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Detection and estimation of valve leakage losses in reciprocating compressor using acoustic emission technique

机译：声发射技术往复式压缩机阀漏损测检测与估计

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Valve problems in reciprocating compressor are often resolved through parameter analysis of acoustic emission (AE) signals or intelligent system without examining the nature of signals related to its source. This study intended to explore the potential of AE signal for the measurement of valve flow rate in order to quantify the severity of valve problems. The study started with time-frequency analysis of AE signal through discrete wavelet transform, followed by valve condition classification and valve flow rate estimation for faulty valves operated from 450 to 750 rpm. The k-nearest neighbours (KNN) and support vector machine (SVM) classification algorithms are employed to classify the valve conditions before estimation of valve flow rate through regression model. The prediction accuracy of valve flow models is found between 74.5 and 98.8%. Finally, the valve leakage loss can be estimated by computing the difference of flow rate between the measured valve and its baseline (normal valve) using AE parameter. (C) 2019 Elsevier Ltd. All rights reserved.
机译：往复式压缩机中的阀门问题通常通过声发射（AE）信号或智能系统的参数分析来解决而不检查与其源相关的信号的性质。该研究旨在探讨AE信号的潜力，用于测量阀流速，以量化阀门问题的严重性。该研究开始于AE信号通过离散小波变换的时频分析，其次是阀状况分类和阀流量估计，故障阀门从450到750rpm操作。用于通过回归模型估计阀流量之前的k-最近邻居（knn）和支持向量机（SVM）分类算法。阀门流模型的预测精度在74.5和98.8％之间。最后，通过使用AE参数计算测量阀和其基线（正常阀）之间的流速差异，可以估计阀漏损耗。 （c）2019年elestvier有限公司保留所有权利。

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