当前位置: X-MOL 学术Waste Manag. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A low-cost LIBS detection system combined with chemometrics for rapid identification of plastic waste.
Waste Management ( IF 8.1 ) Pub Date : 2020-08-14 , DOI: 10.1016/j.wasman.2020.07.046
Rajendhar Junjuri 1 , Manoj Kumar Gundawar 1
Affiliation  

We present, rapid and efficient identification of ten different types of post-consumer plastics obtained from a local recycling unit by deploying a low cost, compact CCD spectrometer in laser-induced breakdown spectroscopy (LIBS) technique. For this investigation, spectral emissions were collected by an Echelle spectrograph equipped with an intensified charge-coupled device (ES-ICCD) as well as a non-gated Czerny Turner CCD spectrometer (NCT-CCD). The performance is evaluated by interrogating the samples in a single-shot as well as accumulation mode (ten consecutive laser shots). The results from principal component analysis (PCA) have shown excellent discrimination. Further, the artificial neural network (ANN) analysis has demonstrated that individual identification accuracies/rates up to ~99 % can be achieved. The data acquired with ES-ICCD in the accumulation of ten shots have shown average identification accuracies ~97 %. Nevertheless, similar performance is achieved with the NCT-CCD spectrometer even in a single shot acquisition which reduces the overall analysis time by a factor of ~15 times compared to the ES-ICCD. Furthermore, the detector/collection system size, weight, and cost also can be reduced by ~10 times by employing a NCT-CCD spectrometer. The results have the potential in realizing a compact and low-cost LIBS system for the rapid identification of plastics with higher accuracies for the real-time application.



中文翻译:

低成本的LIBS检测系统与化学计量学相结合,可快速识别塑料废料。

我们目前通过在激光诱导击穿光谱(LIBS)技术中部署低成本,紧凑型CCD光谱仪,快速有效地识别从本地回收单位获得的十种不同类型的消费后塑料。为了进行这项研究,通过配备增强型电荷耦合器件(ES-ICCD)的Echelle光谱仪和非门控的Czerny Turner CCD光谱仪(NCT-CCD)收集光谱发射。通过以单次以及累积模式(十次连续激光射击)询问样品来评估性能。主成分分析(PCA)的结果显示出出色的判别力。此外,人工神经网络(ANN)分析表明,可以实现高达〜99%的个体识别准确率。用ES-ICCD采集的十张照片中的数据显示平均识别精度约为97%。尽管如此,即使在单次采集中,使用NCT-CCD光谱仪也能达到类似的性能,与ES-ICCD相比,它可以将整体分析时间减少约15倍。此外,通过使用NCT-CCD光谱仪,检测器/收集系统的尺寸,重量和成本也可减少约10倍。该结果具有实现紧凑,低成本的LIBS系统的潜力,该系统可用于实时应用中以更高的精度快速识别塑料。即使在单次采集中,NCT-CCD光谱仪也能达到类似的性能,与ES-ICCD相比,可将整体分析时间缩短约15倍。此外,通过使用NCT-CCD光谱仪,检测器/收集系统的尺寸,重量和成本也可减少约10倍。该结果具有实现紧凑,低成本的LIBS系统的潜力,该系统可用于实时应用中以更高的精度快速识别塑料。即使在单次采集中,使用NCT-CCD光谱仪也能达到类似的性能,与ES-ICCD相比,可将整体分析时间缩短约15倍。此外,通过使用NCT-CCD光谱仪,检测器/收集系统的尺寸,重量和成本也可减少约10倍。该结果具有实现紧凑,低成本的LIBS系统的潜力,该系统可用于实时应用中以更高的精度快速识别塑料。

更新日期:2020-08-14
down
wechat
bug