During　the　process　of　mineral　grinding,　mill　load　parameters　(MLPs)　determine　the　information　of　the　mechanical　signals.　So,　online　MLPs　detection　is　one　of　the　key　factors　for　improving　the　production　efficiency　of　mineral　processing　plants.　In　this　paper,　the　correlation　between　the　multichannel　mechanical　signal　and　the　different　MLPs　is　explored　by　the　power　spectral　density.　Furthermore,　the　contribution　rate　of　the　multisource　and　multicomponent　mechanical　signals　to　the　MLPs　and　mill　load　is　measured　on　the　basis　of　the　correlation　coefficient.　Finally,　a　prediction　model　for　MLPs　can　be　constructed　according　to　an　adaptive　decomposition　strategy　and　the　appropriate　sub-signals.　©　2023　SPIE.　All　rights　reserved.