Fouling caused by excess metal ions in hard water can negatively impact the performance of the circulating cooling water system(CCWS)by depositing ions on the heat exchanger's surface.Currently,the operation optim...Fouling caused by excess metal ions in hard water can negatively impact the performance of the circulating cooling water system(CCWS)by depositing ions on the heat exchanger's surface.Currently,the operation optimization of CCWS often prioritizes short-term flow velocity optimization for minimizing power consumption,without considering fouling.However,low flow velocity promotes fouling.Therefore,it's crucial to balance fouling and energy/water conservation for optimal CCWS long-term operation.This study proposes a mixed-integer nonlinear programming(MINLP)model to achieve this goal.The model considers fouling in the pipeline,dynamic concentration cycle,and variable frequency drive to optimize the synergy between heat transfer,pressure drop,and fouling.By optimizing the concentration cycle of the CCWS,water conservation and fouling control can be achieved.The model can obtain the optimal operating parameters for different operation intervals,including the number of pumps,frequency,and valve local resistance coefficient.Sensitivity experiments on cycle and environmental temperature reveal that as the cycle increases,the marginal benefits of energy/water conservation decrease.In periods with minimal impact on fouling rate,energy/water conservation can be achieved by increasing the cycle while maintaining a low fouling rate.Overall,the proposed model has significant energy/water saving effects and can comprehensively optimize the CCWS through its incorporation of fouling and cycle optimization.展开更多
Each joint of hydraulic drive quadruped robot is driven by the hydraulic drive unit(HDU), and the contacting between the robot foot end and the ground is complex and variable, which increases the difficulty of force...Each joint of hydraulic drive quadruped robot is driven by the hydraulic drive unit(HDU), and the contacting between the robot foot end and the ground is complex and variable, which increases the difficulty of force control inevitably. In the recent years, although many scholars researched some control methods such as disturbance rejection control, parameter self-adaptive control, impedance control and so on, to improve the force control performance of HDU, the robustness of the force control still needs improving. Therefore, how to simulate the complex and variable load characteristics of the environment structure and how to ensure HDU having excellent force control performance with the complex and variable load characteristics are key issues to be solved in this paper. The force control system mathematic model of HDU is established by the mechanism modeling method, and the theoretical models of a novel force control compensation method and a load characteristics simulation method under different environment structures are derived, considering the dynamic characteristics of the load stiffness and the load damping under different environment structures. Then, simulation effects of the variable load stiffness and load damping under the step and sinusoidal load force are analyzed experimentally on the HDU force control performance test platform, which provides the foundation for the force control compensation experiment research. In addition, the optimized PID control parameters are designed to make the HDU have better force control performance with suitable load stiffness and load damping, under which the force control compensation method is introduced, and the robustness of the force control system with several constant load characteristics and the variable load characteristics respectively are comparatively analyzed by experiment. The research results indicate that if the load characteristics are known, the force control compensation method presented in this paper has positive compensation effects on the load characteristics variation, i.e., this method decreases the effects of the load characteristics variation on the force control performance and enhances the force control system robustness with the constant PID parameters, thereby, the online PID parameters tuning control method which is complex needs not be adopted. All the above research provides theoretical and experimental foundation for the force control method of the quadruped robot joints with high robustness.展开更多
Vibration failure in the pumping system is a significant issue for indus-tries that rely on the pump as a critical device which requires regular maintenance.To save energy and money,a new automated system must be devel...Vibration failure in the pumping system is a significant issue for indus-tries that rely on the pump as a critical device which requires regular maintenance.To save energy and money,a new automated system must be developed that can detect anomalies at an early stage.This paper presents a case study of a machine learning(ML)-based computational technique for automatic fault detection in a cascade pumping system based on variable frequency drive(VFD).Since the intensity of the vibrational effect depends on which axis has the most significant effect,a three-axis accelerometer is used to measure it in the pumping system.The emphasis is on determining the vibration effect on different axes.For experiment,various ML algorithms are investigated on collected vibratory data through Matlab software in x,y,z axes and performances of the algorithms are compared based on accuracy rate,prediction speed and training time.Based on the proposed research results,the multiclass support vector machine(MSVM)is found to be the best suitable algorithm compared to other algorithms.It has been demonstrated that ML algorithms can detect faults automatically rather than conventional meth-ods.MSVM is used for the proposed work because it is less complex and pro-duces better results with a limited data set.展开更多
Investigation on spatiotemporal variations of maximum seasonal freeze depth (MSFD) over the Heihe River Basin is of great importance for systematic understanding of regional climate and environmental change, ecologi...Investigation on spatiotemporal variations of maximum seasonal freeze depth (MSFD) over the Heihe River Basin is of great importance for systematic understanding of regional climate and environmental change, ecological-hydrological processes, water resources assessment, construction and resource development. Based on soil and air temperatures at the meteorological stations of the China Meteorological Administration (CMA) over the Heihe River Basin, MSFDs time series are structured into a composite time series over the 1960-2007 period. Evaluating the averaged MSFD time series for 1960 2007 reveals a statistically significant trend of 4.0 cm/decade or a net change of-19.2 cm for the 48-year period over the basin. The MSFD had significantly negative correlation with mean annual air temperature (MAAT), winter air temperature, mean annual ground surface temperature (MAGST), degree days of thawing for the air (DDTa) as well as for the surface (DDTs), and degree days of freezing for the surface (DDFs). While there was significantly positive correlation between DDF,. and MSFD time series, MSFD was deeper and changed greatly in the Heihe River source area. It was shallower in the east-central basin and gradually deepened in other sections of the basin. The MSFD distribution pattern in 2003-2005 is consistent with that of averaged degree days of freezing for air (DDFa) in 1960-2007. However, the maximum of MSFD may not be accurate, because there is no long term observation data in the deep seasonally frozen ground regions near the lower boundary of permafrost. With increasing elevation, averaged DDFa increased at a rate of 51.6 ℃-day/100m, therefore, the MSFG and the date reaching MSFG became deeper and later, respectively.展开更多
Dust collection systems represent a significant portion of a wood product manufacturer’s total electricity use. The system fan works against the static pressure of the entire system—the blast gates, the ductwork, an...Dust collection systems represent a significant portion of a wood product manufacturer’s total electricity use. The system fan works against the static pressure of the entire system—the blast gates, the ductwork, and the upstream or downstream cyclone and/or baghouse. A poor system design (e.g., sharp elbows or undersized ductwork) increases the total amount of static pressure in the system, the fan’s performance curve shifts, increasing the total brake horsepower required by the fan (up to the maximum point on the curve). Additionally, system designers may oversize a dust collection system to ensure adequate dust capture and transport, either to accommodate system expansion or simply to be conservative. Since theoretical fan energy use increases with its velocity cubed, this can be an expensive safety net. This paper presents a comprehensive literature review about industrial cyclone dust collectors energy saving in relation to management, technologies, and policies. Energy-saving technologies like high-efficiency motors (HEMs), variable-speed drives (VSDs), leak detection, and pressure drop reduction have all been examined. Based on energy saving technologies results, it has been found that in the industrial sectors, a sizeable amount of electric energy, and utility bill can be saved using these technologies. Finally, various energy-saving policies were reviewed.展开更多
In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of ...In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of DC drives. Precise control of drives is the main attribute in industries to optimize the performance and to increase its production rate. In motion control, the major considerations are the torque and speed ripples. Design of controllers has become increasingly complex to such systems for better management of energy and raw materials to attain optimal performance. Meager parameter appraisal results are unsuitable, leading to unstable operation. The rapid intensification of digital computer revolutionizes to practice precise control and allows implementation of advanced control strategy to extremely multifaceted systems. To solve complex control problems, model predictive control is an authoritative scheme, which exploits an explicit model of the process to be controlled. This paper presents a predictive control strategy by a neural network predictive controller based single phase induction motor drive to minimize the speed and torque ripples. The proposed method exhibits better performance than the conventional controller and validity of the proposed method is verified by the simulation results using MATLAB software.展开更多
基金Financial support from the National Natural Science Foundation of China (22022816 and 22078358)
文摘Fouling caused by excess metal ions in hard water can negatively impact the performance of the circulating cooling water system(CCWS)by depositing ions on the heat exchanger's surface.Currently,the operation optimization of CCWS often prioritizes short-term flow velocity optimization for minimizing power consumption,without considering fouling.However,low flow velocity promotes fouling.Therefore,it's crucial to balance fouling and energy/water conservation for optimal CCWS long-term operation.This study proposes a mixed-integer nonlinear programming(MINLP)model to achieve this goal.The model considers fouling in the pipeline,dynamic concentration cycle,and variable frequency drive to optimize the synergy between heat transfer,pressure drop,and fouling.By optimizing the concentration cycle of the CCWS,water conservation and fouling control can be achieved.The model can obtain the optimal operating parameters for different operation intervals,including the number of pumps,frequency,and valve local resistance coefficient.Sensitivity experiments on cycle and environmental temperature reveal that as the cycle increases,the marginal benefits of energy/water conservation decrease.In periods with minimal impact on fouling rate,energy/water conservation can be achieved by increasing the cycle while maintaining a low fouling rate.Overall,the proposed model has significant energy/water saving effects and can comprehensively optimize the CCWS through its incorporation of fouling and cycle optimization.
基金Supported by National Key Basic Research Program of China(973 Program,Grant No.2014CB046405)State Key Laboratory of Fluid Power and Mechatronic Systems(Zhejiang University)Open Fund Project(Grant No.GZKF-201502)Hebei Military and Civilian Industry Development Funds Projects of China(Grant No.2015B060)
文摘Each joint of hydraulic drive quadruped robot is driven by the hydraulic drive unit(HDU), and the contacting between the robot foot end and the ground is complex and variable, which increases the difficulty of force control inevitably. In the recent years, although many scholars researched some control methods such as disturbance rejection control, parameter self-adaptive control, impedance control and so on, to improve the force control performance of HDU, the robustness of the force control still needs improving. Therefore, how to simulate the complex and variable load characteristics of the environment structure and how to ensure HDU having excellent force control performance with the complex and variable load characteristics are key issues to be solved in this paper. The force control system mathematic model of HDU is established by the mechanism modeling method, and the theoretical models of a novel force control compensation method and a load characteristics simulation method under different environment structures are derived, considering the dynamic characteristics of the load stiffness and the load damping under different environment structures. Then, simulation effects of the variable load stiffness and load damping under the step and sinusoidal load force are analyzed experimentally on the HDU force control performance test platform, which provides the foundation for the force control compensation experiment research. In addition, the optimized PID control parameters are designed to make the HDU have better force control performance with suitable load stiffness and load damping, under which the force control compensation method is introduced, and the robustness of the force control system with several constant load characteristics and the variable load characteristics respectively are comparatively analyzed by experiment. The research results indicate that if the load characteristics are known, the force control compensation method presented in this paper has positive compensation effects on the load characteristics variation, i.e., this method decreases the effects of the load characteristics variation on the force control performance and enhances the force control system robustness with the constant PID parameters, thereby, the online PID parameters tuning control method which is complex needs not be adopted. All the above research provides theoretical and experimental foundation for the force control method of the quadruped robot joints with high robustness.
文摘Vibration failure in the pumping system is a significant issue for indus-tries that rely on the pump as a critical device which requires regular maintenance.To save energy and money,a new automated system must be developed that can detect anomalies at an early stage.This paper presents a case study of a machine learning(ML)-based computational technique for automatic fault detection in a cascade pumping system based on variable frequency drive(VFD).Since the intensity of the vibrational effect depends on which axis has the most significant effect,a three-axis accelerometer is used to measure it in the pumping system.The emphasis is on determining the vibration effect on different axes.For experiment,various ML algorithms are investigated on collected vibratory data through Matlab software in x,y,z axes and performances of the algorithms are compared based on accuracy rate,prediction speed and training time.Based on the proposed research results,the multiclass support vector machine(MSVM)is found to be the best suitable algorithm compared to other algorithms.It has been demonstrated that ML algorithms can detect faults automatically rather than conventional meth-ods.MSVM is used for the proposed work because it is less complex and pro-duces better results with a limited data set.
基金supported by the Global Change Research Program of China (No. 2010CB951402)the Natural Science Foundation of China (Nos. 91025013, 91325202)+1 种基金the State Key Laboratory of Frozen Soil Engineering (No. SKLFSE-ZY-06), CAS, Chinathe Major Research Plan of the Natural Science Foundation of China (No. 2013CBA01802)
文摘Investigation on spatiotemporal variations of maximum seasonal freeze depth (MSFD) over the Heihe River Basin is of great importance for systematic understanding of regional climate and environmental change, ecological-hydrological processes, water resources assessment, construction and resource development. Based on soil and air temperatures at the meteorological stations of the China Meteorological Administration (CMA) over the Heihe River Basin, MSFDs time series are structured into a composite time series over the 1960-2007 period. Evaluating the averaged MSFD time series for 1960 2007 reveals a statistically significant trend of 4.0 cm/decade or a net change of-19.2 cm for the 48-year period over the basin. The MSFD had significantly negative correlation with mean annual air temperature (MAAT), winter air temperature, mean annual ground surface temperature (MAGST), degree days of thawing for the air (DDTa) as well as for the surface (DDTs), and degree days of freezing for the surface (DDFs). While there was significantly positive correlation between DDF,. and MSFD time series, MSFD was deeper and changed greatly in the Heihe River source area. It was shallower in the east-central basin and gradually deepened in other sections of the basin. The MSFD distribution pattern in 2003-2005 is consistent with that of averaged degree days of freezing for air (DDFa) in 1960-2007. However, the maximum of MSFD may not be accurate, because there is no long term observation data in the deep seasonally frozen ground regions near the lower boundary of permafrost. With increasing elevation, averaged DDFa increased at a rate of 51.6 ℃-day/100m, therefore, the MSFG and the date reaching MSFG became deeper and later, respectively.
文摘Dust collection systems represent a significant portion of a wood product manufacturer’s total electricity use. The system fan works against the static pressure of the entire system—the blast gates, the ductwork, and the upstream or downstream cyclone and/or baghouse. A poor system design (e.g., sharp elbows or undersized ductwork) increases the total amount of static pressure in the system, the fan’s performance curve shifts, increasing the total brake horsepower required by the fan (up to the maximum point on the curve). Additionally, system designers may oversize a dust collection system to ensure adequate dust capture and transport, either to accommodate system expansion or simply to be conservative. Since theoretical fan energy use increases with its velocity cubed, this can be an expensive safety net. This paper presents a comprehensive literature review about industrial cyclone dust collectors energy saving in relation to management, technologies, and policies. Energy-saving technologies like high-efficiency motors (HEMs), variable-speed drives (VSDs), leak detection, and pressure drop reduction have all been examined. Based on energy saving technologies results, it has been found that in the industrial sectors, a sizeable amount of electric energy, and utility bill can be saved using these technologies. Finally, various energy-saving policies were reviewed.
文摘In industrial drives, electric motors are extensively utilized to impart motion control and induction motors are the most familiar drive at present due to its extensive performance characteristic similar with that of DC drives. Precise control of drives is the main attribute in industries to optimize the performance and to increase its production rate. In motion control, the major considerations are the torque and speed ripples. Design of controllers has become increasingly complex to such systems for better management of energy and raw materials to attain optimal performance. Meager parameter appraisal results are unsuitable, leading to unstable operation. The rapid intensification of digital computer revolutionizes to practice precise control and allows implementation of advanced control strategy to extremely multifaceted systems. To solve complex control problems, model predictive control is an authoritative scheme, which exploits an explicit model of the process to be controlled. This paper presents a predictive control strategy by a neural network predictive controller based single phase induction motor drive to minimize the speed and torque ripples. The proposed method exhibits better performance than the conventional controller and validity of the proposed method is verified by the simulation results using MATLAB software.