Expert condition monitoring on hydrostatic self-levitating bearings

García, Ramón Ferreiro; Calvo-Rolle, José Luís; Gómez, Manuel Romero; Catoira, Alberto DeMiguel

doi:10.1016/j.eswa.2012.12.013

Cited by 28 publications

(11 citation statements)

References 18 publications

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“…These proposals are based on Soft Computing techniques, both simple or hybrid. As it is shown in [4,[7][8][9][10][11][12][13][14][15][16][17][18][19][20] these techniques improve the first ones mentioned above.…”

Section: Introductionmentioning

confidence: 93%

Modeling the Electromyogram (EMG) of Patients Undergoing Anesthesia During Surgery

Casteleiro‐Roca

Pérez

Piñón-Pazos

et al. 2015

Advances in Intelligent Systems and Computing

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All fields of science have advanced and still advance significantly. One of the facts that contributes positively is the synergy between areas. In this case, the present research shows the Electromyogram (EMG) modeling of patients undergoing to anesthesia during surgery. With the aim of predicting the patient EMG signal, a model that allows to know its performance from the Bispectral Index (BIS) and the Propofol infusion rate has been developed. The proposal has been achieved by using clustering combined with regression techniques and using a real dataset obtained from patients undergoing to anesthesia during surgeries. Finally, the created model has been tested with very satisfactory results.

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Section: Introductionmentioning

confidence: 93%

Modeling the Electromyogram (EMG) of Patients Undergoing Anesthesia During Surgery

Casteleiro‐Roca

Pérez

Piñón-Pazos

et al. 2015

Advances in Intelligent Systems and Computing

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“…The two methods (MGGP and EN-MGGP) are applied on the data set (as discussed in Section 2) in the prediction of number of days (no.) for estimating the scheduled maintenance of the lathe when subjected to three operations (Idle, turning and facing) for the three experimental (6) in the Appendix. Performance and comparison of models are discussed in Section 5.…”

Section: Graphical User Interface For Implementing the Proposed Evolumentioning

confidence: 99%

“…Vibration monitoring and acoustic emissions are the two most effective and commonly used methods for condition monitoring of machines [6][7][8]. Vibration condition monitoring has been a trusted method for the past thirty years.…”

Section: Introductionmentioning

confidence: 99%

“…The reason behind employing the machine condition monitoring is to generate accurate and quantitative information on the present condition of a machine (for example, lathe) in order to optimally schedule maintenance, achieve maximum productivity, and still avoid unexpected catastrophic failures. It also results in improved risk maintenance and increased machine reliability [2,[4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Model development based on evolutionary framework for condition monitoring of a lathe machine

et al. 2015

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“…Hung et al (2013) successfully applied condition monitoring technique to monitor greenhouse environment whereas Zimroz and Bartkowiak (2013) applied multivariate methods based condition monitoring technique to successfully monitor planetary gearboxes in non-stationary operating conditions. Other successful applications of condition monitoring include in wind and marine turbines , in (Dybała and Radkowski, 2013), and in hydrostatic self-levitating bearings (Garcia et al, 2013).…”

Section: Condition Monitoringmentioning

confidence: 99%

Flexibly-bounded Rationality

2015

Causality, Correlation and Artificial Intelligence for Rational Decision Making

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This chapter describes the theory of flexibly-bounded rationality which extends the theory of bounded rationality. Specifically, it is viewed that a decision making process which encompasses three components, information collection and analysis, the correlation, and the causal machines. Rational decision making entails utilizing information which is imperfect and incomplete jointly with human brain which is erratic on making decisions. The theory of bounded rationality prescribes making this decision despite the fact that the information is incomplete and imperfect and that the human brain is inconsistent and the decision is made within the bounds of these limitations. The theory of flexibly-bounded rationality entails using signal processing to filter noise and outliers in the data and using the correlation machine to complete missing information and artificial intelligence to make more reliable decisions. Flexibly-bounded rationality is applied to condition monitoring and HIV diagnosis problems and it is found to enlarge the bounds within which rational decision making process is employed and, thus, rises the probability of making accurate decisions than the theory of bounded rationality. 147 Causality, Correlation and Artificial Intelligence for Rational Decision Making Downloaded from www.worldscientific.com by UNIVERSITY OF BIRMINGHAM LIBRARY -INFORMATION SERVICES on 03/21/15. For personal use only. Causality, Correlation and Artificial Intelligence for Rational Decision Making Downloaded from www.worldscientific.com by UNIVERSITY OF BIRMINGHAM LIBRARY -INFORMATION SERVICES on 03/21/15. For personal use only.

show abstract

Expert condition monitoring on hydrostatic self-levitating bearings

Cited by 28 publications

References 18 publications

Modeling the Electromyogram (EMG) of Patients Undergoing Anesthesia During Surgery

Modeling the Electromyogram (EMG) of Patients Undergoing Anesthesia During Surgery

Model development based on evolutionary framework for condition monitoring of a lathe machine

Flexibly-bounded Rationality

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