발간년도 : [2018]
| 논문정보 |
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| 논문명(한글) |
[Vol.13, No.4] Interactive Data Visualization Based Realtime Monitoring and Fault Detection System |
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| 논문투고자 |
Seung-Taek Ryoo |
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| 논문내용 |
Effective representation of various types of data from various types of equipment is not a trivial task. The more data items collected for sophisticated data analysis, the more trouble the system operator has to identify important items. In order to solve these problems, it is necessary to develop a real-time interactive data visualization system that can be efficiently observing large-volume data at a glance and confirming fault detection in advance. In this paper, we propose a real - time observation and fault detection system using interactive data visualization method to efficiently manage consecutively generated raw data. The proposed system consists of data collection, data visualization, data fault detection and alarm steps. In the data collection step, the real-time generated device data using the data collection device is stored, and the collected data is massaged and generalized through data preprocessing process. The normalized data is subjected to data analysis, visualization mapping, and rendering in the data visualization step. To visualize and render the defined data primitives, we use heat map, radar chart, and stream graph. In addition, statistical process control (SPC) rule-based fault detection and alarm methods are used to detect data errors. The proposed method can be widely used in various fields such as image generation, data fusion, fault detection and machine learning. |
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