Ultrasound For Monitoring And Quality Inspection In MDS Plastics Recycling

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1 CONTACT Contact name: Seyed Ali Sanaee Organisation: CITG, Recycling Engineering, Delft University of Technology Postal address: PO Box 5048, 2600GA Delft, The Netherlands Telephone: Facsimile: Ultrasound For Monitoring And Quality Inspection In MDS Plastics Recycling Seyed Ali Sanaee, Recycling Eng. CITG, Delft University of Technology Maarten Bakker, Recycling Eng. CITG, Delft University of Technology EXECUTIVE SUMMARY The magnetic density separator (MDS) is currently under development at Delft University for the purpose of separating plastics from shredders and household waste. In MDS, a suspension of water and ferrous nano-particles act as the separating medium. By applying a strong magnetic field from the top, the ferro-fluid effectively causes a gradient in mass density ranging from low at the top (<0.85 gcm -3 ) to the normal density of water at the bottom. Plastic particles are inserted on one end into a channel of flowing magnetised ferro-fluid. After insertion the particles will separate and reach equilibrium at the depth where their mass density complies locally with that of the fluid and can then be easily separated at the other end of the channel. To optimise and monitor the MDS process and performance the particles must be observed and studied under operational conditions. Moreover, if different types of plastic may have the same mass density they will end up in the same fraction. The observation point requires some kind of vision system, and the possible mix-up of different plastics requires quality inspection. However, since the ferro-liquid is completely black, both visible and infrared camera systems are rendered useless for either purpose. Therefore ultrasound sensors are proposed to meet both challenges. For the monitoring part a commercial 2D medical imaging system is tested for its capabilities to observe objects and moving particles inside a ferro-fluid. It is shown that the medical system has potential for monitoring the separation process of waste plastic particles in an MDS. Also, the medical system was fast enough (25 images per second) as to allow real-time viewing inside a ferro-fuid flow with particle speeds up to 30 cm/s. The imaging quality was such that even quantitative through-put analysis (waste mass or volume) may be realised. To study the potential of ultrasound for materials identification the acoustic parameters of a selection of plastic samples was measured through experiments and 3D acoustic modelling of wave generation and propagation in attenuating media. It proves that different types of plastic may be quite distinctive and will allow materials characterization for purposes of quality inspection in an MDS. However, the method of data scanning which makes medical imaging so successful appears not to be optimal for materials characterisation. Therefore, another data scanning method was investigated using experiments and computer simulations. Ultrasound as a technique proves to have great potential for quality inspection. This potential can be realised if the method of data scanning is changed from reflection-oriented, like in medical imaging, to more transmissionoriented. For example the varying offset scan demonstrated in this paper appears quite suitable. In that case the acoustically distinctive material properties of the different plastics become amenable

2 for detection. Future research will involve data scans on shredder residue particles. These will be complemented with 3D acoustic simulations of small particle wave scattering phenomena to investigate all the aspects of ultrasound that are relevant for quality inspection in an MDS machine. INTRODUCTION The European consumption of virgin plastic materials has increased from 24.6 Mton in 1993 to 39.7 Mton in Over a third of these plastics are polyolefins that are quite suitable for recycling. More economic value and wider application could be achieved from these materials when they can be separated into their pure forms. For this purpose the magnetic density separator (MDS) is currently being developed for plastics from car shredders and household waste [W2Plastics, 2008]. In MDS, a suspension of water and ferrous nano-particles act as the separating medium. By applying a strong magnetic field from the top, the ferro-fluid effectively causes a gradient in mass density ranging from low at the top (<0.85 gcm -3 ) to the normal density of water at the bottom [Bakker, E.J. et al., 2009]. Plastic particles are inserted on one end into a channel of flowing magnetised ferro-fluid. After insertion the particles will separate and reach equilibrium at the depth where their mass density complies locally with that of the fluid, after which they can be easily separated at the other end of the channel. To optimise and monitor the MDS process and performance the particles must be observed and studied under operational conditions. However, visual and infrared observation is impossible because the ferro-fluid is opaque. Therefore, ultrasound is proposed instead. For economical MDS operation the flow speed must be at least 30 cm/s, which presents a challenge for the speed of an on-line ultrasound system to visualize the particles in flow. Since medical systems are well established technology they are investigated for their suitability for industrial MDS process monitoring. In view of the lower speed and considerably higher costs of 3D and 4D imaging systems, a choice was made to run trial tests with a state-of-the-art commercial 2D system that could acquire 25 images per second. These tests aimed at the shape consistency, clearness and sharpness of imaged objects inside a ferro-fluid under both static conditions and with moving particles. Besides vision also quality inspection is of interest, the more since different plastics like PP and LDPE have practically the same mass density and may end up in the same separated fraction. For quality inspection the plastic material of the particles must be determined while they are still inside the flow. Firstly it is investigated if the acoustic properties are distinctive enough to allow materials identification. To that end the acoustic wave speed of various plastics is measured in a special set-up, while the acoustic material attenuation is evaluated as a relaxation time with a 3D model for acoustic wave propagation. Having established that plastic acoustic properties are distinctive, an experimental and computer modelling study is carried out to assess the potential sensitivity of ultrasound quality inspection. Especially the method of data scanning proves vital, and a strong indication is obtained that the standard scanning method used by medical ultrasound systems is not optimal for materials identification. ULTRASOUND IMAGING In ultrasound imaging, pulsed waves were sent from the transmitting sensor through the medium in a more or less straight beam. This beam is typically a few degrees wide in the length direction of the array, but in the orthogonal direction it is more restricted and produces the typical 2D sensitivity. Dependent on the angle of scanning this may give pictures that can be suggestive of cross-sections or slices like those produced in a medical MRI or CT scan, but they can also be quite detailed in surface features. When the waves encounter a surface or boundary between different materials they reflect or scatter due to the surface roughness. Some of these wave return to the sensor (now acting as a receiver) where the signals are logged as a function of arrival time. By processing these data the reflecting and scattering boundaries can be reconstructed at the correct distance from the sensor

3 to give a 2D picture of the interior of the medium at hand [Dowsett, David J. et al., 2006]. A linear array of many small piezoelectric sensors is used that are activated in sequence to allow for a suitable width of the reconstructed image. Ultrasound medical imaging is well established and potentially fast, but in this section its potential for monitoring the separation process of plastic particles in an industrial type of MDS is investigated. Potential of medical imaging technology The medical imaging algorithms are designed for waves in human tissues, which acoustic properties are close to that of water. Plastics are generally more reflective and more attenuating, and then there is also the question if the technique will actually work as well in a ferro-fluid. Figure 1 shows the experimental set-up for capturing ultrasonic images of moving particles in ferro-fluid. Three particles of different shapes and materials from car shredder residue are attached to a thin string that is wrapped over two wooden rolls. By rotating one roll from above the fluid the motion of particles in a MDS is approximated. The three particles are mm long, 5-10 mm wide and 2 mm thick. The tests were carried out in a tank filled with ferro-fluid using a commercial ultrasonic sensor array and imaging system. The linear array had 35 mm aperture with 128 elements and was excited by the system with pulses in the bandwidth of 3-11 MHz. The medical imaging system presented images in a range of 15 cm from the sensor array. Figure 2 shows ultrasonic images captured of the triangular plastic particle, on the left in Figure 1, under both static conditions and when the particle moved at 30 cm/s. The latter is the operational flow speed of the prototype MDS. In both cases the shape of the particle is recognizable, clear, and quite sharp. The capability of the medical system for detecting small details from surface scattering in real-time is also clear from the thin string to which the particle was attached. Figure 1: Experimental set-up for simulation of moving particles in ferro-fluid. The potentially good shape consistency and sharpness of ultrasound imaging is demonstrated more stunningly in Figure 3 using a M13 bolt and screw thread that present easily identifiable objects. The left panel shows the ultrasound image when the entire bottom of the bolt (no thread here) is irradiated from the left, which requires that the object is at a slight angle to the wave beam. This picture could easily be mistaken for a frontal view. The right panel in Figure 3 shows a cross

4 section of the top of the bolt, also for left-side irradiation and under a slight angle. Here the long screw thread causes a shadow, which is visible as a blur to the right side of the thread. Figure 2: Images of a small particle in ferro-fluid. Left panel: static. Right panel: moving at 30 cm/s. Figure 3: Metal screw thread with bolt, irradiated from the left side by ultrasound. Left panel: Bolt bottom. Right panel: Bolt top and thread with a shadowing effect. Figure 4: From top to bottom three ultrasound cross-section images of a plastic object, shown on the left side. The thick lines in the photos indicate the plane in which the wave beam was applied. The 2D character of the ultrasound beam suggests that the ultrasound images may be interpreted as cross-section views from which the volumetric shape of an object, such as a particle in a MDS, could be reconstructed using interpolating or morphing techniques. This possibility is strongly suggested by the images in Figure 4 that show three cross-section views of a plastic flat plate (2 mm thick) with a few distinctive features.

5 PLASTICS CHARACTERIZATION There are about polymer variants that could be present in waste. However, shredders and household waste mainly contain polypropylene (PP) and variants of polyethylene (PE), which form the most important group for MDS processing. Specific types are low and high density polyethylene (LDPE, HDPE), linear low density polyethylene (LLDPE) and Ultra-high molecular weight polyethylene (UHMWPE). The mass densities of these materials can be quite close or even identical and make it difficult or even impossible to separate them, even with MDS. On-line quality inspection could detect these occurrences, which requires a reliable technique for materials identification. The acoustic properties may hold a key to identification and their distinctiveness were subjected to the following experimental and theoretical investigation. Experimental set-up Figure 5 shows the experimental set-up used for plastics characterization. Plastic plates were immersed in this small water basin and subjected to a transmission measurement. The transducers operated with pulses of 5MHz centre frequency and 80% bandwidth. Plastic plate Receiver Transmitter Water 15 cm Figure 5: Sketch of the experimental set-up for plastics characterization. The plastic wave speed is calculated from the difference in travel time T between a calibration in a reference medium (water) and the plastic sample transmission measurement. R V 1/(1/ V - T / d) (1) V R is the wave speed of the reference medium and d the thickness of the plastic sample. Acoustic material attenuation Due to the fact that waves are transmitted at a straight angle, shear waves inside the plastics play no role of importance. The acoustic propagation in these material measurements may therefore be investigated using a fluid model. The material attenuation is modelled by a first-order relaxation process that is introduced in a convolution-type constitutive acoustic equation. ( t ) p( ) d u (2) p is pressure, u is displacement, and is the compressibility of the plastic. k0 () t () t H()exp( t t/ ) (3) 2 () t and Ht () are distributed functions known as the Dirac function and Heaviside step function, respectively. is relaxation time. A longer relaxation time complies with stronger attenuation due to energy absorption. Using a 3D model for wave propagation in layered attenuating media and transducer diffraction, the attenuation was modelled and matched to the wave speeds and signals measured with the set-up of Fig. 5. Table 1 presents the parameters for various plastic samples with also the mass densities that were measured with a Pico meter.

6 Distinguishing different types of plastic To help identification of plastics the wave speed may be plotted against mass density. Moreover, it proves that the product of physical material stiffness and relaxation time is another possibility that may be more selective to the plastic type. This is based on the phenomenological inverse relation between the two; i.e. if the stiffness of a certain material is decreased by some process than the acoustic attenuation usually increases, and vice versa. The relevant parameter will be referred to as specific stiffness and is denoted as S. 2 S V (4) is mass density, V wave speed and relaxation time. Note that the first two terms on the righthand side in Eq.(4) indeed present a material stiffness. The specific stiffness and wave speed are plotted against mass density in Figs. 6 and 7. The figures show the tendency of the plastic types to form more or less isolated groups in the -S and/or the -V plane. Polypropylene (PP) tends to have the highest specific stiffness and in that respect it differs from low density polyethylene (LDPE), even though they have practically the same mass density. This is of interest since the mechanism of separation in MDS is based on mass density and therefore separation of plastics with the same mass density is impossible. However, from the difference in acoustic behaviour, plastic identification and quality inspection seems quite feasible. Also the reverse case may happen. From Fig.7 it proves that different plastics can have the same wave speed. However, if the mass densities are different there is also no problem with identification in the operational MDS situation, because the plastics will float at different depths and will be distinctive through that aspect. Table 1: Acoustic properties of selected plastic samples sample material density [kgm -3 ] wave speed [ms -1 ] impedance [MRayl] relaxation time [ns] [db/cm] PP PP PP PE PE LDPE LDPE , LLDPE LLDPE UHMWPE UHMWPE ULTRASOUND QUALITY INSPECTION In the previous sections it is shown that medical imaging systems can be used to observe particles in a ferro-fluid and that the plastic acoustic properties are distinctive. Here the sensitivity of ultrasound for the material is investigated to determine which methods of data scanning could be optimal for a MDS. This is directly related to the capabilities of ultrasound towards quality inspection. The method of scanning for ultrasound data is a key factor since it determines whether there is sufficient information in the data set to carry out identification. In medical imaging sequential scanning is employed with a linear array by which the active sensor changes from one position to the neighbouring one. This proves to give optimum surface information to successfully perform imaging. However, besides a slight difference in reflection factor it seems apparent that the material properties do not really come into play, since most imaging measurements seem aimed at surface scattering. It is expected that material properties only play a dominant role when the acoustic waves penetrate and propagate, or reverberate, inside the particle. Such an emphasis on the interior of a reflecting object would reduce the performance of medical imaging, but may hold the key to materials identification. Besides the wave speed also the particle thickness is of course unknown

7 (except if imaging is used in conjunction). The thickness divided by wave speed gives the travel time (or phase delay) that plays an important role in materials identification. A scanning method is required that offers the possibility of determining both parameters simultaneously, regardless of the actual thickness. Figure 6: Specific stiffness versus mass density to characterise different plastics. Figure 7: Acoustic wave speed versus mass density to characterise different plastics.

8 Experimental set-up The experimental set-up is illustrated in Fig.8. Two small plastic plates of PP and PE were fully immersed in a water tank. A linear array was used (not the medical imaging system) with 128 sensor elements (0.27x5.0 mm), resulting in a scan aperture of 35 mm. Transmitter Element Receiver Element Plastic plate Figure 8: Set-up for varying offset scanning on a plastic plate The excitation was a 5 cycle bursts at 5 MHz from an Agilent function generator that was subsequently amplified by a linear power amplifier to enhance the signal-to-noise ratio. Data acquisition was done using an 80 MHz ADC. For the varying offset scan the transmitter element is kept fixed and the transmitter-receiver offset is increased from one sensor element to the next to form a dataset with 127 measurements. (a) Water (b) (c) Figure 9: Varying offset scans for (a) PP data, (b) PE data, and (c) simulation for PE. Figures 9a and 9b show the scans made for a PP sample (6.0 mm thick) and a PE sample (4.1 mm thick), respectively. From the data the difference in arrival time and especially the difference in

9 amplitude are clearly visible. Especially the last arriving signal gives distinctive information, which signal is caused by waves that emanated from within the plastic. This last signal is different between Figures 9a and 9b in its arrival time relative to the first arrival (which are waves directly reflected from the upper surface), the amplitude distribution, and the transmitter-receiver offset at which the first and last arrivals start to overlap. In Figure 9c a 3D computer simulation is shown for the PE plastic sample from Figure 9b. For this simulation a fluid model is used that apparently accounts for practically all of the features from which materials identification may be done. At close examination, a small head wave contribution (an elastic wave type) may be observed in Figs. 9a and 9b, but its energy seems negligible. Building further on the fluid model it is investigated if the difference in sample thickness in Figures 9a and 9b played an important role. Therefore, in Figures 10a and 10b simulations are shown for PP and PE, respectively, but here the through-thickness travel time (thickness/wave speed) is the same in both simulations. The (relative) arrival time of the last signal is now of course the same in both figures. However, the last arrival signal does again show distinct differences in the amplitude distribution and the transmitter-receiver offset at which the first and last arrivals start to overlap. (a) (b) CONCLUSIONS Figure 10: Comparison of varying offset scans with the same through-thickness travel time (a) PE and (b) PP. The commercial medical imaging system has potential for monitoring of the separation process of waste plastic particles in an MDS. The medical system was also fast enough as to allow real-time viewing inside a ferro-fuid flow with particle (or flow) speeds up to 30 cm/s. The imaging quality was such that quantitative through-put analysis (waste mass or waste volume) may also be realised. The capability of medical imaging systems for materials identification (quality inspection) seems too low to be considered. However, ultrasound as a technique does have great potential for quality inspection. This potential can be realised if the method of data scanning is changed from reflectionoriented to more transmission-oriented, for example the varying offset scan demonstrated in this paper. In that case the acoustically distinctive material properties of the different plastics become amenable for detection.

10 ACKNOWLEDGEMENTS This research was funded by the European Union under the FP7 grant for W2Plastics. The authors also gratefully acknowledge Ruud thoen and Christian Prins of Oldelft, The Netherlands, for making available the medical imaging system used in this research. REFERENCES Bakker, E.J., Rem, P.C., & Fraunholcz, N. (2009): Upgrading mixed polyolefin waste with magnetic density separation. Waste Managements 29, pp Dowsett, David J., Kenny, Patrick A., & Johnston, R. Eugene. (2006). The Physics of Diagnostic Imaging, Hodder Arnold, London. W2Plastics, 2008: