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Analytic signal space partitioning and symbolic dynamic filtering for degradation monitoring of electric motors

Subhadeep Chakraborty, Asok Ray, Aparna Subbu, Eric Keller
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

Xin Jin, Yin Guo, Soumik Sarkar, Asok Ray, Robert M. Edwards
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

S Chakraborty, E Keller, A Ray, J Mayer
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

Subhadeep Chakraborty, Eric Keller, Asok Ray, Jeffrey Mayer
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

Rohan SAMSI, Asok RAY
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]

Quentin Gaudel, Elodie Chanthery, Pauline Ribot, Matthew J. Daigle
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

Soumalya Sarkar, Nurali Virani, Murat Yasar, Asok Ray, Soumik Sarkar
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

Soumalya Sarkar, Soumik Sarkar, Nurali Virani, Asok Ray, Murat Yasar
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

Oliver Wallscheid
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

Xuewu Dai, Zhiwei Gao
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

Asok Ray
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

Man Shan Kan, Andy C.C. Tan, Joseph Mathew
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

A. Acquafresca, E. Biagi, L. Masotti, D. Menichelli
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

P. Baranyi, Yeung Yam, A.R. Varkonyi-Koczy, R.J. Patton, P. Michelberger, M. Sugiyama
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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