Neural network based system for equipment surveillance
Patent
·
OSTI ID:871513
- Aurora, IL
- Bolingbrook, IL
- Glendale Hts., IL
A method and system for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- DOE Contract Number:
- W-31109-ENG-38
- Assignee:
- ARCH Development Corporation (Chicago, IL)
- Patent Number(s):
- US 5745382
- OSTI ID:
- 871513
- Country of Publication:
- United States
- Language:
- English
Review of Neural Networks for Speech Recognition
|
journal | March 1989 |
Modular Construction of Time-Delay Neural Networks for Speech Recognition
|
journal | March 1989 |
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Related Subjects
neural
network
based
equipment
surveillance
method
performing
transient
signals
industrial
device
ascertain
operating
involves
steps
reading
memory
training
data
determining
weighting
values
achieving
target
outputs
close
output
inadequate
wavelet
parameters
determined
yield
desired
set
providing
characteristic
process
comparing
evaluate
process signals
neural network
industrial process
network based
training data
performing surveillance
desired set
neural net
transient signal
/706/702/
network
based
equipment
surveillance
method
performing
transient
signals
industrial
device
ascertain
operating
involves
steps
reading
memory
training
data
determining
weighting
values
achieving
target
outputs
close
output
inadequate
wavelet
parameters
determined
yield
desired
set
providing
characteristic
process
comparing
evaluate
process signals
neural network
industrial process
network based
training data
performing surveillance
desired set
neural net
transient signal
/706/702/