During　the　process　of　mineral　grinding,　the　ball　mill　generates　the　mechanical　signals　containing　rich　information　due　to　different　positions,　which　include　mill　loads　and　mill　load　parameters　(MLPs).　Actually,　as　one　of　the　key　factors,　online　MLPs　detection　is　usually　exploited　to　realize　the　intellectualization　and　improve　the　production　efficiency　of　mineral　processing　plants.　In　this　paper,　on　the　basis　of　the　ensemble　empirical　mode　decomposition　technique,　the　multisource　and　multicomponent　mechanical　signals　of　an　experimental　ball　mill　under　changing　ball,　material,　and　water　load　conditions　are　analyzed　to　obtain　different　physical　sub-signals　via　the　intrinsic　mode　function.　©　2023　SPIE.　All　rights　reserved.