Time　series　comparison　is　an　important　research　topic　with　applications　mainly　in　fields　like　economics,　finance,　geology,　marketing,　medicine,　physics,　signal　processing,　among　many　others,　when　we　want　to　know　if　two　or　more　time　series　have　the　same　stochastic　mechanism.　The　comparison,　classification　and　clustering　of　two　or　several　time　series　models　have　been　considered　in　both　time　and　frequency　domain　approaches　by　means　of　many　statisticians.　Most　of　these　techniques　can　be　applied　for　the　stationary　time　series.　This　paper　deals　with　the　problem　of　testing　equality　among　spectral　densities　of　several　independent　periodically　correlated　processes.　The　asymptotic　distribution　for　the　discrete　Fourier　transform　of　periodically　correlated　time　is　applied　to　test　the　equality　of　several　independent　periodically　correlated　time　series.