Near infrared hyperspectral imagery for waste recycling...

www.evk.biz © EVK DI Kerschhaggl GmbH 2014

Matthias Kerschhaggl ISFR 2015, 08/09/15

Near infrared hyperspectral imagery for waste recycling and real-time quantitative

inline analysis of raw materials

EVK Introduction

We at EVK believe that we can contribute to increasing reuse & recovery of earth resources and to improve working conditions in

waste recovery

www.evk.biz © EVK DI Kerschhaggl GmbH 2014 matthias.kerschhaggl@evk.biz

Who we are

♦ Smart sensing solutions since 1987

♦ 2006: First HSI camera & classification system introduced to market

♦ Real-time classification and sorting

♦ Industry proven in recycling, mining, food processing and pharmaceutical applications

What We Do

♦Simple start From pixel to sorting

♦Imaging & Sorting system with high speed, high resolution and control of ejection unit

♦Software package adapts the system to specific application

5 ©EVK DI Kerschhaggl GmbH 2015

Applications

Metals from slag Household waste

C&D Recovered Paper Wood Sorting

Potato Sorting & Grading

E-Scrap

Nut Sorting

Technical Background Material Identification with HSI

stretching bending rocking

twisting wagging stretching

Absorption spectra according to the molecular composition

C-O-H-N Compounds (e.g. C10H8O4)

HELIOS – Spectral Ranges

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Hyperspectral Imaging Technology

Camera internal classification and RGB visualization of chemical differences for real-time analysis

Plastic Sorting

PE PET PS

Fingerprint: NIR absorption bands due to functional groups (CH,NH,OH) translate into different spectral signatures.

Plastic Sorting

Principal Component Analysis

Partial Least Squares

Chemical Color Imaging: MVDA-projection of HSI data into RGB space

Plastic Sorting

Principal Components

Principal Component Analysis

Partial Least Squares

wavelength wavelength

Recycling

paper cardboard

Mineral Sorting

Calcite CaCO3 vs. Dolomite CaMg(CO3)2

HSI – Quantitative Analysis

wellness.byu.edu

Fig 2: PLS schematics (Wold et al. 2001)

Fernadez-Novales et al. (2009)

X Y Predictors (spectra)

Observations (reference analysis)

Copper Ores Quantitatively

~600 nm bandpass ~130 nm bandpass @ max correlation

Copper Ores Quantitatively

~600 nm bandpass

~130 nm bandpass @ max correlation

Full Range ROI

R2 0.4 0.9

RMSECV [%] 0.2 0.1

Pharmaceutical Engineering

Pharmaceuticals

(left) First derivative normalized spectra of acetylsalicylic acid (red) and paracetamol (green) and (right) paracetamol blister (red) as well as spectra taken from the acetylsalicylic acid package as recorded with the HELIOS hyperspectral imaging camera.

Pharmaceuticals

Pharmaceuticals Quantitatively

R^2=0.98 RMSEC = 1.2 mg/cm2

36 matthias.kerschhaggl@evk.biz

R^2=0.98 RMSEC = 1.2 mg/cm2

mg/cm2

matthias.kerschhaggl@evk.biz

Food Food sorting – Blueberries and stems

Food sorting – Noodles and worms

Inline Dry Matter Measurements

• Dry matter content traced by spectral signatures

• Inferred FIR-filter kernel

allows for concentration prediction

Inline Dry Matter Measurements

HELIOS Camera

R = 0.9 RMS = 1 %

Dry Matter Food Analyzer

• Integrated in sorting machine (INSORT Observer Food Analyzer)

• Valdidated model (R^2=0.9, RMS=5 %)

Dry Matter

Dry Matter Statistics

• DM „heat map“ • DM value histogramm • Mean DM • Standard Deviation of

product DM

Dry Matter Food Analyzer

Validation run of the dry matter measurement using HELIOS with respect to gravimetric reference methods (CEM, HB43).

Accuracy vs. Precision

matthias.kerschhaggl@evk.biz 47

Plots taken from http://en.wikipedia.org

higher precision

higher accuracy

Laboratory precision completed with inline inspection of entire

production stream

Precision vs. Accuracy

• The intrinsic variance of the product is greater than the precision of the lab reference, so better have full sampling rather than super precision!

• „Better you measure all the fries all the time with reasonable precision rather than 1 out of 100.000 with ultra-high precision!“

• It is about large scale trends in the whole product stream not about laboratory measurements of unrepresentatively small quantities!

• A RMS of e.g. 1 % for constant monitoring of the product throughout the entire input stream is already way better than what you can do with a precision of 0.1 % every 30 min on a spatially confined sample!

Courtesy W. Märzinger

Quantitative Analysis: Prospects for Recycling of Polymeric Materials

• enable also quantitative measurements of scanned organic material flows (e.g. moisture content, woodchips vs contaminants, deinking vs non-deink vs paperless etc).

• in-line characterization of organic bulk material streams: - moisture and chlorine content - calorific value for waste to energy processing - sugar content in biodegradable MSW for subsequent bio-based chemical production.

International FoodTec Award

DLG (Deutsche Landwirtschafts-Gesellschaft

/ German Agricultural Society)

Conclusions

♦Hyperspectral Imaging is an already well established technology for sorting solutions in the recycling, mining and food industries.

♦The inferred spectral information is suitable for doing quantitative analysis in various applications.

♦The potential to bring the laboratory into the line with unprecedented statistical power is enormous.

Acknowledgements

M. Jeindl

W. Märzinger

E. Leitner

S. Sacher

Some References

Near infrared hyperspectral imagery for waste recycling...

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