Graphene applied in micronanocomposites have promising electrical and tribological properties, especially in context of sensory applications for electrotribological friction nodes. Due to Graphene's high durability, strength and low friction coefficient affecting the properties of the composite, the applications range from heavy industry (strain sensing paints, windmill blades etc.) to robotics and microsystems (self sensing bearings and shafts). Researched micronanocomposite is manufactured from multilayer graphene precursor with addition of zink oxide and/or copper (II) oxide fillers in thermosetting 4,4'-Bis(maleimido)diphenylmethane and 2,2'-diallylbisphenol or Novolac matrix. Mixed substrate powder exhibits a bimodal particle size distribution as documented using Laser Diffraction method and supported with SEM images. High energy ball co-milling of the powders is decreasing the number of layers in multilayer graphene precursor through the process of intercalation of metal oxide particles between graphene layers. After co-milling, metal oxide median is at the size of 800 nm, and multilayer graphene precursor nanoplatelets radius 4 um. Chronopotentiometry and impedance spectroscopy has been performed after the powder suspended in the aqueous solution ZnCl2 was further intercalated and the results were mathematically modelled. Several conductance models were fit for graphene copper oxide sample with machine learning models such as Hammerstein-Wiener model.