is a white noise process following a normal distribution,the associated confidence interval of prediction can be figured out under any given confidence degree 1–αby constructing random variables satisfying t distribution.Experimental results verify the method’s effectiveness.展开更多
The energy efficiency monitoring is an essential precondition for ground source heat pump system's controlling and energy saving operation. Based on the data monitoring applied in the school building, this work is...The energy efficiency monitoring is an essential precondition for ground source heat pump system's controlling and energy saving operation. Based on the data monitoring applied in the school building, this work is focused on the parameters acquisition and operation analysis of the GSHP system in Tangshan. Results show the average COPs(coefficient of performance) are2.85 and 2.70 in summer and winter, respectively, and heat(cold) unbalance underground existed after whole year operation. The analysis of data also indicates that the direct borehole air-conditioning saved some power consumption obviously in the early stage of summer and energy saving of the GSHP system depended remarkably on its operation and management level. Besides the observation points of ground temperature are laid for a large-scale GSHP system, and the hydraulic balance of the pipes group needs to be concerned specially in safeguarding better reliability.展开更多
A technique using artificial neural networks trained with parameters derived from delay tap plots for optical performance monitoring in 40 Gbit/s duobinary system is demonstrated. Firstly, the optical signal is delay ...A technique using artificial neural networks trained with parameters derived from delay tap plots for optical performance monitoring in 40 Gbit/s duobinary system is demonstrated. Firstly, the optical signal is delay tap sampled to obtain two-dimensional histogram, known as delay tap plots. Secondly, the features of delay tap plots are extracted to train the feed forward, three-layer preceptor structure artificial neural networks. Finally, the outputs of trained neural network are used to monitor optical duobinary signal impairments. Simulation of optical signal noise ratio （ OSNR）, chromatic dispersion （CD）, and differential group delay （DGD） monitoring in 40 Gbit/s optical duo- binary system is presented. The proposed monitoring scheme can accurately identify simultaneous impairments without requiring synchronous sampling or data clock recovery. The proposed technique is simple, cost-effective and suitable for in-service distributed OPM.展开更多
Τhe efficiency of a Mewis propeller duct by the analysis of ship operational data is examined.The analysis employs data collected with high frequency for a three-year period for two siter vessels,one of them fitted w...Τhe efficiency of a Mewis propeller duct by the analysis of ship operational data is examined.The analysis employs data collected with high frequency for a three-year period for two siter vessels,one of them fitted with a Mewis type duct.Our approach to the problem of identifying improvements in the operational performance of the ship equipped with the duct is two-fold.Firstly,we proceed with the calculation of appropriate Key Performance Indicators to monitor vessels performance in time for different operational periods and loading conditions.An extensive pre-processing stage is necessary to prepare a dataset free from datapoints that could impair the analysis,such as outliers,as well as the appropriate preparations for a meaningful KPI calculation.The second approach concerns the development of multiple linear regression problem for the prediction of main engine fuel oil consumption based on operational and weather parameters,such as ship’s speed,mean draft,trim,rudder angle and the wind speed.The aim is to quantify reductions due to the Mewis duct for several scenarios.Key results of the studies reveal a contribution of the Mewis duct mainly in laden condition,for lower speed range and in the long-term period after dry-docking.展开更多
This paper presents a passive monitoring mechanism, loss）, nodes inference （LoNI）, to identify loss）, nodes in wireless sensor network using end-to-end application traffic. Given topology dynamics and bandwidth co...This paper presents a passive monitoring mechanism, loss）, nodes inference （LoNI）, to identify loss）, nodes in wireless sensor network using end-to-end application traffic. Given topology dynamics and bandwidth constraints, a space-efficient packet marking scheme is first introduced. The scheme uses a Bloom filter as a compression tool so that path information can bc piggybacked by data packets. Based on the path information, LoNI then adopts a fast algorithm to detect lossy nodes. The algorithm formulates the inference problem as a weighted set-cover problem and solves it using a greedy approach with low complexity. Simulations show that LoNI can locate about 80% of lossy nodes when lossy nodes are rare in the network. Furthermore, LoNI performs better for the lossy nodes near the sink or with higher loss rates.展开更多
With the growing environmental concerns, green supply chain management （GSCM） is gaining significant attention in the construction industry. Tracking and monitoring the environmental effects brought forth by the par...With the growing environmental concerns, green supply chain management （GSCM） is gaining significant attention in the construction industry. Tracking and monitoring the environmental effects brought forth by the participating members along a supply chain is important to GSCM. The GreenSCOR model developed by the Supply Chain Council provides a generic framework for measuring the total carbon footprint and environmental footprint in a supply chain. The model is based on the Supply Chain Operations Reference （SCOR） model, which represents a supply chain network in a hierarchically structured manner. This paper describes the GreenSCOR framework and its potential application to the construction industry. This paper also presents a web services approach to incorporate the GreenSCOR model to the implementation of collaborative information systems. Each process element in the SCOR model is represented and delivered as individual web service units, which can be reused and integrated using standard web services technologies. The service units are combined and managed in a prototype web service collaborative framework, called SC Collaborator, which is designed and developed for supporting construction supply chain management. An illustrative example is presented to demonstrate the implementation of the GreenSCOR-based SC Collaborator framework.展开更多
There is lack of performance monitoring technologies and related standards and specifications in the Puguang gas field,which is ultra-deep with high sulfur content.In this paper,five key technologies of dynamic monito...There is lack of performance monitoring technologies and related standards and specifications in the Puguang gas field,which is ultra-deep with high sulfur content.In this paper,five key technologies of dynamic monitoring were developed and the related standards and specifications were formulated by investigating high-sulfur gas fields at home and abroad,combined with equipment development,laboratory experiments,theoretical research and field tests.The five key technologies include gas production profile logging,downhole sampling and fluid phase analysis,dynamic water invasion prediction and water producing horizon identification,gas well productivity testing and evaluation,and development monitoring and safety control of high-sulfur ultra-deep wells.Then,these key technologies were applied for verification in the Puguang gas field.And the following research results were obtained.First,the sulfur-resistant gas production profile logging tool has a tem-perature resistance of 175℃and pressure resistance of 105 MPa.Forty-three well times gas production profile logging is carried out with a success ratio of 100%.Second,the high-sulfur downhole pressure sampler has a temperature resistance of 150℃and pressure resistance of 70 MPa.Seven well times downhole pressure sampling is carried out with a success ratio of 100%.Third,elemental sulfur is precipitated in the formation when the formation pressure drops to 29.5 MPa.And no sulfur is deposited in the wellbore when the production rate of gas well is higher than 20×10^(4)m^(3)/d.Fourth,water producing horizons can be identified accurately and water breakthrough time of gas wells can be predicted by using water producing horizon identification technology and dynamic water invasion prediction model.Water influx rates can be controlled and water-free gas production period of gas wells can be extended by optimizing and adjusting the working systems of gas wells.And fifth,full coverage of gas well productivity testing is realized by using the testing technology of"downhole implanted gauge&cable delivery&wellhead flow-variable rate",pressure calculation model and well testing interpretation model,and the productivity evaluation results of gas wells are accurate.Sixth,the dynamic gas tight pressure of the cable multi-stage leakage control system of super-high pressure and gas tightness is 50 MPa,and the processing technology for waste gas of blowout hookup is applied to 143 well times testing operation with zero leakage and zero pollution.In conclusion,these performance monitoring technologies have been playing an important role in scientifically formulating the production and reserves increase measures and ensuring long-term stable production of the Puguang gas field.展开更多
This paper introduces computational fluid used in aerospace engineering, to deal with surface physical and mathematical foundations of CFD, this traffic problems such as queue/platoon distribution, dynamics （CFD）, a...This paper introduces computational fluid used in aerospace engineering, to deal with surface physical and mathematical foundations of CFD, this traffic problems such as queue/platoon distribution, dynamics （CFD）, a numerical traffic flow related problems. approach widely and successfully After a brief introduction of the paper develops CFD implementation methodology for modeling shockwave propagation, and prediction of system performance. Some theoretical and practical applications are discussed in this paper to illustrate the implementation methodology. It is found that CFD approach can facilitate a superior insight into the formation and propagation of congestion, thereby supporting more effective methods to alleviate congestion. In addition, CFD approach is found capable of assessing freeway system performance using less ITS detectors, and enhancing the coverage and reliability of a traffic detection system.展开更多
For joint modulation format identification(MFI)and optical signal-to-noise ratio(OSNR)monitoring,a simple and intelligent optical communication performance monitoring method is proposed,and the feasibility is demonstr...For joint modulation format identification(MFI)and optical signal-to-noise ratio(OSNR)monitoring,a simple and intelligent optical communication performance monitoring method is proposed,and the feasibility is demonstrated by digital coherent optical communication experiments.The experiment results show that for all modulation formats,including 28 GBaud polarization division multiplexing(PDM)QPSK/8-QAM/16-QAM/64-QAM,100%MFI accuracies are achieved even at OSNR values lower than the corresponding theoretical 20%forward error correction limit,as well as the high accuracies for OSNR monitoring.Furthermore,the proposed scheme has a reasonable monitoring level when chromatic dispersion and fiber nonlinear effects are varied.展开更多
Here we present one design based on OWDP for secure high-speed IP network performance monitor system. Based on the analysis of OWDP protocol and the high-speed IP network performance's real-time monitor infrastruc...Here we present one design based on OWDP for secure high-speed IP network performance monitor system. Based on the analysis of OWDP protocol and the high-speed IP network performance's real-time monitor infrastructure, the paper illustrates the potential security problems in OWDP and its possible weakness when applied in the monitor infrastructure. One secure improvement design based on Otway-Rees authentication protocol is put forward, which can improve the security of the implementation of OWDP and the monitor architecture. Having kept OWDP's simplicity and efficiency, the design satisfies the real-time demand of high-speed network performance monitor and will effectively safeguard the monitor procedure against intensive attacks.展开更多
Low-cost,flexible and intelligent optical performance monitoring and management is a key enabling technology for network quality guarantee,especially in the era of explosive growth of communication capacity and networ...Low-cost,flexible and intelligent optical performance monitoring and management is a key enabling technology for network quality guarantee,especially in the era of explosive growth of communication capacity and network scale.However,to the best of our knowledge,it is extremely challenging to implement real-time performance monitoring and operations,administration and maintenance(OAM) in a highly complex dynamic network.In this paper,we propose an innovative optical identification(OID) scheme that can realize both performance monitoring and some advanced OAM sub-functions.The basic concepts,applications,challenges and evolution directions of this OID tool are also discussed.展开更多
基金supported in part by the National Natural Science Foundation of China(62125306)Zhejiang Key Research and Development Project(2024C01163)the State Key Laboratory of Industrial Control Technology,China(ICT2024A06)
文摘In recent decades,control performance monitoring(CPM)has experienced remarkable progress in research and industrial applications.While CPM research has been investigated using various benchmarks,the historical data benchmark(HIS)has garnered the most attention due to its practicality and effectiveness.However,existing CPM reviews usually focus on the theoretical benchmark,and there is a lack of an in-depth review that thoroughly explores HIS-based methods.In this article,a comprehensive overview of HIS-based CPM is provided.First,we provide a novel static-dynamic perspective on data-level manifestations of control performance underlying typical controller capacities including regulation and servo:static and dynamic properties.The static property portrays time-independent variability in system output,and the dynamic property describes temporal behavior driven by closed-loop feedback.Accordingly,existing HIS-based CPM approaches and their intrinsic motivations are classified and analyzed from these two perspectives.Specifically,two mainstream solutions for CPM methods are summarized,including static analysis and dynamic analysis,which match data-driven techniques with actual controlling behavior.Furthermore,this paper also points out various opportunities and challenges faced in CPM for modern industry and provides promising directions in the context of artificial intelligence for inspiring future research.
基金supported by the National Key Research and Development Program of China (Grant No.2019YFB1803700)the Key Technologies Research and Development Program of Tianjin (Grant No.20YFZCGX00440).
文摘A designed visual geometry group(VGG)-based convolutional neural network(CNN)model with small computational cost and high accuracy is utilized to monitor pulse amplitude modulation-based intensity modulation and direct detection channel performance using eye diagram measurements.Experimental results show that the proposed technique can achieve a high accuracy in jointly monitoring modulation format,probabilistic shaping,roll-off factor,baud rate,optical signal-to-noise ratio,and chromatic dispersion.The designed VGG-based CNN model outperforms the other four traditional machine-learning methods in different scenarios.Furthermore,the multitask learning model combined with MobileNet CNN is designed to improve the flexibility of the network.Compared with the designed VGG-based CNN,the MobileNet-based MTL does not need to train all the classes,and it can simultaneously monitor single parameter or multiple parameters without sacrificing accuracy,indicating great potential in various monitoring scenarios.
基金Supported by the National Natural Science Foundation of China (Nos.60474051, 60534020), the Key Technology and Devel-opment Program of Shanghai Science and Technology Department (No.04DZ11008), and the Program for New Century Ex-cellent Talents in the University of China (NCET).
文摘A statistic-based benchmark was proposed for performance assessment and monitoring of model predic- tive control; the benchmark was straightforward and achievable by recording a set of output data only when the control performance was good according to the user’s selection. Principal component model was built and an auto- regressive moving average filter was identified to monitor the performance; an improved T2 statistic was selected as the performance monitor index. When performance changes were detected, diagnosis was done by model validation using recursive analysis and generalized likelihood ratio (GLR) method. This distinguished the fact that the per- formance change was due to plant model mismatch or due to disturbance term. Simulation was done about a heavy oil fractionator system and good results were obtained. The diagnosis result was helpful for the operator to improve the system performance.
基金supported by the National Natural Science Foundation of China(No.62001045)Fund of State Key Laboratory of IPOC(BUPT)(No.IPOC2021ZT17)。
文摘Large-scale dense wavelength division multiplexing(DWDM)multi-channel performance monitoring is one of the indispensable technologies for the flexible optical networks.The existing Labelbased monitoring scheme requires expensive optical demultiplexing components/equipment to avoid the influence of stimulated Raman scattering(SRS),which is not only costly and bulky,but also could not monitor the wavelength channels simultaneously.In this paper,a low-cost,high-accuracy monitoring scheme based on Optical Label Method is proposed for DWDM networks,where the optical channel power and node identification(ID),as the main monitoring targets that both can indicate or evaluate the channel connection status,could be efficiently monitored.In the scheme,a novel digital signal processing(DSP)method of SRS mitigation is proposed and demonstrated,and an asynchronous code-division multiple access(A-CDMA)based digital label encoding and decoding method is adopted to distinguish the node ID so that channel initial added node can be accurately verified,thereby wavelength connection status can be reliably monitored by combining the channel power and node ID information.The simulation results show that each wavelength channel power and node ID can be accurately monitored only by low bandwidth photoelectric detector(PD)under the condition of 80 wavelengths and 10 spans at C-band.
基金Supported by the National Natural Science Foundation of China(61134007,61203157)the National Science Fund for Outstanding Young Scholars(61222303)+1 种基金the Fundamental Research Funds for the Central Universities(22A20151405)Shanghai R&D Platform Construction Program(13DZ2295300)
文摘Control performance monitoring has attracted great attention in both academia and industry over the past two decades. However, most research efforts have been devoted to the performance monitoring of linear control systems, without considering the pervasive nonlinearities(e.g. valve stiction) present in most industrial control systems. In this work, a novel probability distribution distance based index is proposed to monitor the performance of non-linear control systems. The proposed method uses Hellinger distance to evaluate change of control system performance. Several simulation examples are given to illustrate the effectiveness of the proposed method.
基金supported by the Researchers Supporting Program(TUMA-Project2021-27)Almaarefa University,RiyadhSaudi Arabia.Taif University Researchers Supporting Project number(TURSP-2020/161)Taif University,Taif,Saudi Arabia.
文摘Learning Management System(LMS)is an application software that is used in automation,delivery,administration,tracking,and reporting of courses and programs in educational sector.The LMS which exploits machine learning(ML)has the ability of accessing user data and exploit it for improving the learning experience.The recently developed artificial intelligence(AI)and ML models helps to accomplish effective performance monitoring for LMS.Among the different processes involved in ML based LMS,feature selection and classification processesfind beneficial.In this motivation,this study introduces Glowworm-based Feature Selection with Machine Learning Enabled Performance Monitoring(GSO-MFWELM)technique for LMS.The key objective of the proposed GSO-MFWELM technique is to effectually monitor the performance in LMS.The pro-posed GSO-MFWELM technique involves GSO-based feature selection techni-que to select the optimal features.Besides,Weighted Extreme Learning Machine(WELM)model is applied for classification process whereas the parameters involved in WELM model are optimallyfine-tuned with the help of May-fly Optimization(MFO)algorithm.The design of GSO and MFO techniques result in reduced computation complexity and improved classification performance.The presented GSO-MFWELM technique was validated for its performance against benchmark dataset and the results were inspected under several aspects.The simulation results established the supremacy of GSO-MFWELM technique over recent approaches with the maximum classification accuracy of 0.9589.
基金National Natural Science Foundation of China(No.60504033)
文摘Faults in rotating machine are difficult to detect and identify,especially when the system is complex and nonlinear.In order to solve this problem,a novel performance monitoring and fault diagnosis method based on kernel generalized discriminant analysis(kernel GDA,KGDA)was proposed.Through KGDA,the data were mapped from the original space to the high-dimensional feature space.Then the statistic distance between normal data and test data was constructed to detect whether a fault was occurring.If a fault had occurred,similar analysis was used to identify the type of faults.The effectiveness of the proposed method was evaluated by simulation results of vibration signal fault dataset in the rotating machinery,which was scalable to different rotating machinery.
文摘High performance control of an interactive process such as iron and steel plant relies on ability to honor safety and operational constraints;reduce the standard deviations of variables that need to be controlled(e.g.product quantity,quality );de-bottlenecking the process;and,maximize profitability or lower cost(e.g.energy savings, improve hot metal content).These objectives may be prioritized in this order,but can vary and are very difficult to achieve optimally through conventional control.A multivariable predictive controller solution,along with its extensive inferential sensor and built-in optimizer,provides online closed loop control and optimization for many interactive metal and mining processes to lower the energy cost,increase throughput,and optimize product quality and yield. Control loop performance is also a key factor to improve iron and steel plant automation and operation result; Honeywell CPM offers vender-independent product which provides monitoring,tuning,modeling of control loop and sustainable loop performance analysis and maintenance solution towards operation stability and energy saving.
文摘This paper classifies and surveys different approaches proposed for performance monitoring, in particular the optical signal-to-noise ratio (OSNR) monitoring, in transparent reconfigurable WDM networks. Some considerations for future monitoring schemes are discussed.
基金supported by the National Key Technologies R&D program of China during the 11th Five-Year Plan Period (No.2006BAH02A03).
文摘The mode of telecommunication network management is changing from“network oriented”to“subscriber oriented”.Aimed at enhancing subscribers’feeling,proactive performance monitoring(PPM)can enable a fast fault correction by detecting anomalies designating performance degradation.In this paper,a novel anomaly detection approach is the proposed taking advantage of time series prediction and the associated confidence interval based on multiplicative autoregressive integrated moving average(ARIMA).Furthermore,under the assumption that the training residual is a white noise process following a normal distribution,the associated confidence interval of prediction can be figured out under any given confidence degree 1–αby constructing random variables satisfying t distribution.Experimental results verify the method’s effectiveness.
基金Project(2012BAJ06B04)supported by"12th Five-Year Plan"National science and Technology,ChinaProject(2014-228)supported by Department of Housing and Urban Rural Development of Hebei,China
文摘The energy efficiency monitoring is an essential precondition for ground source heat pump system's controlling and energy saving operation. Based on the data monitoring applied in the school building, this work is focused on the parameters acquisition and operation analysis of the GSHP system in Tangshan. Results show the average COPs(coefficient of performance) are2.85 and 2.70 in summer and winter, respectively, and heat(cold) unbalance underground existed after whole year operation. The analysis of data also indicates that the direct borehole air-conditioning saved some power consumption obviously in the early stage of summer and energy saving of the GSHP system depended remarkably on its operation and management level. Besides the observation points of ground temperature are laid for a large-scale GSHP system, and the hydraulic balance of the pipes group needs to be concerned specially in safeguarding better reliability.
基金Supported by the National Natural Science Foundation of China (60978007 61027007 61177067)
文摘A technique using artificial neural networks trained with parameters derived from delay tap plots for optical performance monitoring in 40 Gbit/s duobinary system is demonstrated. Firstly, the optical signal is delay tap sampled to obtain two-dimensional histogram, known as delay tap plots. Secondly, the features of delay tap plots are extracted to train the feed forward, three-layer preceptor structure artificial neural networks. Finally, the outputs of trained neural network are used to monitor optical duobinary signal impairments. Simulation of optical signal noise ratio （ OSNR）, chromatic dispersion （CD）, and differential group delay （DGD） monitoring in 40 Gbit/s optical duo- binary system is presented. The proposed monitoring scheme can accurately identify simultaneous impairments without requiring synchronous sampling or data clock recovery. The proposed technique is simple, cost-effective and suitable for in-service distributed OPM.
文摘Τhe efficiency of a Mewis propeller duct by the analysis of ship operational data is examined.The analysis employs data collected with high frequency for a three-year period for two siter vessels,one of them fitted with a Mewis type duct.Our approach to the problem of identifying improvements in the operational performance of the ship equipped with the duct is two-fold.Firstly,we proceed with the calculation of appropriate Key Performance Indicators to monitor vessels performance in time for different operational periods and loading conditions.An extensive pre-processing stage is necessary to prepare a dataset free from datapoints that could impair the analysis,such as outliers,as well as the appropriate preparations for a meaningful KPI calculation.The second approach concerns the development of multiple linear regression problem for the prediction of main engine fuel oil consumption based on operational and weather parameters,such as ship’s speed,mean draft,trim,rudder angle and the wind speed.The aim is to quantify reductions due to the Mewis duct for several scenarios.Key results of the studies reveal a contribution of the Mewis duct mainly in laden condition,for lower speed range and in the long-term period after dry-docking.
文摘This paper presents a passive monitoring mechanism, loss）, nodes inference （LoNI）, to identify loss）, nodes in wireless sensor network using end-to-end application traffic. Given topology dynamics and bandwidth constraints, a space-efficient packet marking scheme is first introduced. The scheme uses a Bloom filter as a compression tool so that path information can bc piggybacked by data packets. Based on the path information, LoNI then adopts a fast algorithm to detect lossy nodes. The algorithm formulates the inference problem as a weighted set-cover problem and solves it using a greedy approach with low complexity. Simulations show that LoNI can locate about 80% of lossy nodes when lossy nodes are rare in the network. Furthermore, LoNI performs better for the lossy nodes near the sink or with higher loss rates.
文摘With the growing environmental concerns, green supply chain management （GSCM） is gaining significant attention in the construction industry. Tracking and monitoring the environmental effects brought forth by the participating members along a supply chain is important to GSCM. The GreenSCOR model developed by the Supply Chain Council provides a generic framework for measuring the total carbon footprint and environmental footprint in a supply chain. The model is based on the Supply Chain Operations Reference （SCOR） model, which represents a supply chain network in a hierarchically structured manner. This paper describes the GreenSCOR framework and its potential application to the construction industry. This paper also presents a web services approach to incorporate the GreenSCOR model to the implementation of collaborative information systems. Each process element in the SCOR model is represented and delivered as individual web service units, which can be reused and integrated using standard web services technologies. The service units are combined and managed in a prototype web service collaborative framework, called SC Collaborator, which is designed and developed for supporting construction supply chain management. An illustrative example is presented to demonstrate the implementation of the GreenSCOR-based SC Collaborator framework.
基金Project supported by the National Major Science and Technology Project“Safe&Effective Development of High-Sulfur Gas Reservoir(PhaseⅢ)”(No.:2016ZX05017)the Sinopec’s“Ten-Project”Scientific Research Project“Enhanced Gas Recovery Technology for Ultra-Deep&High-Sulfur Gas Field”(No.:P18062).
文摘There is lack of performance monitoring technologies and related standards and specifications in the Puguang gas field,which is ultra-deep with high sulfur content.In this paper,five key technologies of dynamic monitoring were developed and the related standards and specifications were formulated by investigating high-sulfur gas fields at home and abroad,combined with equipment development,laboratory experiments,theoretical research and field tests.The five key technologies include gas production profile logging,downhole sampling and fluid phase analysis,dynamic water invasion prediction and water producing horizon identification,gas well productivity testing and evaluation,and development monitoring and safety control of high-sulfur ultra-deep wells.Then,these key technologies were applied for verification in the Puguang gas field.And the following research results were obtained.First,the sulfur-resistant gas production profile logging tool has a tem-perature resistance of 175℃and pressure resistance of 105 MPa.Forty-three well times gas production profile logging is carried out with a success ratio of 100%.Second,the high-sulfur downhole pressure sampler has a temperature resistance of 150℃and pressure resistance of 70 MPa.Seven well times downhole pressure sampling is carried out with a success ratio of 100%.Third,elemental sulfur is precipitated in the formation when the formation pressure drops to 29.5 MPa.And no sulfur is deposited in the wellbore when the production rate of gas well is higher than 20×10^(4)m^(3)/d.Fourth,water producing horizons can be identified accurately and water breakthrough time of gas wells can be predicted by using water producing horizon identification technology and dynamic water invasion prediction model.Water influx rates can be controlled and water-free gas production period of gas wells can be extended by optimizing and adjusting the working systems of gas wells.And fifth,full coverage of gas well productivity testing is realized by using the testing technology of"downhole implanted gauge&cable delivery&wellhead flow-variable rate",pressure calculation model and well testing interpretation model,and the productivity evaluation results of gas wells are accurate.Sixth,the dynamic gas tight pressure of the cable multi-stage leakage control system of super-high pressure and gas tightness is 50 MPa,and the processing technology for waste gas of blowout hookup is applied to 143 well times testing operation with zero leakage and zero pollution.In conclusion,these performance monitoring technologies have been playing an important role in scientifically formulating the production and reserves increase measures and ensuring long-term stable production of the Puguang gas field.
文摘This paper introduces computational fluid used in aerospace engineering, to deal with surface physical and mathematical foundations of CFD, this traffic problems such as queue/platoon distribution, dynamics （CFD）, a numerical traffic flow related problems. approach widely and successfully After a brief introduction of the paper develops CFD implementation methodology for modeling shockwave propagation, and prediction of system performance. Some theoretical and practical applications are discussed in this paper to illustrate the implementation methodology. It is found that CFD approach can facilitate a superior insight into the formation and propagation of congestion, thereby supporting more effective methods to alleviate congestion. In addition, CFD approach is found capable of assessing freeway system performance using less ITS detectors, and enhancing the coverage and reliability of a traffic detection system.
基金This work was supported by the National Key Research and Development Program of China(No.2021YFB2206303)Key Research and Development Plan of Shandong Province(No.2023CXPT100)+1 种基金Sichuan Science Fund for Distinguished Young Scholars(No.2023NSFSC1969)National Student Research Training Program of China(No.20230613037).
文摘For joint modulation format identification(MFI)and optical signal-to-noise ratio(OSNR)monitoring,a simple and intelligent optical communication performance monitoring method is proposed,and the feasibility is demonstrated by digital coherent optical communication experiments.The experiment results show that for all modulation formats,including 28 GBaud polarization division multiplexing(PDM)QPSK/8-QAM/16-QAM/64-QAM,100%MFI accuracies are achieved even at OSNR values lower than the corresponding theoretical 20%forward error correction limit,as well as the high accuracies for OSNR monitoring.Furthermore,the proposed scheme has a reasonable monitoring level when chromatic dispersion and fiber nonlinear effects are varied.
基金Supported by the86 3National High-Tech Project( 86 3-30 0 -0 2 -0 9-99) and Key Research Project of Hubei Province( 991P110 )
文摘Here we present one design based on OWDP for secure high-speed IP network performance monitor system. Based on the analysis of OWDP protocol and the high-speed IP network performance's real-time monitor infrastructure, the paper illustrates the potential security problems in OWDP and its possible weakness when applied in the monitor infrastructure. One secure improvement design based on Otway-Rees authentication protocol is put forward, which can improve the security of the implementation of OWDP and the monitor architecture. Having kept OWDP's simplicity and efficiency, the design satisfies the real-time demand of high-speed network performance monitor and will effectively safeguard the monitor procedure against intensive attacks.
基金supported in part by the National Key R&D Program of China under Grant No.2019YFB2205302。
文摘Low-cost,flexible and intelligent optical performance monitoring and management is a key enabling technology for network quality guarantee,especially in the era of explosive growth of communication capacity and network scale.However,to the best of our knowledge,it is extremely challenging to implement real-time performance monitoring and operations,administration and maintenance(OAM) in a highly complex dynamic network.In this paper,we propose an innovative optical identification(OID) scheme that can realize both performance monitoring and some advanced OAM sub-functions.The basic concepts,applications,challenges and evolution directions of this OID tool are also discussed.
