Cheng-Wei Fei

Multiobject Reliability Analysis of Turbine Blisk with Multidiscipline under Multiphysical Field Interaction

To study accurately the influence of the deformation, stress, and strain of turbine blisk on the performance of aeroengine, the comprehensive reliability analysis of turbine blisk with multiple disciplines and multiple objects was performed based on multiple response surface method (MRSM) and fluid-thermal-solid coupling technique. Firstly, the basic thought of MRSM was introduced. And then the mathematical model of MRSM was established with quadratic polynomial. Finally, the multiple reliability analyses of deformation, stress, and strain of turbine blisk were completed under multiphysical field coupling by the MRSM, and the comprehensive performance of turbine blisk was evaluated. From the reliability analysis, it is demonstrated that the reliability degrees of the deformation, stress, and strain for turbine blisk are 0.9942, 0.9935, 0.9954, and 0.9919, respectively, when the allowable deformation, stress, and strain are 3.7 × 10−3 m, 1.07 × 109 Pa, and 1.12 × 10−2 m/m, respectively; besides, the comprehensive reliability degree of turbine blisk is 0.9919, which basically satisfies the engineering requirement of aeroengine. The efforts of this paper provide a promising approach method for multidiscipline multiobject reliability analysis.

Optimum Control for Nonlinear Dynamic Radial Deformation of Turbine Casing with Time-Varying LSSVM

With the development of the high performance and high reliability of aeroengine, the blade-tip radial running clearance (BTRRC) of high pressure turbine seriously influences the reliability and performance of aeroengine, wherein the radial deformation control of turbine casing has to be concerned in BTRRC design. To improve BTRRC design, the optimum control-based probabilistic optimization of turbine casing radial deformation was implemented using time-varying least square support vector machine (T-LSSVM) by considering nonlinear material properties and dynamic thermal load. First the T-LSSVM method was proposed and its mathematical model was established. And then the nonlinear dynamic optimal control model of casing radial deformation was constructed with T-LSSVM. Thirdly, through the numerical experiments, the T-LSSVM method is demonstrated to be a promising approach in reducing additional design samples and improving computational efficiency with acceptable computational precision. Through the optimum control-based probabilistic optimization for nonlinear dynamic radial turbine casing deformation, the optimum radial deformation is 7.865 × 10−4 m with acceptable reliability degree 0.995 6, which is reduced by 7.86 × 10−5 m relative to that before optimization. These results validate the effectiveness and feasibility of the proposed T-LSSVM method, which provides a useful insight into casing radial deformation, BTRRC control, and the development of gas turbine with high performance and high reliability.

Multi-feature entropy distance approach with vibration and acoustic emission signals for process feature recognition of rolling element bearing faults:

To accurately reveal rolling bearing operating status, multi-feature entropy distance method was proposed for the process character analysis and diagnosis of rolling bearing faults by the integration of four information entropies in time domain, frequency domain and time–frequency domain and two kinds of signals including vibration signals and acoustic emission signals. The multi-feature entropy distance method was investigated and the basic thought of rolling bearing fault diagnosis with multi-feature entropy distance method was given. Through rotor simulation test rig, the vibration and acoustic emission signals of six rolling bearing faults (ball fault, inner race fault, outer race fault, inner ball faults, inner–outer faults and normal) are gained under different rotational speeds. In the view of the multi-feature entropy distance method, the process diagnosis of rolling bearing faults was implemented. The analytical results show that multi-feature entropy distance fully reflects the process feature of rolling bearing faults with the change of rotating speed; the multi-feature entropy distance with vibration and acoustic emission signals better reports signal features than single type of signal (vibration or acoustic emission signal) in rolling bearing fault diagnosis; the proposed multi-feature entropy distance method holds high diagnostic precision and strong robustness (anti-noise capacity). This study provides a novel and useful methodology for the process feature extraction and fault diagnosis of rolling element bearings and other rotating machinery.

Parametric modeling and updating for bolted joints of aeroengine casings

To establish accurate finite element (FE) model of bolted joint structures of aeroengine stator system (casings), this work implements the parametric FE modeling and updating of bolted joints of aeroengine stator system with multi-characteristic responses (multi-object). Firstly, the parametric FE modeling approach of bolted joint structure was developed based on the thin layer element method. And then the FE model updating thought of aeroengine stator system was developed based on the probabilistic analysis method. Finally, the parametric modeling and updating of the bolted joints of aeroengine stator system with multi-characteristic responses was completed by the optimization iteration calculation of objective function based on the proposed methods and the static stiffness testing data. Through the parametric modeling of bolted joint structures based on the thin layer method, the complexity of FE model of aeroengine casings with many bolted joint structures is reduced. As shown in the FE model updating of casings with multi-characteristic responses analysis, the static stiffness from the updated model are very close to the test data, in which the maximum relative error decreases to 3.9% from 30.52% and the others are less than 3%, so that the design precision of aeroengine stator system with the many and wide variety of bolted joints gets a great improvement. Moreover, the proposed methods of parametric modeling and model updating for multi-characteristic responses are validated to be effective in the simulation and equivalent of the mechanical characteristics of bolted joints in complex systems like aeroengine stator system.

Reliability-Based Design Optimization Method of Turbine Disk with Transformed Deterministic Constraints

AbstractTo improve the computational efficiency of the reliability-based design optimization (RBDO) of a complex structure with nonlinear and implicit limit-state function, the single-loop-single-vector (SLSV)-limit-state factor (LSF) (SLSV-LSF) method was developed by fully considering the advantages of the SLSV approach and the LSF method to transform uncertain constraints into deterministic constraints. The mathematical models of SLSV and LSF were established and the basic RBDO process of the SLSV-LSF method is presented. The shape optimization of an aeroengine turbine disk was completed based on the proposed method. From the reliability sensitivity analysis of the turbine disk, it is revealed that an uncertain constraint of average circumferential stress can be transformed into a deterministic constraint and material density can be regarded as a deterministic variable. Through the min-mass shape design of the turbine disk based on different approaches, it is demonstrated that the developed method main...