Is Wavelet Transform better than FT if I'm only interested in knowing the frequencies and not interested of when did they happen?
Since they seem more fashionable than Fourier transforms, some persons tend to overuse wavelets in contexts where they do not belong, or at least don't do a much better job. 

For "knowing the frequencies", Fourier transforms are the correct tools to use first: it is so easy to badly select a wavelet transformation (including its shape and its sampling) that will give you outcomes difficult to interpret, and even erroneous information. To be more specific, among fast orthogonal transforms (DWT and FFT), due to the restrictions on dyadic wavelets, it is unlikely to have better results with wavelets than Fourier (because of shift-variance, aliasing and badly-shaped FIR wavelets).


  does WT do any better job than FT in detecting the frequencies


It really depends on what you expect in detection, and the nature of your signals, and it often takes more than a transform. However, I would recommend to use wavelets or time-frequency tools if Fourier reveals not sufficient, or in parallel to address statonnarity, etc., but  not instead.