A Data-Driven Approach for Condition Monitoring of Reciprocating Compressor Valves

This paper focuses on condition-monitoring of three different valve failure modes common in reciprocating compressors. They are missing valve poppets, valve spring fatigue, and valve seat wear. First, a targeted instrumentation study is performed on a Dresser–Rand ESH-1 industrial reciprocating compressor to investigate detection methods for these failures. This is followed by the development of a novel health classification methodology based on frequency analysis and Bayes theorem. The method is shown to successfully classify the condition of the valves to a high degree of accuracy when applied to actual seeded valve faults in the compressor.