IEICE TRANSACTIONS on Fundamentals
Fault Detection and Diagnosis of Manipulator Based on Probabilistic Production Rule
Summary :
This paper presents a new strategy to detect and diagnose fault of a manipulator based on the expression with a Probabilistic Production Rule (PPR). Production Rule (PR) is widely used in the field of computer science as a tool of formal verification. In this work, first of all, PR is used to represent the mapping between highly quantized input and output signals of the dynamical system. By using PR expression, the fault detection and diagnosis algorithm can be implemented with less computational effort. In addition, we introduce a new system description with Probabilistic PR (PPR) wherein the occurrence probability of PRs is assigned to them to improve the robustness with small computational burden. The probability is derived from the statistic characteristics of the observed input and output signals. Then, the fault detection and diagnosis algorithm is developed based on calculating the log-likelihood of the measured data for the designed PPR. Finally, some experiments on a controlled manipulator are demonstrated to confirm the usefulness of the proposed method.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E90-A No.11 pp.2488-2495
- Publication Date
- 2007/11/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e90-a.11.2488
- Type of Manuscript
- Special Section PAPER (Special Section on Concurrent/Hybrid Systems: Theory and Applications)
- Category
Authors
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Shinkichi INAGAKI, Koudai HAYASHI, Tatsuya SUZUKI, "Fault Detection and Diagnosis of Manipulator Based on Probabilistic Production Rule" in IEICE TRANSACTIONS on Fundamentals,
vol. E90-A, no. 11, pp. 2488-2495, November 2007, doi: 10.1093/ietfec/e90-a.11.2488.
Abstract: This paper presents a new strategy to detect and diagnose fault of a manipulator based on the expression with a Probabilistic Production Rule (PPR). Production Rule (PR) is widely used in the field of computer science as a tool of formal verification. In this work, first of all, PR is used to represent the mapping between highly quantized input and output signals of the dynamical system. By using PR expression, the fault detection and diagnosis algorithm can be implemented with less computational effort. In addition, we introduce a new system description with Probabilistic PR (PPR) wherein the occurrence probability of PRs is assigned to them to improve the robustness with small computational burden. The probability is derived from the statistic characteristics of the observed input and output signals. Then, the fault detection and diagnosis algorithm is developed based on calculating the log-likelihood of the measured data for the designed PPR. Finally, some experiments on a controlled manipulator are demonstrated to confirm the usefulness of the proposed method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e90-a.11.2488/_p
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@ARTICLE{e90-a_11_2488,
author={Shinkichi INAGAKI, Koudai HAYASHI, Tatsuya SUZUKI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Fault Detection and Diagnosis of Manipulator Based on Probabilistic Production Rule},
year={2007},
volume={E90-A},
number={11},
pages={2488-2495},
abstract={This paper presents a new strategy to detect and diagnose fault of a manipulator based on the expression with a Probabilistic Production Rule (PPR). Production Rule (PR) is widely used in the field of computer science as a tool of formal verification. In this work, first of all, PR is used to represent the mapping between highly quantized input and output signals of the dynamical system. By using PR expression, the fault detection and diagnosis algorithm can be implemented with less computational effort. In addition, we introduce a new system description with Probabilistic PR (PPR) wherein the occurrence probability of PRs is assigned to them to improve the robustness with small computational burden. The probability is derived from the statistic characteristics of the observed input and output signals. Then, the fault detection and diagnosis algorithm is developed based on calculating the log-likelihood of the measured data for the designed PPR. Finally, some experiments on a controlled manipulator are demonstrated to confirm the usefulness of the proposed method.},
keywords={},
doi={10.1093/ietfec/e90-a.11.2488},
ISSN={1745-1337},
month={November},}
Copy
TY - JOUR
TI - Fault Detection and Diagnosis of Manipulator Based on Probabilistic Production Rule
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2488
EP - 2495
AU - Shinkichi INAGAKI
AU - Koudai HAYASHI
AU - Tatsuya SUZUKI
PY - 2007
DO - 10.1093/ietfec/e90-a.11.2488
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E90-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2007
AB - This paper presents a new strategy to detect and diagnose fault of a manipulator based on the expression with a Probabilistic Production Rule (PPR). Production Rule (PR) is widely used in the field of computer science as a tool of formal verification. In this work, first of all, PR is used to represent the mapping between highly quantized input and output signals of the dynamical system. By using PR expression, the fault detection and diagnosis algorithm can be implemented with less computational effort. In addition, we introduce a new system description with Probabilistic PR (PPR) wherein the occurrence probability of PRs is assigned to them to improve the robustness with small computational burden. The probability is derived from the statistic characteristics of the observed input and output signals. Then, the fault detection and diagnosis algorithm is developed based on calculating the log-likelihood of the measured data for the designed PPR. Finally, some experiments on a controlled manipulator are demonstrated to confirm the usefulness of the proposed method.
ER -
English
