Results 221 to 230 of about 12,390 (264)

A memory-based approach to fault detection and diagnosis

1999 European Control Conference (ECC), 1999
Fault detection and diagnosis are functions with enormous importance to advanced intelligent supervisory control systems. In the quest for improved quality and safer operations, we adopt a different approach to fault diagnosis based on the memory-based learning paradigm.
Petya I. Ivanova, Rudolf Kulhavý
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A Fault Detecting System of Intelligent Detection and Diagnosis

Advanced Materials Research, 2011
By testing the running gear system with fault, the vibration signals of gear system are acquired at different speeds. Using wavelet de-noising by threshold to extract the useful feature signals, combining time-frequency analysis with intelligence detection theory of wavelet analysis, the feature signals are decomposed into different frequency bands ...
Ren Ping Shao, Yong Long Li, Wen Tao Hu
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Fault detection and diagnosis for operational control systems

2015 21st International Conference on Automation and Computing (ICAC), 2015
Operational control for complex industrial processes consists of two layers, namely the loop control layer and the operational layer. The former realizes the required loop control for each production unit and the later determines the best set-points to the control loops in the loop control layer.
Ning Sheng, Hong Wang 0001
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Fault detection and diagnosis of networked control system

International Journal of Systems Science, 2008
Consider the plant of Multiple-input Networked Control System (NCS) with long reduced delay. The effect of the disturbances to the NCS is discussed and the iterative method is used to compensate the delay when design a reduced-order state observer with a γ-stability margin (0 < γ < 1) for system.
Yingwei Zhang, Yu Chen, Jie Sheng, Tim Hesketh   +3 more
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On-line fault detection and diagnosis for chiller system

2016 IEEE International Conference on Automation Science and Engineering (CASE), 2016
Fault detection and diagnosis for heating, ventilation and air conditioning system (HVAC) significantly impact energy efficiency and human thermal comfort. A model-based fault diagnosis method is presented in this paper to provide reliable estimation of multiple and simultaneous fault conditions at the component level, in the presence of measurement ...
P. Wang, Robert Gao
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Fault detection and diagnosis of automated manufacturing systems

Proceedings of the 27th IEEE Conference on Decision and Control, 1988
The authors develop a controller methodology for fault detection and diagnosis using Petri nets and fault trees in automated manufacturing systems. The controller has two levels. At the first level there are dedicated diagnostic systems for each of the subsystems, such as machine centers, robots, conveyers, etc.
N. Viswanadham, T.L. Johnson
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Fault Detection, Diagnosis and Identification

1998
In this work we distinguish between two kind of faults: slowly changing and abrupt changing faults. The first often originate from wearing and the latter from a abrupt errors within the process control system. In practice, a supervision system has to deal simultaneously with both types of faults, but here we make a distinction because different methods
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Detecting Novel Classes with Applications to Fault Diagnosis

1992
Existing empirical learning algorithms such as decision trees and neural networks usually measure the quality of the learned model in terms of classification error. However, as machine learning algorithms are adapted for practical applications, other aspects of classifier performance can become critically important.
Padhraic Smyth, Jeff Mellstrom
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Fault detection and diagnosis of a motor bearing shield

Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems, 2011
Recent years have seen increased attention to the Preventive Maintenance (PM) where corrective actions are promptly taken before small faults manifest themselves to be serious failures. Also, these undetected incipient faults present in an unhealthy machine can result in unnecessary waste of energy.
Jittiwut Suwatthikul, Sunisa Sornmuang
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Sensor fault detection and diagnosis in the presence of outliers

Neurocomputing, 2019
Abstract In this paper, a sensor fault detection and diagnosis (FDD) method is proposed for linear state-space models in the presence of outliers. The t-distribution with unknown scale matrix and degrees of freedom (dof) parameter is used to describe the measurement noise. By using the variational Bayesian inference, the states, the scale matrix, and
Chen Xu 0009, Shunyi Zhao, Fei Liu 0001
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