Microphone Phased Array Machinery Fault Diagnostic System (Revised)

Award Information
Agency:
Department of Defense
Amount:
$651,840.00
Program:
SBIR
Contract:
FA9101-06-C-0092
Solitcitation Year:
2005
Solicitation Number:
2005.1
Branch:
Air Force
Award Year:
2007
Phase:
Phase II
Agency Tracking Number:
F051-304-2398
Solicitation Topic Code:
AF05-304
Small Business Information
AVEC, INC.
2000 Kraft Drive, Suite 1109, Virginia Tech Corpor, Blacksburg, VA, 24060
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
175964720
Principal Investigator
 Kyle Schwartz
 Research Engineer
 (540) 961-2832
 kschwartz@avec-engineering.com
Business Contact
 Ricardo Burdisso
Title: President
Phone: (540) 961-2832
Email: avec_inc@verizon.net
Research Institution
N/A
Abstract
The objective of this effort is to develop a remote acoustics-based system to detect rotating equipment health status. The goal is an automated acoustic monitoring system that includes the necessary filtering/data manipulation techniques and expert system/classification/anomaly detection algorithms to diagnose the health of plant equipment (compressors, electric motors, gear trains, fans, etc) in an industrial high-bay area environment. The system will also have the capability to learn and recall the acoustic signature of novel faults and the capability to send an alarm. The health monitoring proposed here is based on a microphone phased array positioned such as to have a direct line of sight to the machine to be monitored. The microphone signals are recorded simultaneously and used to scan or beamform over a grid enclosing the machine to capture its acoustic signature. The acoustic image is then integrated to obtain the machine noise spectrum that is used to identify damage or faults by an automated expert system. The system will operate properly without human intervention while targeting and identifying developing faults. The objective of the Phase II effort is the development and demonstration of a prototype microphone phased array based fault monitoring system on a large-scale plant equipment.

* information listed above is at the time of submission.

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