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Feasibility Study of SDAS Instrumentation's Ability to Identify Mobile Launcher (ML)/Crawler-Transporter (CT) Modes During Rollout Operations

机译:SDAS仪器在推出操作期间识别移动发射器(ML)/履带式运输机(CT)模式的能力研究的可行性研究

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The Space Launch System (SLS) and its Mobile Launcher (ML) will be transported to the launch pad via the Crawler-Transporter (CT) system. Rollout (i.e., transportation) loads produce structural loads on the integrated SLS/Orion Multi-Purpose Crew Vehicle (MPCV) launch vehicle which are of a concern with respect to fatigue. As part of the risk reduction process and in addition to the modal building block test approach that has been adopted by the SLS Program, acceleration data will be obtained during rollout for use in modal parameter estimation. There are several occurrences where the ML/CT will be transported either into the Vertical Assembly Building (VAB) or to the launch pad and back without the SLS stack as part of the Kennedy Space Center (KSC) Exploration Ground Systems (EGS) Integrated Test and Checkout (ITCO). NASA KSC EGS has instrumentation installed on both the ML and CT to record data during rollout, at the launch pad, and during liftoff. The EGS instrumentation on the ML, which includes accelerometers, is referred to as the Sensor Data Acquisition System (SDAS). The EGS instrumentation on the CT, which also includes accelerometers, is referred to as the CT Data Acquisition System (CTDAS). The forces and accelerations applied to the ML and CT during a rollout event will be higher than any of the planned building block modal tests. This can be very beneficial in helping identify nonlinear behavior in the structure. Developing modal parameters from the same test hardware in multiple boundary conditions and under multiple levels of excitation is a key step in developing a well correlated FEM. The purpose of this study was three fold. First, determine the target modes of the ML/CT in its rollout configuration. Second, determine if the test degrees of freedom (DOF) corresponding to the layout of the SDAS/CTDAS accelerometers (i.e. position and orientation) is sufficient to identify the target modes. Third, determine if the Generic Rollout Forcing Functions (GRFF's) ("Development of Generic Crawler/Transporter Rollout Forcing Functions for Coupled System Dynamics Analysis," NASA Exploration Systems Directorate/Cross-Program Systems Integration Technical Assessment Report, ESD 20038, July 31, 2018) is sufficient for identifying the ML/CT target modes accounting for variations in CT speed, modal damping, and sensor/ambient background noise levels. The finding from the first part of this study identified 28 target modes of the ML/CT rollout configuration based upon Modal Effective Mass Fractions (MEFF) and engineering judgement. The finding from the second part of this study showed that the SDAS/CTDAS accelerometers (i.e. position and orientation) are able to identify a sufficient number of the target modes to support model correlation of the ML/CT FEM. The finding from the third part of this study confirms the GRFFs sufficiently excite the ML/CT such that varying quantities of the defined target modes should be able to be extracted when utilizing an Experimental Modal Analysis (EMA) Multi-Input Multi-Output (MIMO) analysis approach. An EMA analysis approach was used because Operational Modal Analysis (OMA) tools were not available and the GRFFs were sufficiently uncorrelated. Two key findings from this third part of the study are that the CT speed does not show a significant impact on the ability to extract the modal parameters and that keeping the ambient background noise observed at each accelerometer location at or below 30 μgrms is essential to the success of this approach. Even though this study relies heavily upon the accuracy of both uncorrelated ML and CT FEM's and unconfirmed rollout forcing functions, all of which will most likely differ from actuality, it provides important insights into the ability to extract modal parameters from the upcoming rollout events.
机译:空间发射系统(SLS)及其移动发射器(ML)将通过履带式运输器(CT)系统运输到发射垫。推出(即,运输)负载在集成的SLS / ORION多功能机组车辆(MPCV)发射车辆上产生结构载荷,这对疲劳有所关注。作为风险降低过程的一部分,除了SLS程序采用的模态构建块测试方法之外,在卷展栏期间将获得加速数据,以用于模态参数估计。在没有SLS堆叠的情况下,ML / CT将输送到垂直组装建筑物(VAB)或后退的情况下,将ML / CT运输到垂直组件建筑物(VAB)和后退。和结账(ITCO)。 NASA KSC EGS在ML和CT上安装了仪器,以记录卷展栏,在发射垫和升降期间记录数据。包括加速度计的M1上的EGS仪器被称为传感器数据采集系统(SDA)。 CT的EGS仪器还包括加速度计的CT被称为CT数据采集系统(CTDA)。在卷展栏事件期间施加到M1和CT的力和加速度将高于任何计划的构建块模态测试。这对于帮助识别结构中的非线性行为非常有益。在多个边界条件下开发来自相同测试硬件的模态参数,并且在多级激励下是开发良好相关的有限元的关键步骤。本研究的目的是三倍。首先,确定其卷展栏配置中M1 / CT的目标模式。其次,确定对应于SDAS / CTDAS加速度计的布局(即位置和方向)的对应的测试自由度(DOF)是否足以识别目标模式。三,确定通用卷展栏强制函数(GRFF's)(“通用履带式/运输机推出耦合系统动态分析的函数,”NASA勘探系统总局/跨计划系统集成技术评估报告,ESD 20038,7月31日, 2018)足以识别ML / CT目标模式核算CT速度,模态阻尼和传感器/环境背景噪声水平的变化。本研究的第一部分的发现基于模态有效质量分数(MEFF)和工程判断,确定了ML / CT推出配置的28个目标模式。本研究第二部分的发现表明,SDAS / CTDA加速度计(即位置和方向)能够识别足够数量的目标模式以支持ML / CT FEM的模型相关性。本研究第三部分的发现证实了GRFF充分激发ML / CT,使得在利用实验模态分析(EMA)多输入多输出(MIMO)时应该能够提取不同数量的定义目标模式。 )分析方法。使用EMA分析方法,因为操作模态分析(OMA)工具不可用,并且GRFF足够不相关。来自该研究的第三部分的两个主要发现是CT速度对提取模态参数的能力并不显示出在每个加速度计位置处观察到的环境背景噪声对其至30μgrms是至关重要的这种方法的成功。尽管本研究依稀依赖于不相关的ML和CT FEM和未经证实的卷展栏强制函数的准确性,但所有这些都可能与现实有所不同,因此它提供了从即将到来的卷展活动中提取模态参数的能力的重要见解。

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