The present work is based on the third-order partial differential equation (PDE) of acoustics of viscoelastic solids for the quasi-equilibrium (QE) component of the average normal stress. This PDE includes the stress-...The present work is based on the third-order partial differential equation (PDE) of acoustics of viscoelastic solids for the quasi-equilibrium (QE) component of the average normal stress. This PDE includes the stress-relaxation time (SRT) for the material and is applicable at any value of the SRT. The notion of a smart deicing system (SDS) for blade shells (BSs) of a wind turbine is specified. The work considers the stress in a BS as the one caused by the operational load on the BS. The work develops key design issues of a prospective ice-detection system (IDS) able to supply an array of the heating elements of an SDS with the element-individual spatiotemporal data and procedures for identification of the material parameters of atmospheric-ice (AI) layer accreted on the outer surfaces of the BSs. Both the SDS and IDS flexibly allow for complex, curvilinear and space-time-varying shapes of BSs. The proposed IDS presumes monitoring of the QE components of the normal stresses in BSs. The IDS is supposed to include an array of pressure-sensing resistors, also known as force-sensing resistors (FSRs), and communication hardware, as well as the parameter-identification software package (PISP), which provides the identification on the basis of the aforementioned PDE and the data measured by the FSRs. The IDS does not have hardware components located outside the outer surfaces of, or implanted in, BSs. The FSR array and communication hardware are reliable, and both cost- and energy-efficient. The present work extends methods of structural-health/operational-load monitoring (SH/OL-M) with measurements of the operational-load-caused stress in closed solid shells and, if the prospective PISP is used, endows the methods with identification of material parameters of the shells. The identification algorithms that can underlie the PISP are computationally efficient and suitable for implementation in the real-time mode. The identification model and algorithms can deal with not only the single-layer systems such as the BS layer without the AI layer or two-layer systems but also multi-layer systems. The outcomes can be applied to not only BSs of wind turbines but also non-QE closed single- or multi-layer deformable solid shells of various engineering systems (e.g., the shells of driver or passenger compartments of ships, cars, busses, airplanes, and other vehicles). The proposed monitoring of the normal-stress QE component in the mentioned shells extends the methods of SH/OL-M. The topic for the nearest research is a better adjustment of the settings for the FSR-based measurement of the mentioned components and a calibration of the parameter-identification model and algorithms, as well as the resulting improvement of the PISP.展开更多
可通过有效控制风力机叶片的升力间接减小风力机的疲劳载荷,提高风力机的可靠性。该文建立了基于尾缘襟翼的风力机叶片试验模型静态升力控制系统仿真平台。该系统在上位机Matlab/Simulink中建立叶片试验模型静态升力的数学模型和系统控...可通过有效控制风力机叶片的升力间接减小风力机的疲劳载荷,提高风力机的可靠性。该文建立了基于尾缘襟翼的风力机叶片试验模型静态升力控制系统仿真平台。该系统在上位机Matlab/Simulink中建立叶片试验模型静态升力的数学模型和系统控制算法,利用下位机PLC进行实时数据采集和输出,并利用用于过程控制的OPC(OLEfor Process Control,OPC)技术实现上位机和下位机的实时数据通信。结果表明:该控制系统通过主动调节尾缘襟翼的偏转角度有效地减小了周期渐变风、周期阵风、阶梯风和湍流风风况下叶片的升力波动幅度。同时,使用单神经元PID控制器能更好地弥补风扰动引起的升力波动,其控制效果优于经典PID控制器。展开更多
文摘The present work is based on the third-order partial differential equation (PDE) of acoustics of viscoelastic solids for the quasi-equilibrium (QE) component of the average normal stress. This PDE includes the stress-relaxation time (SRT) for the material and is applicable at any value of the SRT. The notion of a smart deicing system (SDS) for blade shells (BSs) of a wind turbine is specified. The work considers the stress in a BS as the one caused by the operational load on the BS. The work develops key design issues of a prospective ice-detection system (IDS) able to supply an array of the heating elements of an SDS with the element-individual spatiotemporal data and procedures for identification of the material parameters of atmospheric-ice (AI) layer accreted on the outer surfaces of the BSs. Both the SDS and IDS flexibly allow for complex, curvilinear and space-time-varying shapes of BSs. The proposed IDS presumes monitoring of the QE components of the normal stresses in BSs. The IDS is supposed to include an array of pressure-sensing resistors, also known as force-sensing resistors (FSRs), and communication hardware, as well as the parameter-identification software package (PISP), which provides the identification on the basis of the aforementioned PDE and the data measured by the FSRs. The IDS does not have hardware components located outside the outer surfaces of, or implanted in, BSs. The FSR array and communication hardware are reliable, and both cost- and energy-efficient. The present work extends methods of structural-health/operational-load monitoring (SH/OL-M) with measurements of the operational-load-caused stress in closed solid shells and, if the prospective PISP is used, endows the methods with identification of material parameters of the shells. The identification algorithms that can underlie the PISP are computationally efficient and suitable for implementation in the real-time mode. The identification model and algorithms can deal with not only the single-layer systems such as the BS layer without the AI layer or two-layer systems but also multi-layer systems. The outcomes can be applied to not only BSs of wind turbines but also non-QE closed single- or multi-layer deformable solid shells of various engineering systems (e.g., the shells of driver or passenger compartments of ships, cars, busses, airplanes, and other vehicles). The proposed monitoring of the normal-stress QE component in the mentioned shells extends the methods of SH/OL-M. The topic for the nearest research is a better adjustment of the settings for the FSR-based measurement of the mentioned components and a calibration of the parameter-identification model and algorithms, as well as the resulting improvement of the PISP.
文摘可通过有效控制风力机叶片的升力间接减小风力机的疲劳载荷,提高风力机的可靠性。该文建立了基于尾缘襟翼的风力机叶片试验模型静态升力控制系统仿真平台。该系统在上位机Matlab/Simulink中建立叶片试验模型静态升力的数学模型和系统控制算法,利用下位机PLC进行实时数据采集和输出,并利用用于过程控制的OPC(OLEfor Process Control,OPC)技术实现上位机和下位机的实时数据通信。结果表明:该控制系统通过主动调节尾缘襟翼的偏转角度有效地减小了周期渐变风、周期阵风、阶梯风和湍流风风况下叶片的升力波动幅度。同时,使用单神经元PID控制器能更好地弥补风扰动引起的升力波动,其控制效果优于经典PID控制器。
