Liu, Zhihong ; Eichenlaub, Tobias ; Rinderknecht, Stephan (2023)
A survey of sequential adaptive sampling strategy for transmission power loss measurement.
In: Mechanical Systems and Signal Processing, 183
doi: 10.1016/j.ymssp.2022.109644
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Laboratory experiments for characterizing the power loss behavior in transmissions causes time and energy costs when performing the traditional factorial design strategy. This is because the space filling strategy may locate redundant samples with low information regarding the measurement targets. This article proposes a sequential adaptive sampling methodology for performing efficient and informative power loss measurements. The presented sampling methodology associates surrogate modeling based on a Gaussian Process approach with Subset Simulation. Gaussian Process Regression creates a statistical model with the estimation targets and the expression of uncertainty. Subset Simulation is applied to efficiently identify the regions where an objective function reaches a predefined critical threshold. The proposed adaptive sampling method is implemented for the real-time measurement of a 7-speed DCT on a drivetrain test bench. Compared to the traditional factorial design, the iterative adaption of the proposed method ensures an informative and effective measurement and an automatic termination with reduced time and energy cost.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Liu, Zhihong ; Eichenlaub, Tobias ; Rinderknecht, Stephan |
| Art des Eintrags: | Bibliographie |
| Titel: | A survey of sequential adaptive sampling strategy for transmission power loss measurement |
| Sprache: | Englisch |
| Publikationsjahr: | 15 Januar 2023 |
| Verlag: | Elsevier |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Mechanical Systems and Signal Processing |
| Jahrgang/Volume einer Zeitschrift: | 183 |
| DOI: | 10.1016/j.ymssp.2022.109644 |
| URL / URN: | https://www.sciencedirect.com/science/article/abs/pii/S08883... |
| Kurzbeschreibung (Abstract): | Laboratory experiments for characterizing the power loss behavior in transmissions causes time and energy costs when performing the traditional factorial design strategy. This is because the space filling strategy may locate redundant samples with low information regarding the measurement targets. This article proposes a sequential adaptive sampling methodology for performing efficient and informative power loss measurements. The presented sampling methodology associates surrogate modeling based on a Gaussian Process approach with Subset Simulation. Gaussian Process Regression creates a statistical model with the estimation targets and the expression of uncertainty. Subset Simulation is applied to efficiently identify the regions where an objective function reaches a predefined critical threshold. The proposed adaptive sampling method is implemented for the real-time measurement of a 7-speed DCT on a drivetrain test bench. Compared to the traditional factorial design, the iterative adaption of the proposed method ensures an informative and effective measurement and an automatic termination with reduced time and energy cost. |
| Freie Schlagworte: | Transmission power loss measurement, Sequential adaptive design, Gaussian Process Regression, Subset Simulation |
| Zusätzliche Informationen: | Art.No.: 109644 |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Mechatronische Systeme im Maschinenbau (IMS) |
| Hinterlegungsdatum: | 09 Aug 2022 09:12 |
| Letzte Änderung: | 24 Nov 2022 13:37 |
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