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Fault detection is essential to ensure the proper operation of solar-thermal plants. Hence, monitoring personnel frequently analyze the data to detect unusual behavior. While visualization approaches may considerably support the monitoring of personnel during their work, no existing application can yet deal with the multivariate and time-dependent sensor data, or does not fully support the users' workflow. Thus, this work introduces the visual framework SunScreen. It allows users to explore the sensor data, automatically detected anomalies, and system events (e.g., already detected faults and services). The feedback from the users shows that they appreciate the tool and especially its annotation functionality. However, the system-usability-scale (SUS) results indicate that it does not meet all requirements yet.
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Feierl et al. (2023) studied this question.
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