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Analytic signal space partitioning and symbolic dynamic filtering for degradation monitoring of electric motors
2009
Signal, Image and Video Processing
This study presents an application of the recently reported theories of analytic signal space partitioning (ASSP) and symbolic dynamic filtering (SDF) to address degradation monitoring in permanent magnet ...
smoothly and monotonically with degradation in magnetization of the PMSM. ...
Analytic signal space partitioning Analytic signal space partitioning (ASSP) of time-series data is used for symbol sequence generation that is an essential ingredient of SDF. ...
doi:10.1007/s11760-009-0133-4
fatcat:dvi6ykzqcbehbmn64lmowzmbzq
Anomaly Detection in Nuclear Power Plants via Symbolic Dynamic Filtering
2011
IEEE Transactions on Nuclear Science
Along this line, symbolic dynamic filtering (SDF) has been reported in literature as a real-time data-driven tool of feature extraction for pattern identification from sensor time series. ...
This paper proposes an anomaly detection algorithm for condition monitoring of nuclear power plants, where symbolic feature extraction and the associated pattern classification are optimized by appropriate ...
Michael Doster for his technical support in implementing the simulation experiments using the IRIS simulator. ...
doi:10.1109/tns.2010.2088138
fatcat:do5ob7ydpbgj5f5vgq3cco2ho4
Symbolic identification of dynamical systems: Theory and experimental validation
2010
Proceedings of the 2010 American Control Conference
The underlying concept involves abstraction of a qualitative description of the dynamical system by state-space embedding of the output datastream and discretization of the resultant pseudo-state and input ...
This system identification technique has been experimentally validated for detection of anomalous behavior on a laboratory apparatus of a permanent magnet synchronous motor (PMSM) undergoing gradual demagnetization ...
Recent research has extensively explored the problem of anomaly detection using symbolic dynamic filtering (SDF) [1] - [3] . ...
doi:10.1109/acc.2010.5530662
fatcat:wg4qm6rbc5eibcqoiwexie4ctq
Detection and estimation of demagnetization faults in permanent magnet synchronous motors
2013
Electric power systems research
This paper presents a symbolic dynamic method for health monitoring of permanent magnet synchronous motors (PMSMs), which involves abstraction of a qualitative description from a dynamical system representation ...
The underlying algorithms rely on state-space embedding of the PMSM's output line current and discretization of the resultant pseudo-state and input spaces. ...
Average (computed over all experiments) signal strength at (a) the fault frequency (16.67 Hz) and (b) the odd harmonics (16.67 Hz, 50 Hz and 83.35 Hz) of the lowest fault frequency as a function of degradation ...
doi:10.1016/j.epsr.2012.11.005
fatcat:zkg23qbdjretjfr5y7oev4avi4
Intelligent Sensing in Inverter-fed Induction Motors: Wavelet-based Symbolic Dynamic Analysis
2008
Sensors & Transducers
Wavelet transform allows adaptive usage of windows to extract pertinent information from sensor signals, and symbolic dynamic analysis provides coarse graining of the underlying information for enhanced ...
Feasibility of the proposed intelligent sensing method is demonstrated on an experimental apparatus for early detection of rotor bar breakage in an inverter-fed induction motor. ...
NNC07QA08P and Cooperative Agreement No. NNX07AK49A. The authors gratefully acknowledge the assistance of Dr. E.E. Keller for design and construction of the test apparatus. ...
doaj:282a418d6d224bdfad0003f889f86e64
fatcat:t6b4qc6ruzdgfa7kxvvadzbhci
Diagnosis of Hybrid Systems Using Hybrid Particle Petri Nets: Theory and Application on a Planetary Rover
[chapter]
2018
Fault Diagnosis of Hybrid Dynamic and Complex Systems
Diagnosers are generated from these hybrid automata using a new data structure in order to monitor both the behavior and degradation of such systems. ...
After a review of the state of the art on different existing solutions for diagnosis of hybrid systems under uncertainty, we propose to introduce the Hybrid Particle Petri Nets (HPPN) modeling framework ...
Indeed, discrete, continuous and degradation state spaces, as well as continuous and degradation dynamics are the same as those of the model. ...
doi:10.1007/978-3-319-74014-0_9
fatcat:hspunr7c3ffc7efwon2yut5tju
Spatiotemporal information fusion for fault detection in shipboard auxiliary systems
2013
2013 American Control Conference
This paper addresses the issues of data analysis and sensor fusion that are critical for information management leading to (real-time) fault detection and classification in distributed physical processes ...
The underlying algorithms are developed to achieve high reliability and computational efficiency while retaining the essential spatiotemporal characteristics of the physical system. ...
This pattern space explosion may prohibit use of a complete STPN approach for monitoring of large systems under computational and memory constraints. ...
doi:10.1109/acc.2013.6580426
fatcat:x66v6int45ftzfzbxxuaumsbka
Sensor Fusion for Fault Detection and Classification in Distributed Physical Processes
2014
Frontiers in Robotics and AI
The underlying concept is built upon a semantic framework for multi-sensor data interpretation using graphical models of Probabilistic Finite State Automata (PFSA). ...
This paper proposes a feature extraction and fusion methodology to perform fault detection and classification in distributed physical processes generating heterogeneous data. ...
Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the sponsoring agencies. ...
doi:10.3389/frobt.2014.00016
fatcat:7d7da4abpjca5p72ucoeacpu74
Thermal Monitoring of Electric Motors: State-of-the-Art Review and Future Challenges
2021
IEEE Open Journal of Industry Applications
In order to optimize the dynamic performance limits of a motor during online operation, important motor temperatures must be known in real time. ...
This paper organizes the literary landscape and gives a bird's-eye overview of the three most important estimation classes: Indirect methods, which track temperature-sensitive electrical motor parameters ...
Sensor-Based Temperature Monitoring Temperature sensors are an obvious solution for monitoring the thermal condition of a motor. ...
doi:10.1109/ojia.2021.3091870
fatcat:gyp462sx4bgu3lb554eowwuhyq
From Model, Signal to Knowledge: A Data-Driven Perspective of Fault Detection and Diagnosis
2013
IEEE Transactions on Industrial Informatics
His main research interests include robust adaptive signal processing, state estimation and its applications to condition monitoring of aero engines and wind generators, wireless communication, wireless ...
Zhiwei Gao (SM'08) received the B.Eng. degree in Electric Engineering and Automation, and the M.Eng. and ...
One of the most successful applications of signal-based FDD is the motor current signature analysis (MCSA) for electric motors and generators. ...
doi:10.1109/tii.2013.2243743
fatcat:kph6f6kysnabtpyvgtm5w563ra
2019 Index IEEE Transactions on Industrial Informatics Vol. 15
2019
IEEE Transactions on Industrial Informatics
., +, TII May 2019 2763-
2774
Switching State-Space Degradation Model With Recursive Filter/Smoother
for Prognostics of Remaining Useful Life. ...
., +, TII May 2019
2849-2858
+ Check author entry for coauthors
Switching State-Space Degradation Model With Recursive Filter/Smoother
for Prognostics of Remaining Useful Life. ...
doi:10.1109/tii.2020.2968165
fatcat:utk3ywxc6zgbdbfsys5f4otv7u
Autonomous perception and decision-making in cyber-physical systems
2013
2013 8th International Conference on Computer Science & Education
Perception involves the recently developed framework of Symbolic Dynamic Filtering for abstraction of physical world in the cyber space. ...
For example, under this framework, sensor observations from a physical entity are discretized temporally and spatially to generate blocks of symbols, also called words that form a language. ...
Therefore, the generalized analytic signal in Eq. (2.33) is not an analytic signal in the sense of Gabor [65] for α < 1. ...
doi:10.1109/iccse.2013.6554173
fatcat:243gtheg6vd6jaz7pauyr447aa
A review on prognostic techniques for non-stationary and non-linear rotating systems
2015
Mechanical systems and signal processing
Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. ...
Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under nonstationary and non-linear conditions are also ...
Techniques (examples) Ranking Particle Filtering 85% ANN 99% . . . . . . Electric motor, e.g. ...
doi:10.1016/j.ymssp.2015.02.016
fatcat:rlg2fd26yzhh5ivusfb5vppopi
Toward virtual biopsy through an all fiber optic ultrasonic miniaturized transducer: a proposal
2003
IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control
Created by The Institute of Electrical and Electronics Engineers (IEEE) for the benefit of humanity. ............Channel bank filters ............Digital filters ............Equalizers ............Filtering ...
Created by The Institute of Electrical and Electronics Engineers (IEEE) for the benefit of humanity. ...
doi:10.1109/tuffc.2003.1244749
fatcat:l3jre4etsvcqzfyz2jqggji3gy
SVD-based complexity reduction to TS fuzzy models
2002
IEEE transactions on industrial electronics (1982. Print)
One of the typical important criteria to be considered in real-time control applications is the computational complexity of the controllers, observers, and models applied. ...
Reducing the number of models leads directly to the computational complexity reduction. This work also includes a number of numerical and application examples. ...
The signals representing the inconsistencies between the model and the actual system being monitored are called residuals. ...
doi:10.1109/41.993277
fatcat:xbptidhgwjafblo2pci3yoewyq
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