Laseranalys av skrot/Laser analysis
Advanced scrap sorting based on Laser Induced Breakdown Spectroscopy (LIBS)
Project leader: Arne Bengtson, Swedish Institute for Metals Research
Introduction
With more precise scrap sorting based on chemical content, the recycling of scrap can be increased. With accurate identification and sorting of coating types, the pre-processing of scrap can be more energy efficient and environmentally safe. More accurate sorting based on chemical content (alloy type) will enable steel manufacturers to use higher alloy scrap in the metallurgical processes, without compromising the demands on precise alloy composition for high grade steels. Since this also leads to less use of primary metals in the process, the cost of producing high grade alloys can be decreased. If a higher percentage of steels are produced from scrap, the energy consumption will also decrease. This is beneficial for both the economy and the environment.
Goals
General
To develop the necessary know-how for building a prototype system for scrap sorting of steels based on Laser Induced Breakdown Spectroscopy (LIBS). Two types of sorting tasks will be included:
- Sorting based on surface coatings for further processing (stripping of the coating)
- Sorting based on bulk alloy type for more precise control of chemical content
Industrial
To deliver analysis parameters and to develop analysis software for a LIBS prototype system for sorting and analysis of steel scrap.
Environmental
To decrease the electricity consumption by 300 MWh/year and the consumption of raw material by 800 tons/year. The increase in yield in the metallurgical process thanks to extended analytical sorting of steel grades and Zn-coated scrap is however not accounted for in this estimation. (Estimated effect + 10 years from 2004, for Swedish steel- and scrap industry).
Work plan
The technology and know-how for rapid, efficient sorting of scrap based on chemical composition will be developed using a state-of-the-art LIBS system. This work involves several parts of the analytical process as well as "intelligent" data processing.
Task 1: Investigation and optimisation of the spectral selectivity
Key elements in a large number of steel grades, and surface coatings, will be investigated with the TRS system for optimisation of spectral selectivity. The investigations will be carried out both in air and with an argon stream over the sample surface. The impact of different laser pulse energies and spot sizes will also be investigated.
Task 2: Development of the optical collection system
A few alternative light collection systems will be designed. These systems will be tested under conditions simulating real-world conditions as closely as possible. This work will be an iterative process, with successive modifications of the optical system until the best compromise between robustness and sensitivity is obtained.
Task 3: Development of sample preparation by laser ablation
In this task, a selection of "typical" scrap with varying surface composition will be evaluated for the most efficient surface preparation using laser ablation. The work will in part be carried out in co-operation with other laboratories equipped with more powerful lasers than those available at Swerea KIMAB. Analytical results on laser prepared surfaces will be compared with conventional preparation (grinding, milling) on the same workpieces.
Task 4: Development of data processing based on computational intelligence (CI)
This task involves testing and evaluation of different CI systems for processing and quantifying the OES data from LIBS systems. This will again be an iterative process, where quantification algorithms or "strategies" are being developed. These strategies will critically depend on the demands on the system in terms of selectivity between alloys.
Deliverables for 2004-2008
The project will generate the necessary know-how for design of systems for rapid scrap sorting of steels with LIBS technology. This can be broken down as follows:• Know-how about how to optimise the OES signal acquisition from remote LIBS analysis of both different steel grades and coating types on scrap• Know-how necessary for employing laser ablation as a surface preparation technique when analysing scrap• Know-how necessary for the design of optimised light collection systems for remote LIBS analysis of steels• Software based on CI systems for efficient, accurate data processing of LIBS data in a remote-sensing scrap sorting system.
| R & D activities | Status |
Overall deliverable for 2006: | |
2.1 Construction of a system for focussing the OE signal in an optical fibre.
| A system for external analysis was constructed. It is based on an optical rail onto which is mounted a lens to focus the laser beam on the sample, a lens set-up for collection of the optical plasma and a sample holder.
|
2.2 Verification of the set-up.
| The lens set-up focuses the plasma light onto the optical fibre end, which leads the plasma light into the spectrometer. The element intensities are on the same level as in prior tests with LIBS analyses in internal mode. |
2.3 Different lens focal lengths and different distance to the object, and their influence on OE-signal.
| The signal level of plasma light collection is based on two things. I. The intensity follows the space angle, which declines with a 2nd order polynomial. II. The entire plasma must be imaged on the optical fibre end. If not, the signal will fade. This makes the system sensitive for lateral displacements. The farther the distance between plasma collection lens and the sample, the less the signal is influenced by lateral displacements, due to the reduced displacement in observation angle. |
2.4 Verify prior investigations of time windows and recording of OE-signal in air.
| The same behaviour of plasma extension and windows for time integration in prior tests as in recent external mode tests. The signal must be collected in a window of about 3‑7 µs after emission of a second laser pulse, when using a double pulse featured LIBS. |
2.5 Calibrations
| Several campaigns of calibrations, together with quantitative analysis of actual scrap pieces have been performed. |
2.6 Influence of incident angle of the laser beam on the sample surface, and the angle of observation on the OE-signal
| This has been extensively studied throughout the year. The quantification response of actual scrap pieces is relatively insensitive to the angle of the laser beam. However, the Angle of observation of the plasma is critical, and in particular, the image of the plasma on the tip of the end of the optical fibre is critical for the elemental signals. |
Deliverables for 2007
| R & D activities | Status |
| Development of sample preparation by laser ablation; | |
| 3.1 Investigation of conditions for robust OES-signal for bulk analysis of "dirty", Zn-coated, paint coated and wet surface, respectively.
| Lots of effort has been put in studying the analytical response of dirty and coated scrap pieces. The current laser unit at KIMAB needs 5-30 pulses in order to have a stable classification of the substrate material. However, classification of the coating itself is in most cases sufficient, since the vast majority of these pieces belong to the class of low alloyed steels. Fraunhofer institute (ILT) in Aachen has shown preliminary tests with using pre-ablation of dirty and coated scrap using very high energy laser pulses that ablate up to 150 µm in one pulse. |
| 3.2 Investigation of conditions for robust OES-signal for bulk analysis of surfaces with various topography. Preliminary tests show that this is not a concern in quantification of scrap pieces | Preliminary tests show that this is not a concern in quantification of scrap pieces
|
Deliverables for 2008
R & D activities | Status |
WP4. Development of data processing based on computational intelligence (CI)
|
|
| 4.1 Methodology for criterions of analysis and classification of materials in scrap sorting using CI. Most important elements and determination of intervals of composition. | Preliminary work started
|
| 4.2 Development of a system that sort coated materials from uncoated materials. | Preliminary work started |
| 4.3 Development of a system that sorts Al-based alloys, Cu-based alloys Fe-based alloys. | Not yet initialized
|
| 4.4 Development of a system that classifies categiries of steels with certain criterions and with known precision. | Preliminary work started |
| Final report of the project | Not yet initialized |
Fragmentering
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Miljövärderingsanalyser
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