The Experts below are selected from a list of 279 Experts worldwide ranked by ideXlab platform
Kenta Tsukamoto - One of the best experts on this subject based on the ideXlab platform.
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Residual Life Prediction of Rotating Equipment in Thermal Power Plants Using On-line Estimation with Forgetting Factor
Ieej Transactions on Power and Energy, 2020Co-Authors: Satoru Goto, Kenta TsukamotoAbstract:In this paper, an on-line deterioration prediction and residual life prediction method is proposed for maintenance of Rotating Equipment in thermal power plants. Condition of Rotating Equipment is inspected by vibration measurement. A mathematical model for the deterioration of the Rotating Equipment is derived in order to predict future condition of the Rotating Equipment. Residual life of the Rotating Equipment is predicted by deterioration prediction using on-line estimation of model parameters with forgetting factor. The effectiveness of the residual life prediction method is assured by applying it to actual vibration data of Rotating Equipment.
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Residual Life Prediction of Rotating Equipment in Thermal Power Plants Using Online Estimation with Forgetting Factor
Electrical Engineering in Japan, 2014Co-Authors: Satoru Goto, Kenta TsukamotoAbstract:SUMMARY In this paper, an online deterioration prediction and residual life prediction method is proposed for maintenance of Rotating Equipment in thermal power plants. The condition of Rotating Equipment is inspected by vibration measurement. A mathematical model for the deterioration of the Rotating Equipment is derived in order to predict the future condition of the Rotating Equipment. The residual life of the Rotating Equipment is predicted by deterioration prediction using online estimation of the model parameters with a forgetting factor. The effectiveness of the residual life prediction method is assured by applying it to actual vibration data of Rotating Equipment.
Satoru Goto - One of the best experts on this subject based on the ideXlab platform.
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Residual Life Prediction of Rotating Equipment in Thermal Power Plants Using On-line Estimation with Forgetting Factor
Ieej Transactions on Power and Energy, 2020Co-Authors: Satoru Goto, Kenta TsukamotoAbstract:In this paper, an on-line deterioration prediction and residual life prediction method is proposed for maintenance of Rotating Equipment in thermal power plants. Condition of Rotating Equipment is inspected by vibration measurement. A mathematical model for the deterioration of the Rotating Equipment is derived in order to predict future condition of the Rotating Equipment. Residual life of the Rotating Equipment is predicted by deterioration prediction using on-line estimation of model parameters with forgetting factor. The effectiveness of the residual life prediction method is assured by applying it to actual vibration data of Rotating Equipment.
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Residual Life Prediction of Rotating Equipment in Thermal Power Plants Using Online Estimation with Forgetting Factor
Electrical Engineering in Japan, 2014Co-Authors: Satoru Goto, Kenta TsukamotoAbstract:SUMMARY In this paper, an online deterioration prediction and residual life prediction method is proposed for maintenance of Rotating Equipment in thermal power plants. The condition of Rotating Equipment is inspected by vibration measurement. A mathematical model for the deterioration of the Rotating Equipment is derived in order to predict the future condition of the Rotating Equipment. The residual life of the Rotating Equipment is predicted by deterioration prediction using online estimation of the model parameters with a forgetting factor. The effectiveness of the residual life prediction method is assured by applying it to actual vibration data of Rotating Equipment.
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On-line deterioration prediction residual life evaluation of Rotating Equipment based on vibration measurement
2008 SICE Annual Conference, 2008Co-Authors: Satoru Goto, Yuhki Adachi, Sinji Katafuchi, Toshihiko Furue, Yoshitaka Uchida, Mitsuhoro Sueyoshi, Hironori Hatazaki, Masatoshi NakamuraAbstract:In this paper, an on-line deterioration prediction method and residual life evaluation are proposed for maintenance of Rotating Equipment. Status of the Rotating Equipment is inspected by vibration measurement and a mathematical model for the deterioration of the Equipment is derived in order to predict future condition of the Rotating Equipment. For the construction of the deterioration model, outliers in the vibration data caused by measurement errors and so on are eliminated in order to improve accuracy of the deterioration model. Residual life of the Rotating Equipment is evaluated from the deterioration prediction by using the deterioration model. The effectiveness of the proposed deterioration prediction method and residual life evaluation are assured by actual data of Rotating Equipment in thermal power plants.
Hashem M. Hashemian - One of the best experts on this subject based on the ideXlab platform.
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wireless sensors for predictive maintenance of Rotating Equipment in research reactors
Annals of Nuclear Energy, 2011Co-Authors: Hashem M. HashemianAbstract:Abstract In 2008–2009, the High Flux Isotope Reactor (HFIR) at the Oak Ridge National Laboratory (ORNL) tested the potential of predictive or condition-based maintenance techniques to reduce maintenance costs, minimize the risk of catastrophic failures, and maximize system availability by attaching wireless-based sensors to selected Rotating Equipment at HFIR. Rotating Equipment is an ideal “test case” for the viability of integrated, online predictive maintenance strategies because motors, bearings, and shafts are ubiquitous in nuclear power plants and because the maintenance methods typically performed on Rotating Equipment today (such as portable or handheld vibration data collection Equipment) are highly labor-intensive. The HFIR project achieved all five of its objectives: (1) to identify Rotating machinery of the types used in research reactors and determine their operational characteristics, degradation mechanisms, and failure modes, (2) to establish a predictive maintenance program for Rotating Equipment in research reactors, (3) to identify wireless sensors that are suitable for predictive maintenance of Rotating machinery and test them in a laboratory setting, (4) to establish the requirements and procedures to be followed when implementing wireless sensors for predictive maintenance in research reactors, and (5) to develop a conceptual design for a predictive maintenance system for research reactors based on wireless sensors. The project demonstrated that wireless sensors offer an effective method for monitoring key process conditions continuously and remotely, thereby enhancing the safety, reliability, and efficiency of the aging research reactor fleet.
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Wireless sensors for predictive maintenance of Rotating Equipment in research reactors
Annals of Nuclear Energy, 2011Co-Authors: Hashem M. HashemianAbstract:In 2008-2009, the High Flux Isotope Reactor (HFIR) at the Oak Ridge National Laboratory (ORNL) tested the potential of predictive or condition-based maintenance techniques to reduce maintenance costs, minimize the risk of catastrophic failures, and maximize system availability by attaching wireless-based sensors to selected Rotating Equipment at HFIR. Rotating Equipment is an ideal "test case" for the viability of integrated, online predictive maintenance strategies because motors, bearings, and shafts are ubiquitous in nuclear power plants and because the maintenance methods typically performed on Rotating Equipment today (such as portable or handheld vibration data collection Equipment) are highly labor-intensive. The HFIR project achieved all five of its objectives: (1) to identify Rotating machinery of the types used in research reactors and determine their operational characteristics, degradation mechanisms, and failure modes, (2) to establish a predictive maintenance program for Rotating Equipment in research reactors, (3) to identify wireless sensors that are suitable for predictive maintenance of Rotating machinery and test them in a laboratory setting, (4) to establish the requirements and procedures to be followed when implementing wireless sensors for predictive maintenance in research reactors, and (5) to develop a conceptual design for a predictive maintenance system for research reactors based on wireless sensors. The project demonstrated that wireless sensors offer an effective method for monitoring key process conditions continuously and remotely, thereby enhancing the safety, reliability, and efficiency of the aging research reactor fleet. © 2010 Elsevier Ltd. All rights reserved.
Jeff Hunt - One of the best experts on this subject based on the ideXlab platform.
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CCA - Rotating Equipment automation for directional drilling: Brain over brawn
2011 IEEE International Conference on Control Applications (CCA), 2011Co-Authors: Jeff HuntAbstract:This paper describes the development of Slider automated directional drilling technology and addresses the benefits, automation strategy, the challenges encountered, and the solutions developed over the last 8 years. The paper will examine the following topics: • Challenges a directional driller faces controlling a drilling rig while directionally drilling a well • How automation and control can simplify the execution of repetitive actions and enable the directional drillers to perform their job at a higher level • Benefits of automated drilling • Using automation to protect Rotating Equipment from damage that may be caused by manual operation, thereby decreasing Equipment downtime • Developing automation system architecture that will enable the adaptation of various types of pipe Rotating Equipment • Field examples and a description of the widely accepted Slider technology in today's directional drilling world
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Rotating Equipment automation for directional drilling: Brain over brawn
2011 IEEE International Conference on Control Applications (CCA), 2011Co-Authors: Jeff HuntAbstract:This paper describes the development of Slider automated directional drilling technology and addresses the benefits, automation strategy, the challenges encountered, and the solutions developed over the last 8 years. The paper will examine the following topics: · Challenges a directional driller faces controlling a drilling rig while directionally drilling a well · How automation and control can simplify the execution of repetitive actions and enable the directional drillers to perform their job at a higher level · Benefits of automated drilling · Using automation to protect Rotating Equipment from damage that may be caused by manual operation, thereby decreasing Equipment downtime · Developing automation system architecture that will enable the adaptation of various types of pipe Rotating Equipment · Field examples and a description of the widely accepted Slider technology in today's directional drilling world.
Masatoshi Nakamura - One of the best experts on this subject based on the ideXlab platform.
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On-line deterioration prediction residual life evaluation of Rotating Equipment based on vibration measurement
2008 SICE Annual Conference, 2008Co-Authors: Satoru Goto, Yuhki Adachi, Sinji Katafuchi, Toshihiko Furue, Yoshitaka Uchida, Mitsuhoro Sueyoshi, Hironori Hatazaki, Masatoshi NakamuraAbstract:In this paper, an on-line deterioration prediction method and residual life evaluation are proposed for maintenance of Rotating Equipment. Status of the Rotating Equipment is inspected by vibration measurement and a mathematical model for the deterioration of the Equipment is derived in order to predict future condition of the Rotating Equipment. For the construction of the deterioration model, outliers in the vibration data caused by measurement errors and so on are eliminated in order to improve accuracy of the deterioration model. Residual life of the Rotating Equipment is evaluated from the deterioration prediction by using the deterioration model. The effectiveness of the proposed deterioration prediction method and residual life evaluation are assured by actual data of Rotating Equipment in thermal power plants.
