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Fault diagnosis in split-system air conditioner by analyzing the chaos in the electrical current signal.

Author(s) : DE OLIVEIRA A. C., LIMA FILHO A. C., DA SILVA J. C., BELO F. A., BRITO A. V. de, GOMES DE SOUZA RAMOS J. G.

Type of article: IJR article

Summary

Computational technological advances for data processing have increasingly contributed to the evolution of predictive techniques for fault detection and diagnosis (FDD) of motors and machines. As a novelty, this article presents the application of the Signal Analysis based on Chaos using Density of Maxima (SAC-DM) technique in split-system air conditioner equipment to diagnose the occurrence of faults. To this end, a short-term acquisition of the electrical signal at the equipment input was carried out in a non-invasive way, subsequently, the proposed technique is used for diagnosing compressor capacitor degradation and incrustation in the condenser and evaporator units at different blocking levels. The results prove a better accuracy compared to the Fast Fourier transform (FFT), making it possible to detect and diagnose air conditioner faults, with an accuracy of 100 % for FDD of single faults, 96.55 % for detection and 82.76 % for diagnosis of dual faults. In addition, the technique demands only short-term data acquisition and a single experiment to detect and diagnose the faults.

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Pages: 228-239

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Details

  • Original title: Fault diagnosis in split-system air conditioner by analyzing the chaos in the electrical current signal.
  • Record ID : 30033660
  • Languages: English
  • Source: International Journal of Refrigeration - Revue Internationale du Froid - vol. 172
  • Publication date: 2025/04
  • DOI: http://dx.doi.org/10.1016/j.ijrefrig.2025.01.011

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