17 results about "Flutter" patented technology

The invention discloses a blade flutter monitoring method and device, a monitoring system, a storage medium and a computer program product, and the method comprises the steps: carrying out the modal feature analysis of a blade to determine a flutter monitoring region, laying a flexible sensing element in the flutter monitoring region, and enabling the flexible sensing element to be used for collecting the strain signal of the blade; in the running process of the blade, real-time running parameters of the blade and real-time strain signals collected by the flexible sensing element are obtained; determining a reference strain signal corresponding to the inertial centrifugal force of the blade according to the real-time operation parameters and a preset mapping relation; the mapping relation is the mapping relation between the operation parameters of the blade and the reference strain signal; deducting the reference strain signal from the real-time strain signal to obtain a target strain signal corresponding to the aerodynamic force; and according to the target strain signal and a preset formula, calculating pneumatic work of the blade in a set vibration period, and according to the pneumatic work, judging whether the blade flutters or not. According to the scheme, the accuracy and the real-time performance of flutter judgment are improved.

The invention discloses a method for inhibiting fluttering of a thin-wall workpiece based on a follow-up supporting device, which comprises the following steps of: installing the follow-up supporting device, establishing initial normal contact between a rolling wheel in the follow-up supporting device and the back surface of the thin-wall workpiece and applying pre-tightening force to finish initial calibration of a contact state between the follow-up supporting device and the thin-wall workpiece; based on the contact state, a force sensor and a displacement sensor in the rolling wheel are used for collecting normal contact force and displacement signals; the control unit calculates a modal participation coefficient and a dynamic correction function according to the real-time signal to form a time-varying model of equivalent stiffness and damping of the thin-wall part, and a stepping motor in the follow-up supporting device drives a gear-rack mechanism to finely adjust the position of a rolling wheel, so that self-adaptive adjustment of the supporting force is realized; data recording and feedback optimization; and finishing processing and outputting parameters. The device has the advantages of real-time sensing, self-adaptive adjustment, measurable parameters, compact structure and the like, and the machining precision and the surface quality of the thin-walled workpiece are remarkably improved.

The invention relates to the field of numerical control machining data processing, in particular to a multi-axis linkage numerical control lathe machining data processing method and system. Comprising the following steps: acquiring vibration information, performing time-frequency analysis, and extracting energy change and instantaneous peak value characteristics in a preset high-frequency band; the features are compared with a preset judgment basis, an early sign of flutter is recognized, and when flutter is recognized, a machining parameter adjusting instruction for the rotating speed of the main shaft, the feeding speed and / or the cutting depth is generated; and the adjusted vibration information is obtained for time-frequency analysis, the flutter suppression effect is evaluated, machining parameters are further adjusted according to the flutter suppression effect, and / or an early warning or shutdown alarm is given out, so that closed-loop active suppression control over microcosmic cutting flutter is formed. The problems that due to the fact that a multi-axis linkage numerical control lathe cannot capture key and instantaneous high-frequency vibration mode information in a data collection and analysis frame, tool abrasion prediction is not accurate, the machining quality is reduced, the workpiece rejection rate is increased, and the production efficiency is reduced are solved.

The invention discloses a turbine blade flutter evaluation method adopting a single-channel harmonic balance model. The method comprises the following steps: 1, carrying out structural grid division on a turbine blade to obtain a vibration mode, a vibration frequency and a vibration pitch diameter of a vibration blade; 2, performing fluid grid division on the turbine blade to obtain grid coordinates under a cylindrical coordinate system; 3, aligning the coordinates of the structural grid and the fluid grid to obtain a vibration mode of the fluid grid; 4, adopting a Doppler frequency shift effect to obtain blade vibration frequencies, vibration pitch diameters and inter-blade phase angles of other blade rows except the blade row where the vibration blades are located; 5, realizing mutual transmission of upstream information and downstream information of the rotor-stator interface; 6, single-channel unsteady harmonic balance analysis is achieved; and step 7, evaluating the stability of the turbine blade flutter system. According to the method, the flutter of the multiple rows of turbine blades is evaluated, and the method has the characteristics of low calculation cost and high evaluation accuracy.

This invention discloses an acoustic identification method and system for compressor flutter faults, relating to the field of engine condition monitoring and fault diagnosis technology. The method includes the following steps: optimizing the acoustic measurement point array layout and installing sound pressure sensors according to the array layout; acquiring signals through the sound pressure sensor array and preprocessing the signals; identifying non-integer-order abnormal frequencies and detecting frequency lock-in on the preprocessed signals; calculating the complex coherence between each channel signal and the reference channel and the phase of each channel signal at the locked frequency point; calculating the circumferential order k and wave direction of the flutter using a spatial matching algorithm; performing flutter identification and outputting the flutter identification result. This method can accurately identify the circumferential order and traveling wave direction online, effectively alleviating spatial aliasing problems. Furthermore, the algorithm is lightweight and easy to deploy in real-time on air, providing an efficient and reliable engineering solution for early warning and stability monitoring of compressor flutter.

The embodiment of the invention provides a multi-agent model synchronous simulation method and device for random mistuned bladed disc probability flutter assessment, and the method comprises the steps: decomposing a fluid-solid coupling vibration model into a modal aerodynamic coefficient model of a fluid domain and a blade frequency mistuning quantity model of a solid domain; establishing a fluid domain multi-channel blade grid runner grid model and a solid domain blade finite element model; extracting a predetermined number of input samples; respectively completing deterministic analysis on a fluid domain and a solid domain through fluid mechanics simulation and solid dynamics simulation; respectively constructing a modal aerodynamic coefficient model and a blade frequency detuning quantity model through the training data and the test data; and proxy model simulation is carried out based on the modal aerodynamic coefficient model and the blade frequency detuning amount model, characteristic value response of the detuning bladed disc rotor system is obtained, and random detuning bladed disc probability flutter evaluation is carried out.

The invention discloses a compressor flutter fault acoustic recognition method and system, and relates to the technical field of engine state monitoring and fault diagnosis, and the method comprises the following steps: optimizing the array layout of acoustic measurement points, and installing sound pressure sensors according to the array layout; signal acquisition is carried out through a sound pressure sensor array, and signals are preprocessed; carrying out non-integral-order abnormal frequency identification and frequency locking detection on the preprocessed signal; calculating the complex coherence between each channel signal and the reference channel and the phase of each channel signal at the locking frequency point; calculating a circumferential order k and a wave direction of flutter through a space matching algorithm; carrying out flutter identification, and outputting a flutter identification result; according to the method, the circumferential order and the traveling wave direction can be accurately recognized on line, the space aliasing problem is effectively relieved, the algorithm is light in weight, airborne real-time deployment is easy, and an efficient and reliable engineering solution is provided for early warning and stability monitoring of compressor flutter.

This application discloses a servo motor flutter stabilization control method, device, and system, relating to the field of aircraft servo motor control technology. The method includes: determining that the aircraft has entered the impact unloading stage and triggering an output disturbance request signal when the aircraft's acceleration signal meets the impact unloading condition; responding to the disturbance request signal, calculating the disturbance frequency based on a mechanical model, and obtaining the disturbance amplitude based on the maximum acceleration value by retrieving a matching gradation lookup table; synthesizing a disturbance sinusoidal signal based on the disturbance frequency and the disturbance amplitude; and linearly superimposing the disturbance sinusoidal signal with the servo motor current control signal to obtain a total current control signal; setting the disturbance sinusoidal signal to zero and recording a fault flag when the absolute value of the total current control signal is greater than a current threshold. By superimposing a disturbance sinusoidal signal on the servo motor current control signal, the control dead zone introduced by mechanical backlash can be effectively suppressed, ensuring the accuracy of the control surface following and the stability and timeliness of the aircraft's attitude control.

This invention relates to a method for predicting the critical flutter wind speed of long-span bridges based on the L-P perturbation method, comprising the following steps: S1, obtaining the physical characteristics and aerodynamic parameters of the bridge as basic data through wind tunnel tests; S2, establishing the bridge motion control matrix equation based on modal displacement; S3, deriving explicit solutions for the modal frequencies, damping ratios, and modal characteristics of each modal branch based on the L-P perturbation method; S4, iteratively solving the modal frequencies, and directly solving the damping ratio, amplitude ratio, and phase difference on this basis, observing the change of the modal damping ratio ξ with the wind speed U in each direction, and determining the critical flutter wind speed; solving the problem that the existing explicit closed-form solution of the three-degree-of-freedom flutter initiation condition requires multiple iterative calculations of the modal frequencies, damping ratios, and mode shapes, and is difficult to clearly explain the influence of structural and aerodynamic parameters on aerodynamic instability, thus failing to accurately predict the critical flutter wind speed of long-span bridges.

The invention relates to the technical field of aviation test flight, in particular to a TD-DMDc and OE fusion-based flutter test flight data modal automatic identification method, which comprises the following steps of: respectively extracting modal parameters from flutter test flight data by using an OE model and a TD-DMDc method, preliminarily screening, and obtaining candidate modal pairs; according to the candidate modal pair, single-modal reconstruction is carried out through an OE model and a TD-DMDc method, and corresponding single-modal reconstruction signals are obtained; according to the single-mode reconstruction signals respectively corresponding to the OE model and the TD-DMDc method, obtaining a comprehensive similarity measurement value by calculating the correlation between the single-mode reconstruction signals; performing envelope analysis on the flutter flight test data to obtain a real modal number; and obtaining a real mode according to the comprehensive similarity measurement value and the number of the real modes. According to the method, the parametric index and the behavioral index are fused, so that a modal verification system which is more robust and closer to physical reality can be constructed.

- Method and device for generating a fluttering phenomenon on at least part of an aircraft.- The device (1) comprises a plurality of sensors (4) arranged on the aircraft (AC) and configured to measure input data, an avionics computer (5) configured to determine, from said input data, at least one control command for at least one control surface (3) of the aircraft (AC) using a control law comprising at least one gain value, said control law being configured to obtain a control command enabling the generation of a flutter mode on at least one part (2) of the aircraft (AC), and a control system (6) configured to control the control surface (3) of the aircraft (AC) so as to generate said flutter mode using the control command determined by the avionics computer (5), said device (1) thus enabling the generation of a flutter phenomenon under controlled conditions and the easy and safe study of the behavior of the aircraft (AC) subjected to this flutter. Figure for the abbreviation: Figure 1.

The invention discloses a mode matching method for bridge segment model flutter test design, which comprises the following steps: carrying out bridge dynamic characteristic finite element analysis, and determining a basic torsional mode, an equivalent mass inertia moment and a torsional mode frequency of a bridge; determining a first vertical bending mode, a second vertical bending mode and corresponding bridge section turning radiuses and bending-torsion frequency ratios; calculating a formation similarity coefficient; calculating flutter critical wind speed values of the bridge segment model under different modal combinations; and determining a segment model flutter wind tunnel test modal matching result based on the flutter critical wind speed values of the bridge segment model under different modal combinations. The method is used for solving the problems that according to a bridge segment model flutter test mode matching method in the prior art, misjudgment of the flutter performance of a bridge is likely to be caused, and related pneumatic parameters need to be obtained in advance. The purpose of more accurately performing modal matching on the flutter test of the bridge section model without acquiring any pneumatic parameter of the bridge section in advance is achieved.

The invention relates to a high-aspect-ratio unmanned aerial vehicle wing flutter suppression method considering wingtip deflection angle influence, belongs to the technical field of aeroelasticity of aircrafts, and solves the problems that in the prior art, flutter critical speed prediction is not accurate, and passive flutter suppression measures are low in efficiency. And the flutter energy cannot be counteracted in real time. According to the high-aspect-ratio unmanned aerial vehicle wing flutter suppression method, the coupling influence of a structural power subsystem and an aerodynamic subsystem is considered, the critical speed of high-aspect-ratio wing flutter with a wingtip deflection angle can be predicted, and a relational expression between a control surface control signal and flutter control influence factors is obtained; the method has a good effect of suppressing the flutter of the wing of the high-aspect-ratio unmanned aerial vehicle considering the influence of the wingtip deflection angle, and meanwhile, the theoretical method provided by the invention is simple and clear and is convenient for engineering application.

A method for evaluating turbomachinery blade flutter using a single-channel harmonic balance model includes the following steps: Step 1: Mesh the turbomachinery blades to obtain the vibration modes, vibration frequencies, and vibration pitch diameters of the vibrating blades; Step 2: Mesh the turbomachinery blades into a fluid mesh to obtain the mesh coordinates in a cylindrical coordinate system; Step 3: Align the coordinates of the structural mesh and the fluid mesh to obtain the vibration modes of the fluid mesh; Step 4: Utilize the Doppler frequency shift effect to obtain the blade vibration frequencies, vibration pitch diameters, and inter-blade phase angles of blades in other blade rows besides the vibrating blade; Step 5: Enable the mutual transfer of upstream and downstream information at the rotor-stationary interface; Step 6: Perform single-channel unsteady harmonic balance analysis; Step 7: Evaluate the stability of the turbomachinery blade flutter system. This invention enables the evaluation of flutter in multi-row turbomachinery blades, featuring low computational cost and high evaluation accuracy.

The application belongs to the technical field of aircraft ground flutter simulation test, and particularly relates to a flutter speed tracking method and device for aircraft ground flutter simulation test, which comprises the following steps: measuring vibration response signals of an aircraft structure by using a sensor; obtaining a step vibration amplitude response signal based on the vibration response signals; performing smoothing processing on the step vibration amplitude response signal to obtain a continuous change vibration amplitude response signal; calculating a vibration amplitude response change trend parameter based on the continuous change vibration amplitude response signal; obtaining an equivalent wind speed change amount by referring to the vibration amplitude response change trend parameter; calculating an equivalent aerodynamic force change amount based on the equivalent wind speed change amount; and controlling the change of an exciter output to apply the equivalent aerodynamic force to the aircraft structure.

The invention relates to the technical field of axial flow turbine last-stage long blade analysis, in particular to an axial flow turbine last-stage long blade flutter analysis method which comprises the steps that modal analysis is conducted on an axial flow turbine last-stage long blade, and the low-order modal vibration frequency and the vibration mode of the axial flow turbine last-stage long blade are obtained; based on pitch diameters, frequencies, vibration modes and aerodynamic thermal working condition boundary conditions of modal vibration of the last-stage long blade of the axial flow turbine under different blade connection states, periodic work and corresponding aerodynamic damping coefficients of the blade under the current working condition are calculated through flutter analysis; based on the aerodynamic damping coefficient and the mechanical damping coefficient, calculating to obtain a total damping coefficient; flutter judgment is conducted according to the total damping coefficient, and if the total damping coefficient is larger than 0, it is judged that the blade has no flutter risk under the current working condition; if the total damping coefficient is less than 0, judging that the flutter risk exists; the development efficiency of the last-stage long blade of the axial flow turbine can be improved, and the development cost can be reduced.

This invention provides a Flutter engine management method, system, medium, and native client; the native client has a Flutter engine management module; the Flutter engine management module includes an engine cache pool; the method includes the following steps: initializing the Flutter engine management module so that the engine cache pool includes at least one Flutter engine; after initialization, receiving a first signal sent by the Flutter client and setting the engine state of the Flutter engine to an available state; when loading the Flutter interface, retrieving a target Flutter engine with an available engine state from the engine cache pool and binding the target Flutter engine to the Flutter interface; after binding, setting the engine state of the target Flutter engine to a "in use" state and sending a second signal to the Flutter client so that the Flutter client performs the corresponding jump operation of the Flutter interface based on the second signal; this invention saves the time required to create a Flutter engine, optimizes the loading speed of the Flutter interface in the native client, and thus improves the user experience.