Quantitative Evaluation on Valve Leakage of Reciprocating Compressor Using System Characteristic Diagnosis Method
Source abstract
Abstract
High impact and strong noise complicate the response of reciprocating compressor (RC). It requires a complex signal processing method that is a single response-based or excitation-based fault diagnosis method applied to RC valve leakage fault diagnosis. This paper proposes a quantitative diagnosis method of RC valve leakage that is based on system characteristic diagnosis method. First, the current signal of the RC induction motor and the cylinder vibration signal are introduced as the excitation and response signals, the mathematical model of the RC motor current is established, and the influence mechanism of the valve leakage on the RC vibration is analyzed. Subsequently, the ensemble empirical mode decomposition and comb filter are respectively used to extract the fault characteristic information of excitation signal and response signal to obtain the excitation condition indicators (CIs), response CIs, and system CIs. Finally, the support vector machine based on the obtained CIs classified the valve leakage failure patterns of different severity, and a fault diagnoser was constructed for the quantitative diagnosis of valve leakage fault. The results of experiment and application proved that the proposed method could realize the quantitative diagnosis of RC valve leakage fault while using simple signal processing technology.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Machine Fault Diagnosis Techniques · Mechanical Failure Analysis and Simulation · Hydraulic and Pneumatic Systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Anhui University of Science and Technology, Huainan 232001, China
State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Anhui University of Science and Technology, Huainan 232001, China
State Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
Shaanxi Automobile Holding Group Huainan Special Purpose Vehicle Co. Ltd., Huainan 232001, China
School of Advanced Manufacturing Engineering, Hefei University, Hefei 232000, China
Funding
National Natural Science Foundation Project in China · Anhui Provincial Natural Science Foundation Project · Anhui Provincial Education Department Fund · State Key Laboratory of Mechanical Manufacturing System Engineering Open Research Fund · Research on key technology and industrialization application of unmanned intelligent patrol vehicle · Anhui Provincial Key Laboratory of Intelligent Equipment and Technology Open Fund · Anhui University of Science and Technology Innovation Fund
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