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<p>This work proposes and experimentally evaluates a noninvasive method for estimating the speed of hermetic compressors using vibration measurements. The approach employs an all-phase fast Fourier transform (ApFFT) combined with a rate limiter filter and a correction procedure to obtain the dominant frequency regardless of the frequency resolution, which enables the use of reduced acquisition windows. In this way, a rapid response is achieved at low computational cost, making it suitable for embedded systems and applications with transient behavior, such as operation under varying speed or fault conditions. Experimental tests evaluating compressor startup, steady-state operation, and stall conditions demonstrated that the proposed method generally outperforms the conventional FFT. Notably, the proposed method reduced the mean absolute error by 29% and 30% in short acquisition windows (12 samples, 0.048 s) during startup and steady-state operations, respectively, when compared with the second best results. While the traditional FFT yielded marginally better results for very short windows during stall tests due to a delay introduced by the outlier filter, the proposed method proved reliable overall, increasing accuracy and reducing delay in estimations.</p>

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Noninvasive Compressor Speed Estimation From Vibration Measurements Using ApFFT

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月24日

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  • Gabriel Thaler,
  • João P. Z. Machado,
  • Rodolfo C. C. Flesch,
  • Victoria de C. Taveira

摘要

This work proposes and experimentally evaluates a noninvasive method for estimating the speed of hermetic compressors using vibration measurements. The approach employs an all-phase fast Fourier transform (ApFFT) combined with a rate limiter filter and a correction procedure to obtain the dominant frequency regardless of the frequency resolution, which enables the use of reduced acquisition windows. In this way, a rapid response is achieved at low computational cost, making it suitable for embedded systems and applications with transient behavior, such as operation under varying speed or fault conditions. Experimental tests evaluating compressor startup, steady-state operation, and stall conditions demonstrated that the proposed method generally outperforms the conventional FFT. Notably, the proposed method reduced the mean absolute error by 29% and 30% in short acquisition windows (12 samples, 0.048 s) during startup and steady-state operations, respectively, when compared with the second best results. While the traditional FFT yielded marginally better results for very short windows during stall tests due to a delay introduced by the outlier filter, the proposed method proved reliable overall, increasing accuracy and reducing delay in estimations.