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Results for “health/performance monitoring”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Efficient Oculometric Assessment of Altered Neural Function

Eye movements have long been known to shed light on the locus and nature of serious brain injuries and pathologies. Recent scientific findings linking eye movements and higher-order psychometric performance and recent technical advances in eye-tracking precision have enabled the harnessing of an assortment of oculometrics as sensitive and reliable biomarkers of mild neural impairment across a wide range of stressors and brain regions. Oculometrics is, therefore, a promising new tool for the assessment of spaceflight effects on sensorimotor performance and on the effectiveness of candidate countermeasures, even with small sample populations

eye movements↗

DOE OSTI2020

Distribution Transformer Health Monitoring using Smart Meter Data

The distribution electric grid has become a highly complex and intelligent network with changing load and customer types. This has generated unprecedented challenges and opportunities for utility companies–opportunities especially in the area of asset health/performance management. Moreover, several utilities are increasingly moving from the traditional reactive and time-based asset monitoring approach to a more proactive condition based method. However, this needs to be done in a low-cost and efficient manner. Here, this paper explores how existing sensor infrastructure such as smart meters can be utilized to provide utility operators with more visibility into the health and operation of their assets. The paper focuses primarily on service transformers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Capturing Historic Reliability Performance Through Graph Databases: A Model Based System Engineering Approach

With the goal of improving the performance and reliability of high dependable technological systems such as nuclear power plants, advanced monitoring and health management systems are employed to inform system engineers on observed degradation processes and anomalous behaviors of assets and components. This information is captured in the form of large amount of data which can be heterogenous in nature (e.g., numeric, textual). Such large data availability poses challenges when system engineers are required to parse and analyze them in order to track historic reliability performance of assets and components. This paper tackles directly this challenge by providing means to organize data in the form of a graph: a knowledge graph. The presented approach distinguish itself from current knowledge graph-based methods by the fact that model-based system engineering (MBSE) models are used to “put data into context”. In particular, MBSE models are used as skeleton of a knowledge graph; numeric and textual data elements, once processed, are associated to MBSE model elements. Thus, a knowledge graph captures both system architecture (though MBSE models) and health/performance data. Such feature opens the door to new data analytics methods designed to identify causal relations between observed phenomena.

97 - MATHEMATICS AND COMPUTING↗