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Study of Failure Diagnostic Methods and Intelligent Diagnostic System for Reciprocating Compressors

机译:往复式压缩机故障诊断方法与智能诊断系统研究

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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 compressors 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.
机译:根据诊断所采用的信号将往复式压缩机的故障诊断方法分为三类。它们是参数方法,振动方法和油分析方法。本文在对正常失效进行分析和归纳的基础上,讨论了这些方法的适用范围和操作难点。建议将压缩机的正常故障分为热力学性能故障和机械功能故障。对于前者,可以采用以气缸压力信号为主要诊断信号的参数方法。对于后者,振动信号频谱可用于诊断。同时介绍了基于神经网络的智能诊断系统的结构,并给出了原理图。

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