  In this work, we propose a new detector function based on wavelet transform
to discriminate between turbulent and non-turbulent regions in an intermittent
velocity signal. The derivative-based detector function, which is commonly used
in intermittency calculation schemes, shows large fluctuations within turbulent
parts of the signal and requires averaging over a certain ``smoothing period''
to remove the fake drop-outs, introducing subjectivity in calculating
intermittency. The new detector function proposed here is obtained by averaging
the ``pre-multiplied wavelet energy'' over the entire frequency range,
resulting in a function that is much smoother than the derivative-based
detector and at the same time has a good discriminatory property. This makes
the choice of the smoothing period unnecessary and removes the subjectivity
associated with it. We demonstrate the effectiveness of the wavelet detector
within the framework of the widely-used method by Hedley and Keffer (1974, J.
Fluid Mech., V64, pp625), for a range of velocity signals representing the
different stages of roughness-induced transition. The wavelet detector function
works well in detecting the edge intermittency of a canonical turbulent
boundary layer as well, thereby highlighting its generality. Our detector can,
in principle, be used with any method of specifying threshold for obtaining an
indicator function.
