1 Primož Potočnik, Edvard Govekar, Semi-supervised vibration-based classification and condition monitoring of compressors, Mechanical Systems and Signal Processing 93 (2017) 51–65. (Available online 16 February 2017) © 2015. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ Link to published article: https://www.sciencedirect.com/science/article/pii/S088832701730047X DOI: https://doi.org/10.1016/j.ymssp.2017.01.048 SEMI-SUPERVISED VIBRATION-BASED CLASSIFICATION AND CONDITION MONITORING OF COMPRESSORS Primož Potočnik 1 University of Ljubljana, Faculty of Mechanical Engineering, 1000 Ljubljana, Slovenia Edvard Govekar University of Ljubljana, Faculty of Mechanical Engineering, 1000 Ljubljana, Slovenia Abstract Semi-supervised vibration-based classification and condition monitoring of the reciprocating compressors installed in refrigeration appliances is proposed in this paper. The method addresses the problem of industrial condition monitoring where prior class definitions are often not available or difficult to obtain from local experts. The proposed method combines feature extraction, principal component analysis, and statistical analysis for the extraction of initial class representatives, and compares the capability of various classification methods, including discriminant analysis (DA), neural networks (NN), support vector machines (SVM), and extreme learning machines (ELM). The use of the method is demonstrated on a case study which was based on industrially acquired vibration measurements of reciprocating compressors during the production of refrigeration appliances. The paper presents a comparative qualitative analysis of the applied classifiers, confirming the good performance of several nonlinear classifiers. If the model parameters are properly selected, then very good classification performance can be obtained from NN trained by Bayesian regularization, SVM and ELM classifiers. The method can be effectively applied for the industrial condition monitoring of compressors. Keywords Condition monitoring, Reciprocating compressors, Classification, Semi-supervised, Neural networks, Extreme learning machines. 1. Introduction Condition monitoring (CM) of machines and products is an established and important part of successful modern industrial production. In order to manufacture fault-free products, various non-destructive, time 1 Corresponding author. E-mail address: primoz.potocnik@fs.uni-lj.si (P. Potočnik)