COMPUTER-IMPLEMENTED METHOD, COMPUTER-BASED PRODUCT, AND MONITORING SYSTEM FOR CONTACTLESS ASSESSMENT OF RHEOLOGICAL PROPERTIES OF FLUID CEMENT-BASED PRODUCTS

Abstract

A computer-implemented method and a computer-based product and monitoring system for contactless assessment of rheological properties of a fluid cement-based product, the method performing a first analysis which obtains the rotation speed of the mixing blades (31) of a truck-mounted concrete mixer drum (30) and detects the variation of the speed constituting a first parameter, performing a second analysis which obtains at least a sequence of images of the fluid product contained within the mixer drum (30), identifies particles, shapes, groups of particles, contours, and/or slope of the fluid product within the collection of sequential images, detects variations of speed and displacement direction of the particles and shapes, constituting a second parameter, performing a third analysis that detects a correlation between each first and second parameters from which the system calculates at least one parameter of rheological properties of the fluid product.

Claims

1. A computer-implemented method for contactless assessment of rheological properties of cement-based fluid products comprising: obtaining first data related to a displacement speed of a set of mixing blades contained in a mixer drum during at least one period of time; obtaining at least one image sequence of a fluid product contained within the mixer drum during the at least one period of time; determining a first parameter, in a first analysis, related to a variation of the displacement speed of the set of mixing blades; determining a second parameters, in a second analysis, related to a variation of a local displacement direction and speed of a surface of a fluid product contained in the mixer drum by implementing, in a computer processing unit, a second algorithm that: analyzes the at least one image sequence identifying particles, shapes, groups of particles, contours, and/or slopes of the surface of the fluid product and a displacement direction and speed thereof during the at least one period of time, indicative of a local displacement direction and speed of the surface of the fluid product; detects variation in the local displacement direction and speed of the surface of the fluid product obtained from the analysis of the at least one image sequence constitutive of the second parameter; calculating, in a third analysis, at least one rheological property parameter of the fluid product by implementing, in a computer processing unit, a third algorithm that: detects a correlation between each first parameter and at least one of the subsequent second parameters; and calculates, based on the detected correlations, at least one of the rheological property parameters of the fluid product.

2. The method according to claim 1, wherein the third algorithm, in order to calculate at least one rheological properties parameter of the fluid product, considers for said calculation data matrixes that store and correlate the following data of previous examples: variations in the displacement speed of the mixing blades; variations in the displacement direction and speed of the particles, shapes, groups of particles, contours, and/or slopes of the fluid product; at least one rheological properties parameter of each fluid product.

3. The method according to claim 2, wherein the third analysis comprises, on top of obtaining the composition and quantity of the analyzed fluid product, where the data matrixes taken into consideration by the third algorithm store and correlate, additionally, for each previous example, information about the composition and quantity of the fluid product.

4. The method according to claim 1, wherein the third analysis comprises: detecting and measuring a temporal gap existing between one starting moment of each first parameter and one starting moment of each respective second subsequent parameter and/or between one final moment of each first parameter and one final moment of each respective second subsequent parameter and utilize said temporal gap in the calculation of the rheological property parameters of the fluid product; and/or determining the duration of the variation that determines each first parameter, and the duration of the variation that determines each respective second subsequent parameter and utilize said durations of the variations in the calculation of the rheological property parameters of the fluid product.

5. The method according to claim 1, wherein the second algorithm comprises a visual recognition algorithm.

6. The method according to claim 1, wherein the acquisition of data related to the displacement speed of the mixing blades of the mixer drum comprises implementing in a computer processing unit, during the first analysis, a first algorithm that: analyzes the aforementioned at least one sequence of images of the fluid product; identifies edges, ridges, joints, lines, marks, and or stains on the mixing blades, and/or of the mixing drum when the mixing drum is a rotating drum, in the different images of the aforementioned at least one image sequence; tracks displacement direction and speed of the edges, ridges, joints, lines, marks, and or stains during at least a period of time.

7. The method according to claim 1, wherein the acquisition of data related to the displacement speed of the mixing blades of the mixer drum is performed through a device detecting the rotation of the mixer drum.

8. The method according to claim 1, wherein the acquisition of the first data comprises the acquisition of rotational speed of the mixing blades and also vertical and horizontal acceleration data of the mixer drum where the mixing blades are housed.

9. The method according to claim 8, wherein the at least one period of time, during which the first and second analysis are performed, is a period of time during which no relevant horizontal nor vertical accelerations of the mixer drum are detected.

10. The method according to claim 1, wherein the method comprises performing a fourth analysis, in a computer processing unit that implements a fourth algorithm, that comprises detecting when the rheological properties parameter is out of predefined bounds, and generate, in response to said detection, an alert signal.

11. The method according to claim 10, wherein the method comprises, in response to the alert signal, performing a fifth analysis, in a computer processing unit that implements a fifth algorithm that comprises: obtaining one information regarding the composition and quantity of the fluid product; calculating a series of modified rheological properties parameters of the fluid product, considering at least the information related to composition and quantity of the fluid product, the rheological properties parameter calculated by the third analysis, and a corrective admixture with a determined composition and quantity added to the fluid product, calculating the composition and quantity of said corrective admixture so that the modified rheological properties parameter of the fluid product fits within the predefined acceptable bounds.

12. The method according to claim 11, wherein the fifth algorithm takes into consideration, to perform said determination of the composition and quantity of the corrective admixture, data matrixes that store and correlate the following data of previous examples: composition and quantity of the different fluid products; at least one rheological properties parameter of each of the initial compositions; a composition and quantity of a corrective admixture added to each of said different fluid products; at least one rheological properties parameter of each of said different fluid products after the addition of the corrective admixture.

13. The method according to claim 1, wherein the method comprises detecting, through the first analysis, a stoppage of the mixing blades of the mixer drum, and performing a sixth analysis, in a computer processing unit that implements a sixth algorithm, comprising: detecting variations in the optical and/or smoothness properties of the surface of the fluid product, within the image sequence, during a period of time immediately after the detected stoppage, determining a sixth parameter; and using said sixth parameter in the calculation of the rheological properties of the fluid product.

14. The method according to claim 1, wherein the method comprises detecting a water addition and/or an admixture addition to the fluid product by performing a seventh analysis, in a computer processing unit that implements a seventh algorithm, comprising: analyzing the rheological properties of the fluid product detected in the third analysis detecting variations thereof over time; detecting unexpected variations of the rheological properties of the fluid product over time by comparing the detected variations with expected variations of the rheological properties of the fluid product over time due to its expected curing process, considering stored information about composition of the fluid product; detecting an amount of added water and/or added admixtures added to the fluid mixture responsible of the unexpected variations of the rheological properties of the fluid product over time by calculate the amount of added water and/or added admixtures required to, when mixed with the fluid product with known composition, modify the expected variations of the rheological properties of the fluid product over time to match with the detected variations of the rheological properties of the fluid product over time.

15. A system for the contactless assessment of rheological properties of cement-based fluid products comprising: a mixer drum with an opening and including mixing blades in its interior, and a device associated with the mixing blades and configured to obtain first data related to a displacement speed of a set of mixing blades contained in a mixer drum during at least one period of time; at least one image acquisition device focused towards the interior of the mixer drum and configured to obtain at least one image sequence of a fluid product contained within the mixer drum during the at least one period of time; and at least one computing unit that features at least one processor configured to implement a method comprising: determining a first parameter, in a first analysis, related to a variation of the displacement speed of the set of mixing blades; determining a second parameters, in a second analysis, related to a variation of a local displacement direction and speed of a surface of a fluid product contained in the mixer drum by implementing, in a computer processing unit, a second algorithm that: analyzing the at least one image sequence identifying particles, shapes, groups of particles, contours, and/or slopes of the surface of the fluid product and a displacement direction and speed thereof during the at least one period of time, indicative of a local displacement direction and speed of the surface of the fluid product; detecting variation in the local displacement direction and speed of the surface of the fluid product obtained from the analysis of the at least one image sequence, constitutive of the second parameter; calculating, in a third analysis, at least one rheological property parameter of the fluid product by implementing, in a computer processing unit, a third algorithm that: detects a correlation between each first parameter and at least one of the subsequent second parameters; and calculates, based on the detected correlations, at least one of the rheological property parameters of the fluid product.

16. The system according to claim 15, wherein the mixer drum rotates around an inclined axis, being the opening concentric to said axis, and being the mixing blades a set of helicoidal blades attached to the interior of the mixer drum's surface, being the mixer drum mounted on a truck, where the image acquisition device is located outside of the mixer drum facing the opening.

17. The system according to claim 16, wherein the system comprises a user interface, located in the truck's cabin, in communication with the aforementioned at least one computing unit to display at least some of the results of the calculations performed as a part of the method implemented by the at least one computing unit, wherein the computation unit is internal to the truck or is at least partially external to the truck in wireless communications with the rest of the system.

18. The system according to claim 17, wherein the system comprises, moreover, additional mixer drums associated to additional image acquisition devices.

19. The system according to claim 15, wherein the image acquisition device comprises one or more video cameras, and/or one or more infrared video cameras, and/or at one or more laser detection and location sensors (LIDAR).

20. A computer-based product comprising code instructions, that when executed by a computation device implement a method comprising: determining a first parameter, in a first analysis, related to a variation of the displacement speed of the set of mixing blades; determining a second parameters, in a second analysis, related to a variation of a local displacement direction and speed of a surface of a fluid product contained in the mixer drum by implementing, in a computer processing unit, a second algorithm that: analyzes the at least one image sequence identifying particles, shapes, groups of particles, contours, and/or slopes of the surface of the fluid product and a displacement direction and speed thereof during the at least one period of time, indicative of a local displacement direction and speed of the surface of the fluid product; detects variation in the local displacement direction and speed of the surface of the fluid product obtained from the analysis of the at least one image sequence, constitutive of the second parameter; calculating, in a third analysis, at least one rheological property parameter of the fluid product by implementing, in a computer processing unit, a third algorithm that: detects a correlation between each first parameter and at least one of the subsequent second parameters; and calculates, based on the detected correlations, at least one of the rheological property parameters of the fluid product.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0108] The present disclosure will become more fully understood from the following description of an exemplary embodiment taken in conjunction with the accompanying figures and drawings, which are to be understood as illustrative but not limiting, wherein like reference numerals refer to like elements, in which:

[0109] FIG. 1. is a schematic view of the side elevation of a concrete mixer truck featuring a mixer drum and equipped with the present system, according to a first embodiment in which all the components of the system are mounted on said truck, and the method is fully executed on said truck;

[0110] FIG. 2. Is a schematic view of the side elevation of a concrete mixer truck fleet, the system including a computation unit located remotely and in wireless communications with each of the trucks in the fleet, each of said trucks featuring a mixer drum and at least one image acquisition device.

[0111] FIG. 3A, FIG. 3B, and FIG. 3C are schematic views of the sequence of images from the mixer drum's interior acquired by the at least one image acquisition device, where the mixing blades and the surface of the fluid product are visible, where different particles, shapes, groups of particles, contours, and/or slopes of the fluid product, and the edges, ridges, joints, lines, marks, and or stains of the mixing blades are represented by rectangles, identified respectively during the second and first analysis, and where the displacement directions and speeds for the aforementioned identified elements are represented by arrows.

DETAILED DESCRIPTION OF AN EXEMPLARY EMBODIMENT

[0112] The enclosed drawings and figures show exemplary embodiments by way of illustration but not limitative of the present invention.

[0113] The system proposed in this disclosure, according to the embodiment represented by FIG. 1, includes a mixer drum 30, rotating along an inclined axis, mounted on a concrete mixer truck and featuring a set of helicoidal mixing blades 31 attached to the interior of said mixer drum, and a narrow opening concentric with the inclined axis and located on the top part of the mixer drum 30.

[0114] Located outside of the mixer drum 30, facing its opening and focused towards the interior of the mixer drum 30, is at least one image acquisition device 20, normally one or more video cameras, with normal and/or infrared vision, and/or a LIDAR measuring system providing a three-dimensional map of the volume of the mixing blades and the fluid product moving inside the interior of the mixer drum, providing detection of the slopes of the fluid product.

[0115] The system also comprises of at least one computation unit 10 featuring at least one processor and connected to said at least one image acquisition device 20 to acquire image sequences from the interior of the mixer drum 30, as shown on FIG. 3A, FIG. 3B and FIG. 3C.

[0116] Within this image sequence, provided as way of example, rectangles have been used to highlight some of the identified elements, as well as their displacement direction and speed schematically represented by arrows. The identified elements include particles and groups of particles on the surface of the fluid product, as well as a frontal edge that, in FIG. 3B and FIG. 3C flows over one of the mixing blades and falls, becoming a slope. Within these pictures a mark on one of the mixing blades has been identified and represented with a line, allowing for the automatic detection of the rotation speed and direction of the blades 31.

[0117] The positioning of the aforementioned at least one image acquisition device differs according to the particular design of each mixer truck and mixer drum, but generally it's located in an area close to the loading chute, so that it has a viewing angle sufficient to record at least a portion of the surface of the fluid product contained inside the mixer drum, preferably a major proportion of said product, considering also the different levels of filling of said rotating drum according to the volume of fluid product contained therein.

[0118] In some configurations the image acquisition device can be installed above the loading chute, while in others it can be installed below it. In general terms, one will try to install these devices in an angle relative to the mixer drum's axis in such way that a good view of its interior can be obtained, while they don't disturb or are affected by the loading of the fluid product into the mixer drum, and the cleaning of said drum.

[0119] Given the characteristics of the loading and subsequent cleaning of the mixer truck (indispensable after each load) that are commonplace, it's proposed in one embodiment that said at least one image acquisition device 20 is fixed to the rest of the truck with a movable support, switching from an operation position, as described so far, to a folded or protected position in which said at least one image acquisition device 20 is kept removed from the drum's opening, facilitating the loading, cleaning, and unloading operations, thus protecting said device.

[0120] Optionally, the displacement of said at least one image acquisition device 20 can be an automatic displacement, controlled by the computation unit 10, for instance, when the acquisition of images is required to execute the proposed method.

[0121] Optionally, it is proposed that the truck's cabin includes a user interface 11, usually a screen or touchscreen, that displays to the driver the information provided by the system, in particular the rheological properties parameters of the fluid product calculated by the system, as well as suggested admixtures to be added, in case these are calculated. Optionally, this user interface may be a wireless interface, featuring a battery that allows for its operation outside the truck's cabin as well. In this case the interface can be a mobile phone, a tablet, a laptop computer, or any other equivalent device, featuring a specific software application, acting as the user interface 11.

[0122] This user interface 11 may alert of deviations of the rheological characteristics, speed of rotation and number of revolutions of the drum during transport, actions taken automatically by the system or actions that the user needs to authorize and/or perform manually, etc. This element is used, additionally, to obtain information about the visual assessment of rheological properties that the drivers perform, as is commonplace in the industrial practice, and use said information to improve the training of the Artificial Intelligence algorithms. There are certain mechanisms to promote participation and precision in these assessments, such as “gamification” techniques where the visual rheological assessment becomes a competitive game between drivers and rewards the ones that provide the most precise evaluations.

[0123] Given that the optical devices that are part of the at least one image acquisition device are delicate, additional measures can be added to protect them during the loading and subsequent cleaning operations. These can take multiple forms, for example, the aforementioned movable support, and/or an air current that blows away dust and droplets from the optical devices, and/or a sprayed water jet device to clean the optical devices, etc.

[0124] The system is able to determine, through the analysis of at least one sequence of images obtained by the image acquisition device 20, if the vision of the cameras and/or LIDAR is totally or partially obstructed, if the cameras lost focus, if the viewing angle is incorrect, etc.

[0125] Signaling elements may be added to the rotating mixer drum, in a way that they don't affect the normal operations (e.g. a small plate with a bar or QR code, or a certain clearly distinguishable color and/or shape, etc.), that help in determining the correct calibration of both the image quality and the viewing angle of the optical devices.

[0126] In case the system detects any inconvenient and when it's not able to correct it automatically, it will emit an alert to the corresponding personnel indicating the issue and the necessary adjustment; once resolved it will check again for a correct operation and inform the corresponding personnel whether the intervention has been successful or not.

[0127] Additionally, the system may feature a light source to light up the interior of the mixer drum 30, that is activated when convenient, to improve the quality of the acquired images, facilitating their subsequent analysis. This light source may be of white light and/or of particular wavelengths (colors), adjusted or automatically adjustable, that improve the image acquisition and subsequent processing.

[0128] The system comprises at least one memory storage unit that stores the acquired images. The system may also include a wireless communications antenna for the transmission of information to remote devices, to a wireless user interface 11, and/or to receive instructions. Said wireless antenna may be used, for instance, to communicate to the system relevant information about the fluid product loaded inside the mixer drum 30, for example the composition and quantity of fluid product, the predefined acceptable range of rheological properties parameters, etc.

[0129] Optionally the computation unit 10 and the user interface 11 may be integrated in a single device.

[0130] The computation unit 10 will be, in a preferred embodiment, a computer with enough capacity to perform certain analysis in real time and without the need to connect to a central server, given that said unit has already stored the necessary Artificial Intelligence models to apply in each case; said models can be downloaded automatically for each load and for each fluid product composition, in case they can't all be stored in its internal memory storage. This type of computers is commonplace in the industrial practice, for instance models such as Raspberry Pi, Arduino, and similar.

[0131] It is possible to incorporate one or more remote computation units, such as servers and/or central computers, that store all the records, video files, images, etc., and that generate the analysis models used by the system mounted on the truck, based on Artificial Intelligence learning algorithms. In other words, these remote units will store historical data of past examples, which will be used for the calculations of the proposed method, and/or for the improvement of the algorithms employed for said calculations.

[0132] These units carry out all the functions that, given their capacity, cannot be performed by the units mounted on the truck, and those that are not necessary in real time, such as the storage of historical data (databases, etc.), generating and updating Artificial Intelligence evaluation models, etc.

[0133] Optionally, the system can include a cleaning system for the lenses and optical devices, that can be activated automatically when needed, for instance a water or air pressure cleaning; the concrete mixer trucks feature as standard said pressurized circuits.

[0134] Optionally, other sensors can be included, such as sensors that determine the inclination angle of the truck, both in the longitudinal as the transversal axes, to take this information into consideration when evaluating the rheological properties of the fluid product. Additionally, horizontal and vertical acceleration sensors can be included, to account for the movement of the truck when performing the rheological assessment, or to discard certain data that are obtained during periods with considerable accelerations.

[0135] Optionally, images and video recordings can be obtained of the control and acceptance tests, such as the Abrams Cone test (ASTM C-143), to add this information to the training data set and thus be able to perform quantitative and qualitative assessments with a higher degree of precision and quality. For this purpose, it is planned to use a portable camera, for instance integrated into the wireless user interface device 11, or attached to a stand, a tripod, a support arm, etc., that fixes the camera in an adequate and reproducible position (within a tolerance margin), optionally a sheet or plate to improve contrast, and/or a light source. This camera will record the performance of the various rheological assessment tests and can obtain both quantitative and qualitative data of the fluid product, which are constantly incorporated into the data matrixes that feed the learning and evaluation models.

[0136] According to another embodiment as per FIG. 2, the aforementioned at least one computation unit 10, or at least some parts of it, are external to the truck, minimizing thus the number and complexity of the devices mounted on the truck, and said computation unit may, in turn, control additional mixer drums 30′, each featuring at least one additional image acquisition device 20′, equivalent to the mixer drum 30 and the image acquisition device 20 described so far.

[0137] In this way, the devices mounted on the trucks are minimized, and resources can be shared, allowing central computing unit to perform most of the calculations for the multitude of trucks in a fleet.

[0138] Regarding the proposed method, FIG. 3A, FIG. 3B, and FIG. 3C show a schematic sequence of images from the interior of the mixer drum 30 obtained by an image acquisition device 20, where it can be noticed that the mixing blades 31 of the mixer drum 30 have turned and thus a displacement of the particles of the surface of the fluid product has occurred.

[0139] In these figures the particles, edges, marks, etc., have been represented with rectangles, automatically detected by the algorithms, and the arrows represent the displacement direction and speed of said detected elements.

[0140] It can be appreciated in these figures how the fluid product flows over the front of one of the mixing blades 31, as said blades 31 turns. The detection of said overflow, of the height reached by the fluid product before flowing over, of the speed of the fall, and/or of its contour during said fall are particularly revealing of the rheological properties of the fluid product.

[0141] The fluid cement-based products, such as concrete, are often modelled as a plastic or Bingham fluids, which have a minimum yield stress required to produce a displacement (usually described in term of a shear or agitation speed, “shear rate”). The relationship between the shear rate and the shear stress necessary to produce movement in the fluid is known as viscosity, and can be deduced from the slope of the curve when represented on a shear rate vs. shear stress diagram.

[0142] Due to these rheological characteristics, the agitation or mixing speed of the fluid product is a key parameter for the rheological evaluation, therefore the proposed system is capable of assessing the rheology of the fluid product in question at different mixing speeds, which can be even zero (resting speed), thus considering the effect of accelerations and decelerations of the mixer drum to perform and improve the evaluation. The concrete mixer trucks always feature a rotation speed control for the mixer drum, on which the system can actuate if the truck's configuration allows, or instruct the truck driver to modify said rotation speed to perform the rheological evaluation. For this reason, the computation unit of the proposed system may have direct control over said speed of rotation of the mixer drum, or can instruct the operator, typically the truck driver, through the aforementioned user interface 11.

[0143] During the agitation or mixing, the system evaluates the volume of fluid product contained within the mixer drum and its movement, for particles or groups of particles that can be identified on the surface (evaluating position, rotation, speed, direction, acceleration, etc.) as well as the whole surface of the whole of the fluid product, for instance determining the height the fluid product reaches over the mixing blades before flowing over and falling, angles and slopes that the fluid product reaches inside the mixer drum, if during the fall the fluid product remains together or it separates into chunks or droplets (may also include the size, shape, distribution, etc. of said droplets), if it generates splashes as it falls, among others.

[0144] The evaluation of the fluid product at low mixing speed, or at resting speed, and specially during the transition between mixing and resting speeds, on top of allowing for a better quantitative evaluation, also allows for a qualitative evaluation of characteristics like segregation (sinking of the larger particles to the bottom due to density differences and loss of cohesion), the effect known as “bleeding” (appearance of a liquid phase, usually of a different shade and/or with spots, on the surface, which may also be accompanied by the appearance of bubbles and/or foam), among others, that cannot be appreciated when the fluid product is being mixed because these effects do not occur while the fluid product is being agitated.

[0145] Besides the aforementioned, the present system is capable of determining, also by visual analysis and using the same hardware devices, the speed and direction of rotation of the mixer drum, and record the number of rotations. Both the rotation speed during transport as the number of revolutions are usually limited (with minimum and maximum values) in the applicable standards.

[0146] Additionally, the system can check that the mixing or “re-mixing” process is carried out according to specifications, understood as a minimum amount of time and/or number of revolutions that the mixer drum must rotate at a minimum predefined speed, after the addition of any substance used to modify the rheological properties of the fluid product, such as water and/or admixtures.

[0147] Additionally, the system can detect the addition of water, admixtures, and other materials, whether authorized or not, through the analysis of the acquired images. A complete video recording of the entire loading, transport, and unloading process can be stored, to improve the traceability of the whole process, and for that end any obstruction or deactivation of the system can also be recorded and flagged as suspicious activity of unauthorized manipulation or tampering, especially if by the end of said obstruction or interruption a noticeable change has taken place in the rheology of the fluid product.

[0148] Yet another advantage is that, given known additions of water and/or admixtures, a “before-and-after” evaluation can be performed, and by knowing the composition and proportions of raw materials in the fluid product, they allow the personnel versed in mix composition design to obtain water and/or admixtures dosage vs. rheological properties curves, such as water content vs. slump, which are a very useful tool when employed in the design and optimization of mix compositions. The system can record and produce said curves and relationships automatically based on data coming from different sources.

[0149] The system can also detect, moreover, rheological variations that are difficult to explain based on the proportions of raw materials in the mix, in other words, when the proportions and loading of said raw materials components are correct. This occurrence is commonplace in the industrial practice, and may indicate that one or more of the raw materials employed have changed in their characteristics, thus producing a change in the rheology of the fluid product, even when their dosage has been the same as in past occasions. This may also indicate a miscalibration of one or more raw materials scales and/or dosage systems at the batching facility. Even though the system is not intended to identify the causes of these variations, the mere detection and immediate notification to the corresponding personnel provides great value and novelty.

[0150] The system can detect lumps of dry materials inside the fluid product, that are usually caused in certain loading conditions when the aggregates and the cement are not fully mixed with the water, and also when the aggregates employed in the production already contain such lumps or particle agglomerations (usually caused by contamination with clays). The system can also detect other anomalous materials when their size is large enough (for instance, starting at double the maximum size of aggregates and upwards), such as pieces of wood, plastics, etc., that are usual contaminations of the aggregates and are detrimental to the performance and/or casting of the fluid product.

[0151] Yet another advantage of the system is that it can estimate the remaining volume of the fluid product inside the mixer drum based on the visual information acquired of the fluid product in movement and/or resting, and/or from three-dimensional information of the fluid product in movement and/or resting, and/or by the number of revolutions of the mixer drum in the loading and unloading direction. This complementary information is of high value in the industrial practice, both for the determination of poured volume as for remainders of returned products, and/or for the addition of water and/or admixtures in a correct proportion if it was necessary to adjust the rheology of a partial load, for instance, when the pouring procedure is slow and the remainder product loses fluidity after some time.

[0152] The system can also detect a remainder of fluid product and/or washing water inside the mixer drum prior to a new load, and alert the corresponding personnel. It's a frequent problem in the industry that trucks, that are supposedly empty, enter the loading area with washing water still inside the drum, which alters the rheology of the fluid product loaded into them and produces quality issues.

[0153] Furthermore, the system can detect damage and/or wear of the mixer drum and its mixing blades, for instance, the loss of wear plates that are usually welded to the edge of the mixing blades so that abrasion of the fluid product does not wear the blades out.

Example 1

[0154] According to a particular exemplary embodiment, a single video camera is installed and a complete load (six cubic meters) of the fluid product is analyzed for its behavior during transport inside a concrete mixer truck, for concrete product of type HA25/B/20/IIa (in Spain it's one of most commonly used reinforced concrete mixes), with the following composition for one cubic meter of concrete: [0155] Cement CEM II A-M (P-L) 42.5 R: 280 kg [0156] Fine aggregate: natural siliceous sand AF-0/4-M-S-L (4.34% moisture content): 897 kg [0157] Coarse aggregate: crushed siliceous gravel AG-4/20-M-S (0.57% moisture content): 950 kg [0158] Water (network): 160 liters [0159] Plasticizer admixture: Sikaplast 1003: 1.68 kg [0160] Superplasticizer admixture: Sikament 3003: 2.52 kg

[0161] Some properties of the constituent materials are known, for example the grading curves (particle size distribution) of the fine and the coarse aggregates, the sand equivalent of the fine aggregate, the moisture content and water absorption of the aggregates, etc., as well as characteristics of the cement, admixtures, and the mixing water. All materials comply with the standards'specifications for their use in concrete production. It's verified that the concrete mixer truck does not have any remainders of washing water from a previous load, nor any other materials prior to loading.

[0162] The following values have been obtained on the tests performed on the fresh concrete: [0163] Slump, as per Abrams Cone test (ASTM C-143): 60 mm [0164] Air content: 3.9% [0165] Density: 2259 kg/m.sup.3 [0166] Electrical resistivity (manual resistivity meter with 4 electrodes): 5 Ohm/m [0167] Visual assessment: standard workability, no segregation or bleeding, correct proportion of fine and coarse aggregates. All the values obtained are within normal ranges for the mixture at hand.

[0168] Both the mixture composition and the characteristics of the raw materials, as well as the test results of fresh concrete and visual assessments were made available to the Artificial Intelligence system that correlates said information with the images acquired by the camera during the mixing inside the truck's drum. Based on a certain amount of test results and image analysis the system is capable of adjusting the different relative weights of the neural networks to identify the properties of the images leading to a rheology assessment, in this example expressed as millimeters of slump according to the Abrams Cone test as described in ASTM C-143, with a high-enough degree of confidence.