A Literature Review of the Positive Displacement Compressor: Current Challenges and Future Opportunities

Lu, Kui; Sultan, Ibrahim A.; Phung, Truong H.

doi:10.3390/en16207035

Cited by 6 publications

(1 citation statement)

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“…In addition, recorded signals are usually affected by disturbances and interferences that represent severe challenges to feature extraction technologies [ 18 ]. Valves, in particular, are components susceptible to faults, and significant challenges exist [ 19 , 20 ] in understanding the mechanisms leading to faults in such components. Within this framework, condition monitoring using vibration signals and extracting useful features is essential for addressing these problems.…”

Section: Introductionmentioning

confidence: 99%

Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor

Medina,

Sánchez,

Cabrera

et al. 2024

Sensors

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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.

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Section: Introductionmentioning

confidence: 99%