Next Article in Journal
Polymer Optical Fiber Tip Mass Production Etch Mechanism to Achieve CPC Shape for Improved Biosensor Performance
Next Article in Special Issue
Development of a Wireless Mesh Sensing System with High-Sensitivity LiNbO3 Vibration Sensors for Robotic Arm Monitoring
Previous Article in Journal
Dopamine/2-Phenylethylamine Sensitivity of Ion-Selective Electrodes Based on Bifunctional-Symmetrical Boron Receptors
Previous Article in Special Issue
Battery Charger Prototype Design for Tire Pressure Sensor Battery Recharging
Article Menu
Issue 2 (January-2) cover image

Export Article

Open AccessArticle
Sensors 2019, 19(2), 284; https://doi.org/10.3390/s19020284

Visual-Acoustic Sensor-Aided Sorting Efficiency Optimization of Automotive Shredder Polymer Residues Using Circularity Determination

School of Environment and Spatial Informatics, China University of Mining & Technology, Xuzhou 221116, China
*
Authors to whom correspondence should be addressed.
This paper is an extended version of our paper published in International Symposium on Sensor Science (I3S 2018).
Received: 31 October 2018 / Revised: 6 January 2019 / Accepted: 7 January 2019 / Published: 12 January 2019
(This article belongs to the Special Issue I3S 2018 Selected Papers)
  |  
PDF [7480 KB, uploaded 12 January 2019]
  |  

Abstract

To reduce the emissions and weight of vehicles, manufacturers are incorporating polymer materials into vehicles, and this has increased the difficulty in recycling End-of-Life vehicles (ELVs). About 25–30% (mass) of an ELV crushed mixture is the unrecyclable material known as automotive shredder residues (ASRs), and most of the vehicle polymers are concentrated in this fraction. Thus, these vehicle polymers are conventionally disposed of in landfills at a high risk to the environment. The only way to solve this problem is through the development of a novel separation and recycling mechanism for ASRs. Our previous research reported a novel sensor-aided single-scrap-oriented sorting method that uses laser-triangulation imaging combined with impact acoustic frequency recognition for sorting crushed ASR plastics, and we proved its feasibility. However, the sorting efficiencies were still limited, since, in previous studies, the method used for scrap size determination was mechanical sieving, resulting in many deviations. In this paper, a new method based on three-dimensional (3D) imaging and circularity analysis is proposed to determine the equivalent particle size with much greater accuracy by avoiding the issues that are presented by the irregularity of crushed scraps. In this research, two kinds of commonly used vehicle plastics, acrylonitrile-butadiene-styrene (ABS) and polypropylene (PP), and their corresponding composite materials, acrylonitrile-butadiene-styrene/polycarbonate (ABS/PC) and polypropylene/ethylene-propylene-diene-monomer (PP/EPDM), were studied. When compared with our previous study, with this new method, the sorting efficiency increased, with PP and PP/EPDM and ABS and ABS/PC achieving about 15% and 20% and 70% and 90%, respectively. The sorting efficiency of ASR polymer scraps can be optimized significantly by using sensor-aided 3D image measurement and circularity analysis. View Full-Text
Keywords: sensor-aided sorting; automotive shredder residues; circularity determination; particle size distribution sensor-aided sorting; automotive shredder residues; circularity determination; particle size distribution
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Huang, J.; Xu, C.; Zhu, Z.; Xing, L. Visual-Acoustic Sensor-Aided Sorting Efficiency Optimization of Automotive Shredder Polymer Residues Using Circularity Determination. Sensors 2019, 19, 284.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top