CruiseBench：用于发动机剩余使用寿命预测的真实飞行对齐N-CMAPSS基准测试
CruiseBench: A Real-Flight-Aligned N-CMAPSS Benchmark for Engine RUL Prediction
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中文总结 AI 辅助
研究发动机RUL预测问题，提出CruiseBench基准测试及CPM-N-CMAPSS方法，通过固定协议处理数据，排除部分因素，利用多种模型实验给出基线结果，为RUL模型比较提供可重复子基准及数据基础。
中文摘要 AI 辅助
剩余使用寿命（RUL）预测对发动机维护规划至关重要。N-CMAPSS通过模拟实际飞行剖面来扩展C-MAPSS，增加了真实感，但降低了评估控制。本文提出CruiseBench，一个从N-CMAPSS派生的巡航阶段RUL基准测试。它引入CPM-N-CMAPSS，应用固定协议处理屏蔽行，排除虚拟传感器等。实验给出基线结果，消融研究表明飞行阶段选择等影响结果。CruiseBench提供可重复子基准，CPM-N-CMAPSS为未来研究提供数据基础。
英文摘要
Remaining useful life (RUL) prediction estimates how long an engine can continue safe operation and is central to maintenance planning. N-CMAPSS extends C-MAPSS by simulating run-to-failure aero-engine trajectories using recorded real-flight profiles and retaining complete within-flight time series rather than cycle-level snapshots. However, this added realism reduces evaluation control because full-flight records increase data volume and entangle degradation cues with operating-regime variation, complicating preprocessing choices and direct comparisons of RUL modeling performance. To mitigate this issue, this paper proposes CruiseBench, a cruise-stage RUL benchmark derived from N-CMAPSS. It introduces CPM-N-CMAPSS (Cruising-Period Mask for N-CMAPSS), a mask artifact that stores cycle-local cruising intervals identified by the common-altitude method for the nine accessible subdatasets. CruiseBench applies a fixed protocol to the masked rows, using scenario descriptors and measured sensors as inputs while excluding virtual sensors, health parameters, and auxiliary metadata from the feature tensor, preserving native-resolution windows, and applying dataset-wise RUL caps. Experiments with LSTM, GRU, TCN, and TSMixer provide baseline results for this setting. Under CruiseBench-eta5-W256-S10, TSMixer obtains the lowest average RMSE, $3.4\pm1.71$, and Saxena score, $(2.50\pm2.99)\times 10^{4}$. Ablation studies show that flight-stage selection, temporal downscaling method, and RUL-cap threshold affect reported results. With its fixed cruise-stage protocol, CruiseBench provides a reproducible sub-benchmark for controlled RUL model comparison and CPM-N-CMAPSS provides a stage-specific data foundation for future transfer-learning and domain-adaptation studies.
