Algorithms | latest | clearance-factor

Clearance factor

The clearance factor is defined as the ratio of the peak amplitude and the squared mean of the square roots of the absolute amplitudes.

$ClearanceFactor=\frac{max|x|}{(\frac{1}{N}\sum _{i=0}^{N-1}\sqrt{|x[i]|}{)}^2}$

Applications

• Fault detection in bearings

  For rotating machinery, this feature is maximum for healthy bearings and goes on decreasing for defective ball, defective outer race, and defective inner race respectively. The clearance factor has the highest separation ability for defective inner race faults.

  ⸺ https://de.mathworks.com/help/predmaint/ug/signal-features.html

References

• https://de.mathworks.com/help/predmaint/ug/signal-features.html

Code

INFO

The following snippet is written in a generic and unoptimized manner. The code aims to be comprehensible to programmers familiar with various programming languages and may not represent the most efficient or idiomatic Python practices. Please refer to implementations for optimized implementations in different programming languages.

code.py

import numpy as np


def clearance_factor(signal: np.ndarray) -> float:
    return np.max(np.abs(signal)) / (np.mean(np.sqrt(np.abs(signal))) ** 2)

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