Ready-mixed concrete slump digital prediction method based on rheological parameters and stirring current

Abstract

The invention relates to a monitoring technology in the technical field of premixed concrete production, and discloses a rheological parameter and stirring current-based premixed concrete slump digital prediction method, which comprises the following steps: recording an idle current I0 and a stable current I before feeding of a stirrer, and recording the idle current I0 and the stable current I within a specified time, measuring a plastic viscosity value eta and yield stress 0 of the mixture by using a concrete rheometer, and recording current stabilization time Tx, total stirring time T and slump YX at the end of stirring; then, a function model of the slump value of the concrete mixture, the idle current, the stable current, the plastic viscosity, the yield stress, the stirring time and the total stirring time is established according to multiple times of actual measurement data; a digital prediction module for the performance of the concrete mixture is established by fitting multiple groups of actually measured data, so that the slump value of the concrete mixture is predicted in real time before the concrete mixture is discharged, a mixing station is helped to further optimize the mixing time according to construction requirements, and the method is easy to operate, concise and efficient.

Description

Technical Field

[0001] The invention relates to monitoring technology in the technical field of ready-mixed concrete production, in particular to a digital prediction method for the slump of ready-mixed concrete based on rheological parameters and stirring current. Background Art

[0002] With the development of intelligent construction industry, various production facilities of concrete mixing plants are also becoming more precise and digitalized. However, the flow performance of ready-mixed concrete and the stability of factory quality have always been the most difficult problems to deal with in the supply process of concrete mixing plants. The most common complaint from construction units is that the slump of concrete does not meet the requirements of the construction site, sometimes too large, sometimes too small. The return of concrete due to insufficient slump has caused huge losses to the concrete mixing plant. In order to ensure the slump of concrete when it arrives at the site, in addition to reducing the slump loss during transportation, it is particularly important to accurately control the slump of concrete before it leaves the mixing station.

[0003] Before producing a concrete mix of a specific strength grade, concrete manufacturers usually conduct trial mixes and adjustments on a laboratory mixer. However, when the adjusted mix is ​​mixed in a large mixer, due to the difference in mixing power and the deviation in the moisture content of sand and gravel, the slump of the large mixer is quite different from that of the laboratory, and the fluctuation is also large. In production, the slump of concrete out of the machine is judged by naked eye observation using a camera, and the judgment error caused by human influence is also large. Therefore, it is necessary to establish a real-time, digital prediction method for the slump of concrete mixtures in the mixing plant.

[0004] At present, some mixing stations have partially regulated the slump of concrete based on the change of the mixing current of the mixer. For concrete of the same strength grade, there are different slumps (120-160mm), while the working current of the mixer is still similar, and the amplitude change is not significant. Based on the mixing current, only the approximate range of the slump can be predicted, and the accuracy is not accurate enough to effectively represent the actual slump out of the machine. In practice, concretes of different strength grades and the same slump have great differences in rheology. When the slump is the same, concretes with higher strength grades usually have higher yield stress and may lose more slump over time. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the problems of inaccurate slump judgment and low degree of digitization of concrete mixture in mixing stations in the prior art, and to provide a digital prediction method for the slump of premixed concrete based on rheological parameters and stirring current, so as to realize precise control of the slump and mixing time of concrete mixture in the mixer.

[0006] To achieve the above object, the present invention provides the following technical solution: a digital prediction method for the slump of ready-mixed concrete based on rheological parameters and stirring current, comprising the following steps:

[0007] (1) Determine a concrete production line and a concrete grade to be produced;

[0008] (2) Before feeding, record the mixer idling current I0; after the mixing plant finishes feeding and concrete mixing begins, record the mixer stable current I, the unit of current value is A;

[0009] (3) Within 2 minutes after the current stabilizes, record the concrete plastic viscosity value η measured by the concrete rheometer in Pa·s; record the concrete yield stress 0 measured by the concrete rheometer in Pa;

[0010] (4) Record the stirring current stabilization time Tx and the total stirring time T, both in seconds;

[0011] (5) At the end of the test mixing (i.e. time T), the slump of concrete is YX, in mm;

[0012] (6) Repeat steps (2) to (5) to obtain multiple sets of idling current, stable current, plastic viscosity, yield stress, current stabilization time, total stirring time, and slump data, and establish a function model of slump, stirring current, and rheological parameters based on the multiple sets of data;

[0013] (7) Based on the function model established in step (6), a digital module for predicting the slump of concrete mixture is established to calculate the slump value of a certain grade of concrete with different mixing times.

[0014] Preferably, the model used by the concrete rheometer to test plastic viscosity and yield stress is the Bingham model.

[0015] Preferably, the value of the idling current of the mixer is completed within 2 minutes of the no-load operation of the mixer, and the value of the stable current is completed within 5 minutes after 1 minute of starting the feeding and stirring.

[0016] Preferably, the stirring current stabilization time here is taken as the moment when the current fluctuation is no longer greater than 0.5 A, and can be adjusted as appropriate according to the difference in grid voltage.

[0017] Preferably, a cross-plate rheometer is used, and the test is set to reach a set breakdown speed of 0.6 rps within a breakdown time of 15-30 s, and then the shear speed is decreased in a step-by-step manner. During the step-down section, a torque value is collected every 2-10 s until the rotor stops. 10-50 torque values ​​are collected for each set of tests, and then the plastic viscosity η (Pa*s) and yield stress 0 (Pa) of the concrete are automatically converted by the instrument.

[0018] Preferably, the established slump prediction digital module is implemented by the following steps:

[0019] (1) Built-in prediction model, fitting required data ≥ 12 groups;

[0020] (2) The prediction model is fitted using a multivariate linear model, i.e., Y = a*(I-I0)+b*η+c*0+d*(T-Tx)+e, where a, b, c, d, e are constants obtained from the fitting, I0-idling current, I-stable current, η-plastic viscosity, 0 yield stress, Tx-stable time, T-total stirring time, and Y-predicted slump;

[0021] (3) The prediction model obtained by fitting was significant at P<0.05.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] The present invention utilizes the relationship between concrete mixing current, mixing time and concrete rheological properties, and establishes a digital prediction module for concrete mixture performance by fitting multiple groups of measured data, thereby realizing real-time prediction of the slump value of the concrete mixture before it leaves the machine, thereby predicting the actual working performance of the mixture, optimizing the mixing time of each batch of concrete, effectively improving the efficiency of concrete fluidity control work in the mixing station, reducing the frequency of returns due to unqualified slump, and helping the mixing station to trace production quality. The invention is easy to operate, simple and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 The concrete related parameters of Example 1 of this patent;

[0025] Figure 2 The concrete related parameters of Example 2 of this patent;

[0026] Figure 3 Shear regime designed for this patented rheological test module;

[0027] Figure 4 This is an illustration of the working of the digital prediction module of this patent. DETAILED DESCRIPTION

[0028] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings. The specific implementation described here is only used to explain the present invention, and does not limit the present invention.

[0029] Embodiment 1:

[0030] (1) A C40 concrete production line was determined;

[0031] (2) In each test: before adding materials, record the mixer idling current I0; 1 minute after the mixing plant starts mixing materials, record the mixer stable current I; within 2 minutes after the current stabilizes, record the concrete plastic viscosity value η measured by the concrete rheometer; record the concrete yield stress 0 measured by the concrete rheometer; record the stirring current stabilization time Tx and the total stirring time T; test the concrete slump YX at the end of mixing (i.e. time T);

[0032] (3) Repeat step (2) to obtain multiple sets of idling current, stable current, plastic viscosity, yield stress, current stabilization time, total stirring time and slump data, and establish a function model of slump, stirring current and rheological parameters based on the multiple sets of data. The specific data are shown in Table 1, and the multivariate linear fitting model is shown in Formula 1, Y = -2.87*(I-I0)-3.95*η-0.02*0+0.22*(T-Tx)+360.74;

[0033] (4) Input the function model established in step (3) into the digital prediction module for concrete mixture slump prediction, and use the module to control the performance of concrete mixture out of the machine. For example, there is a group of C40 concrete production with an idling current of 38.7A, a stable current of 47.4A, a current plastic viscosity of 47.7Pa*s, a yield stress of 692Pa, and the current begins to stabilize 67s after mixing. It is expected to reach a slump of 160mm out of the machine. According to formula 1, the total mixing time can be inversely calculated to be 185s.

[0034] Embodiment 2:

[0035] (1) A C30 concrete production line was determined;

[0036] (2) In each test: before adding materials, record the mixer idling current I0; 1 minute after the mixing plant starts mixing materials, record the mixer stable current I; within 2 minutes after the current stabilizes, record the concrete plastic viscosity value η measured by the concrete rheometer; record the concrete yield stress 0 measured by the concrete rheometer; record the stirring current stabilization time Tx and the total stirring time T; test the concrete slump YX at the end of mixing (i.e. time T);

[0037] (3) Repeat step (2) to obtain multiple sets of idling current, stable current, plastic viscosity, yield stress, current stabilization time, total stirring time and slump data, and establish a function model of slump, stirring current and rheological parameters based on the multiple sets of data. The specific data are shown in Table 2, and the multivariate linear fitting model is shown in Formula 2, Y = -17.68*(I-I0)-0.93*η+0.70*0-0.08*(T-Tx)+74.30;

[0038] (4) Input the function model established in step (3) into the digital prediction module for concrete mixture slump prediction, and use the module to control the performance of concrete mixture out of the machine. For example, there is a group of C30 concrete production with an idling current of 38.2A, a stable current of 42.9A, a current plastic viscosity of 42.6Pa*s, a yield stress of 346Pa, and the current begins to stabilize 65s after mixing. It is expected that the material will be discharged after the mixing stops at 180s. According to formula 2, the slump of the concrete can be predicted to be 185mm.

Claims

1. A digital prediction method for the slump of ready-mixed concrete based on rheological parameters and stirring current, characterized in that: The steps include: (1) Determine a concrete production line and a concrete grade to be produced; (2) Before feeding, record the mixer idling current I0; after the mixing plant finishes feeding and concrete mixing begins, record the mixer stable current I, the unit of current value is A; (3) Within 2 minutes after the current stabilizes, record the concrete plastic viscosity value η measured by the concrete rheometer in Pa·s; record the concrete yield stress 0 measured by the concrete rheometer in Pa; (4) Record the stirring current stabilization time Tx and the total stirring time T, both in seconds; (5) At the end of the test mixing (i.e. time T), the slump of concrete is YX, in mm; (6) Repeat steps (2) to (5) to obtain multiple sets of idling current, stable current, plastic viscosity, yield stress, current stabilization time, total stirring time, and slump data, and establish a function model of slump, stirring current, and rheological parameters based on the multiple sets of data; (7) Based on the function model established in step (6), a digital module for predicting the slump of concrete mixture is established to calculate the slump value of a certain grade of concrete with different mixing times.

2. A digital prediction method for the slump of ready-mixed concrete based on rheological parameters and stirring current according to claim 1, characterized in that: The model used by the concrete rheometer to test plastic viscosity and yield stress is the Bingham model.

3. A digital prediction method for slump of ready-mixed concrete based on rheological parameters and stirring current according to claim 1, characterized in that: The value of the mixer's idling current is taken within 2 minutes of the mixer's no-load operation, and the value of the stable current is taken within 5 minutes after 1 minute of starting material feeding and stirring.

4. A digital prediction method for slump of ready-mixed concrete based on rheological parameters and stirring current according to claim 1, characterized in that: Here, the stirring current stabilization time is taken as the moment when the current fluctuation no longer exceeds 0.5A, and can be adjusted as appropriate according to the difference in grid voltage.

5. The method for digitally predicting the slump of ready-mixed concrete based on rheological parameters and stirring current according to claim 1, characterized in that: Using a cross-plate rheometer, the test was set to reach a set breakdown speed of 0.6 rps within a breakdown time of 15-30 s, and then the shear speed was decreased in steps. During the step-down section, a torque value was collected every 2-10 s until the rotor stopped. Each set of tests collected 10-50 torque values, which were then automatically converted by the instrument to obtain the plastic viscosity η (Pa*s) and yield stress 0 (Pa) of the concrete.

6. The method for digitally predicting the slump of ready-mixed concrete based on rheological parameters and stirring current according to claim 1, characterized in that: The established slump prediction digital module is implemented through the following steps: (1) Built-in prediction model, fitting required data ≥ 12 groups; (2) The prediction model is fitted using a multivariate linear model, i.e., Y = a*(I-I0)+b*η+c*0+d*(T-Tx)+e, where a, b, c, d, e are constants obtained from the fitting, I0-idling current, I-stable current, η-plastic viscosity, 0 yield stress, Tx-stable time, T-total stirring time, and Y-predicted slump; (3) The prediction model obtained by fitting was significant at P<0.05.

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