DIGITAL PARTICLE ANALYSIS

Abstract

A computer-implemented method for characterization of solid particles, especially sand particles, includes the steps of: providing a sample of solid particles to be analyzed in a predefined sample area; taking at least one digital image of the sample of solid particles with a camera of a mobile computer device; performing an imaging particle analysis of the at least one digital image for extracting at least one particle size parameter and/or at least one particle shape parameter of the population of particles identified in the at least one digital image; making available the at least one particle size parameter and/or the at least one particle shape parameter via a user interface, via a machine interface and/or on a data storage medium.

Claims

1. A computer-implemented method for characterization of solid particles comprising the steps of: a) providing a sample of solid particles to be analyzed in a predefined sample area; b) taking at least one digital image of the sample of solid particles with a camera of a mobile computer device or a camera connected to a mobile device; c) performing an imaging particle analysis of the at least one digital image for extracting at least one particle size parameter and/or at least one particle shape parameter of the population of particles identified in the at least one digital image; d) making available the at least one particle size parameter and/or the at least one particle shape parameter via a user interface, via a machine interface and/or on a data storage medium.

2. The method according to claim 1, whereby the mobile computer device comprises a human interface device.

3. The method according to claim 1, whereby the mobile computer device is selected from a mobile phone, a mobile computer or a portable computer, and/or a head-mounted display with camera.

4. The method according to claim 1, whereby the camera is a camera for taking images in the visible spectrum.

5. The method according to claim 1, whereby the camera has a resolution of at least 2 megapixels.

6. The method according to claim 1, whereby the sample area comprises a reference scale and/or has a known size.

7. The method according to claim 1, whereby the predefined sample area is a two-dimensional sample area.

8. The method according to claim 1, whereby the particles of the sample are selected from sand, aggregates, fibers and/or glass spheres.

9. The method according to claim 1, whereby when taking the image, the camera is aligned so that a share of the sample area in the image is maximized.

10. The method according to claim 1, whereby a minimum detectable particle size is calculated by taking into account the resolution of the camera, the length share of the sample area in the total area of the image, and the real length of the sample area.

11. The method according to claim 1, whereby, if a minimum detectable particle size is below a predetermined threshold, a warning is provided to the user, alignment instructions are provided to the user and/or a setting of the camera.

12. The method according to claim 1, whereby the at least one particle size parameter extracted comprises the particle size distribution of the population of particles identified in the at least one digital image.

13. The method according to claim 1, whereby for each of the at least one digital image, an outline image is generated, and, the outline image is made available in step d) via a user interface, via a machine interface and/or on a data storage medium.

14. The method according to claim 1, whereby in step b), at least two digital images are taken and for each image an imaging particle analysis is performed in step c), and by taking into account each of the at least one particle size parameter and/or the at least one particle shape parameter individually extracted from the at least two images, a deviation, deviation of the at least one particle size parameter and/or the at least one particle shape parameter is determined.

15. The method according to claim 14, whereby, if the deviation is above a predetermined threshold, a warning is provided to the user and/or whereby a digital image and/or an outline image giving rise to diverging parameters is identified and/or indicated.

16. The method according to claim 1, whereby the at least one particle size parameter comprises at least one statistical parameter selected from the group of average particle size, mean diameter, D.sub.xvalue with x=1-100 and/or fineness modulus.

17. The method according to claim 1, whereby the at least one particle size parameter extracted comprises a deviation from a predefined nominal value and/or nominal distribution.

18. The method according to claim 1, whereby, for particle sizes below the minimum detectable particle size, the particle size distribution is extrapolated based on the extracted particle size distribution.

19. The method according to claim 1, whereby the at least one particle shape parameter extracted comprises the roundness, sphericity, aspect ratio, roughness, solidity, flakiness index, shape index, percentage of crushed and broken surfaces, and/or angularity.

20. The method according to claim 1, whereby the at least one particle shape parameter is extracted with regard to particles of a predetermined size only, or whereby, for each of at least two or more predefined size fractions of the particles, at least one individual particle shape parameter is extracted.

21. The method according to claim 1, comprising the step of assigning at least one attribute to the sample of solid particles.

22. The method according to claim 1, whereby the method is at least partly performed on the mobile computer device.

23. The method according to claim 1, whereby the image analysis in step c) and/or the making available in step d) is/are conducted on a separate computer device.

24. The method according to claim 1, whereby the image is stored on an external computer device.

25. A system comprising a mobile computer device, and optionally an additional separate computer device, whereby the system comprises: (i) means for carrying out the steps a) to d), of the method of claim 1, and/or (ii) means for carrying out at least the steps a) and b) of the method of claim 1, and means for transferring at least one digital image of a sample of solid particles, optionally together with at least one attribute, to the separate computer device.

26. A system comprising a computer device, whereby the system comprises means for receiving at least one digital image of a sample of solid particles and means for carrying out steps c) and/or d) of the method of claim 1.

27. A computer-readable medium comprising instructions which, when executed by a mobile computer device, cause the mobile computer device to carry out at least the steps a) to b) of the method of claim 1.

28. A computer-readable medium comprising instructions which, when executed by a computer device, cause the external computer device to receive at least one digital image and perform steps c) and/or d) of the method of claim 1.

29. A method for providing a formulation of a curable composition comprising at least a binder and solid particles, whereby the solid particles are different from the binder, and whereby the method comprises the steps of (i) obtaining at least one particle size parameter and/or at least one particle shape parameter of the solid particles and (ii) determining nature and/or proportion of at least one component of the formulation by taking into account the at least one particle size parameter and the at least one particle shape parameter.

30. The method according to claim 29, whereby the formulation is made available with a computer device via a user interface, via a machine interface and/or on a data storage medium.

31. A system comprising a computer device, whereby the system comprises means for carrying out at least step (ii) of the method of claim 29.

32. A computer-readable medium comprising instructions which, when executed by a computer device, cause the computer device to perform at least step (ii) of the method of claim 29.

33. A method for producing a curable composition comprising at least a binder and solid particles, whereby the solid particles are different from the binder, and whereby the method comprises the steps of (i) obtaining at least one particle size parameter and/or at least one particle shape parameter of the solid particles and (ii) mixing the solid particles with the binder and any optional further component, whereby the at least one particle size parameter and the at least one particle shape parameter are considered for determining nature and/or proportion of at least one of the components in the composition.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0200] The drawings used to explain the embodiments show:

[0201] FIG. 1A flow chart of an inventive computer-implemented method;

[0202] FIG. 2A schematic overview of a system comprising means for carrying out the method of FIG. 1;

[0203] FIG. 3A schematic view of the second step of the method of FIG. 1 whereby a user (not shown) holding a smartphone is taking an image of a sample of solid particles of different sizes;

[0204] FIG. 4 An example of the structure of a data file;

[0205] FIG. 5A flow chart of another computer-implemented method;

[0206] FIG. 6A bar plot of selected particle shape parameters (roundness, sphericity and aspect ratio) per particle sieve size fraction;

[0207] FIG. 7 An outline image overlaid over a digital image;

[0208] FIG. 8A schematic view of a light pad;

[0209] FIG. 9A comparison between a sample of particles on the non-illuminated surface of the light pad of FIG. 8 (left side) and the same sample of particles on the illuminated surface of the light pad of FIG. 8 (right side);

[0210] FIG. 10 Another bar plot of selected particle shape parameters (roundness/R, sphericity/SP and aspect ratio/AR) per particle sieve size fraction together with the corresponding particle count per particle sieve size fractions with sizes >0.5 mm.

EXEMPLARY EMBODIMENTS

[0211] FIG. 1 shows a flow chart of an inventive computer-implemented method 10. In a first step 11, a sample of solid particles to be analyzed, e.g. a sand sample with particle sizes ranging from >0 to 2 mm, is provided on a two-dimensional sample area of known size. The sample area is for example formed by a sheet of paper of A4 size.

[0212] In a second step 12, a digital image of the sample of solid particles is taken with a camera of a mobile computer device, e.g. a smartphone. The camera for example has a 4K resolution.

[0213] Thereafter, in a third step 13, an imaging particle analysis of the digital image is performed for extracting at least one particle size parameter, e.g. the particle size distribution, and/or at least one particle shape parameter, e.g. roundness or sphericity, of the population of particles identified in the at least one digital image.

[0214] In a fourth step 14, the at least one particle size parameter and the at least one particle shape parameter are made available via a user interface, e.g. a display of the mobile computer device.

[0215] In an optional fifth step 15a, a formulation of a curable composition comprising at least a binder and solid particles is provided, whereby nature and/or proportion of at least one component of the formulation, especially an additive, e.g. a plasticizer, in the formulation, is determined by taking into account the at least one particle size parameter and the at least one particle shape parameter.

[0216] Alternatively or in addition, in an optional step 15b, a curable composition comprising at least a binder and solid particles is provided, whereby step 15b comprises mixing the solid particles with the binder and any optional further component, whereby, the at least one particle size parameter and the at least one particle shape parameter are considered for determining nature and/or proportion of at least one of the components, especially of an additive, in the composition.

[0217] FIG. 2 shows a schematic overview of a system 20 comprising means for carrying out the method shown in FIG. 1.

[0218] Specifically, the system 20 comprises a smartphone 21 with a camera 22, a touch sensitive display comprising input device 23 and a display 24, a data processing unit 25 with a random access memory, a data storage device 29 and a wireless communication interface 28.

[0219] In operation, an application 26 is executed in the data processing unit 25, whereby the application is configured for performing steps 12 and 14 of the method described with FIG. 1.

[0220] Specifically, the application 26 assists a user in taking an image of solid particles in a two-dimensional sample area 30 with the built-in smartphone camera 22. Thereby, the application is for example configured for automatically warning the user and/or for preventing taking the image as long as there is a non-plane-parallel alignment. This can be achieved by assessing the position sensors of the smartphone (not shown). Also, the application is configured for automatically adjusting light conditions in order to obtain a balanced exposure. The digital image taken is stored in the random access memory and/or the data storage 29.

[0221] Additionally, the application 26 asks the user to enter one or more attributes of the sample via the input device and assigns a unique identifier to the sample. Attributes are e.g. the maximum grain size of the solid particles, the type of the solid particles (natural, crushed, manufactured, recycled; re-used solid particles), the state of the solid particles (wet or dry), the pretreatment (washed or untreated), the location of the source of the solid particles, the intended use (project name, customer name); and/or a general comment.

[0222] The query can e.g. be made by presenting to the user input fields, selection fields, maps and/or text input fields on the display 24 and storing the data provided by the user via the input device 23 together with the at least digital image in the random access memory and/or the data storage 29.

[0223] For example, the location of the source of particles can be provided manually by the user, e.g. by entering geo coordinates in input fields and/or by marking the position on a map shown on the display 24. It is however possible to automatically provide the location of the source of the solid particles e.g. by sensors of a global navigation satellite system, such as e.g. GPS, Galileo, Beidou and/or Glonass sensors. Thereby, the user might be requested to confirm the automatically determined position.

[0224] In the system 20 shown in FIG. 2, step 13 of the method shown in FIG. 1 is performed on an external server 21a. Specifically, the image taken with the smartphone camera 22, optionally together with the attributes, is transferred via the wireless communication interface 28 (or any other communication interface) and a network (e.g. the internet; not shown) to the server 21a. The server 21a receives the data via its communication interface 28a and forwards it to an imaging particle analysis application 26a running in a processing unit 25a.

[0225] The image, optionally together with the attributes can be stored on a data storage 29a of the server 21a for later sharing, recalling and/or further evaluation.

[0226] The application 26a performs an imaging particle analysis of the digital image whereby at least one particle size parameter, e.g. the particle size distribution, and at least one particle shape parameter, e.g. roundness or sphericity, of the population of particles identified in the at least one digital image is extracted. Thereby one or more attributes may be considered in the analysis as well.

[0227] The application 26a is implemented for example with image analysis algorithms such as e.g. software packages and/or libraries provided in Matlab, OpenCV and/or ImageJ, and/or with artificial intelligence software.

[0228] After the image analysis is finished, the at least one particle size parameter, e.g. the particle size distribution, and at least one particle shape parameter, e.g. roundness or sphericity, are sent back to the smartphone 21 or the application 25 being executed on it, respectively, via the communication interfaces 28a, 28.

[0229] The application 25a then makes available the at least one particle size parameter and/or the at least one particle shape parameter via the display 24, or saves the parameters on the data storage 29, preferably together with the attributes, for later sharing, recalling and/or further evaluation. This data can be stored for example in the form of a data file having a file format chosen from json, csv, txt, pdf, and/or a proprietary file format. Especially, a file format capable of being read by the application called Sika Mix Design App and/or any other additional application is chosen. See FIG. 4 for an example.

[0230] Additionally, the application 25 is configured for sharing the at least one particle size parameter and the at least one particle shape parameter and the attributes with another user by sending them, in particular as a data file, via the communication interface 28 to a further computer device 40, e.g. a smartphone of another user. This can for example be initiated by the user via input device 23, e.g. by pressing a button shown on the display 24.

[0231] Furthermore, the system 20 may comprise an optional mix design application 27, which can be executed with the processing unit 25. The mix design application is configured for providing a formulation of a curable composition comprising at least a binder and solid particles is provided, whereby nature and/or proportion of at least one component of the formulation, especially an additive, e.g. a plasticizer, in the formulation, is determined by taking into account the at least one particle size parameter and the at least one particle shape parameter obtained with the first application 26.

[0232] Thus, for example, the first application can forward the at least one particle size parameter and the at least one particle shape parameter, and optionally the attributes, to the mix design application 27 via an appropriate application interface.

[0233] Also the data to be sent to the mix design application 27 can be provided and transferred to the mix design application 27 in the form of a data file. In addition or alternatively, the mix design application can be configured for loading this data from the data storage 29 and/or in the form of a data file.

[0234] The mix design application 27 is configured for making available the formulation provided on the display 24, sending it via the communication interface 28 to another computer system, e.g. server 21a, or to a further smartphone 40, and/or save it on the data storage 29 for later sharing, recalling and/or further evaluation.

[0235] FIG. 3 shows a schematic view of step 12 of the method shown in FIG. 1. Thereby, a user (not shown), holding a smartphone 21 in his hands, takes an image of a sample of solid particles L (large), M (medium), S (small) of different sizes, e.g. sand particles with particle sizes ranging from >0 to 2 mm, being provided on a white sheet of paper of A4 size serving as a two-dimensional sample area 30. The sheet of paper is placed on a surface with high contrast, e.g. black surface, 30a that in all directions of space is larger than the two-dimensional sample area 30. Thus, the two-dimensional sample area 30 is fully surrounded by a frame of a different color.

[0236] FIG. 4 shows an example of the structure of a data file 50 in pdf file format. The data file 50 comprises a table 51 with attributes provided by the user, e.g. the type of the solid particles (natural, crushed, manufactured, recycled; re-used solid particles), the state of the solid particles (wet or dry), the pretreatment (washed or untreated), the location of the source of the solid particles, the intended use (project name, customer name); and/or a general comment.

[0237] Also, the file 50 comprises a graph 52 representing the particle size distribution, a table 53 comprising the calculated sieve size pass rate of the solid particles and/or the calculated proportion of retained solid particles, and a table 54 with statistical parameters, such as D.sub.10, D.sub.50, D.sub.85, and D.sub.100 values as well as the fineness modulus of the solid particles analyzed.

[0238] Furthermore, the file 50 comprises a two-dimensional plot 55 indicating the mean particle shape (for example roundness or sphericity) with a marker 55a. Additionally, the file 50 comprises a bar plot 57 displaying the mean value of selected particle shape parameters (for example roundness, sphericity and aspect ratio) per particle sieve size fraction. A more detailed view of the bar plot 57 is shown in FIG. 6.

[0239] FIG. 5 shows a flow chart of another computer-implemented method 60. Thereby, the particle size distribution and at least one particle shape parameter of a sample of solid particles are provided in a first step 61. These parameters can be obtained with the method shown in FIG. 1 or with any other method, e.g. manually.

[0240] Subsequently, in next step 62a, a formulation of a curable composition comprising at least a binder and solid particles is provided, whereby nature and/or proportion of at least one component of the formulation, especially an additive, e.g. a plasticizer, in the formulation, is determined by taking into account the particle size distribution and the at least one particle shape parameter.

[0241] This can be achieved with a mix design application as described above, i.e. mix design application 27. This application is configured for making available the formulation provided on the display 24, sending it via the communication interface 28 to another computer system, e.g. server 21a, or to a further smartphone 40, and/or save it on the data storage 29 for later sharing, recalling and/or further evaluation.

[0242] Alternatively or in addition, in an optional step 62b, a curable composition comprising at least a binder and solid particles is provided, whereby step 62b comprises mixing the solid particles with the binder and any optional further component, whereby, the at least one particle size parameter and/or the at least one particle shape parameter are considered for determining nature and/or proportion of at least one of the components, especially of an additive, in the composition.

[0243] As a representative example, a curable mortar composition comprising cement (CEM I), water, a plasticizer (Sika? Viscocrete? 111 P) and silica sand (D.sub.85-value=2.36 mm) was produced as follows: [0244] 1. The particle size distribution as well as the sphericity, roundness and aspect ratio (=particle shape parameters) of the sand used were determined according to the method shown in FIG. 1. [0245] 2. The particle size distribution as well as the particle shape parameters were transferred to the Sika Mix Design App (available from Sika Services AG) for calculation of a mortar composition with a predefined slump flow of 370 mm (according to EN 12350-5:2019). Thereby, the proportions of cement, water, plasticizer and silica sand were adjusted to achieve the target slump flow. [0246] 3. Subsequently, the mortar composition as calculated by the Sika Mix Design App was produced by mixing the respective proportions of cement, water, plasticizer and silica sand. Then the slump flow of the so produced mortar composition was determined (according to EN 12350-5:2019) in order to compare the real slump flow of the mortar composition produced with the target slump flow of 370 mm. [0247] 4. For reasons of comparison, steps 2 and 3 were repeated without considering the particle shape parameters (sphericity, roundness and aspect ratio) in the Sika Mix Design App but otherwise identical conditions. Thus, in this case only the particle size distribution was considered in the Sika Mix Design App when calculating the mortar composition.

[0248] The results were as follows:

TABLE-US-00001 Measured Deviation from slump flow Target slump flow Target slump flow 370 mm Slump flow of composition 374 mm 4 mm (+1.1%) calculated with particle size and particle shape parameters Slump flow of composition 346 mm ?24 mm (?6.5%) calculated without particle shape parameters

[0249] Thus, when considering the shape parameters, it is possible to predict a mortar composition that has a slump flow very close to the desired target value. Without the shape parameters, the deviation from the target slum flow is significantly higher.

[0250] Similar tests have been performed with other sands (not shown here). A statistical evaluation of the data has shown that considering the particle shape parameters for calculating a mortar composition having a desired target slump flow is highly relevant in general and results in significantly better predictions when compared with calculations that are not taking into account the shape parameters.

[0251] FIG. 7 shows an outline plot overlaid over the corresponding digital image. The outline plot can be used in addition to check the quality of the digital image and/or the analysis performed.

[0252] FIG. 8 shows a schematic view of a light pad 70 which can be used as the two dimensional sample area 30 instead of the sheet of paper used in the setup of FIG. 3. The light pad comprises of a light emitting luminous surface 71 made of a translucent layer that is illuminated with a white LED light source 73 (indicated by a dashed rectangle) from the backside. The light emitting luminous surface 71 has a size of a DIN A4 paper and is fully surrounded by a black frame 72.

[0253] FIG. 9 shows a sample of particles on the non-illuminated surface of the light pad 70 of FIG. 8 (left side) and the same sample of particles on the illuminated surface of the light pad 70 of FIG. 8 (right side). As evident from the comparison, the contrast on the right side is clearly better and there are no shadows visible.

[0254] FIG. 10 shows an example of the particle counts of a sample of sand particles with a particle size >0.5 mm per particle sieve size fractions (right axis), and additionally the corresponding mean values of three different particle shape parameters (roundness/R, sphericity/SP and aspect ratio/AR) per particle sieve size fraction (left axis).

[0255] The data shown in FIG. 10 was obtained with the method and the system described in FIGS. 1 and 2. The application 26 used in this method may be further configured to calculate an overall mean value of the particle shape parameters for a selectable range of particle sieve size fractions, e.g. from a lower threshold of 4 mm to an upper threshold of 8 mm or alternatively from a lower threshold of 1 mm up the maximum sieve size fraction of 16 mm.

[0256] It will be appreciated by those skilled in the art that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics thereof. The presently disclosed implementations and embodiments are therefore considered in all respects to be illustrative and not restricted.

[0257] For example, instead of using server 21a, the application 26 can be configured as a standalone application capable of executing all of the steps 11, 12, 13, 14 and optionally 15a of the method of FIG. 1.

[0258] Likewise, it is possible to omit optional functions of the system 20, e.g. sharing of data with other computer devices, or adding additional functions, such as for example automatically retrieving of positional data via positioning sensors.

[0259] The method can as well be used for characterizing solid particles other than sands.

[0260] Also, it is possible to provide system 20 with mix design application 27 but without application 26. Such a system is for example suitable for performing the method as shown in FIG. 5. Thereby, the at least one particle size parameter and the at least one particle shape parameter can be inputted manually and/or being read from the data storage 29 and/or any other data storage, e.g. data storage 29a of server 21.