摘要
Three categories of failure diagnostic methods for reciprocating compressors are classified according to the signals adopted by the diagnosis. They are parameter method, vibration method, and oil analysis method. In this paper, the applicable range and operational difficulties of these methods are discussed on the basis of analysis and induction upon normal failure. It is proposed that a compressor's normal failure can be divided into thermodynamical property failure and mechanical function failure. As to the former, the parameter method that takes a cylinder pressure signal as the main diagnostic signal may be applied; and as to the latter, the vibration signal frequency spectrum can be used to diagnose. At the same time, the structure of an intelligent diagnostic system based on neural networks is introduced, and its schematic is given.
Three categories of failure diagnostic methods for reciprocating compressors are classified according to the signals adopted by the diagnosis. They are parameter method, vibration method, and oil analysis method. In this paper, the applicable range and operational difficulties of these methods are discussed on the basis of analysis and induction upon normal failure. It is proposed that a compressor's normal failure can be divided into thermodynamical property failure and mechanical function failure. As to the former, the parameter method that takes a cylinder pressure signal as the main diagnostic signal may be applied; and as to the latter, the vibration signal frequency spectrum can be used to diagnose. At the same time, the structure of an intelligent diagnostic system based on neural networks is introduced, and its schematic is given.
