Influence Of Mode Shapes Research Articles

Unbalance position of aeroengine flexible rotor analysis and identification based on dynamic model and deep learning

The rotor system design is gradually becoming lighter as the thrust-weight ratio of the new generation of aeroengines improves, making the power turbine rotor structure more slender and flexible, and it is difficult to judge the axial distribution of unbalance. Meanwhile, the engine rotor’s working speed is above the second critical speed and even exceeds the third-order speed. The small imbalance of the rotating shaft will cause large vibration, coupled with the influence of mode shape, resulting in difficulty in rotor dynamic balance, low efficiency and poor effect of the flexible rotor dynamic balance. Therefore, finding out the unbalance position is of great significance to determine the balance plane during rotor dynamic balance, and improve the balance efficiency and effect of flexible rotor. Firstly, the paper established the dynamic model of power turbine rotor, analyzed the vibration response law of rotor with unbalance at different positions, and found out the sensitive position of rotor unbalance. Then, a power turbine rotor unbalance position identification method, based on deep learning, one-dimensional convolution neural network (1D-CNN) is proposed. The multiple measured response data of the rotor with different unbalance positions are input into 1D-CNN for training. Finally, at subcritical speed, critical speed and supercritical speed, the accuracy of 1D-CNN method for rotor unbalance position identification is 99.5%, 99.5%, and 99.0% respectively, which verifies the effectiveness, feasibility of 1D-CNN method for rotor unbalance position identification, and provides a new solution for intelligent identification of aeroengine rotor unbalance position.

A Design Method to Prevent Low Pressure Turbine Blade Flutter

A design approach to avoid flutter of low pressure turbine blades in aircraft engines is described. A linearized Euler analysis, previously validated using experimental data, is used for a series of parameter studies. The influence of mode shape and reduced frequency are investigated. Mode shape is identified as the most important contributor to determining the stability of a blade design. A new stability parameter is introduced to gain additional insight into the key contributors to flutter. This stability parameter is derived from the influence coefficient representation of the cascade, and includes only contributions from the reference blade and its immediate neighbors. This has the effect of retaining the most important contributions to aerodynamic damping while filtering out terms of less significance. This parameter is utilized to develop a stability map, which provides the critical reduced frequency as a function of torsion axis location. Rules for preliminary design and procedures for detailed design analysis are defined. [S0742-4795(00)01401-0]

Transient stresses at Parkfield, California, produced by the M 7.4 Landers earthquake of June 28, 1992: Observations from the UPSAR dense seismograph array

The M 7.4 Landers earthquake triggered widespread seismicity in the western United States. Because the transient dynamic stresses induced at regional distances by the Landers surface waves are much larger than the expected static stresses, the magnitude and the characteristics of the dynamic stresses may bear upon the earthquake triggering mechanism. The Landers earthquake was recorded on the UPSAR (U.S. Geological Survey Parkfield Small Aperture Array) array, a group of 14 triaxial accelerometers located within a 1‐square‐km region 10 km southwest of the town of Parkfield, California, 412 km northwest of the Landers epicenter. No triggered earthquakes were observed at Parkfield. Multiple filter analysis shows that the displacements, obtained by double integration, are dominated by the fundamental mode Love and Rayleigh modes, with some higher‐mode contributions for periods shorter than 10 s. Most of the surface waves propagated along the great circle path from Landers, but a late arriving surface wave appears to have been scattered from the Sierra Nevada Mountains. We used a standard geodetic inversion procedure to determine the surface strain and stress tensors as functions of time from the observed displacements. Peak dynamic strains and stresses at Earth's surface are about 7 μstrain and 0.035 MPa, respectively, and they have a flat amplitude spectrum between 2‐s and 15‐s period. These stresses agree well with stresses predicted from a simple equation using the ground velocity spectrum observed at a single station. Peak stresses ranged from about 0.035 MPa at the surface to about 0.12 MPa between 2 and 14 km depth, with the sharp increase of stress away from the surface resulting from the rapid increase of rigidity with depth and from the influence of mode shapes. Because of the free‐surface boundary conditions, the horizontal components of the stress tensor tend to dominate in the top 5–6 km of the crust, which might cause triggered seismicity to have strike‐slip or normal mechanisms. Comparison of dynamic stresses induced by the Landers, Loma Prieta, and Petrolia earthquakes at a variety of sites indicates that the Landers stresses were not spectacularly larger than those induced by the other sources. Landers dynamic stresses were comparable to Coalinga static stresses at Parkfield. The effective strain caused by Landers at Parkfield, where no earthquakes were triggered, are the same amplitude as those at some sites in Nevada where earthquakes were triggered. Comparing various authors' observations of dynamic stresses, there is no obvious characteristic of these stresses that correlates with the triggered seismicity.