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김민성,윤석호,W. Vance Payne,Piotr A. Domanski 대한기계학회 2010 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.24 No.7
Development of a reference model to predict the value of system parameters during fault-free operation is a basic step for fault detection and diagnosis (FDD). In order to develop an accurate and effective reference model of a heat pump system, experimental data that cover a wide range of operating conditions are required. In this study, laboratory data were collected under various operating conditions and then filtered through a moving window steady-state detector. Over five thousand scans of steady-state data were used to develop polynomial regression models of seven system features. A reference model was also developed using an artificial neural network (ANN),and it is compared to the polynomial models.
A Data-Clustering Technique for Fault Detection and Diagnostics in Field-Assembled Air Conditioners
W. Vance Payne,허재혁,Piotr A. Domanski 대한설비공학회 2018 International Journal Of Air-Conditioning and Refr Vol.26 No.2
Fault detection and diagnostics (FDD) can be used to monitor the performance of air conditioners (ACs) and heat pumps (HPs), signal any departure from their optimal performance, and provide diagnostic information indicating a possible fault if degradation of performance occurs. For packaged systems fully assembled in a factory, an FDD module can be fully developed for all units of a given model based on laboratory tests of a single unit. For field-assembled systems, laboratory tests of a representative AC or HP installation can lead to the development of a “back-bone” preliminary FDD algorithm; however, in situ adaptation of these algorithms is required because of installation variations in the field. This paper describes a method for adapting a laboratory-based FDD module to field-assembled systems by automatically customizing the in situ FDD fault-free performance correlations. We validated the developed data-clustering technique with a set of nearly 6000 data points to generate fault-free correlations for an HP operating in the cooling mode in our laboratory. The study evaluated several fault-free feature models and indicated that the use of different order correlations during stages of data collection produced better fits to the data.