## 1 Introduction
These PST recycling technologies could provide plastic mixture products from ELVs but fail in the sorting of plastic materials individually and then producing pure plastic products. Further, more precise sorting technologies like sensor aided sorting methods could be applied. In addition to traditional PST for recycling of ELV plastics, in the last decade, novel sorting methods of indirect material detection, such as recognition by using different sensor technologies and then a material separation process by using additional force field (like a compressed air nozzle) have been developed and implemented in processing and recycling processes. These kinds of sorting technologies are called \"Sensor Based Sorting\" or \"Sensor Aided Sorting\", and are defined as single grain separation for contact-free detection of externally identifiable and measurable separation parameters. This technology has brought revolution to the design of dry separation processes in solid industrial waste recycling and mineral processing. These techniques allow the design of material recovery processes with high sorting efficiency, which lead to enhanced resource efficiency and therefore to a higher grade of sustainability [20]. Professional sensor aided sorting technologies for waste plastic recycling have also be developed and applied, such as visual optical sorting, near infrared (NIR) and middle infrared (MIR) sorting, tribo-electrification sorting _etc._ However, all of them are incapable of sorting ASR plastics. Since visual optical sorters are only available for color detection, they cannot distinguish different materials with homochromatic features; an NIR spectral detector is able to distinguish most kinds of plastics with high precision but it is not available for black and dark dyed polymers, such as plastics used in vehicles and electronic products, since black and dark dye like soot absorbs nearly 100% of NIR radiation and results in inadequate reflection. The MIR spectral method generates sufficient reflected signals on the surface of black and dark dyed polymers but this method takes several minutes for material recognition, which hampers its industrial utilization; vehicle plastics are always modified and reinforced by padding with different additives like talc. Additives have an influence on the tribo-electrification properties of plastics, hence the tribo-electrification sorter for commonly used plastics is no longer applicable to ASR plastic recycling [21, 22, 23, 24, 25, 26]. Also, over the last decade, sensor aided sorting by using impact Acoustic Emission (AE) has been developed and applied for fine processing and refinery. This technology was first applied in the food industry, for example it has been utilized for nuts such as pistachio or walnut separation [23]. During their growth period some nut pieces are empty or infested by insects with some pupals or mature insects inside. These damaged pieces of nuts need to be eliminated from intact ones. However, to investigate the inner part of nuts is difficult and some internal investigation method like radioactive measurement is not appropriate for foods. Hence the technology of using impact AE was developed. Impact acoustic sorting is a non-destructive method which does not need to break physical or chemical structures of the tested objects. The precondition is that impact must occur in the range of elastic collision on both bodies. During the impact process, part of the kinetic energy of the active impact rigid body is transferred to both impact bodies in the form of vibrations. Then the vibration of the impact bodies is further transferred into ambient air, which results in acoustic wave emission (AE), _i.e._, the sounds propagate in all directions. The impact AE and impact bodies have the same vibrational frequency response which is caused by the impact process, therefore an impact acoustic emission carries information of the corresponding impact. Properties of impact AE signal are associated with the characteristics of the impact body and its material.