RESEARCH AND DEVELOPMENT OF HIGH TEMPERATURESTRUCTURAL MATERIALS FOR AERO-ENGINE APPLICATIONS

The status of research, development of superalloys and materials processing ＆ fabrication technologies for aero-engine applications in China Aviation Industry, with an emphasis on recent achievements at BIAM including directionally solidified and single crystal superalloys for blade and vane applications, wrought superqlloys for aero-engine disks and rings, and powder metalurgy （PM） superalloys for high performance disk applications were described. It was also reviewed the development of new class of high temperature structural materials, such as structural intermetallics, and advanced material processing technologies including rapid solidification, spray forming and so on. The trends of research and development of the above mentioned superalloys and processing technologies are outlined. Cast, wrought and PM superalloys are the workhorse materials for the hot section of current aero-engines. New high temperature materials and advanced processing technologies have been and will be the subject of study. It is speculated that high performance, high purity and low cost superalloys and technologies will play key roles in aero-engines.

Convergence Analysis of the Numerical Solution for Cathode Design of Aero-engine Blades in Electrochemical Machining

As a main difficult problem encountered in electrochemical machining （ECM）, the cathode design is tackled, at present, with various numerical analysis methods such as finite difference, finite element and boundary element methods. Among them, the finite element method presents more flexibility to deal with the irregularly shaped workpieces. However, it is very difficult to ensure the convergence of finite element numerical approach. This paper proposes an accurate model and a finite element numerical approach of cathode design based on the potential distribution in inter-electrode gap. In order to ensure the convergence of finite element numerical approach and increase the accuracy in cathode design, the cathode shape should be iterated to eliminate the design errors in computational process. Several experiments are conducted to verify the machining accuracy of the designed cathode. The experimental results have proven perfect convergence and good computing accuracy of the proposed finite element numerical approach by the high surface quality and dimensional accuracy of the machined blades.

An Effective Fault Diagnosis Method for Aero Engines Based on GSA-SAE

The health status of aero engines is very important to the flight safety.However,it is difficult for aero engines to make an effective fault diagnosis due to its complex structure and poor working environment.Therefore,an effective fault diagnosis method for aero engines based on the gravitational search algorithm and the stack autoencoder(GSA-SAE)is proposed,and the fault diagnosis technology of a turbofan engine is studied.Firstly,the data of 17 parameters,including total inlet air temperature,high-pressure rotor speed,low-pressure rotor speed,turbine pressure ratio,total inlet air temperature of high-pressure compressor and outlet air pressure of high-pressure compressor and so on,are preprocessed,and the fault diagnosis model architecture of SAE is constructed.In order to solve the problem that the best diagnosis effect cannot be obtained due to manually setting the number of neurons in each hidden layer of SAE network,a GSA optimization algorithm for the SAE network is proposed to find and obtain the optimal number of neurons in each hidden layer of SAE network.Furthermore,an optimal fault diagnosis model based on GSA-SAE is established for aero engines.Finally,the effectiveness of the optimal GSA-SAE fault diagnosis model is demonstrated using the practical data of aero engines.The results illustrate that the proposed fault diagnosis method effectively solves the problem of the poor fault diagnosis result because of manually setting the number of neurons in each hidden layer of SAE network,and has good fault diagnosis efficiency.The fault diagnosis accuracy of the GSA-SAE model reaches 98.222%,which is significantly higher than that of SAE,the general regression neural network(GRNN)and the back propagation(BP)network fault diagnosis models.

Machining the Integral Impeller and Blisk of Aero-Engines:A Review of Surface Finishing and Strengthening Technologies

The integral impeller and blisk of an aero-engine are high performance parts with complex structure and made of difficult-to-cut materials. The blade surfaces of the integral impeller and blisk are functional surfaces for power transmission, and their surface integrity has signif- icant effects on the aerodynamic efficiency and service life of an aero-engine. Thus, it is indispensable to finish and strengthen the blades before use. This paper presents a comprehensive literature review of studies on finishing and strengthening technologies for the impeller and blisk of aero-engines. The review includes independent and inte- grated finishing and strengthening technologies and dis- cusses advanced rotational abrasive flow machining with back-pressure used for finishing the integral impeller and blisk. A brief assessment of future research problems and directions is also presented.

Aero-engine Blade Fatigue Analysis Based on Nonlinear Continuum Damage Model Using Neural Networks

Fatigue life and reliability of aero-engine blade are always of important significance to flight safety.The establishment of damage model is one of the key factors in blade fatigue research.Conventional linear Miner＇s sum method is not suitable for aero-engine because of its low accuracy.A back propagation neutral network（BPNN） based on the combination of Levenberg-Marquardt（LM） and finite element method（FEM） is used to describe process of nonlinear damage accumulation behavior in material and predict fatigue life of the blade.Fatigue tests of standard specimen made from TC4 are carried out to obtain material fatigue parameters and S-N curve.A nonlinear continuum damage model（CDM）,based on the BPNN with one hidden layer and ten neurons,is built to investigate the nonlinear damage accumulation behavior,in which the results from the tests are used as training set.Comparing with linear models and previous nonlinear models,BPNN has the lowest calculation error in full load range.It has significant accuracy when the load is below 500 MPa.Especially,when the load is 350 MPa,the calculation error of the BPNN is only 0.4%.The accurate model of the blade is built by using 3D coordinate measurement technology.The loading cycle in fatigue analysis is defined from takeoff to cruise in 10 min,and the load history is obtained from finite element analysis（FEA）.Then the fatigue life of the compressor blade is predicted by using the BPNN model.The final fatigue life of the aero-engine blade is 6.55 104 cycles（10 916 h） based on the BPNN model,which is effective for the virtual design of aero-engine blade.

Aero-engine Thrust Estimation Based on Ensemble of Improved Wavelet Extreme Learning Machine

Aero-engine direct thrust control can not only improve the thrust control precision but also save the operating cost by reducing the reserved margin in design and making full use of aircraft engine potential performance.However,it is a big challenge to estimate engine thrust accurately.To tackle this problem,this paper proposes an ensemble of improved wavelet extreme learning machine(EW-ELM)for aircraft engine thrust estimation.Extreme learning machine(ELM)has been proved as an emerging learning technique with high efficiency.Since the combination of ELM and wavelet theory has the both excellent properties,wavelet activation functions are used in the hidden nodes to enhance non-linearity dealing ability.Besides,as original ELM may result in ill-condition and robustness problems due to the random determination of the parameters for hidden nodes,particle swarm optimization(PSO)algorithm is adopted to select the input weights and hidden biases.Furthermore,the ensemble of the improved wavelet ELM is utilized to construct the relationship between the sensor measurements and thrust.The simulation results verify the effectiveness and efficiency of the developed method and show that aero-engine thrust estimation using EW-ELM can satisfy the requirements of direct thrust control in terms of estimation accuracy and computation time.

Bifurcation analysis of aero-engine's rotor system under constant maneuver load

When an aircraft is hovering or doing a dive-hike flight at a fixed speed, a constant additional inertial force will be induced to the rotor system of the aero-engine, which can be called a constant maneuver load. Take hovering as an example. A Jeffcott rotor system with a biased rotor and several nonlinear elastic supports is modeled, and the vibration characteristics of the rotor system under a constant maneuver load are analytically studied. By using the multiple-scale method, the differential equations of the system are solved, and the bifurcation equations are obtained. Then, the bifurcations of the system are analyzed by using the singularity theory for the two variables. In the EG-plane, where E refers to the eccentricity of the rotor and G represents the constant maneuver load, two hysteresis point sets and one double limit point set are obtained. The bifurcation diagrams are also plotted. It is indicated that the resonance regions of the two variables will shift to the right when the aircraft is maneuvering. Furthermore, the movement along the horizontal direction is faster than that along the vertical direction. Thus, the different overlapping modes of the two resonance regions will bring about different bifurcation modes due to the nonlinear coupling effects. This result lays a theoretical foundation for controlling the stability of the aero-engine＇s rotor system under a maneuver load.

Application of multi-outputs LSSVR by PSO to the aero-engine model

Considering the modeling errors of on-board self-tuning model in the fault diagnosis of aero-engine, a new mechanism for compensating the model outputs is proposed. A discrete series predictor based on multi-outputs least square support vector regression （LSSVR） is applied to the compensation of on-board self-tuning model of aero-engine, and particle swarm optimization （PSO） is used to the kernels selection of multi-outputs LSSVR. The method need not reconstruct the model of aero-engine because of the differences in the individuals of the same type engines and engine degradation after use. The concrete steps for the application of the method are given, and the simulation results show the effectiveness of the algorithm.

Linear-in-Parameter Models Based on Parsimonious Genetic Programming Algorithm and Its Application to Aero-Engine Start Modeling

A novel Parsimonious Genetic Programming （PGP） algorithm together with a novel aero-engine optimum data-driven dynamic start process model based on PGP is proposed. In application of this method, first, the traditional Genetic Programming（GP） is used to generate the nonlinear input-output models that are represented in a binary tree structure; then, the Orthogonal Least Squares algorithm （OLS） is used to estimate the contribution of the branches of the tree （refer to basic function term that cannot be decomposed anymore according to special rule） to the accuracy of the model, which contributes to eliminate complex redundant subtrees and enhance GP＇s convergence speed; and finally, a simple, reliable and exact linear-in-parameter nonlinear model via GP evolution is obtained. The real aero-engine start process test data simulation and the comparisons with Support Vector Machines （SVM） validate that the proposed method can generate more applicable, interpretable models and achieve comparable, even superior results to SVM.

Reliability Based Design Optimization of Aero-Engine Spindle Ball Bearings

Aero-engine spindle ball bearings work in harsh conditions which are affected by relatively complex stresses. One of the key factors which affects bearing performance is its structure. In this paper,we used reliability based design optimization method to solve the structure design problem of aero-engine spindle ball bearings.Compared with the optimization design method, the value of equivalent dynamic load using reliability optimization design method was the least by MATLAB simulation. Also the design solutions show that the optimized structure possesses higher reliability than the original solution.

Failure Assessment of Aero-engine Support Structure due to Blade-off

Aero-engine blade-off event could cause serious malfunction and endanger flight safety,which is an important issue widely concerned for a long period.This paper presents a comprehensive review on the regulation requirements,the major research methods and status at home and abroad.Firstly,the relevant certification regulations and standards about aero-engine structure safety due to blade-off event were overviewed and the research gaps between the abroad and the domestic were compared.Then,the simulation and experimental methodologies on aero-engine supporting structures undertake abnormal load due to blade-off event were discussed as major issue.Finally,the safety certification verification technology system for aero-engine support structures during blade-off event was proposed.

Recognition and practice on remanufacturing engineering management of military aero-engines

The technologies of design, manufacture and MRO （maintenance, repair and overhaul） tor the mili- tary aero-engines, particularly for the fighters, are much more difficult to be mastered than those for any other aero-engines. They have been monopolized by only a few countries and the core technologies have never been transferred due to high risk, high investment, high barrier and high cost. Therefore, our country has long relied on mapping and copying the others＇ engines to satisfy the domestic demand due to not having our own indepen- dent technologies for the design and manufacture of military aero-engines. However, through over 20 years of unremitting effort, the independent MRO has been achieved for all the Chinese fighter engines, covering in- R＆D （research and development） and in-service engines; and the MRO technologies, capabilities, quality, cost-efficiency have reached or exceeded those of original manufacturers. It has grown out of nothing, and then from weak to strong. In particular, dozens of projects concerning the R＆D and engineering application of re- manufacturing have obtained the independent intellectual property rights and are playing an irreplaceable role in achieving leaping improvement of independent MRO for Chinese military aero-engines.

Power System Analysis of an Aero-Engine

The aim of this study is analyzed in detail for better understanding of energy and power of an aero-engine. In this regard, this study presents energy equations were applied to the turbofan engine components. The engine has a thrust range of 82 to 109 kN. It consists of fan, axial low pressure compressor (LPC), axial high pressure compressor (HPC), an annular combustion chamber, high-pressure turbine (HPT) and low pressure turbine (LPT). The results show that power of the engine flow approaches a maximum value to be 82.85 MW in the combustor outlet, while minimum power is observed at LPC inlet with the value of 1.37 MW. Furthermore, important parameters of the engine are also analyzed from reverse-engineering method. It is expected that results of this study will be beneficial of power, cogeneration and aero-propulsive generation systems in similar environment.

基于ResNet-LSTM的航空发动机性能异常检测方法

为了实现数据驱动的航空发动机性能异常的智能检测,提出了一种基于残差网络(ResNet)-长短期记忆网络(LSTM)的发动机性能异常检测方法。采用发动机性能数据图像化方法,在数据降维的同时,完备保留数据的关联特征和时序特征;以残差单元构建发动机性能异常检测模型,在加深网络结构的同时,消除深层网络梯度消失问题,提高发动机性能图像空间关联特征的提取能力。同时,引入LSTM,提出基于ResNet-LSTM的发动机性能异常检测模型,通过ResNet与LSTM的融合,强化异常检测模型对时序特征的提取,提升发动机性能异常检测的准确率;通过发动机运行数据进行验证。结果表明:在训练集上,该方法的异常检测准确率为94.95%,比基于ResNet18、ResNet34、ResNet50异常检测模型的分别提高10.87%、8.00%、3.23%;在测试集上,该方法的异常检测准确率为92.15%,比基于ResNet18、ResNet34、ResNet50异常检测模型的分别提高11.81%、9.45%、3.78%。

基于热-力耦合的航空发动机叶片堆焊修复数值模拟

压气机叶片极易出现各类损伤缺陷,因此研究其修复技术有十分重大的意义。利用某有限元软件,使用顺序热-力耦合模型对受损叶片氩弧焊堆焊修复过程进行了数值模拟,同时使用Inconel718合金进行单道堆焊试验。结果表明,数值仿真结果与试验结果吻合良好,所用有限元模型能有效模拟氩弧焊堆焊修复过程。分析不同堆焊层数、不同堆焊方案下叶片温度场、热变形和残余应力情况,模拟过程中熔池形状与实际熔池形状较为吻合,热源中心温度达到堆焊要求;通过对比不同层数下热变形量和残余应力值发现,变形量和残余应力值会随着堆焊层数的增加而增大;顺序堆焊在冷却后的变形和残余应力均大于往复堆焊;为了减小叶身残余应力,应该在保证修复质量的前提下,尽量减少叶尖修复的长度和堆焊层数,并采用往复堆焊。最后对比修复后叶片和完好叶片的固有频率,分析发现二者频率几乎相等,表明使用堆焊对损伤叶片进行修复具有较高的修复质量。

RELIABILITY ANALYSIS FOR AN AERO ENGINE TURBINE DISK UNDER LOW CYCLE FATIGUE CONDITION

Reliability analysis methods based on the linear damage accumulation law (LDAL) and load-life interference model are studied in this paper. According to the equal probability rule, the equivalent loads are derived, and the reliability analysis method based on load-life interference model and recurrence formula is constructed. In conjunction with finite element analysis (FEA) program, the reliability of an aero engine turbine disk under low cycle fatigue (LCF) condition has been analyzed. The results show the turbine disk is safety and the above reliability analysis methods are feasible.

基于MIC特征提取与BO-CatBoost的航空发动机RUL预测

针对航空发动机传感器监测的退化参数提取困难,易受噪声干扰及发动机剩余使用寿命预测精度不足等问题,利用最大信息系数、贝叶斯优化算法和类别特征梯度提升算法,提出了一种新的发动机剩余使用寿命预测模型。首先,为有效解决特征提取不足的问题,对采集的传感器历史监测特征进行最大信息系数相关性计算,提取出对发动机寿命运行周期影响较大的关键退化特征。其次,为解决剩余使用寿命预测中的梯度偏差及预测偏移问题,使用基于贝叶斯优化的类别特征梯度提升方法对航空发动机进行剩余使用寿命预测。最后,在美国航空航天局提供的商用模块化航空推进系统仿真数据集上进行实验,结果表明所提预测方法的性能较好,验证了该方法的有效性。

航空发动机可调静叶调节机构WC-Co强化层摩擦学性能研究

航空发动机可调静叶(VSV)调节结构为影响航空发动机正常工作以及飞行安全的重要结构,在VSV调节角度的过程中,转轴-衬套的磨损是影响角度调节精度的重要因素。为提高VSV系统转轴-衬套摩擦副的抗磨损性能,利用大气等离子喷涂技术在转轴表面制备WC-Co抗磨损涂层,采用自主研发的转轴-衬套摩擦磨损试验机针对转轴-衬套进行模拟工况磨损性能评价。结果表明:在模拟工况下,转轴-衬套摩擦副的摩擦力矩与载荷关系最为密切,随载荷增大,摩擦力矩增大。对磨损后的表面进行表面成分分析及微观形貌观察可以得出:温度升高摩擦副发生黏着磨损现象,导致磨损加剧,引起颗粒断裂;在相同温度条件下,载荷增大导致接触应力增大,接触面被磨损;而磨损系数随温度升高呈先减后增的趋势。研究结果为VSV系统转轴-衬套设计提供参考依据。

航空燃气涡轮-电混合动力系统关键技术分析

本文介绍了串联式和并联式混合动力系统的基本原理与性能特点,对混合动力的性能优势来源进行了原理性阐述。针对混合动力的系统架构,分析了性能设计、控制系统、电机设计以及热管理方面的关键技术。航空燃气涡轮-电混合动力技术的发展,有可能对传统航空发动机领域产生颠覆性变革。需要打破原有航空发动机热力机械设计思维,将动力系统所涉及的推进、电能以及热管理进行融合设计,推动航空动力系统效能进一步提升。

一种基于TCN-LGBM的航空发动机气路故障诊断方法

长时间工作在高温高压、强振动等恶劣气路环境下的航空发动机经常面临部件疲劳、腐蚀和性能退化的问题,且其故障诊断时序逻辑性不强、故障参数耦合较深等特点十分明显,为此提出一种基于时间卷积神经网络(Temporal Convolutional Network,TCN)和轻量级梯度提升机(Light Gradient Boosting Machine,LGBM)的航空发动机气路故障诊断方法。故障诊断分为故障特征提取和分类诊断两个过程:引入TCN框架,在保证故障数据训练时序逻辑的基础上,实现对远层历史信息和当前层信息的特征融合构建,融合通道注意力机制增强了高质量特征的权重;基于LGBM模型实现对特征的快速分类,利用贝叶斯方法实现对模型超参数的快速优化。以基于PROOSIS软件建模的某军用小涵道比涡扇发动机故障仿真数据为例,对6种故障模式进行诊断识别。仿真结果表明了所提方法的有效性;通过与其他模型对比体现了该方法的优越性。