Mathematical Techniques in Multisensor Data Fusion
Mathematical Techniques in Multisensor Data Fusion
Minimum Entropy Approach for Multisensor Data Fusion
SPWHOS '97 Proceedings of the 1997 IEEE Signal Processing Workshop on Higher-Order Statistics (SPW-HOS '97)
Multi-resolution and Multi-sensor Data Fusion for Remote Sensing in Detecting Air Pollution
SSIAI '02 Proceedings of the Fifth IEEE Southwest Symposium on Image Analysis and Interpretation
Differential Data Protection for Dynamic Distributed Applications
ACSAC '03 Proceedings of the 19th Annual Computer Security Applications Conference
IEEE Transactions on Parallel and Distributed Systems
Multi-sensor Data Fusion Using the Influence Model
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 3
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
Approaches to Multisensor Data Fusion in Target Tracking: A Survey
IEEE Transactions on Knowledge and Data Engineering
Sensor and Data Fusion: A Tool for Information Assessment and Decision Making (SPIE Press Monograph Vol. PM138)
The Application of Multi-sensors Fusion in Vehicle Transmission System Fault Diagnosis
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 02
IMSCCS '07 Proceedings of the Second International Multi-Symposiums on Computer and Computational Sciences
SENSORCOMM '07 Proceedings of the 2007 International Conference on Sensor Technologies and Applications
Feature Extraction in Ball Mill Pulverizing System Based on Multi-sensor Data Fusion
CSSE '08 Proceedings of the 2008 International Conference on Computer Science and Software Engineering - Volume 01
Multi-Sensor Data Fusion Based on Fault Detection and Feedback for Integrated Navigation Systems
IITAW '08 Proceedings of the 2008 International Symposium on Intelligent Information Technology Application Workshops
WKDD '09 Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining
Data fusion with a multisensor system for damage control and situational awareness
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
A New Method of Multi-sensor Vibration Signals Data Fusion Based on Correlation Function
CSIE '09 Proceedings of the 2009 WRI World Congress on Computer Science and Information Engineering - Volume 06
RBF Network Based Feature-Level Data Fusion for Robotic Multi-sensor Gripper
CSO '09 Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization - Volume 01
Four Statistical Approaches for Multisensor Data Fusion under Non-Gaussian Noise
CASE '09 Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009)
Fusion of Multisensor Data: Review and Comparative Analysis
GCIS '09 Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02
A New Scheme for Multisensor Image Fusion System
IAS '09 Proceedings of the 2009 Fifth International Conference on Information Assurance and Security - Volume 02
Application of Fuzzy Data Fusion in Multi-sensor Environment Monitor
CIS '09 Proceedings of the 2009 International Conference on Computational Intelligence and Security - Volume 02
Decentralized Multi-sensor Data Fusion Algorithm Using Information Filter
ICMTMA '10 Proceedings of the 2010 International Conference on Measuring Technology and Mechatronics Automation - Volume 01
Expert Systems with Applications: An International Journal
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This paper reports on a new integrated vehicle health maintenance system (IVHMS) based on fault detection and feedback. A fuzzy multi-sensor data fusion Kalman model was used to help reduce IVHMS failure risk. The IVHMS was tested, and sensors with and without faults were identified. The results demonstrate that multi-sensor data fusion based on fault detection and fuzzy Kalman feedback is an effective method of reducing risk in an IVHMS. Use of the fuzzy Kalman filter approach reduced the time needed to perform complex matrix manipulations to control higher order systems in the IVHMS. Moreover, the approach was able to capture the nonlinearity of engine operations under the influence of various anomalies.