Next Article in Journal
Development and Testing of a Dual Accelerometer Vector Sensor for AUV Acoustic Surveys
Next Article in Special Issue
Surface Acoustic Wave Sensors for Hydrogen and Deuterium Detection
Previous Article in Journal
Artificial Neural Network-Based Early-Age Concrete Strength Monitoring Using Dynamic Response Signals
Previous Article in Special Issue
Room-Temperature Ammonia Sensor Based on ZnO Nanorods Deposited on ST-Cut Quartz Surface Acoustic Wave Devices
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(6), 1325;

Study on Impact Acoustic—Visual Sensor-Based Sorting of ELV Plastic Materials

School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221000, China
Author to whom correspondence should be addressed.
Academic Editors: Jikui Luo, Weipeng Xuan and Richard Yong Qing Fu
Received: 11 April 2017 / Revised: 1 June 2017 / Accepted: 2 June 2017 / Published: 8 June 2017
(This article belongs to the Special Issue Acoustic Wave Resonator-Based Sensors)
Full-Text   |   PDF [6367 KB, uploaded 8 June 2017]   |  


This paper concentrates on a study of a novel multi-sensor aided method by using acoustic and visual sensors for detection, recognition and separation of End-of Life vehicles’ (ELVs) plastic materials, in order to optimize the recycling rate of automotive shredder residues (ASRs). Sensor-based sorting technologies have been utilized for material recycling for the last two decades. One of the problems still remaining results from black and dark dyed plastics which are very difficult to recognize using visual sensors. In this paper a new multi-sensor technology for black plastic recognition and sorting by using impact resonant acoustic emissions (AEs) and laser triangulation scanning was introduced. A pilot sorting system which consists of a 3-dimensional visual sensor and an acoustic sensor was also established; two kinds commonly used vehicle plastics, polypropylene (PP) and acrylonitrile-butadiene-styrene (ABS) and two kinds of modified vehicle plastics, polypropylene/ethylene-propylene-diene-monomer (PP-EPDM) and acrylonitrile-butadiene-styrene/polycarbonate (ABS-PC) were tested. In this study the geometrical features of tested plastic scraps were measured by the visual sensor, and their corresponding impact acoustic emission (AE) signals were acquired by the acoustic sensor. The signal processing and feature extraction of visual data as well as acoustic signals were realized by virtual instruments. Impact acoustic features were recognized by using FFT based power spectral density analysis. The results shows that the characteristics of the tested PP and ABS plastics were totally different, but similar to their respective modified materials. The probability of scrap material recognition rate, i.e., the theoretical sorting efficiency between PP and PP-EPDM, could reach about 50%, and between ABS and ABS-PC it could reach about 75% with diameters ranging from 14 mm to 23 mm, and with exclusion of abnormal impacts, the actual separation rates were 39.2% for PP, 41.4% for PP/EPDM scraps as well as 62.4% for ABS, and 70.8% for ABS/PC scraps. Within the diameter range of 8-13 mm, only 25% of PP and 27% of PP/EPDM scraps, as well as 43% of ABS, and 47% of ABS/PC scraps were finally separated. This research proposes a new approach for sensor-aided automatic recognition and sorting of black plastic materials, it is an effective method for ASR reduction and recycling. View Full-Text
Keywords: sensor-based sorting; impact acoustics; ELV recycling; automobile shredder residue sensor-based sorting; impact acoustics; ELV recycling; automobile shredder residue

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).

Share & Cite This Article

MDPI and ACS Style

Huang, J.; Tian, C.; Ren, J.; Bian, Z. Study on Impact Acoustic—Visual Sensor-Based Sorting of ELV Plastic Materials. Sensors 2017, 17, 1325.

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



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