Novel orbit-attitude combination mode for solar power satellites to reduce mass and fuel

Active vibration control is the most effective method for stochastic multidimensional vibration in wind tunnel tests, in which vibration monitoring is the core foundation. Vibrations are induced by the disturbances of several complex air flow instabilities under extreme test conditions with high attack angles. Here, a decoupled unified observation method is proposed in order to fully monitor stochastic multidimensional vibration. First, stochastic multidimensional vibration is explained using the Cartesian coordinate system. Then, the multidimensional vibration decoupling of the pitch plane and the yaw plane is realized according to the proposed decoupling design principle of the long cantilever sting. A unified observation method is presented, based on inertial force theory, to observe multidimensional vibration due to acceleration in each decoupling plane. Verification experiments were conducted in lab and a transonic wind tunnel, using an established real-time monitoring system. The results of lab experiments indicate that, in the frequency region of 0–120 Hz, three vibration modes of a selected stochastic vibration can be decoupled and observed through the vibration components in pitch plane and yaw plane. In addition, wind tunnel tests were carried out according to the working conditions (α = −4~10° with γ = 45°) at Ma = 0.6 and Ma = 0.7, respectively. The results show that six vibration modes of two selected stochastic vibrations can be decoupled and observed through the vibration components in pitch plane and yaw plane. The experimental results prove that stochastic vibration can be fully monitored in multiple dimensions through the vibration components in pitch plane and yaw plane using the proposed decoupled unified observation method. Therefore, these results lay the foundation for active vibration control.

A Decoupled Unified Observation Method of Stochastic Multidimensional Vibration for Wind Tunnel Models.

In wind tunnel tests, the cantilever sting is usually used to support aircraft models because of its simple structure and low aerodynamic interference. However, in some special conditions, big-amplitude and low-frequency vibration would occur easily on the model not only in the pitch direction but also in the yaw direction, resulting in inaccurate data and even damage of the supporting structure. In this paper, aiming at suppressing the vibration in pitch and yaw plane, a multidimensional system identification and active vibration control system on the basis of piezoelectric actuators is established. A vibration monitoring method based on the strain-displacement transformation (SDT) matrix is proposed, which can transform strain signals into vibration displacements. The system identification based on chirp-Z transform (CZT) is applied to improve the adaptability and precision of the building process for the system model. After that, the hardware platform as well as the software control system based on the classical proportional-derivative (PD) algorithm is built. A series of experiments are carried out, and the results show the exactness of the vibration monitoring method. The system identification process is completed, and the controller is designed. Vibration control experiments verify the effectiveness of the controller, and the results indicate that vibrations in pitch and yaw directions are attenuated apparently. The spectrum power is reduced over 14.8 dB/Hz, which prove that the multidimensional identification and active vibration control system has the capability to decline vibration from different directions.

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Multidimensional System Identification and Active Vibration Control of a Piezoelectric-Based Sting System Used in Wind Tunnel

The invention discloses a dimension reduction monitoring method for random multi-dimensional vibration of an aircraft model, belongs to the field of aircraft wind tunnel model vibration monitoring, and relates to a dimension reduction monitoring method for multi-dimensional vibration applied to a strut tail boom type aircraft model wind tunnel test. According to the dimension reduction monitoringmethod, multi-dimensional vibration of the aircraft model is decoupled in a pitching plane and a yawing plane, dimensionality reduction is expressed as inertia observation forces on two planes perpendicular to each other through utilizing an acceleration sensor arranged on a multi-dimensional vibration monitoring system, vibration characteristics of selected random vibration are observed in the pitching plane and the yawing plane in a dimensionality reduction mode, and random multi-dimensional vibration monitoring of the aircraft model is realized. According to the dimension reduction monitoring method provided by the invention, the measurement accuracy degree is improved, and the observation method is high in feasibility and strong in adaptability, and can be applied to a rapidly developed aircraft wind tunnel simulation test.

Dimension reduction monitoring method for random multi-dimensional vibration of aircraft model

The invention relates to the technical field of electrostatic spinning, and particularly discloses an electrostatic spinning fiber average diameter forecasting method based on a neural network. The method includes the steps: taking electrostatic spinning process parameters and electrostatic spinning fiber diameters as training samples; building a BP neural network model; inputting the training samples to train the BP neural network model; inputting the electrostatic spinning process parameters into the trained BP neural network model; forecasting the diameters of electrostatic spinning fibersby the trained BP neural network model to obtain diameter forecasting values and the like. According to the electrostatic spinning fiber average diameter forecasting method based on the neural network, by the aid of a BP neural network technique, a forecasting model is built, the average diameter of electrostatic spinning fibers is acquired, experiment efficiency is effectively improved, the method is simple and high in efficiency, reliability of forecasting results is higher, and trial-and-error cost is reduced.

Electrostatic spinning fiber average diameter forecasting method based on neural network

In wind tunnel tests, the low-frequency and large-amplitude vibration of the cantilever sting result in poor test data in pitch plane and yaw plane, more seriously, even threatens the safety of wind tunnel tests. To ensure the test data quality, a multidimensional vibration suppression method is proposed to withstand the vibration from any direction, which is based on a system with stackable piezoelectric actuators and velocity feedback employing accelerometers. Firstly, the motion equation of the cantilever sting system is obtained by Hamilton’s principle with the assumed mode method. Then, the multidimensional active control mechanism is qualitatively analyzed and a negative velocity feedback control algorithm combined with a root mean square (RMS) evaluation method is introduced to realize active mass and active damping effect, meanwhile, a weight modification method is performed to determine the sequence number of the stacked piezoelectric actuators and the weight of control voltages in real time. Finally, a multidimensional vibration suppression system was established and verification experiments were carried out in lab and a transonic wind tunnel. The results of lab experiments indicate that the damping ratio of the system is improved more than 4.3 times and the spectrum analyses show reductions of more than 23 dB. In addition, wind tunnel test results have shown that for the working conditions (α = −4~10° with γ = 0° or α = −4~10° with γ = 45°) respectively at 0.6 Ma and 0.7 Ma, the remainder vibration is less than 1.53 g, which proves that the multidimensional vibration suppression method has the ability to resist vibration from any direction to ensure the smooth process of wind tunnel tests.

Multidimensional Vibration Suppression Method with Piezoelectric Control for Wind Tunnel Models.

The invention provides a multi-dimensional vibration control method of a fulcrum bar tail supporting type aircraft model, belongs to the field of vibration active control, and relates to the multi-dimensional vibration control method of the fulcrum bar tail supporting type aircraft model based on a piezoelectric ceramic actuator and applied to an aircraft model wind tunnel test. The multi-dimensional vibration control method comprises the steps that two components of main vibration acceleration of the aircraft model are measured by a pitch acceleration sensor and a yaw acceleration sensor which are arranged on the centroid of the aircraft model, a main vibration vector of the aircraft model is obtained, and the real-time vibration plane of a fulcrum bar is determined; and the inertial force is introduced to solve a dynamic bending moment on an active section of a multi-dimensional vibration damper, and then the stress distribution on the active section is obtained, and the vibration control force is solved in real time according to the stress of the piezoelectric ceramic actuator on the active section. A multi-dimensional vibration active control system is adopted, the stability and reliability of the active vibration control system of a wind tunnel model are improved, the service life of the piezoelectric ceramic actuator is prolonged, and thus the wind tunnel test data quality and wind tunnel test safety are ensured.

Multi-dimensional vibration control method of fulcrum bar tail supporting type aircraft model

An active vibration control method based on energy-fuzzy for cantilever structures excited by aerodynamic loads

The invention discloses a piezoelectric ceramic driver output control method based on a neural network, belongs to the field of wind tunnel model test vibration suppression and relates to a piezoelectric ceramic driver output control method which is based on the neural network and applied to a wind tunnel active vibration suppression strut. According to the method, a data collection hardware system of a piezoelectric ceramic driver is installed first, experimental data of input voltage and output force of the piezoelectric ceramic driver is collected, a neural network model of the piezoelectric ceramic driver is established, processed experimental data is used as input and output of the neural network model, appropriate initial parameters are selected to train the system neural network model, and finally the trained neural network model is called to be applied to a project. Compared with a traditional linear control method, through the method, a nonlinear error on a control model is avoided, a control result is more accurate, and precision is higher. Besides, the method has high adaptability and can be applied to all systems which contain piezoelectric ceramic drivers.

Tang Linlin

Papers

Multidimensional Vibration Suppression Method with Piezoelectric Control for Wind Tunnel Models.

Multi-dimensional vibration control method of fulcrum bar tail supporting type aircraft model

A Decoupled Unified Observation Method of Stochastic Multidimensional Vibration for Wind Tunnel Models.

An active vibration control method based on energy-fuzzy for cantilever structures excited by aerodynamic loads

Piezoelectric ceramic driver output control method based on neural network