Skip to main navigation
Skip to search
Skip to main content
Manipal Academy of Higher Education, Manipal, India Home
Help & FAQ
Home
Profiles
Research units
Research output
Equipment
Search by expertise, name or affiliation
Noise-resilient process fault detection via multi-scale pls and distribution monitoring metrics
K. Ramakrishna Kini
, Fouzi Harrou
,
Muddu Madakyaru
*
, Ying Sun
,
Mukund Kumar Menon
*
Corresponding author for this work
Research output
:
Contribution to journal
›
Article
›
peer-review
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Noise-resilient process fault detection via multi-scale pls and distribution monitoring metrics'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
INIS
distribution
100%
detection
100%
monitoring
100%
noise
100%
metrics
100%
least square fit
60%
performance
40%
distance
40%
signal-to-noise ratio
40%
comparative evaluations
20%
depth
20%
sensitivity
20%
industry
20%
environment
20%
modeling
20%
layers
20%
tanks
20%
density
20%
decomposition
20%
randomness
20%
forests
20%
machine learning
20%
charts
20%
indicators
20%
operation
20%
benchmarks
20%
kernels
20%
decision making
20%
reactors
20%
Chemical Engineering
Learning System
100%
Multilayer Neural Networks
100%
Continuous Stirred Tank Reactor
100%
Computer Science
Measurement Noise
40%
Engineering
Noise Scenario
20%