Instead of saying "I'm going to try this, maybe it will work", you should instead be asking if wavelet transforms are appropriate given the domain you are building a model for. Don't just transform data in the hopes that it will magically work.
You’ve just described modern machine learning.
Do you know how we discovered X-Rays? Henri Becquerel realized his photographic plates had been darkened after being left in a drawer with uranium sulfate.
Do you know how electric guitar distortion was discovered? Willie Kizart dropped his Fender amp.
Worse things have happened than experimenting by throwing one more transform on your inputs before processing them.
How do you determine if they are good for your application and how do you choose which family of wavelets to apply?