A Feature Extraction Method for Prognostic Health Assessment of Gas Compressor Valves

被引:0
|
作者
Chesnes, Jacob J. [1 ]
Nelson, Daniel A. [2 ]
Kolodziej, Jason R. [1 ]
机构
[1] Rochester Inst Technol, Dept Mech Engn, Rochester, NY 14623 USA
[2] Novity Inc, Adv Dev, San Carlos, CA 94070 USA
关键词
continuous and periodic condition assessment; diagnostic feature extraction; prognosis; RECIPROCATING-COMPRESSOR;
D O I
10.1115/1.4065546
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This article presents features derived from the pressure-volume (PV) diagram that is useful in estimating different valve faults in reciprocating compressors with a strong potential of remaining useful life prediction. The PV diagram is expected to deviate depending on valve wear conditions. Common valve degradation scenarios are explored in this work (leakage, seat wear, and spring fatigue) and are located in the suction and discharge assemblies of a Dresser-Rand ESH-1 compressor commonly used in the petrochemical industry. The proposed method estimates well-understood physical phenomena, the polytropic exponent on the compression, and expansion phase as well as the discharge and suction valve loss power and uses them as features for a quadratic discriminant analysis. The features are created through in-cylinder pressure, suction pressure, discharge pressure, and crank angle measurements collected on a single-stage, dual-acting compressor operating on air with wear precisely machined and seeded into the poppets of the inlet and outlet valves. A very high classification accuracy is achieved in distinguishing the wear types, severity, and location with strong prognostic trends.
引用
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页数:9
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