An Overview of Bearing Candidates for the Next Generation of Reusable Liquid Rocket Turbopumps

There is a consensus in the aerospace field that the development of reusable liquid rockets can effectively reduce the launch expense.The pursuit of a long service life and reutilization highly depends on the bearing components.However,the rolling element bearings(REBs)used in the existing rocket turbopumps present obvious and increasing limitations due to their mechanical contacting mode.For REBs,high rotational speed and long service life are two performance indexes that mutually restrict each other.To go beyond the DN value(the product of the bearing bore and rotational speed)limit of REBs,the major space powers have conducted substantial explorations on the use of new types of bearings to replace the REB.This review discusses,first,the crucial role of bearings in rocket turbopumps and the related structural improvements of REBs.Then,with the prospect of application to the next generation of reusable liquid rocket turbopumps,the bearing candidates investigated by major space powers are summarized comprehensively.These promising alternatives to REBs include fluid-film,foil,and magnetic bearings,together with the novel superconducting compound bearings recently proposed by our team.Our more than ten years of relevant research on fluid-film and magnetic bearings are also introduced.This review is meaningful for the development of long-life and highly reliable bearings to be used in future reusable rocket turbopumps.

Turbopump Condition Monitoring Using Incremental Clustering and One-class Support Vector Machine

Turbopump condition monitoring is a significant approach to ensure the safety of liquid rocket engine （LRE）.Because of lack of fault samples,a monitoring system cannot be trained on all possible condition patterns.Thus it is important to differentiate abnormal or unknown patterns from normal pattern with novelty detection methods.One-class support vector machine （OCSVM） that has been commonly used for novelty detection cannot deal well with large scale samples.In order to model the normal pattern of the turbopump with OCSVM and so as to monitor the condition of the turbopump,a monitoring method that integrates OCSVM with incremental clustering is presented.In this method,the incremental clustering is used for sample reduction by extracting representative vectors from a large training set.The representative vectors are supposed to distribute uniformly in the object region and fulfill the region.And training OCSVM on these representative vectors yields a novelty detector.By applying this method to the analysis of the turbopump＇s historical test data,it shows that the incremental clustering algorithm can extract 91 representative points from more than 36 000 training vectors,and the OCSVM detector trained on these 91 representative points can recognize spikes in vibration signals caused by different abnormal events such as vane shedding,rub-impact and sensor faults.This monitoring method does not need fault samples during training as classical recognition methods.The method resolves the learning problem of large samples and is an alternative method for condition monitoring of the LRE turbopump.

Entropy production by dissipation effects and characteristic vortex evolution in a rocket turbopump

The relationship between entropy production and vortex evolution affects the efficiency and stability of rotating machinery.This study investigated the energy characteristics of a rocket turbopump and revealed the correlated mechanisms of the entropy production rate using the dissipation effects and characteristic vortex evolution.For the first time,direct and turbulent dissipation and rigid and shear vorticity decomposition methods were utilized to analyze the correlation between flow loss and characteristic vorticities in rotating machinery.With an increase in the flow rate,the hydraulic losses of the dissipation effects and wall decreased by 60%and 38.3%,respectively,and the proportions of the input energy decreased(from 13%to 8%)and remained stable(8%),respectively.The local direct dissipative entropy production(DDEP)in the inducer-impeller is strongly related to shear entropy,and the correlated effect of total enstrophy on DDEP is weaker than that of shear vorticity,indicating that rigid enstrophy suppresses direct dissipation.The correlation between turbulent dissipation and rigid enstrophy was significantly weaker in the static flow passage of the turbopump owing to the weak rigid rotational effect.The correlation between the rigid entropy and local turbulent dissipative entropy production(TDEP)gradually increased with increasing flow rate,reaching a medium correlation(the maximal correlated degree in the turbopump)and exhibiting rigid rotation effects on the hydraulic loss.Moreover,the flow rate significantly affected the correlation(except for the diffuser),and the two characteristic vorticities reached a maximum at the designed flow rate owing to optimal efficiency and minimum hydraulic loss.

Identification of Backflow Vortex Instability in Rocket Engine Inducers

Bayesian estimation is applied to the analysis of backflow vortex instabilities in typical three-and four bladed liquid propellant rocket(LPR)engine inducers.The flow in the impeller eye is modeled as a set of equally intense and evenly spaced 2D axial vortices,located at the same radial distance from the axis and rotating at a fraction of the impeller speed.The circle theorem and the Bernoulli’s equation are used to predict the flow pressure in terms of the vortex number,intensity,rotational speed,and radial position.The theoretical spectra so obtained are frequency broadened to mimic the dispersion of the experimental data and parametrically fitted to the measured pressure spectra by maximum likelihood estimation with equal and independent Gaussian errors.The method is applied to three inducers,tested in water at room temperature and different loads and cavitation conditions.It successfully characterizes backflow instabilities using the signals of a single pressure transducer flush-mounted on the casing of the impeller eye,effectively by-passing the aliasing and data acquisition/reduction complexities of traditional multiple-sensor cross correlation methods.The identification returns the estimates of the model parameters and their standard errors,providing the information necessary for assessing the accuracy and statistical significance of the results.The flowrate is found to be the major factor affecting the backflow vortex instability,which,on the other hand,is rather insensitive to the occurrence of cavitation.The results are consistent with the data reported in the literature,as well as with those generated by the auxiliary models specifically developed for initializing the maximum likelihood searches and supporting the identification procedure.

基于Hessian局部线性嵌入和MLP-Mixer的液体火箭发动机涡轮泵轻量化故障诊断框架

作为液体火箭发动机推进剂输送系统的关键部件,涡轮泵的运行状态直接影响着整个运载系统的性能,然而,现有的故障诊断方法往往面临特性参数选择片面及计算复杂度高等问题。针对上述局限,提出了面向涡轮泵的轻量化故障诊断框架。所提方法利用Hessian局部线性嵌入算法对信号时域、频域及时频特征进行降维,并引入一种轻量化的深度学习模型MLP-Mixer作为分类器,进而实现不同故障状态的辨识。采用某型号涡轮泵试车数据验证了所提方法的有效性,结果表明,该方法能够在保障诊断精度的同时有效降低计算复杂度,提高诊断效率。

液体火箭发动机涡轮泵管式扩压器时序效应数值研究

为分析管式扩压器的时序效应对高速涡轮泵性能以及压力脉动的影响并阐明其影响机制,对某液体火箭发动机高速涡轮泵全流域进行三维定常和非定常数值计算,研究了管式扩压器时序效应对涡轮泵外特性的影响规律,采用熵产理论对涡轮泵内部的能量损失进行分析,并通过压力脉动均方根方法对涡轮泵内的压力脉动进行评估。结果表明:随着管式扩压器叶片与蜗壳隔舌夹角的增大,涡轮泵效率和扬程整体趋势均为先升高后降低,两者的变化幅度分别为0.75%、1.68%,当管式扩压器叶片吸力面出口边与蜗壳隔舌的夹角为20.5°、25.5°时,涡轮泵具有较好的性能,其影响机制由蜗壳隔舌下方的扩压管出口附近涡流和能量损失变化决定。动静干涉效应是涡轮泵内压力脉动的主要原因,时序效应对涡轮泵出口和蜗壳隔舌附近压力脉动的变化幅度分别为37.7%、67.6%。蜗壳流道内压力脉动的最大值位于蜗壳隔舌下方扩压管出口区域,时序效应对压力脉动最大值的变化幅度为20.5%。研究结果可为液体火箭发动机涡轮泵性能和振动的优化提供一定的参考。

宽工作范围诱导轮空化不稳定及抑制

涡轮泵是液体火箭发动机的心脏,在特定工况下其内部会发生空化不稳定现象,导致涡轮泵振动量级大幅增加,严重影响发动机整机工作可靠性.以决定涡轮泵抗空化能力的关键部件诱导轮为研究对象,利用空化可视化实验和数值仿真对其内部空化流动特性进行深入分析,获得60%~120%设计点流量范围完整空化性能曲线,提出一种基于壳体改进的旋转空化抑制措施,并揭示抑制机理.结果表明:该型诱导轮抗空化能力随流量降低逐渐增强,空化首先发生在泄漏涡中,随空化数降低,泄漏涡空化逐渐沿吸力面向下游发展,影响相邻叶片冲角,在小流量范围诱发显著的1.2倍叶轮转频超同步旋转空化现象,直至空化延伸至叶片流道出口,导致扬程断裂;在叶尖前缘壳体设置台阶不会影响诱导轮稳态空化性能,但会改变泄漏涡空化的发展规律,使其呈现向上游摆动的趋势,削弱对相邻叶片冲角的影响,实现对全流量范围旋转空化的有效抑制.文章研究对于降低涡轮泵振动量级,进一步提升液体火箭发动机工作可靠性有一定指导意义.

涡轮泵用不同槽型流体动压型机械密封运行特性对比研究

针对火箭发动机低温介质涡轮泵端面密封的泄漏突增问题,基于工程经验提出激光脸(槽深3、5μm)和螺旋槽3种槽型结构,并与原使用的雷列槽进行端面流场与密封性能对比分析,同时对4种槽型结构进行密封动态追随性比较分析。结果发现:低温介质下雷列槽端面密封流体动压较弱,影响端面开启的主要因素为流体介质静压力;在转速和压力增大的条件下雷列槽存在负动态刚度系数,角向的稳定性较差,存在泄漏风险;激光脸泄漏量较低且处于混合润滑状态,不会因密封端面脱开而引起密封动态不稳定;槽深5μm与槽深3μm激光脸相比有更大的开启力与较低的相变率,综合性能更优;螺旋槽结构动压效应较强,其开启力随转速和压力的线性变化都保障了密封环的追随性;螺旋槽结构具有较强变工况适应性,但泄漏量水平始终较高。

液体火箭发动机涡轮泵多维度传感器优化布置

针对液体火箭发动机涡轮泵健康监测时存在的结构重要模态信息遗漏、故障敏感信息提取不全等问题,提出了一种涡轮泵传感器多维度优化布置方法,并采用故障模拟实验台进行了实验验证。首先,建立了涡轮泵待优化区域的有限元模型并开展了结构约束模态分析以及轴承故障仿真瞬态动力学分析;其次,基于离散人工蜂群算法及瞬态分析结果得出传感器布置候选点集;再次,综合传感器多维度评估方法得出最终的传感器布置方法;最后,通过实验对比分析了传感器布置方法与传统方法的综合指标。计算结果表明:相对于有效独立法,布置测点优化后,传感器监测信号的模态振型符合率提高了20.1%,对轴承故障检测的准确率提高了27.5%,验证了多维度优化布置方法具有良好的故障诊断综合性能。

可重复使用液体火箭发动机涡轮泵轴承设计及试验

可重复使用液体火箭发动机研制需求的出现,对涡轮泵结构可靠性设计提出了更高的要求。针对涡轮泵中轴承在低温、高速、重载、重复启停等恶劣工况下容易失效的问题,以某型可重复使用液氧/煤油火箭发动机涡轮泵为研究对象,从结构、材料、保持架等方面对涡轮泵轴承进行了设计和动力学计算分析。根据涡轮泵工作工况,设计了低温和常温轴承运转试验系统,进行了轴承重复启停运转试验,试验过程中对轴承温度和运转转速进行监测以便判断轴承状态,试验后检查轴承钢球和滚道均正常,并对轴承设计参数进行复测发现无较大偏差。试验结果表明,设计的涡轮泵轴承在设计转速下可以完成预定的重复启停运转,同时试后同批次轴承搭载发动机试车考核成功重复点火十余次。

重复使用火箭涡轮泵轴承故障特征提取方法优化

涡轮泵轴承是可重复使用火箭的关键,因此能够有效提取出轴承故障特征频率从而展开故障诊断十分重要。将奇异值分解(SVD)和包络谱解调法相结合,对火箭涡轮泵轴承展开故障特征提取。对轴承内环、外环及滚动体故障数据进行处理和分析,结果表明,针对信号中含有大量噪声的数据,相比传统的包络谱解调法,改进方法的故障特征提取效果明显提升。通过该方法提取出的3种故障低频特征频率的相对幅值相比于传统包络谱解调均有提升。同时,可以有效降低高频噪声的干扰,尤其在高频区依然可以看到比较明显的特征频率,而传统包络谱解调法的高频区基本被噪声覆盖。通过计算得出信号的信噪比均有60 dB以上的提升。

考虑表面粗糙度影响的低温涡轮泵特性与动静间隙流动分析

为分析低温涡轮泵过流部件表面粗糙度对其性能特性的影响,阐明表面粗糙度对涡轮泵动静间隙流场的影响机制,选择增材制造闭式叶轮涡轮氧泵为研究对象,在考虑低温介质热力学效应影响的前提下,采用液氮作为增压输送介质,对涡轮泵低温性能开展实验测试和数值计算。研究结果表明:在13 500~26 000 r/min转速范围内,相较于光滑壁面,考虑过流部件表面粗糙度后,采用液氮作为模拟介质得到的涡轮氧泵数值计算结果与实验测试数据吻合较好;随着离心叶轮及蜗壳等主流表面粗糙度从光滑壁面增加至36μm,涡轮氧泵扬程及效率分别下降了9.1%、10.6%;随着动静间隙过流部件表面粗糙度从0增加至20μm,涡轮泵叶轮轴向力合力系数显著降低了25.8%。研究结果对后续深入揭示表面粗糙度对低温涡轮泵动静间隙流场特性影响规律以及过流部件表面质量分区控制具有重要借鉴意义及参考价值。

重复使用火箭发动机涡轮泵载荷谱编制方法

重复使用火箭一子级发动机通过多次点火将火箭送入预定轨道后,返回并定点回收,多次启动-关机会产生损伤累积及疲劳问题,掌握液体发动机涡轮泵真实载荷谱,是可重复使用火箭发动机研制中一项重要工作。针对重复使用火箭一子级发动机涡轮泵提出了载荷谱编制方法。根据回收任务方案,确定任务全周期飞行剖面,建立火箭动力学方程,计算一子级各飞行剖面发动机推力调节范围及质量流量。基于推进剂组分、质量流量等参数推算涡轮泵转速及功率变化,编制转速谱和功率谱。通过对SpaceX公司猎鹰9一子级陆地回收任务CRS-11分析,编制该任务全周期载荷谱,得到一子级发动机推力谱、涡轮泵转速谱和功率谱,通过真实推力数据验证载荷谱编制方法。研究结果可为重复使用发动机研制提供支撑。

基于注意力机制的火箭涡轮泵支承刚度辨识

作为重要的动力学参数,刚度辨识及预测对于涡轮泵动力特性具有关键意义,为此提出一种融合注意力机制和双向长短期记忆(Bi⁃directional long short⁃term memory,BiLSTM)网络的预测模型。将动力学响应融合输入,使用LSTM神经网络有效挖掘时序相关的历史特征。再将两层LSTM网络反向叠加组成BiLSTM模型,适应动力学信息复杂、序列冗长特点,深入挖掘参数间的非线性特征。随后引入Attention层,利用注意力机制获取特征分配权重,增强关键信息。最后通过某型涡轮泵的动力学数据训练辨识模型。结果表明,对于涡轮泵刚度特性,Attention⁃BiLSTM模型在序列数据处理方面具有显著优势,预测平均绝对百分比误差(Mean absolute percentage error,MAPE)可达2.1945%。而单一结构的RNN、LSTM和BiLSTM模型的预测MAPE分别为10.4977%、5.4973%和2.7986%。可见该方法有效避免了复杂的动力学反问题求解,实现了非线性参数的动态识别。

基于VMD和FCM的火箭发动机涡轮泵状态监测方法

面向重复使用火箭发动机的状态监测与故障诊断需求,针对振动信号的非平稳性和难以提取有效故障特征的问题,提出一种基于变分模态分解(Variational Mode Decomposition, VMD)和模糊C均值聚类(Fuzzy C-Means, FCM)的状态监测方法。采用优化VMD算法自适应地将振动信号分解为多个本征模态分量(Intrinsic Mode Function, IMF),根据加权相关样本熵最大准则选取关键IMF分量;利用t分布随机近邻嵌入(t-SNE)对关键IMF分量的多维时域、频域特征降维,得到特征向量矩阵;利用模糊C均值聚类算法实现发动机工作状态的监测。将该方法应用于发动机涡轮泵工作状态监测,结果表明其能够提取振动信号关键特征,准确识别涡轮泵工作状态,测试集识别准确率达92.50%,为火箭发动机状态监测与故障诊断提供了理论支撑。

空化诱导轮内流动不稳定性的最大似然估

The article illustrates the application of Bayesian estimation to the identification of flow instabilities,with special reference to rotating cavitation,in a three-bladed axial inducer using the unsteady pressure readings of a single transducer mounted on the casing just behind the leading edges of the impeller blades.The typical trapezoidal pressure distribution in the blade channels is parametrized and modulated in time and space for theoretically reproducing the expected pressure generated by known forms of cavitation instabilities(cavitation auto-oscillations and higher-order surge cavitation modes,n-lobed subsynchronous/synchronous/super-synchronous rotating cavitation).The Fourier spectra of the theoretical pressure so obtained in the rotating frame are transformed in the stationary frame,frequency broadened to better approximate the experimental results,and parametrically fitted by maximum likelihood estimation to the measured auto-correlation spectra.Each form of instability generates a characteristic distribution of sidebands in addition to its fundamental frequency.The identification makes use of this information for effective detection and characterization of multiple simultaneous flow instabilities with intensities spanning over about 20 db down to about 4 db signal-to-noise ratios.The same information also allows for effectively bypassing the aliasing limitations of traditional cross-correlation methods in the discrimination of multiple-lobed azimuthal instabilities from the measurements returned by arrays of equally spaced sensors.The method returns both the estimates of the model parameters and their standard deviations,providing the information needed for the assessment of the statistical significance of the results.The proposed approach represents therefore a promising tool for experimental research on flow instabilities in high-performance turbopumps.

滚动轴承-火箭发动机液氢涡轮泵转子系统的动力特性分析

用有限元方法建立火箭发动机液氢涡轮泵转子的离散化模型,并提出考虑滚动轴承内间隙、运行表面波纹度和滚动体离心力等因素的二自由度滚动轴承模型,从而建立了滚动轴承-液氢涡轮泵转子系统的非线性动力学模型。通过数值仿真研究了液氢涡轮泵转子系统动力学问题集中的启动阶段的非线性动力特性。发现在启动阶段不但有同步共振,而且会发生亚谐共振。径向载荷的大小会显著影响同步及亚谐共振的起始时间。滚动体的离心力和滚动轴承的波纹度对转子系统的动力特性有明显影响。

长中短叶片离心叶轮内部流动的数值模拟

采用Navier-Stokes方程和Spalart-A llm aras湍流模型对8叶片和24叶片的高速复合离心叶轮内部的流动进行了数值模拟,对小流量和设计点两种工况进行了计算和对比分析,得到了叶轮内的速度和压力分布;发现具有4长、4中、16短的24叶片的复合叶轮内部及出口的速度分布比4长4中的8叶片的叶轮更均匀;而且中、短叶片对液流有加功作用,可以增加叶轮出口吸力面的压力,有效阻止液流的脱流。通过实验和数值模拟,验证了叶轮流道里的回流是影响低比转速离心泵效率和小流量不稳定的一个重要因素;采用具有中、长、短的闭式复合叶轮离心泵适合用来输送小流量、高扬程的液态介质。

密封和内阻尼对火箭发动机液氢涡轮泵转子系统动力稳定性的影响

考虑内阻尼的Timoshenko梁一轴有限元离散化转轴,用Muszynska密封力模型描述非线性密封流体激振力,建立实际火箭发动机液氢涡轮泵转子系统的非线性有限元模型。结合已有试验数据,结合打靶法和Floquet 理论研究该系统在刚性支承和柔性支承两种工况下密封和内阻尼对系统稳定性的影响。分析轴承阻尼、轴向雷诺数以及密封各参数在两种支承下对系统临界失稳角速度的影响。

基于PCA相似系数与SVM的涡轮泵故障检测算法

提出了一种基于主元分析法(principal component analysis,PCA)相似系数与支持向量机(support vector machine,SVM)的故障检测算法用于液体火箭发动机涡轮泵试车后故障检测。该算法将历史信号按合理的步长分段,对信号段进行小波去噪预处理;再将每个步长信号平分为多段,采用主元分析法对每段信号进行降维处理;以第1段信号为基准,计算其他各段信号与第1段信号的相似系数,将所得相似系数组成向量作为故障特征;提取历史信号的所有故障特征向量构建SVM的训练样本集,并由此得到SVM决策函数用于待检信号的故障检测。用某型号涡轮泵振动加速度信号对算法进行验证,结果表明对时长21.50 s的待检信号,算法检出故障发生时刻为20.0076 s,非常接近故障真实出现时刻(约20.007 s),未出现虚警和漏警。算法具备了良好的准确性。