PMID- 35009719
OWN - NLM
STAT- MEDLINE
DCOM- 20220112
LR  - 20220114
IS  - 1424-8220 (Electronic)
IS  - 1424-8220 (Linking)
VI  - 22
IP  - 1
DP  - 2021 Dec 28
TI  - Multistage Centrifugal Pump Fault Diagnosis Using Informative Ratio Principal 
      Component Analysis.
LID - 10.3390/s22010179 [doi]
LID - 179
AB  - This study proposes a fault diagnosis method (FD) for multistage centrifugal 
      pumps (MCP) using informative ratio principal component analysis (Ir-PCA). To 
      overcome the interference and background noise in the vibration signatures (VS) 
      of the centrifugal pump, the fault diagnosis method selects the fault-specific 
      frequency band (FSFB) in the first step. Statistical features in time, frequency, 
      and wavelet domains were extracted from the fault-specific frequency band. In the 
      second step, all of the extracted features were combined into a single feature 
      vector called a multi-domain feature pool (MDFP). The multi-domain feature pool 
      results in a larger dimension; furthermore, not all of the features are best for 
      representing the centrifugal pump condition and can affect the condition 
      classification accuracy of the classifier. To obtain discriminant features with 
      low dimensions, this paper introduces a novel informative ratio principal 
      component analysis in the third step. The technique first assesses the feature 
      informativeness towards the fault by calculating the informative ratio between 
      the feature within the class scatteredness and between-class distance. To obtain 
      a discriminant set of features with reduced dimensions, principal component 
      analysis was applied to the features with a high informative ratio. The 
      combination of informative ratio-based feature assessment and principal component 
      analysis forms the novel informative ratio principal component analysis. The new 
      set of discriminant features obtained from the novel technique are then provided 
      to the K-nearest neighbor (K-NN) condition classifier for multistage centrifugal 
      pump condition classification. The proposed method outperformed existing 
      state-of-the-art methods in terms of fault classification accuracy.
FAU - Ahmad, Zahoor
AU  - Ahmad Z
AUID- ORCID: 0000-0002-3571-8907
AD  - Department of Electrical, Electronics and Computer Engineering, University of 
      Ulsan, Ulsan 44610, Korea.
FAU - Nguyen, Tuan-Khai
AU  - Nguyen TK
AUID- ORCID: 0000-0001-8999-6745
AD  - Department of Electrical, Electronics and Computer Engineering, University of 
      Ulsan, Ulsan 44610, Korea.
FAU - Ahmad, Sajjad
AU  - Ahmad S
AUID- ORCID: 0000-0002-1585-5998
AD  - Department of Electrical, Electronics and Computer Engineering, University of 
      Ulsan, Ulsan 44610, Korea.
FAU - Nguyen, Cong Dai
AU  - Nguyen CD
AUID- ORCID: 0000-0002-5632-1028
AD  - Department of Electrical, Electronics and Computer Engineering, University of 
      Ulsan, Ulsan 44610, Korea.
FAU - Kim, Jong-Myon
AU  - Kim JM
AUID- ORCID: 0000-0002-5185-1062
AD  - Department of Electrical, Electronics and Computer Engineering, University of 
      Ulsan, Ulsan 44610, Korea.
AD  - Predictive Diagnosis Technology Cooperation, Ulsan 44610, Korea.
LA  - eng
GR  - S3126818/Korea Technology and Information Promotion Agency/
PT  - Journal Article
DEP - 20211228
PL  - Switzerland
TA  - Sensors (Basel)
JT  - Sensors (Basel, Switzerland)
JID - 101204366
SB  - IM
MH  - *Algorithms
MH  - Principal Component Analysis
MH  - *Vibration
PMC - PMC8747656
OTO - NOTNLM
OT  - fault diagnosis
OT  - multistage centrifugal pump
OT  - principal component analysis
COIS- The authors declare no conflict of interest.
EDAT- 2022/01/12 06:00
MHDA- 2022/01/13 06:00
PMCR- 2021/12/28
CRDT- 2022/01/11 01:07
PHST- 2021/12/02 00:00 [received]
PHST- 2021/12/25 00:00 [revised]
PHST- 2021/12/26 00:00 [accepted]
PHST- 2022/01/11 01:07 [entrez]
PHST- 2022/01/12 06:00 [pubmed]
PHST- 2022/01/13 06:00 [medline]
PHST- 2021/12/28 00:00 [pmc-release]
AID - s22010179 [pii]
AID - sensors-22-00179 [pii]
AID - 10.3390/s22010179 [doi]
PST - epublish
SO  - Sensors (Basel). 2021 Dec 28;22(1):179. doi: 10.3390/s22010179.