Analysis of Signals from Air Conditioner Compressors with Ordinal Patterns

Abstract

Abstract Most machines have devices that monitor their operation. In particular, air conditioners are routinely monitored through several measurements. A desirable outcome of such monitoring is identifying when the device will likely require maintenance. We present the use of Ordinal Patterns, a symbolic transformation of time series, that enables the visual assessment of the type of operation. We juxtapose two machines in different operational conditions, from which six variables are measured. We analyze the expressiveness of these measurements and identify those that best separate the two machines. The technique is visually appealing because it outputs points in a plane whose position reveals hidden dynamics.