Home » Detection and Differentiation of Sand Content in Hydraulic Transport using Acoustic Emission Technology

Detection and Differentiation of Sand Content in Hydraulic Transport using Acoustic Emission Technology

Deep-sea mining represents an opportunity for an alternative supply of high-tech raw materials. A concept for the extraction of polymetallic nodules from the seabed envisages the use of a harvester that extracts the nodules using a hydraulic principle. To design an effective and efficient mining process, the composition of the material flows must be continuously monitored. A promising technology for this task is the Acoustic Emission (AE) technology, which has already been successfully used for material flow characterisation of aggregates transported by belt conveyors. In the scientific investigations presented in this paper, AE technology was used to differentiate different sand contents of hydraulic material flows. Differentiation of the different sand contents using interval analysis of the AE signals was possible in a laboratory environment. These results provide a basis for further investigations of more complex material flows consisting of water, sediment and polymetallic nodules.

Authors/Autoren: Sunny Schoone M.Sc., Maximilian Getz M.Sc. and Univ.-Prof. Dr.-Ing. Elisabeth Clausen, Institute for Advanced Mining Technologies (AMT), RWTH Aachen, Aachen/Germany

1  Introduction

The demand for critical raw materials is increasing due to industrial and social developments. This increase in demand is supported by a more intensive need for raw materials used in energy transition and the electrification of the mobility industry. To secure a sufficient supply at an early stage, companies already form long-term contracts (ten to 20 years) with various mining companies (1, 2). This is complicated by the fact that the supply of selected metals, e. g., cobalt, depends on a very limited field of mining companies. These include Glencore, China Molybdenum and the Eurasian Resources Group. All of which are active in the Democratic Republic of Congo (DRC) (3). Access to new sources of raw materials could help to disrupt this market situation and meet demand on an alternative basis. In this context, deep-sea polymetallic deposits, and polymetallic nodules, in particular, -re-present an important option. (4)

The focus of this work is on the extraction of polymetallic nodules by deep-sea mining utilising a polymetallic nodule collector (harvester). To ensure the greatest possible process reliability and efficiency, all sub-processes within the polymetallic nodule collector are to be monitored by sensors. To achieve this goal, both input and output variables must be recorded. The continuous digital recording of the composition of the material flow is vital information for the successful determination of the valuable content for subsequent processing steps. Through the continuous sensor-based recording of the material flows in the harvester, the respective process steps – extraction, sediment separation, transfer to the vertical riser system – can be monitored and controlled by comparing target and actual values. In addition to increasing quality and performance, this continuous material flow analysis is an indispensable basic parameter for the targeted automation of the mining and sediment extraction processes. An increase in the performance of the entire mining process not only improves the efficiency of the process but also ensures a reduction in the occurrence of sediment plumes by separating the sediment as early as possible in the mining process. Thus, supporting compliance with environmental regulations for deep-sea mining. (5)

The Institute for Advanced Mining Technologies (AMT) at RWTH Aachen University considers Acoustic Emission (AE) technology to be a suitable sensor technology for monitoring hydraulic transport processes in the deep sea due to its robustness and miniaturisation. These material flows need to be monitored from the uptake of the polymetallic nodules, through pre-processing and then to the discharge of the harvester to avoid gangue material being transported to the mining vessel at the sea surface. (5)

AMT is one of the pioneers in the application of AE technology in harsh mining environments (6, 7, 8). This technology is a robust, non-destructive and passive sensor technology that has been successfully used in other material characterisation projects (8).

Since this technology incl. analysis, sensor application, integration into PLCs, etc. has not been used in deep-sea environments so far, the AMT is trying to investigate the applicability of this technology for material flow characterisation in hydraulic transport processes using different test series to define the possibilities and limits for the use of AE technology. At a later stage, the application of AE technology is intended to detect and characterise the material flow in its entirety. A basis for this is the elaboration of the different possible basic states of the individual components, water, different sediments and polymetallic nodules. Thus, in the first step, the influence of different load states of sediment, i. e. sand was investigated. The aim is to investigate the feasibility, possible limits and selectivity to differentiate between various loading conditions.

2  Notions of deep-sea mining

Approximately 73 % of the earth’s surface is covered by water. The fishing-, gas-, oil- and shipping industry make extensive use of the seas and the continental shelf regions (9). For the last 200 years a continuous increase in the need for waterways led to an increase in the economic utilization of the open water zone. While increasing demand for metals has resulted in rising interest in deep-sea mining. (4)

In the 1950s John L. Mero has researched deep-sea polymetallic nodules – also known as manganese nodules – as a potential commercial source for metals (10). The 1970s and 1980s saw a multitude of exploration and research activities for polymetallic nodules. Some of which were conducted in the Clarion-Clipperton-Zone (CCZ) (11). In terms of economic viability, the CCZ is the most promising area. The nodule abundance in the CCZ is about 15 kg/m2 on average (12). Other economically relevant deposits for manganese nodules are in the Peru Basin, the Penrhyn Basin and the Central Indian Basin (4, 13).

The first mining trials for manganese nodules go back to the years 1974 to 1979. Testing different methods for mining the nodules were a focus of these mining trials. Commercial mining of the nodules failed due to the collapse of world metal prices, technological advances in onshore exploration and mining, and the strict provisions of the United Nations Convention on the Law of the Sea (UNCLOS) (14, 15). The UNCLOS, which entered into force in 1994, is a multilateral treaty with 320 articles and regulates almost all areas of international maritime law (16).

Increasing metal prices due to technological advances led to a reoccurring interest in deep-sea mining in the 21st century (17, 18). To organise the management of the so-called Common Heritage of Humanity, the International Seabed Authority (ISA) was enacted in Jamaica. It has the task of regulating, organising and controlling deep-sea mining. It also develops resource-specific regulations, such as a mining code, and administers exploration licences (19, 20). Since 2001, 30 exploration licences have been issued by the ISA, 18 of which are for manganese nodules, seven for polymetallic sulphides and five for cobalt-rich iron and manganese crusts (21).

Apart from geopolitical and juristical questions, the technological feasibility of deep-sea mining is a topical issue. Figure 1 depicts a potential concept of a holistic system for the extraction of polymetallic nodules. For a simplified description, it is common to divide a deep-sea mining production system into three subsystems: mining support vessel, vertical riser and mining equipment. The latter being the focus of the upcoming elaboration. (22)

Fig. 1. Concept for deep-sea mining of polymetallic nodules (22). // Bild 1. Konzept einer Manganknollengewinnung (22).

The mining equipment is a harvester, whose nodule collector is based on a hydraulic principle. After the collection sediment separation is conducted and the material flow is guided toward the vertical riser system.

Due to the environmental conditions and requirements, extensive demands are placed on the implementation of such a harvester. Thus, the highest possible level of technology and automation is to be achieved to ensure a high level of process reliability. The Blue Harvesting project (project number: 18138 – EIT Raw Materials), which is based on the Horizon 2020 projects Blue Mining (grant agreement no. 604500) and Blue Nodules (grant agreement no. 688975), starts at this point. (23, 24, 25). This project aims at developing a mining and processing platform that can meet the demanding ecological, economical and technological requirements for the deep-sea mining of polymetallic nodules. More explicitly, the environmental impacts of polymetallic nodule mining are to be assessed and minimised. (25) One component of this project is the sensor-based characterisation of the material flows present in the harvester for efficient process control. AE technology will be utilized for this task.

3  Fundamentals

3.1  Principles of the hydraulic transport of solids

The suction of the harvester creates a multi-phase, dispersed material flow. The solid particles of the disperse phase are generally referred to as grains or particles, which can differ in important characteristics such as size, density or grain shape. (26, 27).

Since solids mostly have a polydisperse character and can be described, e. g., in their geometry in distribution functions and equivalent values, suspensions are not treated as homogeneous fluids in hydraulic conveying technology. Rather, suspensions can be regarded as heterogeneous mixtures of substances in which the interactions of the particles of the individual phases must considered. (28)

In practice, heterogeneous suspensions are predominantly conveyed in horizontal or inclined pipelines under turbulent flow conditions to prevent settling of the solid phase and thus clogging. For this purpose, it is important not to fall below the critical transport velocity. (28)

On the other hand, the balancing mechanisms of the liquid molecules act more intensively with increasing transport velocity, which leads to an intensification of the turbulence. An increased transport velocity also triggers an inherent rotation – also known as Magnus force – due to the incident flow of solid particles. This force acts transversely to the direction of flow and against gravity. Due to the greater proximity of the solid particles to the inner pipe wall, this phenomenon intensifies and creates a friction effect between the outer part of the flow and the inner pipe wall (Figure 2). (29)


Fig. 2. Forces acting on solid particles in a horizontal pipe flow according to (29). // Bild 2. Wirkende Kräfte auf Feststoffpartikel in einer horizontalen Rohrströmung nach (29).

Impact processes between particles or between particles and the inner pipe wall lead to the overcoming of gravity and act as a Magnus force or as turbulence. This phenomenon is enhanced by increasing the transport velocity. (29)

Pipe bends also influence turbulence and thus contact of solids with an inner pipe wall. These deflections cause centrifugal forces to act on the solid particles. As a result, the solid particles are very likely to be moved against the wall by the centrifugal force of the flow (Figure 3).

Fig. 3. Exemplary representation of the motion behaviour of solid matter in a pipe bend according to (31). // Bild 3. Beispielhafte Darstellung des Bewegungsverhaltens fester Materie in einem Rohrbogen in Anlehnung an (31).

When the solid particles hit the inner wall of the pipe, impact and friction processes occur again. The resulting forces move the solid particles back into the direction of flow. In the case of a forced deflection, the phenomenon is further intensified. (29, 30)

The interactions with the inner pipe wall resulting from the flow behaviour of disperse material flows can be used to determine the composition of the disperse material flow via the impact and friction effects.

3.2  Acoustic emission testing

AE is the phenomenon of transient elastic wave generation in materials due to rapid releases of strain energy and it is comparable to seismic phenomena. The standards DIN EN 13554 and DIN EN 1330-9 delimit this physical phenomenon to airborne and structure-borne sound. Most of the AE waves have frequencies in the range from 20 kHz to 2 MHz. According to (8) and (32), AE can be triggered by various physical effects such as friction, plastic deformation, erosion and many more. (8)

The transient elastic waves travel through a solid body and generate surface waves, which can be detected by an AE sensor. AE sensors utilise the piezoelectric effect and convert the wave energy into a transient electrical voltage signal. Such a signal is depicted in figure 4.

Fig. 4. AE signal sample. // Bild 4. AE-Rohsignal der Versuchsreihe. Source/Quelle: AMT

Signals shaped like this are called AE bursts. The conversion of the signals after the detection of the surface wave by the AE sensor and the subsequent algorithm-based processing of the signals form the basis for the signal-based analysis presented in the result section of this paper. (8)

3.3  Principles of the applied data analysis

The recorded AE signals of the material flow were analysed by applying interval analysis. The method for signal processing was successfully used in material flow characterisation on conveyor belts in land-based mining (8). Interval analysis as a method is described in the following paragraphs.

An interval analysis divides the AE signal into predefined windows (Figure 5).

Fig. 5. AE signal sample including interval analysis. // Bild 5. AE-Rohsignal mit Intervallanalyse. Source/Quelle: AMT

The windows isolate several data points, which are then used for calculating various statistical features. (8)

In this paper the Root-Mean-Square (RMS) of the beforehand described intervals was used as a statistical feature. The RMS originates from electrical engineering and describes the power of a periodic signal over a predefined interval. (8) Thus, analogous to the examples previously shown in the literature, the basic feasibility of distinguishing different loading conditions in a sand-laden hydraulic material flow shall be provided.

Before the analysis, the main hypothesis was that increasing sand loading in a hydraulic transport process would also increase the detected AE activity in the measured AE signals. Therefore, in this paper, the basic feasibility of detecting and distinguishing different contents of sand in a two-component material flow was investigated by analysing the calculated RMS curves.

4  Conducted experiments

4.1  Experimental setup

The test series was carried out on a test stand in the AMT’s test centre. The setup of the test stand is shown in figure 6.

Fig. 6. Drawing of the test setup according. // Bild 6. Zeichnung des Versuchsstands. Source/Quelle: AMT

An Auras P 40 ND A wastewater pump positioned in the centre of a 1,000 l rectangular tank pumps a mixture of water and sand in a closed circuit through a pipe system of PVC and iron pipes. The pump operates at a flow rate of 120 m3⁄h, which corresponds to roughly 33 l/s.

An AE sensor was attached to the 75° iron pipe bend (8). The deflection in the pipe system increases the turbulent flow because of the physical effects occurring there (cf. chapter 3.1). Due to the arrangement of the pipe sections, it can be assumed that the metallic pipe bend section represents a promising contact point between the components of the hydraulic material flow and the inner pipe wall. Due to the centrifugal forces and the inertia of the components transported in the material flow, the sample is in constant contact with the horizontal inner surface of the bend. Therefore, the AE sensor is attached to the outer surface of the bend with a magnetic mount to ensure a sufficient transmission path of the emissions to the sensor and thus a high-quality raw signal.

4.2  Experimental procedure

Table 1. Comparison of the dosed and the measured loading of the mass flow rate. // Tabelle 1. Gegenüberstellung der dosierten und der gemessenen Beladung des Massenstroms. Source/Quelle: AMT

The tests consisted of 15 sub-segments. In the first segment, clear water was pumped through the test stand. After this 15 min segment, 25 kg of quartz sand were added over 2 min. After 15 min, another 25 kg of sand were added. This process was repeated until a total mass of 300 kg of sand had been added to the tank. For two more segments, 50 kg were added. At a cumulative mass of 400 kg of sand filled in, the experiment was stopped. In each 15 min sub-segment, five samples of the material flow at the pipe outlet were taken. The weight and volume of each sample were measured to determine the mixture density and thus the sand content. The mixture density was determined by subtracting the density of water at a room temperature of 25 °C from the mixture density. Quartz sand was used as a test ingredient. It had an average particle size of 0.11 mm and a density of 2.65 g/cm3.

The AE signals were measured continuously throughout the experiments. The continuous signals were stored as Technical Data Management Streaming (TDMS) files at 1 min intervals to simplify data handling.

Due to the chosen scale of the experimental setup and the test series, deviations from an ideal experimental setup occurred. During the test, quartz sand settled in the tank. To obtain a real value of the mass flow composition, the pumped suspension was continuously subjected to a turbidity test. Table 1 compares the ideal target suspension with the actually achieved sand loading during the test.

4.3  Configuration of measurement system

In addition to the manual, discontinuous turbidity measurement, the AE technology was used as described in the experimental setup. For this purpose, the experimental setup was expanded to include an AE measuring point, which was attached to the pipeline system in the direct vicinity of the process (Figure 6).

The AE sensor was mounted with a magnetic holder centrally at the apex in the pipe plane. The application of the sensor also included the smoothing of the outer pipe wall and the use of a coupling agent (0.1 ml copper paste) to minimise interference.

All in all, the entire measurement system consisted of the aforementioned piezoelectric AE sensor (VS375-M), a preamplifier (AEP3N), a decoupling box (DCPL2) from Vallen Systeme GmbH and an analogue/digital converter (AD converter, NI 9775) from National Instruments. The measuring system was supplemented by a Dell Latitude laptop (Figure 7).

Fig. 7. Set up of the AE measurement system. // Bild 7. Aufbau der AE Messkette. Source/Quelle: AMT

For determining the signal characteristics, as described in chapter 3.2, an interval-based calculation depending on the defined sampling rate of fs = 1 MHz is conducted. The corresponding data acquisition with an interval width of N = 1,000,000 samples is considered a reasonable configuration for material flow characterisation.

5  Results

For the presentation of the results, a core state was cut out of the respective operating state and shown in comparison. The periods of material infill during which sand is added to the system were explicitly cut out. Figure 8 shows an excerpt from the entire result of the case study. The calculated RMS in volt is plotted against the test time in seconds. The results shown are extracts from the respective 15 min sub-segments of the test compositions. The trend of possible differentiation between different sand contents using AE technology can be confirmed.

Fig. 8. Comparison of the RMS curve of a one-component (water) and the RMS curve of all two-component ma-terial flows (water and sand). // Bild 8. Vergleich des RMS-Verlaufs eines Einkomponenten (Wasser)-Materialstroms und den RMS-Verläufen aller Zwei-Komponentenmaterialströme (Wasser und Sand). Source/Quelle: AMT

The RMS curve of an almost pure water mass flow compared to a two-component material flow loaded with 0.67 % sand can be distinguished from each other in terms of the RMS value. Also, not only a separation between a pure water flow and a multiphase flow of sand and water can be seen, but also the differences in the signal intensity increase continuously with increasing sand content. This is due to an increasing interaction between the sand particles and the inner pipe wall as the solids content increases.

From this result, the visual observation of the RMS curves alone can confirm the hypothesis posed at the beginning. In the following, the result shown in Figure 8 was supplemented by another investigation to validate the result. In Figure 9, the RMS values calculated by the interval analysis were assigned to the respective sand contents and shown as a boxplot. This representation not only shows the intensity of the AE signal, but also describes the distribution of the RMS values determined in each case.

Fig. 9. RMS curves displayed as boxplot. // Bild 9. RMS-Verläufe als Boxplot dargestellt. Source/Quelle: AMT

When looking at the results presented, it can be visually determined that the 15 different operating states can be distinguished from each other. The analysis of the boxplots also proves the main hypothesis.

However, in the area between a sand content of 1.45 and 1.85 %, slight overlaps of the results were observed. This can be seen in the graph in Figure 8 as well as in the boxplot in Figure 9.

An explanation for this slight overlap in the results can be explained by the presentation of the turbidity density test (Figure 10).

Fig. 10. Results of the turbidity measurement compared against theoretical sand content if no sedimentation of the sand in the tank occurs. // Bild 10. Trübedichte Untersuchung während der Versuchsdurchführung. Source/Quelle: AMT

One interpretation of this result is that there was inadequate mixing between the added sand and the carrier medium water, especially at the beginning of the test series. In the range of 100 kg (1.45 %) and 125 kg sand (1.85 %) added there was only a slight change of the sand content in the water. This leads to only a slight increase in AE activities and could explain the described problems in the differentiation of the two two-component material flows. The reason for the discrepancy between the added sand mass and the sand mass that is actually in the hydraulic circuit is the sedimentation in the tank.

6  Achieved succes

For the investigation of the feasibility of distinguishing different sand contents of a hydraulic mass flow, it was proven that a dispersed hydraulic mass flow with increasing sand content increases the intensity of generated AE activities. This assumption could be provided by performing interval analysis of AE signals.

Linking this back to deep sea mining indicates that applying AE technology for material flow characterisation is feasible for the given set-up. As a next step the material flows occurring during manganese nodule mining with a harvester will be in the focus of research. Successfully applying the AE technology to characterising these more complex multiphase flows will be the goal of the upcoming steps.



(1) Marscheider-Weidemann, F.; Langkau, S.; Hummen, T.; Erdmann, L.; Tercero Espinoza, L. A.; Angerer, G.; Marwede, M.; Benecke, S.: Rohstoffe für Zukunftstechnologien 2016. Deutsche Rohstoffagentur (DERA) in der Bundesanstalt für Geowissenschaften und Rohstoffe (BGR), Berlin, 2016, ISBN 978-3-9435-6672-7.

(2) Herzig, P.: Mineralische Rohstoffe aus der Tiefsee – Entstehung, Potential und Risiken. GEOMAR Helmholtz-Zentrum für Ozeanforschung, Kiel, 2019.

(3) Schütte, P.: Kobalt – Information zur Nachhaltigkeit. Bundesamt für Geowissenschaften und Rohstoffe, Hannover, 2020.

(4) Gelpke, N.; Visbeck, M.: World ocean review – Rohstoffe aus dem Meer – Chancen und Risiken. maribus gGmbH, Hamburg, 2014, ISBN 978-3-86648-220-3.

(5) BLUE NODULES. Deliverable report D3.7. Design report model for an Acoustic Emission System. Institute for Advanced -Mining Technologies, RWTH Aachen University, 2019.

(6) Nienhaus, K.; Wotruba, H.; Vraetz, T.; Baltes, R.; Boos, F. D.; Neubert, K.; Knapp, H.: Verfahren und Anordnung zur Analyse eines Stoffstroms. Patentveröffentlichungsnummer: PCT/DE2015/100504, 2015.

(7) Vraetz, T.; Boos, F. D.; Baltes, R.; Nienhaus, K.; Schropp, C.; Neubert, K.; Knapp, H.; Wotruba, H. (Hrsg.); Pretz, T. (Hrsg.): Material Stream Characterization with Acoustic Emission Technology. 7th Sensor-Based Sorting & Control 2016, Shaker Verlag, Aachen, 2016, ISBN 978–3–8440–4323–5.

(8) Vraetz, T.: Entwicklung und Anwendung eines innovativen Konzepts zur Inline-Charakterisierung von Stoffgemischen in kontinuierlichen Massenströmen mittels der Acoustic Emission Technologie. Dissertation, RWTH Aachen University, 2018, ISBN 978-9-41277-36-6.

(9) Gierloff-Emden, H.-G.: Geographie des Meeres – Ozeane und -Küsten. Walter de Gruyter, Berlin, 1980, ISBN 3-11-002124-2.

(10) Mero, J. L.: Ocean-floor manganese nodules. Economic -Geology, 1962.

(11) Parianos, J.; Lipton, I.; Nimmo, M.: NI 43-101 Technical Report TOML Clarion Clipperton Zone Project, Pacific Ocean. AMC Consultants Pty Ltd, Brisbane, 2016.

(12) Volkmann, S. E.; Lehnen, F.; Kukla, P. A.: Estimating the economics of a mining project on seafloor manganese nodules. Mineral Economics, Bd. 32, Nr. 3, S. 287 – 306, 2019.

(13) Baker, B.; Beaudoin, Y.: SPC, Deep Sea Minerals; Manganese Nodules, a physical, bio-logical, environmental, and technical review. Secretariat of the Pacific Community (SPC), 2013.

(14) Glasby, G. P.: Deep Seabed Mining: Past Failures and Future Prospects. Marine Georesources & Geotechnology, Bd. 20, Nr. 2, S. 161 – 176, 2002.

(15) Yamazaki, T.; Brockett, T.: History of Deep-Ocean Mining. Encyclopedia of Maritime and Offshore Engineering. J. Carlton, P. Jukes, and Y.-S. Choo Eds. Chichester: John Wiley & Sons Ltd, 2017.

(16) Auswärtiges Amt: Internationales Seerecht – Das Übereinkommen der Vereinten Nationen zum Seerecht, Bereiche des Seevölkerrechts. www.auswaertiges-amt.de/de/aussenpolitik/themen/internationalesrecht/einzelfragen/seerecht/internationales-seerecht/213318 (zuletzt geprüft am 22.12.2020).

(17) Exner, A.; Held, M.; Kummerer, K.: Kritische Metalle in der Großen Transformation. Springer Verlag, Berlin, 2016.

(18) Hein, J. R.; Mizell, K.; Koschinsky, A.; Conrad, T. A.: Deep-ocean mineral deposits as a source of critical metals for high- and green-technology applications: Comparison with land-based resources. Ore Geology Reviews, Bd. 51, S. 1  –  14, 2013.

(19) Jaeckel, A.; Gjerde, K. M.; Ardron, J. A.: Conserving the common heritage of humankind – Options for the deep-seabed mining regime. Marine Policy, Bd. 78, S. 150 – 157, 2017.

(20) ISA: Draft regulations on exploitation of mineral resources in the Area (ISBA/25/C/WP.1). International Seabed Authority, Kingston, 2019.

(21) ISA: Status of contracts for exploration and related matters, including information on the periodic review of the implementation of approved plans of work for exploration (Twenty-sixth session, no. ISBA/26/C/4), International Seabed Authority, Kingston, 2019.

(22) Grima, M.; van Gelder, R. A. C.; Heeren, J.; Verichev, S. N.; van Wijk, J. M.: Into the deep: a risk based approach for research to deepsea mining. CEDA Dredging Days 2011: Dredging and Beyond, 2011.

(23) Blue Mining: Homepage of Blue Mining; https://bluemining.eu, zuletzt geprüft am 22.04.2021.

(24) Blue Nodules: Homepage of Blue Nodules; https://blue-nodules.eu, zuletzt geprüft am 13.03.2020.

(25) Blue Harvesting: Homepage of Blue Harvesting; https://blueharvesting-project.eu, zuletzt geprüft am 22.04.2021.

(26) Müller, W.: Mechanische Verfahrenstechnik und ihre -Gesetzmäßigkeiten. Oldenbourg Wissenschatfsverlag, 2014.

(27) Fristam Pumpen KG (GmbH & Co.), www.fristam.de, zuletzt geprüft am 14.10.2020.

(28) Surek, D.; Stempin, S.: Angewandte Strömungsmechanik für Praxis und Studium. Vieweg+Teubner Verlag, 2007.

(29) Buhrke, H.; Kecke, H. J.; Richter, H.: Strömungsförderer: -hydraulischer und pneumatischer Transport in Rohrleitungen. Vieweg+Teubner Verlag, 1989.

(30) Cai, B.: Untersuchung zum Einfluss der Partikelgrößenverteilung und Partikelform auf den Druckverlust bei horizontaler Fluid-Feststoff-Rohrströmung. VDI-Verlag GmbH, Düsseldorf, 1992.

(31) Forkert Technology Services GmbH: Präsentation Strömungsoptimierung, www.forkert-t-s.com, zuletzt geprüft am 15.07.2017.

(32) Berg, J.: Entwicklung und prototypischer Einsatz eines Infrarotkamerasystems für Automatisierungslösungen im Rohstoffsektor. Dissertation, RWTH Aachen University, 2017, ISBN 978-3-941277-29-8.

Authors/Autoren: Sunny Schoone M.Sc., Maximilian Getz M.Sc. and Univ.-Prof. Dr.-Ing. Elisabeth Clausen, Institute for Advanced Mining Technologies (AMT), RWTH Aachen, Aachen/Germany