Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor
Reciprocating compressors and centrifugal pumps are rotating machines used in industry, where fault detection is crucial for avoiding unnecessary and costly downtime. A novel method for fault classification in reciprocating compressors and multi-stage centrifugal pumps is proposed. In the feature ex...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/2/461 |
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| author | Ruben Medina René-Vinicio Sánchez Diego Cabrera Mariela Cerrada Edgar Estupiñan Wengang Ao Rafael E. Vásquez |
| author_facet | Ruben Medina René-Vinicio Sánchez Diego Cabrera Mariela Cerrada Edgar Estupiñan Wengang Ao Rafael E. Vásquez |
| author_sort | Ruben Medina |
| collection | DOAJ |
| description | Reciprocating compressors and centrifugal pumps are rotating machines used in industry, where fault detection is crucial for avoiding unnecessary and costly downtime. A novel method for fault classification in reciprocating compressors and multi-stage centrifugal pumps is proposed. In the feature extraction stage, raw vibration signals are processed using multi-fractal detrended fluctuation analysis (MFDFA) to extract features indicative of different types of faults. Such MFDFA features enable the training of machine learning models for classifying faults. Several classical machine learning models and a deep learning model corresponding to the convolutional neural network (CNN) are compared with respect to their classification accuracy. The cross-validation results show that all models are highly accurate for classifying the 13 types of faults in the centrifugal pump, the 17 valve faults, and the 13 multi-faults in the reciprocating compressor. The random forest subspace discriminant (RFSD) and the CNN model achieved the best results using MFDFA features calculated with quadratic approximations. The proposed method is a promising approach for fault classification in reciprocating compressors and multi-stage centrifugal pumps. |
| first_indexed | 2024-03-08T09:47:26Z |
| format | Article |
| id | doaj.art-f24f12bd48674371b87cd7ba5ccc2228 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-08T09:47:26Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-f24f12bd48674371b87cd7ba5ccc22282024-01-29T14:14:58ZengMDPI AGSensors1424-82202024-01-0124246110.3390/s24020461Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating CompressorRuben Medina0René-Vinicio Sánchez1Diego Cabrera2Mariela Cerrada3Edgar Estupiñan4Wengang Ao5Rafael E. Vásquez6CIBYTEL-Engineering School, Universidad de Los Andes, Mérida 5101, VenezuelaGIDTEC, Universidad Politécnica Salesiana, Cuenca 010105, EcuadorGIDTEC, Universidad Politécnica Salesiana, Cuenca 010105, EcuadorGIDTEC, Universidad Politécnica Salesiana, Cuenca 010105, EcuadorMechanical Engineering Department, Universidad de Tarapacá, Arica 1010069, ChileNational Research Base of Intelligent Manufacturing Service, Chongqing Technology and Business University, 19# Xuefu Avenue, Nan’an District, Chongqing 400067, ChinaSchool of Engineering, Universidad Pontificia Bolivariana, Circular 1 # 70-01, Medellín 050031, ColombiaReciprocating compressors and centrifugal pumps are rotating machines used in industry, where fault detection is crucial for avoiding unnecessary and costly downtime. A novel method for fault classification in reciprocating compressors and multi-stage centrifugal pumps is proposed. In the feature extraction stage, raw vibration signals are processed using multi-fractal detrended fluctuation analysis (MFDFA) to extract features indicative of different types of faults. Such MFDFA features enable the training of machine learning models for classifying faults. Several classical machine learning models and a deep learning model corresponding to the convolutional neural network (CNN) are compared with respect to their classification accuracy. The cross-validation results show that all models are highly accurate for classifying the 13 types of faults in the centrifugal pump, the 17 valve faults, and the 13 multi-faults in the reciprocating compressor. The random forest subspace discriminant (RFSD) and the CNN model achieved the best results using MFDFA features calculated with quadratic approximations. The proposed method is a promising approach for fault classification in reciprocating compressors and multi-stage centrifugal pumps.https://www.mdpi.com/1424-8220/24/2/461detrended fluctuation analysisreciprocating compressorsmulti-fault classificationcentrifugal pumpmulti-fractal feature extractionvibration signals |
| spellingShingle | Ruben Medina René-Vinicio Sánchez Diego Cabrera Mariela Cerrada Edgar Estupiñan Wengang Ao Rafael E. Vásquez Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor Sensors detrended fluctuation analysis reciprocating compressors multi-fault classification centrifugal pump multi-fractal feature extraction vibration signals |
| title | Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor |
| title_full | Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor |
| title_fullStr | Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor |
| title_full_unstemmed | Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor |
| title_short | Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor |
| title_sort | scale fractal detrended fluctuation analysis for fault diagnosis of a centrifugal pump and a reciprocating compressor |
| topic | detrended fluctuation analysis reciprocating compressors multi-fault classification centrifugal pump multi-fractal feature extraction vibration signals |
| url | https://www.mdpi.com/1424-8220/24/2/461 |
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