Determination of effective parameters for diagnosis and classification of air-conditioning refrigerant noise by logistic regression

Abstract

In the present study, refrigerant noise generated from an air-conditioning unit in operation was characterized as water or gas sounds by jury testing and was diagnosed and classified by logistic regression performed with objective sound quality parameters. A chi(2) test was conducted to determine the parameters that influenced the probability for refrigerant noise to occur. Furthermore, the probability of refrigerant noise occurring is determined, based on objective sound quality parameters. Normalization of units was carried out to identify the relative influence of each parameter on the probability of such noise occurring. Further, re-logistic regression was performed with parameters selected based on the chi(2) test. The classification of the air conditioner refrigerant noise is important because appropriate measures can be chosen by the refrigerant noise classification. The water sound has low-frequency characteristics and the gas sound has high-frequency characteristics. There are differences in improvement of two noises. Therefore, a clear distinction must be made between the refrigerant noises to reduce mistakes in improvement. Probability-based optimal cutoff values were determined for the classification of water and gas sounds. Air-conditioning refrigerant noise was classified by taking into account the logistic regression and cutoffs. New experiments on the generation of refrigerant noise were conducted to validate the logistic regression classification. Data obtained from the experiments were classified at an accuracy level of 95.1%. (C) 2018 Institute of Noise Control Engineering.