A p−V Diagram Based Fault Identification for Compressor Valve by Means of Linear Discrimination Analysis

Author:

Li Xueying,Ren Peng,Zhang Zhe,Jia Xiaohan,Peng XueyuanORCID

Abstract

The pressure-volume diagram (p−V diagram) is an established method for analyzing the thermodynamic process in the cylinder of a reciprocating compressor as well as the fault of its core components including valves. The failure of suction/discharge valves is the most common cause of unscheduled shutdowns, and undetected failure may lead to catastrophic accidents. Although researchers have investigated fault classification by various estimation techniques and case studies, few have looked deeper into the barriers and pathways to realize the level determination of faults. The initial stage of valve failure is characterized in the form of mild leakage; if this is identified at this period, more serious accidents can be prevented. This study proposes a fault diagnosis and severity estimation method of the reciprocating compressor valve by virtue of features extracted from the p−V diagram. Four-dimensional characteristic variables consisting of the pressure ratio, process angle coefficient, area coefficient, and process index coefficient are extracted from the p−V diagram. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were applied to establish the diagnostic model, where PCA realizes feature amplification and projection, then LDA implements feature dimensionality reduction and failure prediction. The method was validated by the diagnosis of various levels of severity of valve leakage in a reciprocating compressor, and further, applied in the diagnosis of two actual faults: Mild leakage caused by the cracked valve plate in a reciprocating compressor, and serious leakage caused by the deformed valve in a hydraulically driven piston compressor for a hydrogen refueling station (HRS).

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Optimization,Mechanical Engineering,Computer Science (miscellaneous),Control and Systems Engineering

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1. A Feature Extraction Method for Prognostic Health Assessment of Gas Compressor Valves;Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems;2024-06-07

2. Development of Digital Twin for Reciprocating Compressor Using Machine Learning Methodic;Lecture Notes in Networks and Systems;2024

3. Feasibility exploration of strain-based indicator diagram reconstruction for reciprocating compressor fault diagnosis;Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering;2023-10-17

4. Fault Diagnosis and Health Management of Power Machinery;Machines;2023-03-27

5. Fault diagnosis of reciprocating compressor based on the prediction of comprehensive index extracted from the expansion process in indicator diagram;Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering;2023-03-23

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