| Presentation | 2011-01-21 Fault Detection and Prediction of Industrial Plants Based on Gaussian Processes Shinsaku OZAKI, Toshikazu WADA, Shunji MAEDA, Hisae SHIBUYA, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This report proposes a fault and pre-fault detection method for industrial plants based on Gaussian process. Industrial plants can be monitored via attached sensors that measures temperature, pressure, voltage, electric current, and so on. Based on these sensor outputs, health monitoring of the target plant can be designed. The difficulty of this design problem is that the system fault can appear as statistical abnormality observed as irregular ensemble of the sensor outputs andlor temporal abnormality observed as irregularity of the time sequences. Furthermore, those systems are operated by human and it is difficult to distinguish the abnormalities caused by human-operation and system fault. We already proposed an abnormality detection system based on ICA and linear prediction, which avoids incorrect detections of abnormalities caused by human operations by recognizing and masking them. This method, however, cannot detect the system fault during the human operation. For solving this problem, we propose a unified method for statistical and temporal abnormality detection based on Gaussian Processes in this report. This method can detect system fault under normal human operation. We confirmed the effectiveness of our method through experiments on long-term sensory data sampled from real industrial plant. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Abnormality detection / Gaussian processes / Independent component analysis / Statistical and Temporal analysis |
| Paper # | PRMU2010-175,MVE2010-100 |
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| Conference Information | |
| Committee | MVE |
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| Conference Date | 2011/1/13(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Registration To | Media Experience and Virtual Environment (MVE) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Fault Detection and Prediction of Industrial Plants Based on Gaussian Processes |
| Sub Title (in English) | |
| Keyword(1) | Abnormality detection |
| Keyword(2) | Gaussian processes |
| Keyword(3) | Independent component analysis |
| Keyword(4) | Statistical and Temporal analysis |
| 1st Author's Name | Shinsaku OZAKI |
| 1st Author's Affiliation | Faculty of Systems Engineering, Wakayama University() |
| 2nd Author's Name | Toshikazu WADA |
| 2nd Author's Affiliation | Faculty of Systems Engineering, Wakayama University |
| 3rd Author's Name | Shunji MAEDA |
| 3rd Author's Affiliation | Production Engineering Research Laboratory, Hitachi, Ltd. |
| 4th Author's Name | Hisae SHIBUYA |
| 4th Author's Affiliation | Production Engineering Research Laboratory, Hitachi, Ltd. |
| Date | 2011-01-21 |
| Paper # | PRMU2010-175,MVE2010-100 |
| Volume (vol) | vol.110 |
| Number (no) | 382 |
| Page | pp.pp.- |
| #Pages | 6 |
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