| Presentation | 2018-09-21 Anomaly Detection for Various Operations of Machine Kazuki Kobayashi, Masatoshi Sekine, Satoshi Ikada, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this paper, we propose an anomaly level estimation method for various operation of machine. Our proposed method has two main functions: 1) making feature extraction models automatically in both time and frequency domains, 2) estimating anomaly level in each time and frequency. The outline of our proposed method is as follows. First, the spectrogram of sensor data such as vibration data and sound data are calculated. Second, the features of them are extracted from the summarized information using deep learning. By inputting the spectrogram divided for each time or each frequency, we can obtain the vibration features for each time or each frequency. Finally, the probability density model for anomaly level estimation is built. It explains the relations between time and vibration features or, frequency and vibration feature. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Anomaly Detection / Anomaly Level Estimation / Vibration Analysis / Feature Extraction / Machine Learning / Neural Network / Deep Learning |
| Paper # | PRMU2018-56,IBISML2018-33 |
| Date of Issue | 2018-09-13 (PRMU, IBISML) |
| Conference Information | |
| Committee | PRMU / IBISML / IPSJ-CVIM |
|---|---|
| Conference Date | 2018/9/20(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Shinichi Sato(NII) / Hisashi Kashima(Kyoto Univ.) |
| Vice Chair | Yoshihisa Ijiri(Omron) / Toru Tamaki(Hiroshima Univ.) / Masashi Sugiyama(Univ. of Tokyo) / Koji Tsuda(Univ. of Tokyo) |
| Secretary | Yoshihisa Ijiri(NEC) / Toru Tamaki(Osaka Univ.) / Masashi Sugiyama(Nagoya Inst. of Tech.) / Koji Tsuda(AIST) |
| Assistant | Go Irie(NTT) / Yoshitaka Ushiku(Univ. of Tokyo) / Tomoharu Iwata(NTT) / Shigeyuki Oba(Kyoto Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Infomation-Based Induction Sciences and Machine Learning / Special Interest Group on Computer Vision and Image Media |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Anomaly Detection for Various Operations of Machine |
| Sub Title (in English) | |
| Keyword(1) | Anomaly Detection |
| Keyword(2) | Anomaly Level Estimation |
| Keyword(3) | Vibration Analysis |
| Keyword(4) | Feature Extraction |
| Keyword(5) | Machine Learning |
| Keyword(6) | Neural Network |
| Keyword(7) | Deep Learning |
| 1st Author's Name | Kazuki Kobayashi |
| 1st Author's Affiliation | Oki Electric Industry Co., Ltd.(OKI) |
| 2nd Author's Name | Masatoshi Sekine |
| 2nd Author's Affiliation | Oki Electric Industry Co., Ltd.(OKI) |
| 3rd Author's Name | Satoshi Ikada |
| 3rd Author's Affiliation | Oki Electric Industry Co., Ltd.(OKI) |
| Date | 2018-09-21 |
| Paper # | PRMU2018-56,IBISML2018-33 |
| Volume (vol) | vol.118 |
| Number (no) | PRMU-219,IBISML-220 |
| Page | pp.pp.133-138(PRMU), pp.133-138(IBISML), |
| #Pages | 6 |
| Date of Issue | 2018-09-13 (PRMU, IBISML) |