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METHODS FOR AUTOMATING MODEL VALIDATION: STEADY-STATE IDENTIFICATION APPLIED ON GRIPEN FIGHTER ENVIRONMENTAL CONTROL SYSTEM MEASUREMENTS

机译:自动模型验证的方法:稳态识别在格里芬战斗机环境控制系统测量中的应用

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Model Validation and Verification (V&V) has historically often been considered a final step in the model development process. However, to justify model-based design decisions throughout the entire system development process, a methodology for continuous model V&V is essential. That is, model V&V activities should be fast and easy to reiterate as new information becomes available.Using a high fidelity simulation model of the Environmental Control System (ECS) in the Saab Gripen fighter aircraft as a guiding example, this paper further extends to an existing semi-automatic framework for model steady-state validation developed during ECS model validation efforts. Generic methods for identification of steady-state operation are a prerequisite for steady-state validation of industry grade physics based models against in-situ measurements. Four different established methods for steady-state identification are investigated and compared: steady-state conditions on the standard deviation estimated from in-situ measurements, conditions on the variation coefficient, t-test on the slope of a simple regression line, and comparison of differently estimated variances. The methods’ applicability, on ECS measurements in particular, is evaluated utilizing steady-state identification needs defined during Gripen ECS model validation activities.
机译:历史上,模型验证和验证(V&V)通常被认为是模型开发过程中的最后一步。但是,为了证明在整个系统开发过程中基于模型的设计决策的合理性,一种用于连续模型V&V的方法至关重要。也就是说,随着新信息的出现,典范的V&V活动应该迅速且易于重申。 以Saab Gripen战斗机的环境控制系统(ECS)的高保真仿真模型为指导示例,本文进一步扩展到在ECS模型验证工作期间开发的用于模型稳态验证的现有半自动框架。用于识别稳态操作的通用方法是针对基于现场测量的工业级基于物理的模型进行稳态验证的先决条件。研究并比较了四种不同的确定稳态的方法:从现场测量估算的标准偏差的稳态条件,变异系数的条件,简单回归线斜率的t检验以及比较不同估计的方差。该方法在ECS测量中的适用性,是通过在Gripen ECS模型验证活动中定义的稳态识别需求进行评估的。

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