 |
| New interface methods developed at
ARRI allow fast and easy installation, setup and programming
of wireless sensor networks for CBM / PHM |
 |
 |
| Network Configuration Wizard for
fast programming and setup of sensor networks for CBM/PHM |
|
Objective:
- Develop improved methods for intelligent automated
Diagnostics and Prognostics for engineered machinery,
aerospace, and vehicle systems
- Provide a unified and rigorous framework for computer-aided
Condition-Based Maintenance (CBM) and Prognostics & Health
Management (PHM) based on wireless sensor networks
 |
Remote site User Interfaces for
CBM/PHM sensor networks including WiFi laptop, graphical
LabVIEW analysis, and handheld PDA query capability. |
Approach:
- Graphical User Interface (based on LabVIEW) for fast
installation and programming of wireless sensor networks
for CBM and PHM of machinery and vehicles.
- Communication and scheduling protocols for energy-aware
sampling of sensors and data logging of real-time signals
for diagnostics and prognostics.
- Methods for fast analysis of time signals of vibration,
temperature, pressure, etc. based on integrated statistical
time series analysis and frequency domain techniques.
- Overall scheme for CBM that integrates both data-based
methods and model-based methods into a unified approach
for generating the most effective fault classification
feature vectors.
- Overall scheme for PHM that integrates intelligent
decision methods including neural networks, fuzzy logic,
Dempster-Shafer, Petri nets, etc. to best diagnose
fault conditions and prescribe appropriate repair actions.
- Effective methods for scheduling equipment removal
from service, repair, and restoration to service based
on formal extensions to Manufacturing Requirements
Planning (MRP) methods.
- Remote site monitoring of machinery diagnostic signals
and waveforms over the internet using wireless sensor
network methods.
Accomplishments:
- New methods or fast setup and programming of a wireless
sensor network for CBM/PHM in machinery spaces.
- New framework based on time matrices for fast scheduling
of sensors that accommodates both sensor addition and
sensor failure.
- Methods for use of commercial sensors in CBM/PHM
including both Microstrain, Inc., and Berkeley XBOW
sensors.
- Method and apparatus for remote site monitoring
over the internet.
- With our method, it is now as easy to deploy and
program a wireless sensor network for CBM/PHM as it
is to program a PC.
- A specific wireless sensor network has been developed
for Condition-Based Maintenance of a machinery room,
including equipment monitoring, fault diagnosis, and
health prognosis using advanced decision schemes.
Publications:
[1] |
G. Vachtsevanos, F.L. Lewis, M. Roemer, A. Hess, B. Wu, Intelligent Fault Diagnosis and Prognosis for Engineering Systems, John Wiley, New York, 2006. |
[2] |
F.L. Lewis, “Wireless Sensor Networks,” in Smart Environments: Technologies, Protocols, Applications, ed. D.J. Cook and S.K. Das, Wiley, New York, 2004. |
[3] |
A. Tiwari, P. Ballal, and F.L. Lewis, “Energy-Efficient Wireless Sensor Network Design & Implementation for Condition Based Maintenance,” ACM Trans. on Sensor Networks, to appear, 2006. |
[4] |
A. Tiwari, F.L. Lewis, and S.S. Ge, “Wireless Sensor Networks for Machine Condition Based Monitoring,” Proc. Int. Conf. Control, Automation, Robotics, and Vision, pp. 461-467, invited paper, Kunming, China, Dec 2004. |
[5] |
A.N. Das, F.L. Lewis, and D. Popa, “Data-logging and supervisory control in wireless sensor networks,” Proc. ACIS Int. Workshop on Self-Assembling Wireless Networks (SAWN), pp. 330-338, Las Vegas, June 2006. |
Related Topics :
Health Monitoring :
Femtosecond
Laser Machining
PiezoMEMS
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