CZ201350A3 - Validation vertical screw conveyor and method of modeling mechanical processes - Google Patents

Abstract

The conveyor consists of a drive to which a screw mounted in the housing is attached and provided at the bottom with a material inlet and a material outlet at the top and positioned on the support part (9), the conveyor housing (1) being transparent and two-way in the conveyor (1) a control unit (16) is connected through which the conveyor (1) is bi-directionally connected to the evaluation device (17), the drive (5) being provided with at least one speed sensor (8) and / or at least one torque sensor (11), at least one high-speed camera (13) is provided at the conveyor (1) and at least one weighing sensor (10) is provided at the support part (9) and at the inlet (2) at the conveyor (1) and at the outlet (at least). 3) of the material connected to each other by means of a circulation connection (14), which is provided with at least one tomographic sensor (15) or a material input (2) connected to the input one The container (18) and the material outlet (3) are connected to the outlet container (19), where the inlet container (18) and / or the outlet container (19) are provided with at least one weight sensor (10). The method of modeling mechanical processes consists in first performing steps with the calibration standard and then with at least one validated material: feeding the conveyor (1) with the inlet (2), moving the auger (4) up to the outlet (3) into the circulation connection (14) or into the outlet container (19), during which the values of the mechanical-physical quantities are measured by means of a sensor / sensors (8, 10, 11 and / or 15) and subsequently processed by an evaluation device (17) by a high-speed The camera (13) senses the movement of the material and creates a fast map vector

Description

VALIDATION VERTICAL Worm CONVEYOR AND MODELING MODE

MECHANICAL PROCESSES ^ JOHOH * SHIP

Technical field

The invention relates to the determination of the influence of the properties of bulk materials on the transport functionality. It solves the execution of control and simulation experiments, in particular the simulation of the conveying process on a vertical screw, simulation of flow and velocity fields, interactions between structural elements and transported materials having an impact on the conveyance of screw conveyors.

State of the art

Design of transport equipment is realized in practice based on knowledge of input parameters. New equipment should be designed with regard to the properties of the transported materials. A key parameter entering such a system is the knowledge of the mechanical-physical properties of the bulk materials being transported. On the basis of measurement and finding of these properties it is possible to perform calibration and verification of behavior of models of these masses by means of computer technology. All applications, whether of a particular type of conveyor or container, require their specific approaches. They also bring new necessary procedures in the design of both transport systems and the way of their optimization and development.

It is known that when creating a new type of device for conveying bulk (particulate) materials, it is necessary to perform real tests of the functionality of the device. If the type of device is unconventional, the output parameters are usually in the range of estimates or ranges of empirical values. Based on the first real tests on the prototype, the transport process can only be optimized by adjusting the design, by changing the values of the input parameters of the drive, or by adjusting the properties of the transported bulk material. For example, by varying the speed of the screw conveyor drive, the vertical conveyance of the material can be accelerated, but in economic terms, this drive consumes more energy and increases the noise and wear of the functional parts of the device. At present, standards are generally based, but these standards do not cover all possible conditions that may occur in the field of bulk materials transport on unconventional conveyors. Modifications of an already existing engineering work in the process of use and in its required activity are undesirable in terms of shutdown of the transport system of which the equipment is part. In the field of vertical and inclined conveying by a screw conveyor, the influence of the shape of the transported material particles on the transport process is not completely specified. The solution to this problem in the post production process of the device is not optimal in terms of its existence. The problem is partially solved by a mathematical model of particle motion on the worm, but does not cover all possible situations that may arise. Only a global view and the individual solved partial measures combined can give an objective picture to solve a particular problem of the conveying process on the screw conveyor. The very principle of particle acceleration during transport by screw is influenced by the following design solution at the inlet and outlet. Individual adjustment of the device to meet the expected parameters without previous objective prediction and finding of specific influencing parameters is not suitable from the point of view of possible further wider use of the device.

Worm conveyors are often used in practice for the transport of bulk (particulate) materials. Since these materials are diverse and their consistency, shape, moisture, etc. cannot be accurately predicted in advance, these products are problematic for both transport and storage.

In many cases, the new particulate matter is worrying because already designed conveyor lines are not adapted to this type of raw material and, when passing through a transport node, they degrade particles or cause other problems that may lead to material blockage, equipment shutdown and loss of considerable finances . Conversely, the newly designed equipment cannot be adapted to suit the full range of materials and traffic conditions.

Nowadays, 3D design of transport and storage facilities is well established in construction companies. The output is 3D models, from which it is possible to determine a large number of unknowns, such as weight, volume, design, strength parameters, center of gravity, etc. 3D models also help in the creation of drawing documentation and error checking, which naturally makes the equipment design cheaper and faster. However, the most important thing, whether the device will work with a given particulate matter, so far it was not possible to verify without prototype production and subsequent testing. As the demands on the newly designed equipment are far higher than in the past and transport equipment manufacturers do not have experience with new materials, a new design method needs to be developed for the development and control of transport equipment.

Constructional arrangements of worm conveyors are described, for example, in Jasaň V., Theory and Construction of Conveyors, University of Technology in Košice, 1984 or in Dražan F., Theory and Construction of Conveyors, Czech Technical University in Prague, 1983.

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SUMMARY OF THE INVENTION

Said disadvantages of the prior art are solved by a method and apparatus for validating the motion kinetics of particulate matter on a screw conveyor according to the invention.

Structurally, the screw conveyor is designed so that its body is placed on the supporting part and can also be operated in an inclined state. The conveyor body consists of a drive connected directly to the worm, a driving element (worm), transparent and non-transparent covers, which can be removable and control units. One or more high speed cameras are disposed around the conveyor to track the movement of the material.

The conveyor comprises at least two speed sensors, each of which is provided with at least one output, at least one output of one speed sensor being connected to the control unit. The conveyor further comprises at least one speed sensor, which is part of the drive unit, and at least one speed sensor, which is connected directly on the feedback worm to the control unit.

Alternatively, the conveyor further comprises at least two torque sensors, each of which at least one output is connected to an evaluation unit. The at least one torque sensor is part of the drive unit and at least one part of the worm, or may be between the drive unit and the worm.

According to another alternative, the conveyor further comprises at least two material weight sensors, wherein at least one is located in the conveyor and at least one at the material inlet or outlet to the conveyor, at least one output of each of the sensors being connected to the evaluation unit.

Furthermore, the conveyor may comprise a noise sensor (microphone), a photo sensor and a position sensor of the device itself. By means of a control unit, which may be, for example, a frequency converter, the conveyor is connected to an evaluation unit (PC, tablet, etc.).

The equipment can be operated as a circulation system (by means of interconnection of the charging and discharging parts) or as a "flow-through" where there are reservoirs at the inlet and outlet (filling and discharging). In the "flow" connection it is also possible to continuously find out how the material has changed (whether it degraded, etc.).

It is an object of the invention to optimize and validate the properties of worm conveyor components and the properties of the materials to be conveyed. The particle acceleration is optimized and validated depending on the speed and weight of the transported particles, the mechanical-physical properties of the mass, and the speed or resistance of the worm to the transported material in the individual particles. · ············ The aim is to increase the efficiency of transport optimization in order to save energy and overall production costs, also in terms of time in the development of a new prototype or modified type together with ensuring the functionality of the equipment of the required principle of the screw conveyor.

The validation of the whole principle and process of operation is carried out on the basis of optical measurement and scanning by at least one digital camera system in individual constructionally functional and process transport sections of the equipment, where different acceleration of particles of transported material occurs, which can be traced using high speed camera.

The advantage is the possibility of identification and validation of critical design and principle transport process transition points, or critical adjustment optimization parameters in the area of efficient transport and acceleration of material particles by the screw conveyor, or the possibility of mapping the influence of mechanical-physical properties and specific amount of material in the screw conveyor for different loads. Another advantage is in particular the detection and achievement of efficient lossless material transport by the screw in cases where clumps and accumulation of particles occur.

Another advantage is the possibility of identifying the formation of blocking or braking of the screw by the particles of the transported material also with respect to the degradation of these particles and the possibility of mapping the frequency of this undesired process in a particular design of the screws for different settings of optimization input parameters on the control unit.

The optimization and validation methods described above most commonly use FEM (Finite Element Method), DEM (Discreet element method) or CFD (Computational fluid dynamics) methods and most commonly ANSYS, EDEM or FLUENT software for evaluation.

The DEM simulation method is used in combination with the EDEM evaluation software. By combining these methods, it is possible to greatly increase the efficiency of both material transport in the system and reduce the cost of the system, both for development and operation.

DEM simulation is a modern 4D virtual design method where dynamic material flow can be simulated on a 3D modeled device or situation. The input setpoints for using this method are the mechanical-physical properties of the material, such as · · materiálu materiálu materiálu materiálu materiálu materiálu materiálu · · · · · · · · · · · · · Zr ··· ··· ·· Granularity, moisture, bulk density, bulk angle, initial cohesive stress, internal and external friction angle, rolling resistance, restitution coefficient, etc.

In order to create a simulation of a dynamic process, it is necessary to define and model the conveyed material. The particle size and mechanical-physical properties are set for the material particles. These are then programmed in the EDEM application in processes according to the measured granulometry and another set of input measured values to create a real mixture for dynamic simulation.

Another condition for performing the simulation is the creation of a working environment. There are two options. The first is to model situations or devices in external 3D modeling programs such as Autodesk Inventor, Solidworks, Catia, ProEngineer and others. Models created in this way must be converted to the appropriate format, which is then imported into the DEM simulation application. Another option is to model the device directly in the EDEM application, which is, however, more demanding in terms of the complexity of control when creating the model.

It is known from practice that even the best software can not completely replace reality. Even these simulations need to be validated and calibrated in simple processes so that when used in more complex processes on transport and storage facilities, they are the same or close to the real situation with the smallest deviation. Every transport and storage facility is something specific and dynamic processes of material behavior on these facilities as well. It is necessary to validate and calibrate these simulations directly on the relevant equipment related to this issue. The method of the present invention employs a device that is directly designed to calibrate and validate these dynamic processes on screw conveyors. This calibration is carried out in such a way that mechanical and physical properties are measured at the selected locations of the test facilities at which the dynamic flow of the material changes significantly, either directly or indirectly. These are then validated and corrected computational models in the DEM method.

If the basic dynamic processes for a given material are validated and calibrated by all necessary tests, the evaluation of the simulation dynamics in the transport process can be started. In the 3D model of the device, the appropriate driving element speeds are programmed, as well as the amount of material entering the system and the duration of the simulation. After the calculation is finished, the color spectrum of velocities, moments, energies is set and it is possible to observe changes in the properties of particulate matter at a given moment directly on the animation. All these values can be •

Depending on the time it is possible to save them in a graph, animate images and then use them to optimize the entire transport system. The output values are therefore tables, graphs, and diagrams that describe problems and negative effects on the system in more detail.

Using DEM, it is possible to verify the correctness of procedures in the design of both the equipment and the transport process itself. However, this cannot be done without knowing the behavior of the conveyed material.

The main input parameters for the DEM method are friction coefficients, specific gravity of the particulate material, the coefficient of restitution, particle size and shape, and the shear modulus value and Poisson constant for the measurement of forces. Most of these parameters need to be measured realistically, and validation modeling and simulation tests performed in DEM. In the next step, it is necessary to have a comparison with the real process of transport, where the tests are performed most often by scanning with high-speed cameras and using PIV evaluation methodology. The essence of mass calibration in DEM is to achieve a state of behavior as in real mass.

Values are generally best obtained using shear machines. The accuracy of the measurements was compared with a linear and rotary shear device. In both cases, the same external friction angle was measured and these methodologies can be considered correct from the measurement point of view. However, from the point of view of the input parameter for the DEM method, these values are questionable. It is also necessary to know the static friction values, since the DEM computational engine is based on using this value. From the viewpoint of the behavior of the material particles, however, the shear test is important for comparison with the static friction values. Only in this way can the properties and abilities of the internal movement of the particles be attributed to the shape of the individual particles. Shear tests are limited by particle size. Rotation tests are more preferred, particularly for determining internal friction. In the application of vertical conveying by a screw, the internal friction is not as important as the external friction, but in terms of the movement of the individual particles it is necessary to know this value, which could be directly or indirectly related to the static friction between individual particles of conveyed mass. It is not excluded that during DEM calibration, the simulation model will not behave more realistically using internal friction values as a parameter of the friction interaction between individual particles.

Another parameter affecting the simulation is rolling friction, which can be measured on an inclined plane. In terms of accurate measurement, this method complicates the use of particles that are subject to deformation or degradation in the measurement process.

Another input parameter needed to simulate mass transport is the restitution coefficient. It is a description of the reflective properties of materials. Experimentally, the particle bounce from the substrate can be measured using a high-speed camera (which scans the particle bounce), and the rebound route evaluation software can obtain the necessary data to determine the necessary restitution coefficient. This method is most suitable for material particle shapes having similar dimensions in all three axes. Due to the reflection, the particles rotate and they make it difficult to accurately trace the reflected particle. It is necessary to perform tests for all types of material entering the simulation to use DEM.

Values such as shear modulus and Poisson's constant can be determined from the tables in most cases. These two parameters are mainly used to evaluate the forces that affect the design geometry and the material being transported in the DEM.

The final simulation in DEM needs to be verified on a real model. For this, basic validation experiments are used to calibrate the simulation using input measured parameters, which are obtained by laboratory measurements. These values are not absolute, but always within certain ranges that are used to calibrate the model in DEM. Once the desired DEM calibration model has been matched with a real experiment by selecting DEM input parameters, these inputs can be used in another more complex simulation describing the process of conveying material on a vertical screw conveyor. The output of DEM simulations are velocity field values, kinetic and potential energy, or for example the torque values of the worm geometry. The results obtained have no value unless they are compared with real experiments. Validation is made possible by a modern measuring PIV system using a high-speed camera and sophisticated computing software to sense the movement or position of the transported particles.

In order to optimize the system, it is therefore necessary to find the necessary optimization parameters for solving the problems associated with the given transport system, which are obtained by measuring on real models or transport systems. Using the obtained parameters it is then possible to optimize (validate) the transport system using DEM on a virtually created 3D model. Using the obtained parameters it is possible to create a series of virtual measurements, which during the evaluation can be corrected and thus optimize the system. When optimized using mathematical modeling and process simulation where physical prototyping is not required, 4 · 4 · 4 · 4 · Which are inserted into the transport system, it is sufficient to create a virtual model of the system or the transport section and change it as needed; and Optimize elements directly in the virtual model.

In summary, a simulation method according to the present invention will be used to design a new or optimize an existing conveyor. The simulation methods need to be verified, eg, by mathematical methods, according to the present invention using an EDEM application. A physical model (prototype) of the screw conveyor must also be built for verification and validation. This verification device is used to validate mathematical methods to confirm that the simulation results are realistic and that these results are applicable in practice. During this simulation of the device operation, mechanical quantities are sensed electronically (pressure, speed, energy consumption, friction, etc.). Areas of interest are primarily areas where the dynamic flow of material changes significantly, which are primarily the filling and emptying points of equipment. Both the conveyed material and the material of the conveyor are monitored. Sensing is done by direct methods - sensors are placed on the device (strain gauges, pressure sensors, speed sensors) as well as indirect methods - by visual way (cameras). Then, the evaluation unit compares the mathematical model with the measuring device. The result is an optimization of the mathematical model; general validation principle for worm conveyor assessment.

Based on monitoring and evaluation of dynamic processes of particulate matter by means of DEM simulations, the proposed processes will be improved, accelerated and cheaper in development processes. Repairs and unplanned shutdowns of problem equipment will be minimized using this design methodology.

For better illustration, the relationships between input and output variables from both real and simulation environments and what can be optimized and validated are summarized in the table below:

· 2 2 2 2 2

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Laboratory Measurement <,

Input quantities - real What to optimize Input quantities - simulation static friction coefficient internal friction external friction coefficient of rolling friction coefficient of restitution optimization of particle velocities and functional elements of the structure coefficient of static friction coefficient of rolling friction coefficient of restitution Poisson constant shear modulus optimization of forces Poisson constant shear modulus particle size particle shape bulk density bulk density material moisture optimization of particles forming the transported material particle size particle shape density

<♦ ♦

* ♦ 4

Output quantities - real Validation Output quantities - simulation particle velocity <- --------> particle speed torque design <- --------> torque design forces on construction and particles <- forces on structure and particles particle paths <- --------> particle paths audio frequency < -> number of contacts Particle time speed of the functional part <- --------> speed of functional parts speed of the functional part <- --------> speed of functional parts weight change <- --------> weight change particle size change <- ________> particle size change change of construction angle --------> change of construction angle humidity change ambient temperature material temperature component temperature <- --------> option according to the license

Evaluation + validation

<♦

Clarification of drawings

The invention is explained in more detail with reference to the drawings, in which Figure 1 shows the body of a validation vertical screw conveyor, Figure 2 a more detailed description of the validation vertical screw conveyor, Figure 3 possible locations of a camera for sensing movement of conveyed material validation, Figure 5 is a drawing of a worm validation conveyor of Example 1, Figure 6 a block diagram for describing Example 2 - input and output validation, Figure 7 is a drawing of a worm validation conveyor of Example 2, Figure 8 filling and power of the drive, figure 9 is a drawing of a worm validation conveyor of the embodiment 3, figure 10 — a graph of the measured-

-9faοΙλΟ ZF) - \ Ο worm validation conveyor from example 3, figure 10 graph of measured speeds from real environment and from simulation according to example 1, figure 11 graph of measured weights from real environment and from simulation according to example 2, figure 12 graph of measured values torque from real environment and from the simulation according to example 3.

Examples

Customers' requirements for screw conveyors can be high conveying heights, conveying capacities, speeds while reducing production costs, power consumption. energy, component wear and noise reduction. The problem of filling and emptying the equipment should be considered in such a way as to minimize losses during conveyor operation. The following examples are used to optimize these processes.

Example 1 - Continuous validation

The validation vertical screw conveyor 1 according to Figures 1 to 5. The conveyor 1 is formed by a drive 5, to which a worm 4, which is housed in shells 6, 7, is connected via a shaft. The sheath 7 is divided into two parts with a sheath 6 inserted. The lower part of the housing 7 is provided with a material inlet 2 and the upper part of the housing 7 is provided with a material outlet 3. The housing 6 is transparent, both parts of the housing 7 being opaque. The conveyor 7 is located on the supporting part 9. The drive 5 is provided with at least one speed sensor 8 and / or at least one torque sensor 11, at the housing 6 the conveyor 1 is provided with at least one high-speed camera 13 and A control unit 16 is connected bidirectionally to the conveyor 1 and through it the conveyor 1 is bidirectionally connected to the evaluation device 17.

The material inlet 2 is connected to the material outlet 3 by means of a circulation connection 14. The circulation connection 14 is provided with at least one tomography sensor 15.

In the validation conveyor 1, the material circulates, a steady state of transport is achieved, conveyor 1 is independent of other transport systems, particle acceleration is validated only in relation to quality conveyor 1, optimized only in relation to quality conveyor 1 and critical and boundary conditions are detected for steady-state operation and continuous material transport, both for real validation conveyor 1 and real input materials, and for the conveyor model and material in the DEM simulation.

-10 ·········································

Precisely in order to assess the validation conveyor 1 independently of other transport systems, the material inlet 2 and the output 3 are connected via a circulation connection 14. To verify the correct operation of the validation conveyor 1, a calibration standard is first used, followed by the measured material or multiple materials.

The spherical material is introduced into the conveyor 1 and is continuously conveyed to the screw 4 via the circulation connection 14. The first material insertion is carried out after the circulation connection 14 has been disconnected at the material exit point 3. After pouring the spherical particles, the circulation connection 14 is reconnected. The screw 4 transports the material upwards to the material outlet 3, the amount of material in the validation conveyor 1 being recorded by the weight sensor 10. The upward conveying speed of the material is adjusted by the speed of the screw 4 by the control unit 16 which communicates with the speed sensor 8. These speeds can be adjusted very precisely and recorded by the evaluation unit 17. After a certain transport time, the circulation rate of the conveyed material stabilizes upwards and this speed is sensed by the camera system 13 at the transparent housing 6. Further, it is possible tomographic sensor 15 and verify in time the continuous transport of material and the time to reach steady state of circulation. Sensing by the camera system 13 takes place at different screw speeds 4 set by the control unit 16 and outputs the spherical particle velocity data over time at a precisely set screw speed 4, which is provided by the 8 speed sensor. The measured values are processed by the evaluation device 17.

After the validation measurement, the measured and stored values from the sensors (plots) are plotted in correlation tables and graphs so that they coincide with the generated values from the DEM simulation method. After comparing the values, the DEM calculation is corrected by adjusting the input parameters, a new calculation is performed, and if the generated values are close to the measured values from the real validation conveyor 1, the values can be stored in dynamic material libraries where they are prepared for optimization conveyors using the DEM method. If the generated values from the DEM are not close to the real values from the validation conveyor 1, the correction and calculation is repeated.

The velocity data obtained from this real measurement and from the simulation are given in Table 1 and Figure 10.

Table 1 - Movement velocity of real material sensed by high speed camera and evaluated by PIV method and velocity simulated by DEM:

you- PIV [m / s] time. step [with] You- DEM [m / s] you- PIV [m / s] time. step [with] you- DEM [m / s] you- PIV [m / s] time. step [with] you- DEM [m / s] 1 0,0279 0.01 0,0313 34 0.0308 0.28 0.0329 67 0,0235 0.56 0.0256 2 0,0293 0.02 0,0334 35 0,0298 0.29 0.0308 68 0.0228 0.57 0,0294 3 0.0306 0.03 0,0274 36 0,0287 0.30 0,0297 69 0.0238 0.58 0.0344 4 0.0312 0.03 0,0280 37 0,0279 0.31 0.0271 70 0.0247 0.58 0.0322 5 0.0301 0.04 0,0270 38 0,0277 0.32 0,0278 71 0.0254 0.59 0,0353 6 0.0303 0.05 0.0255 39 0,0274 0.33 0.0254 72 0.0251 0.60 0.0244 7 0.0310 0.06 0,0249 40 0,0281 0.33 0.0256 73 0,0265 0.61 0,0338 8 0.0310 0.07 0,0355 41 0,0293 0.34 0,0294 74 0,0267 0.62 0,0317 9 0.0319 0.08 0,0288 42 0,0290 0.35 0,0277 75 0,0269 0.63 0,0295 10 0.0319 0.08 0,0295 43 0,0293 0.36 0,0293 76 0,0277 0.63 0,0268 11 0.0327 0.09 0,0281 44 0,0300 0.37 0,0221 77 0,0289 0.64 0,0221 12 0,0315 0.10 0.0254 45 0,0298 0.38 0,0223 78 0,0281 0.65 0.0237 13 0,0291 0.11 0,0229 46 0,0313 0.38 0.0322 79 0,0280 0.66 0,0279 14 0,0269 0.12 0,0266 47 0.0308 0.39 0.0303 80 0,0284 0.67 0,0336 15 Dec 0,0263 0.13 0,0313 48 0,0298 0.40 0,0296 81 0,0288 0.68 0,0284 16 0.0252 0.13 0.0302 49 0.0301 0.41 0,0297 82 0,0296 0.68 0,0316 17 0.0237 0.14 0.0329 50 0,0295 0.42 0,0280 83 0,0297 0.69 0,0269 18 0,0231 0.15 0,0287 51 0,0289 0.43 0.0271 84 0,0311 0.70 0,0331 19 Dec 0,0230 0.16 0,0260 52 0,0298 0.43 0,0282 85 0,0298 0.71 0,0262 20 May 0.0247 0.17 0,0293 53 0.0301 0.44 0.0310 86 0,0299 0.72 0,0261 21 0,0245 0.18 0,0284 54 0.0309 0.45 0,0290 87 0,0298 0.73 0.0312 22nd 0.0259 0.18 0,0284 55 0.0323 0.46 0,0281 88 0,0290 0.73 0,0264 23 0,0265 0.19 0,0331 56 0.0326 0.47 0,0298 89 0,0284 0.74 0.0306 24 0,0267 0.20 0,0313 57 0,0337 0.48 0,0279 90 0,0298 0.75 0,0297 25 0,0270 0.21 0,0292 58 0,0343 0.48 0.0305 91 0.0306 0.76 0.0305 26 0,0269 0.22 0,0292 59 0,0317 0.49 0,0353 92 0,0316 0.77 0.0312 27 Mar: 0,0278 0.23 0.0322 60 0,0313 0.50 0,0355 93 0.0301 0.78 0.0257

9991 • ·

28 0,0276 0.23 0.0309 61 0,0289 0.51 0,0282 94 0,0299 0.78 0.0257 29 0,0285 0.24 0,0299 62 0,0279 0.52 0,0318 95 0,0300 0.79 0.0326 30 0,0290 0.25 0,0287 63 0,0273 0.53 0,0291 96 0.0307 0.80 0,0282 31 0.0308 0.26 0.0253 64 0.0258 0.53 0,0375 97 0,0291 0.81 0,0280 32 0.0305 0.27 0,0233 65 0.0256 0.54 0.0326 98 0,0293 0.82 0,0284 33 0,0294 0.28 0.0255 66 0.0244 0.55 0,0285 99 0,0284 0.83 0.0236

Based on the measured values from the above-mentioned real equipment and the output values from the simulation, the operator can gradually adjust the speed of the material movement to achieve the desired simulation compliance with the real equipment. The obtained value of the optimum speed is then used in the design of the final parameters of the equipment.

The result of Example 1 is that the difference between the output from the simulation model setup and the measurement output on the physical model is minimized based on operator input values.

Example 2 - Input and output validation

Validation vertical screw conveyor 1 according to Figures 1, 2, 3, 6 and 7. The conveyor 1 is formed by a drive 5, to which a screw 4, which is housed in jackets 6, is connected via a shaft.

The housing 7 is divided into two parts between which the housing 6 is inserted. The lower part of the housing 7 is provided with a material inlet 2 and the upper part of the housing 7 is provided with a material outlet 3. The housing 6 is transparent, both parts of the housing 7 being opaque. The conveyor 1 is located on the support part 9. The drive 5 is provided with at least one speed sensor 8 and / or at least one torque sensor 11, at the housing 6 the conveyor 1 is provided with at least one high-speed camera 13 and weight sensor

10. The control unit 16 is bi-directionally connected to the conveyor 1 and through it the conveyor 1 is bi-directionally connected to the evaluation device 17.

The material inlet 2 is connected to the input container 18 and the material outlet 3 is connected to the output container 19. The input container 18 and / or the output container 19 is provided with at least one weight sensor 10.

In the validation conveyor 1, the material does not circulate, unlike example 1, a steady state of transport is achieved in relation to the inlet 2 and the outlet 3 of the material, the conveyor 1 is dependent

4 4449 on other transport systems, particle acceleration is only validated in other transport systems. in relation to the input 2 and output 3 of the material, it is optimized based on the conveyance performance and the transport processes for the downstream filling and emptying system are optimized and validated, both for the real validation conveyor 6 and the real input materials, in the DEM simulation.

Therefore, in order to assess the dependence of the validation conveyor 6 on another conveying system, at least one inlet container 18 for at least one material type is attached to the validation conveyor 1, in contrast to Example 1, instead of a circulation connection 14 at the material inlet 2. Similarly, at least one output container 19 is connected at the material exit point 3 instead of the circulation link 14. To verify the correct operation of the validation conveyor 1, a calibration standard is first used, and then the measured material or multiple materials.

A spherical material is inserted into the inlet container 48, which is connected to the material inlet 2, which is conveyed to the screw 4 via the material inlet 4. The screw 4 transports the material upwards through the upper part of the material outlet 3 to the outlet container 19, the amount of material in the inlet container 18 and the outlet container 19 is recorded by the weight sensors 10. The duration of the emptying is adjusted by the speed of rotation of the screw 4 by the control unit 16, which is connected to the speed sensor 8. These speeds can be adjusted very precisely and recorded by the evaluation unit 17. After some time, the input tray 18 is emptied and the output tray 19 is filled. The upward conveying speed of the auger 4 is sensed by the camera system 13 at the transparent sheath 6. and filling the output container 19 with the weight sensors 10 takes place at different screw speeds 4 set by the control unit 16 and output the time change data in the input container 18 or the output container 19. The measured values are processed by the evaluation device 17.

After the validation measurement, the measured and stored values from the sensors (plots) are plotted in correlation tables and graphs so that they coincide with the generated values from the DEM simulation method. After comparing the values, the DEM calculation is corrected by adjusting the input parameters, a new calculation is performed, and if the generated values are close to the measured values from the real validation conveyor £, the values can be

-14Save into dynamic material libraries where they are ready to optimize the development or modification of worm conveyors using the DEM method. If the generated values from the DEM do not approach the real values of the conveyor belt 1, the correction and calculation is repeated.

Data on the measured mass change values from this real measurement on the input tray 18 and from the simulation are shown in Table 2 and Figure 11.

Table 2 - weight of real material sensed by weighing sensor and weight simulated by DEM:

Weight [kg] Time [with] DEM [kg] Weight [kg] Time [with] DEM [kg] Weight [kg] Time [with] DEM [kg] 1 0,7006 0.00 0.7034 34 0.4802 3.30 0.4830 67 0.2202 6.60 0.2230 2 0,7000 0.10 0.7028 35 0.4744 3.40 0.4772 68 0.2124 6.70 0.2152 3 0.6978 0.20 0,7006 36 0.4620 3.50 0.4648 69 0.2080 6.80 0.2108 4 0.6932 0.30 0.6960 37 0.4502 3.60 0.4530 70 0.2022 6.90 0.2050 5 0.6874 0.40 0.6902 38 0.4446 3.70 0.4474 71 0.1912 7.00 0.1940 6 0.6848 0.50 0.6876 39 0.4388 3.80 0.4416 72 0.1790 7.10 0.1818 7 0.6824 0.60 0.6852 40 0.4272 3.90 0.4300 73 0.1738 7.20 0.1766 8 0.6796 0.70 0.6824 41 0.4168 4.00 0.4196 74 0.1702 7.30 0.1730 9 0.6710 0.80 0.6738 42 0.4126 4.10 0.4154 75 0.1634 7.40 0.1662 10 0.6610 0.90 0.6638 43 0.4044 4.20 0.4072 76 0.1526 7.50 0.1554 11 0.6558 1.00 0.6586 44 0.3958 4.30 0.3986 77 0.1422 7.60 0.1450 12 0.6528 1.10 0.6556 45 0.3866 4.40 0.3894 78 0.1396 7.70 0.1424 13 0.6452 1.20 0.6480 46 0.3794 4.50 0.3822 79 0.1342 7.80 0.1370 14 0.6330 1.30 0.6358 47 0.3718 4.60 0.3746 80 0.1252 7.90 0.1280 15 Dec 0.6250 1.40 0.6278 48 0.3658 4.70 0.3686 81 0.1128 8.00 0,1156 16 0.6176 1.50 0.6204 49 0.3576 4.80 0.3604 82 0.1076 8.10 0.1104 17 0.6114 1.60 0.6142 50 0.3446 4.90 0.3474 83 0.1030 8.20 0.1058 18 0.5962 1.70 0.5990 51 0.3386 5.00 0.3414 84 0,0954 8.30 0,0982 19 Dec 0.5848 1.80 0.5876 52 0.3352 5.10 0.3380 85 0,0830 8.40 0,0858 20 May 0.5818 1.90 0.5846 53 0.3250 5.20 0.3278 86 0.0784 8.50 0,0812

21 0.5784 2.00 0.5812 54 0.3166 5.30 0.3194 87 0,0742 8.60 0,0770 22nd 0.5700 2.10 0.5728 55 0.3116 5.40 0.3144 88 0,0648 8.70 0,0676 23 0.5558 2.20 0.5586 56 0.3076 5.50 0.3104 89 0.0518 8.80 0.0546 24 0.5472 2.30 0.5500 57 0.2996 5.60 0.3024 90 0,0410 8.90 0,0438 25 0.5414 2.40 0.5442 58 0.2884 5.70 0.2912 91 0,0358 9.00 0.0386 26 0.5350 2.50 0.5378 59 0.2806 5.80 0.2834 92 0,0296 9.10 0.0324 27 Mar: 0.5254 2.60 0.5282 60 0.2762 5.90 0.2790 93 0.0228 9,20 0.0256 28 0.5174 2.70 0.5202 61 0.2716 6.00 0.2744 94 0.0124 9,30 0.0152 29 0.5128 2.80 0.5156 62 0.2620 6.10 0.2648 95 0.0044 9.40 0.0072 30 0.5078 2.90 0.5106 63 0.2482 6.20 0.2510 96 0.0000 9.50 0,0026 31 0.4972 3.00 0.5000 64 0.2418 6.30 0.2446 97 0.0000 9.60 0.0004 32 0.4892 3.10 0.4920 65 0.2366 6.40 0.2394 98 0.0000 9.70 0.0000 33 0.4856 3.20 0.4884 66 0.2308 6.50 0.2336 99 0.0000 9.80 0.0000

Based on the measured values from the above-mentioned real equipment and the output values from the simulation, the operator can gradually adjust the speed of the material movement to achieve the desired simulation compliance with the real equipment. The obtained value of the optimum discharge rate is then used in the design of the final parameters of the plant.

Example 3 - Validation with Optimization of Filling and Drive Performance

The validation vertical screw conveyor 1 according to Figures 1, 2, 3, 8 and 9. The conveyor 1 is formed by a drive 5 to which a screw 4, which is housed in shells 6, is connected via a shaft.

The housing 7 is divided into two parts between which the housing 6 is inserted. The lower part of the housing 7 is provided with a material inlet 2 and the upper part of the housing 7 is provided with a material outlet 3. The housing 6 is transparent, both parts of the housing 7 being opaque. The conveyor 1 is located on the support part 9. The support part 9 allows the conveyor body to be tilted at a minimum angle of 15 ° and thus also to provide a tilting transport. The support part 9 is provided with a conveyor body position sensor 20 1. The drive 5 is provided with at least one speed sensor 8 and / or at least one torque sensor 11, at the housing 6 the conveyor 1 is provided with at least one high-speed camera 13 and provided with at least one weighing sensor

10. The control unit 16 is bi-directionally connected to the conveyor 1 and through it the conveyor 1 is bi-directionally connected to the evaluation device 17.

• ·

The material input 2 is connected to the input container 18 and the material output 3 is connected to the output container 19. The input container 18 and / or the output container 19 is provided with at least one weight sensor 10.

Validation conveyor 1 validates and optimizes the downstream filling system, transport variable and load states in relation to material input 2 and output 3, and continuous transport, validates and optimizes dependencies on other transport systems, validates particle acceleration relative to input 2 and output 3 of the material, optimized based on the traffic performance in relation to the cant, and optimized and validated the transport processes for the subsequent filling system with variable cant and discharging, both for real validation conveyor 1 and real input materials as well as the conveyor and material model in the DEM simulation.

To verify the correct operation of the validation conveyor 1, a calibration standard is used first, and then the measured material or multiple materials.

The spherical material is inserted into the inlet container 18, which is connected to the material inlet 2, which is conveyed to the screw 4 via the material inlet 2. The screw 4 transports the material and overcomes the set cant detected by the validation conveyor position sensor 20. at the end of the screw 4 through the material outlet 3 to the output container 19, the change in the amount of material in the input container 18 and the output container 19 is recorded by the weight sensors 10. The emptying time is adjusted by the rotation speed of the screw 4 by the control unit 16 connected to the sensor 8, or the duration of emptying can be influenced by changing the position of the validation conveyor 1 recorded by the position sensor 20. The speed can be set and recorded very precisely by the evaluation unit 17, and the torque is also sensed by the sensor 11. After a certain time, the input tray 18 becomes empty and the output tray 19 is filled. different set screw speeds 4.

After the validation measurement, the measured and stored values from the sensors (plots) are plotted in correlation tables and graphs so that they coincide with the generated values from the DEM simulation method. After comparing the values, the DEM calculation is corrected by adjusting the input parameters, a new calculation is performed and, if generated

values are close to the measured values from the real validation conveyor 1, the values can be stored in dynamic material libraries where they are prepared to optimize the development or modification of worm conveyors using the DEM method. If the generated values from the DEM are not close to the real values from the validation conveyor 1, the correction and calculation is repeated.

The measured values of the change of the rotational moment on the worm 4 at a certain position of the validation conveyor 1 from this real measurement and from the simulation are given in Table 3 and Figure 12.

Table 3 - torque values from real-time measurements and torque values simulated by DEM:

Screw torque [Nm] Time [with] Worm Torque DEM [Nm] Screw torque [Nm] Time [with] Worm Torque DEM [Nm] Screw torque [Nm] Time Μ Worm Torque DEM [Nm] 1 0,0279 0.01 0,0313 34 0.0308 0.28 0.0329 67 0,0235 0.56 0.0256 2 0,0293 0.02 0,0334 35 0,0298 0.29 0.0308 68 0.0228 0.57 0,0294 3 0.0306 0.03 0,0274 36 0,0287 0.30 0,0297 69 0.0238 0.58 0.0344 4 0.0312 0.03 0,0280 37 0,0279 0.31 0.0271 70 0.0247 0.58 0.0322 5 0.0301 0.04 0,0270 38 0,0277 0.32 0,0278 71 0.0254 0.59 0,0353 6 0.0303 0.05 0.0255 39 0,0274 0.33 0.0254 72 0.0251 0.60 0.0244 7 0.0310 0.06 0,0249 40 0,0281 0.33 0.0256 73 0,0265 0.61 0,0338 8 0.0310 0.07 0,0355 41 0,0293 0.34 0,0294 74 0,0267 0.62 0,0317 9 0.0319 0.08 0,0288 42 0,0290 0.35 0,0277 75 0,0269 0.63 0,0295 10 0.0319 0.08 0,0295 43 0,0293 0.36 0,0293 76 0,0277 0.63 0,0268 11 0.0327 0.09 0,0281 44 0,0300 0.37 0,0221 77 0,0289 0.64 0,0221 12 0,0315 0.10 0.0254 45 0,0298 0.38 0,0223 78 0,0281 0.65 0.0237 13 0,0291 0.11 0,0229 46 0,0313 0.38 0.0322 79 0,0280 0.66 0,0279 14 0,0269 0.12 0,0266 47 0.0308 0.39 0.0303 80 0,0284 0.67 0,0336 15 Dec 0,0263 0.13 0,0313 48 0,0298 0.40 0,0296 81 0,0288 0.68 0,0284

16 0.0252 0.13 0.0302 49 0.0301 0.41 0,0297 82 0,0296 0.68 0,0316 17 0.0237 0.14 0.0329 50 0,0295 0.42 0,0280 83 0,0297 0.69 0,0269 18 0,0231 0.15 0,0287 51 0,0289 0.43 0.0271 84 0,0311 0.70 0,0331 19 Dec 0,0230 0.16 0,0260 52 0,0298 0.43 0,0282 85 0,0298 0.71 0,0262 20 May 0.0247 0.17 0,0293 53 0.0301 0.44 0.0310 86 0,0299 0.72 0,0261 21 0,0245 0.18 0,0284 54 0.0309 0.45 0,0290 87 0,0298 0.73 0.0312 22nd 0.0259 0.18 0,0284 55 0.0323 0.46 0,0281 88 0,0290 0.73 0,0264 23 0,0265 0.19 0,0331 56 0.0326 0.47 0,0298 89 0,0284 0.74 0.0306 24 0,0267 0.20 0,0313 57 0,0337 0.48 0,0279 90 0,0298 0.75 0,0297 25 0,0270 0.21 0,0292 58 0,0343 0.48 0.0305 91 0.0306 0.76 0.0305 26 0,0269 0.22 0,0292 59 0,0317 0.49 0,0353 92 0,0316 0.77 0.0312 27 Mar: 0,0278 0.23 0.0322 60 0,0313 0.50 0,0355 93 0.0301 0.78 0.0257 28 0,0276 0.23 0.0309 61 0,0289 0.51 0,0282 94 0,0299 0.78 0.0257 29 0,0285 0.24 0,0299 62 0,0279 0.52 0,0318 95 0,0300 0.79 0.0326 30 0,0290 0.25 0,0287 63 0,0273 0.53 0,0291 96 0.0307 0.80 0,0282 31 0.0308 0.26 0.0253 64 0.0258 0.53 0,0375 97 0,0291 0.81 0,0280 32 0.0305 0.27 0,0233 65 0.0256 0.54 0.0326 98 0,0293 0.82 0,0284 33 0,0294 0.28 0.0255 66 0.0244 0.55 0,0285 99 0,0284 0.83 0.0236

Based on the measured values from the above-mentioned real equipment and the output values from the simulation, the operator can gradually adjust the position of the validation conveyor 1 and achieve the desired simulation conformity with the real equipment. The obtained value of the optimum emptying speed and rotational torque is then used in the design of the final performance parameters of the plant drive.

Industrial applicability

The solution according to the invention can be used wherever existing or developing new screw conveyors are optimized, especially in the mining, transport, pharmaceutical, material, pigment and the like industries and in the research and development of new types of screws.

Claims (4)

PATENT CLAIMS with t Validation vertical screw conveyor, consisting of a drive, to which a worm is attached by means of a shaft, which is housed in jackets and has a material inlet at the bottom and a material outlet at the upper part, characterized in that it is located on the supporting part (9). ), the casing of the conveyor (1) is transparent and a control unit (16) is connected bidirectionally to the conveyor (1) through which the conveyor (1) is bi-directionally connected to the evaluation device (17), the drive (5) being provided with at least one sensor ( 8) a speed and / or at least one torque sensor (11), in place of the housing (6) the conveyor (1) is provided with at least one high-speed camera (13) and is provided with at least one weight sensor (10) in the carrier (9); further, at the conveyor (1), either the material inlet (2) and the material outlet (3) are connected to each other by means of a circulation connection (14), which is provided with at least one tomographic sensor (15), or a material inlet (2) connected to the input container (18) and a material outlet (3) connected to the output container (19), wherein the input container (18) and / or output container (19) are provided with at least one weighing sensor (10). Validation vertical screw conveyor according to claim 1, characterized in that the support part (9) is further provided with a position sensor (20) of the conveyor (1). Method for modeling mechanical processes using a validation vertical screw conveyor according to claim 1, characterized in that the following steps are performed first with the calibration standard and then with one or more validated materials: material is supplied to the conveyor (1) with the inlet (2) from the circulation connection (14) or from the inlet container (18), movement of the screw (4) is started, which transports the material upwards to the material outlet (3) 14) or into the output reservoir (19), while during transport, the values of mechanical-physical quantities are measured by means of sensors (8,10, 11 and / or 15), which are subsequently processed by the evaluation device (17), using a high-speed camera ( 13) -20 · · • • 9 9 9 9 9 «« «« «9 · 9 9 9 9« « ···· The material movement is scanned through a transparent sheath (6), from which a vector velocity map is created using the PIV method, software modeling of the conveyed material using the EDEM application and simulation using the DEM simulation method is performed. the measured values from the sensors / sensors are plotted into the comparison tables and graph so that they correspond in time to the generated values from the DEM simulation method; after the values are compared, the DEM calculation is corrected by adjusting the input parameters; until the generated values are close to the measured values from a real validation conveyor (1), whereupon these values are stored in dynamic material libraries and / or o are used to optimize the development or modification of worm conveyors. Method for modeling mechanical processes by means of a validating vertical screw conveyor according to claims 2 and 3, characterized in that the conveyor is operated at a minimum angle of 15 °, wherein at the same time the position data of the conveyor (1) are read by the sensor (20). they are then processed by the evaluation device (17).