Component machine testing using neural network processed vibrati

Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Mechanical measurement system

Patent

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

395 21, 395 22, 73581, G01M 700

Patent

active

058549935

ABSTRACT:
A component machine testing technique is provided that performs diagnostic analysis on a vibration signal of the component machine that has been separated from power and load machine background noise in a first neural network. The diagnostic analysis, with operator direction through an interactive interface, uses a second neural network in performing a series of diagnostic operations followed by archival of any experience acquired in the testing operation being performed.
In the diagnostic analysis, both time based and frequency based vibration signal information from the component machine under test are used together through a simultaneous multiple display interactive interface under operator direction.

REFERENCES:
patent: 5313407 (1994-05-01), Tiernan et al.
patent: 5333240 (1994-07-01), Matsumoto et al.
patent: 5361628 (1994-11-01), Marko et al.
patent: 5419197 (1995-05-01), Ogi et al.
patent: 5426720 (1995-06-01), Bozich et al.
patent: 5566092 (1996-10-01), Wang et al.
patent: 5566273 (1996-10-01), Huang et al.
patent: 5579232 (1996-11-01), Tong et al.

LandOfFree

Say what you really think

Search LandOfFree.com for the USA inventors and patents. Rate them and share your experience with other people.

Rating

Component machine testing using neural network processed vibrati does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Component machine testing using neural network processed vibrati, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Component machine testing using neural network processed vibrati will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFUS-PAI-O-1430622

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.