Picid: A Modular Evaluation Infrastructure for Reproducible PHM Across Tasks and Domains 文章

ArXiv CS.AI2026-05-28NEWSen作者: Lev Telyatnikov, Raffael Theiler, Leandro Von Krannichfeldt, Olga Fink

摘要

arXiv:2605.28345v1 Announce Type: new Abstract: Progress in Prognostics and Health Management (PHM) is hindered by the lack of standardized and reusable evaluation practices across tasks, datasets, and application domains. Reported results are often difficult to reproduce and compare, as key protocol choices, such as data splits, preprocessing, label alignment, temporal windowing, and metrics, are often implicit or implemented ad hoc. We introduce \picid, a modular evaluation infrastructure that formalizes the PHM evaluation pipeline as an explicit, executable, and reproducible protocol. Through well-defined abstractions, \picid enforces deterministic, leakage-safe dataset construction while remaining flexible across diverse PHM settings. The framework supports fault detection, diagnostics, and prognostics through a unified interface and can be extended to new datasets and model classes without violating protocol invariants.

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