CN119189028A - A concrete mixing control method suitable for high temperature and high humidity environment - Google Patents
A concrete mixing control method suitable for high temperature and high humidity environment Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B28—WORKING CEMENT, CLAY, OR STONE
- B28C—PREPARING CLAY; PRODUCING MIXTURES CONTAINING CLAY OR CEMENTITIOUS MATERIAL, e.g. PLASTER
- B28C5/00—Apparatus or methods for producing mixtures of cement with other substances, e.g. slurries, mortars, porous or fibrous compositions
- B28C5/003—Methods for mixing
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B28—WORKING CEMENT, CLAY, OR STONE
- B28C—PREPARING CLAY; PRODUCING MIXTURES CONTAINING CLAY OR CEMENTITIOUS MATERIAL, e.g. PLASTER
- B28C7/00—Controlling the operation of apparatus for producing mixtures of clay or cement with other substances; Supplying or proportioning the ingredients for mixing clay or cement with other substances; Discharging the mixture
- B28C7/0007—Pretreatment of the ingredients, e.g. by heating, sorting, grading, drying, disintegrating; Preventing generation of dust
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B28—WORKING CEMENT, CLAY, OR STONE
- B28C—PREPARING CLAY; PRODUCING MIXTURES CONTAINING CLAY OR CEMENTITIOUS MATERIAL, e.g. PLASTER
- B28C7/00—Controlling the operation of apparatus for producing mixtures of clay or cement with other substances; Supplying or proportioning the ingredients for mixing clay or cement with other substances; Discharging the mixture
- B28C7/02—Controlling the operation of the mixing
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Abstract
本发明涉及混凝土拌合领域，公开了适用于高温高湿环境的混凝土拌合控制方法，用于解决进行混凝土拌合时，会出现无法根据实际情况自动进行搅拌时间控制的问题，包括，获取拌合设备的情况数据，根据拌合设备的情况数据评估得到设备影响系数，获取原材料数据，根据原材料数据评估得到材料影响系数，通过温湿度传感器，获取拌合车间的温度与湿度，根据拌合车间的温度与湿度评估得到环境影响系数，根据设备影响系数、材料影响系数以及环境影响系数综合评估得到拌合时间调节指数，根据拌合时间调节指数得到实际拌合时间，根据实际拌合时间对混凝土拌合时间进行控制。本发明有效实现自动对拌合时间的调整，提高拌合效率。
The present invention relates to the field of concrete mixing, and discloses a concrete mixing control method suitable for a high temperature and high humidity environment, which is used to solve the problem that the mixing time cannot be automatically controlled according to the actual situation when the concrete is mixed, including obtaining the situation data of the mixing equipment, evaluating the equipment influence coefficient according to the situation data of the mixing equipment, obtaining the raw material data, evaluating the material influence coefficient according to the raw material data, obtaining the temperature and humidity of the mixing workshop through a temperature and humidity sensor, evaluating the environmental influence coefficient according to the temperature and humidity of the mixing workshop, comprehensively evaluating the equipment influence coefficient, the material influence coefficient and the environmental influence coefficient to obtain a mixing time adjustment index, obtaining the actual mixing time according to the mixing time adjustment index, and controlling the concrete mixing time according to the actual mixing time. The present invention effectively realizes the automatic adjustment of the mixing time and improves the mixing efficiency.
Description
Technical Field
The invention relates to the field of concrete mixing, in particular to a concrete mixing control method suitable for a high-temperature and high-humidity environment.
Background
The concrete mixing is a process of uniformly mixing cement, sand, cobble, water and necessary additives or blending materials according to a certain mixing ratio to prepare the concrete mixture which has good workability and meets the construction requirements. The process is a key link of concrete production, directly influences the performance and engineering quality of the concrete, and needs to strictly control parameters such as raw material quality, proportion ratio, mixing time and the like.
Concrete mixing is a core process in concrete production, directly affecting its workability, uniformity and final strength and durability. Conventional concrete mixing methods typically set a fixed mixing time according to empirical formulas or industry specifications under standard environmental conditions. However, in a high-temperature and high-humidity environment, many dynamic factors can obviously influence the mixing quality and temperature rise of concrete, and the existing concrete mixing method lacks a mixing time control mechanism based on multi-factor dynamic adjustment, so that the problems of over-stirring or non-uniformity caused by fixed stirring time cannot be avoided.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a concrete mixing control method suitable for a high-temperature high-humidity environment, which can meet the mixing control of concrete in the high-temperature high-humidity environment.
The invention solves the technical problems by the following technical proposal:
The concrete mixing control method suitable for the high-temperature and high-humidity environment comprises the following steps of:
Step 1, acquiring condition data of mixing equipment, wherein the condition data comprise the abrasion degree of a mixing blade, the rotating speed of a mixing building and the internal temperature of the mixing building, and evaluating and obtaining equipment influence coefficients according to the condition data of the mixing equipment;
step 2, raw material data are obtained, wherein the raw material data comprise aggregate moisture content, cement temperature and aggregate size distribution degree, and material influence coefficients are obtained according to raw material data evaluation;
Step 3, acquiring the temperature and the humidity of a mixing workshop through a temperature and humidity sensor, and evaluating according to the temperature and the humidity of the mixing workshop to obtain an environmental influence coefficient;
step 4, comprehensively evaluating according to the equipment influence coefficient, the material influence coefficient and the environment influence coefficient to obtain a mixing time adjustment index in the following manner In the followingExpressed as a blending time adjustment index,Represented as a device influence coefficient,Expressed as a coefficient of influence of the material,Represented as an environmental impact coefficient,、、Weight coefficients expressed as device influence coefficients, material influence coefficients, and environmental influence coefficients;
and 5, obtaining actual mixing time according to the mixing time adjustment index, and controlling the concrete mixing time according to the actual mixing time.
Preferably, the step of obtaining the equipment influence coefficient according to the condition data evaluation of the mixing equipment comprises the following steps:
a vibration sensor is arranged at the key part of the mixing building;
Recording vibration signals generated in the running process of the mixing building through a vibration sensor, setting sampling frequency and sampling time, and acquiring the signals in a time sequence;
Removing high-frequency noise and low-frequency interference by using a band-pass filter, and only reserving signals related to the vibration of the stirring blade, namely stirring blade vibration signals;
acquiring vibration signal data of the stirring blade during initial operation, recording the vibration signal data as an initial vibration signal, and obtaining a vibration difference value of each moment according to a difference value of the vibration signal of the stirring blade and the initial vibration signal at each moment;
Clustering the vibration difference values at each moment, and calculating according to the clustering result to obtain the abrasion degree of the stirring blade;
acquiring the current rotating speed of the mixing building, the current internal temperature of the mixing building, the standard rotating speed of the mixing building, the ideal operating temperature of equipment and the highest internal temperature allowed by the equipment in real time;
According to the abrasion degree of the stirring blade, the rotating speed of the stirring building and the temperature evaluation inside the stirring building, the equipment influence coefficient is obtained, and the specific acquisition mode is as follows:
;
In the formula, Represented as a device influence coefficient,Expressed as the degree of wear of the stirring vanes,The standard rotating speed of the mixing tower is shown,In order to mix the current rotational speed of the building,Indicated as the current internal temperature of the mixing plant,Indicated as the ideal operating temperature of the device,Expressed as the highest internal temperature allowed by the device.
Preferably, the step of clustering the vibration difference values at each moment includes:
Step 1.1, taking the vibration difference values as clustering characteristics, taking the vibration difference values at all moments in the detection time as a data set, and taking each vibration difference value in the data set as a data point;
step 1.2, determining an optimal cluster number K of the data set by using an elbow method;
Randomly selecting K data points in a data set as initial clustering centers, calculating Euclidean distances from the data points to the initial clustering centers, traversing the K initial clustering centers for each data point, and distributing the K initial clustering centers to the cluster clusters corresponding to the initial clustering centers closest to the initial clustering centers;
step 1.4, traversing all data points to obtain initial clustering clusters, and calculating the average value of the data points in each initial clustering cluster to obtain a new clustering center;
And 1.5, repeating the step 1.3 and the step 1.4 until the clustering center is not changed any more, and obtaining a final clustering cluster and a final clustering center.
Preferably, the step of calculating the wear degree of the stirring blade according to the clustering result comprises the following steps:
Calculating the ratio of the number of data points in each final cluster to the total number of data sets to obtain the weight of each final cluster;
Weighting and summing the weight of each final cluster and the final cluster center to obtain the abrasion degree of the stirring blade, wherein the calculation formula is as follows WhereinExpressed as the degree of wear of the stirring vanes,Expressed as the weight of the j-th final cluster,Denoted as the j-th final cluster center, K is the best cluster number for the dataset.
Preferably, the step of obtaining the material influence coefficient according to the raw material data evaluation comprises the following steps:
installing a moisture sensor in the aggregate conveying belt, and monitoring the moisture content of the aggregate in real time through the moisture sensor;
monitoring the cement temperature in real time by using an infrared thermometer;
acquiring diameter data of the aggregate through a screening experiment, and evaluating according to the diameter data of the aggregate to obtain the size distribution degree of the aggregate;
according to the aggregate moisture content, the cement temperature and the aggregate size distribution degree, the material influence coefficient is obtained by evaluation, and the concrete obtaining mode is as follows:
;
In the formula, Expressed as a coefficient of influence of the material,For the degree of size distribution of the aggregate,The water content of the aggregate is the water content of the aggregate,Is the cement temperature.
Preferably, the step of obtaining the diameter data of the aggregate through the sieving experiment comprises the following steps:
selecting a certain amount of aggregate samples from the aggregate, and drying the aggregate samples;
sequentially stacking the screens according to the screen mesh specification from large to small, placing a receiving tray at the bottommost part, and pouring the aggregate sample into the screen mesh with the largest aperture;
Starting a screen vibrating machine to screen the aggregate samples, sequentially weighing the residual aggregate mass of each layer of screen from the screen at the top after screening, and calculating the ratio of the residual aggregate mass of each layer of screen to the total mass of the aggregate samples to obtain the corresponding mass ratio of each layer of screen.
Preferably, the step of obtaining the aggregate size distribution degree according to the diameter data evaluation of the aggregate comprises the following steps:
calculating the dispersion degree of the average particle size and the particle size distribution of the aggregate;
Obtaining the particle size with the cumulative passing rate of sixty percent from the sieving curve, and calculating the particle size uniformity coefficient with the particle size with the cumulative passing rate of ten percent;
evaluating according to the average particle size of the aggregate and the discrete degree of the particle size distribution to obtain a particle size distribution index;
According to the discrete degree of particle size distribution, the particle size uniformity coefficient and the particle size distribution index, the aggregate size distribution degree is obtained by evaluation, and the concrete obtaining mode is as follows:
;
In the formula, Expressed as the degree of aggregate size distribution,Expressed as the degree of dispersion of the particle size distribution,Expressed as a coefficient of uniformity of the particle size,Expressed as particle size distribution index.
Preferably, the step of obtaining the environmental impact coefficient according to the temperature and humidity evaluation of the mixing workshop comprises the following steps:
acquiring real-time temperature data of a mixing workshop through a temperature sensor, and acquiring the allowable maximum workshop temperature;
Acquiring real-time humidity data of a mixing workshop through a humidity sensor, and acquiring allowable maximum workshop humidity;
according to the real-time temperature data and the real-time humidity data, the environmental influence coefficient is obtained by evaluation, and the specific acquisition mode is as follows:
;
In the formula, Represented as an environmental impact coefficient,Represented as real-time temperature data,Expressed as the maximum allowable shop temperature,Represented as real-time humidity data,Expressed as the maximum allowable plant humidity.
Preferably, the step of obtaining the actual mixing time according to the mixing time adjustment index comprises the following steps:
Setting an initial mixing time and a mixing time threshold, and when the mixing time adjustment index is equal to the mixing time threshold, setting the mixing time as the initial mixing time;
Calculating the ratio of the mixing time adjustment index to the mixing time threshold value to obtain a time adjustment coefficient;
the actual mixing time is obtained by multiplying the time adjustment coefficient and the initial mixing time, and the actual mixing time is obtained by the following steps:
;
In the formula, Expressed as the actual mixing time, is given,Expressed as the initial mix time, is indicated,Represented as a time adjustment coefficient.
The beneficial effects of the invention are as follows:
1. According to the concrete mixing control method suitable for the high-temperature high-humidity environment, situation data of mixing equipment are obtained, equipment influence coefficients are obtained according to the situation data evaluation of the mixing equipment, raw material data are obtained, material influence coefficients are obtained according to the raw material data evaluation, temperature and humidity of a mixing workshop are obtained through a temperature and humidity sensor, environment influence coefficients are obtained according to the temperature and humidity evaluation of the mixing workshop, mixing time adjustment indexes are obtained according to the comprehensive evaluation of the equipment influence coefficients, the material influence coefficients and the environment influence coefficients, actual mixing time is obtained according to the mixing time adjustment indexes, concrete mixing time is controlled according to the actual mixing time, automatic adjustment of mixing time is effectively achieved, and mixing efficiency is improved.
Drawings
Fig. 1 is a flowchart of a concrete mixing control method suitable for a high-temperature and high-humidity environment according to an embodiment of the application.
Detailed Description
The invention is further illustrated by the following examples, which are intended to be illustrative only and not limiting in any way.
A concrete mixing control method suitable for a high-temperature and high-humidity environment comprises the following steps:
Step 1, acquiring condition data of mixing equipment, wherein the condition data comprise the abrasion degree of a mixing blade, the rotating speed of a mixing building and the internal temperature of the mixing building, and evaluating and obtaining equipment influence coefficients according to the condition data of the mixing equipment;
in this embodiment, it should be specifically described that the step of obtaining the device influence coefficient according to the condition data of the mixing device includes:
a vibration sensor is arranged at a key part (such as a stirring shaft or an equipment shell) of the mixing building, so that the sensor can collect main vibration signals when the mixing building runs;
Recording vibration signals generated in the running process of the mixing building through a vibration sensor, setting sampling frequency and sampling time, and acquiring the signals in a time sequence;
the high frequency noise and low frequency interference are removed using a band pass filter which is a signal processing means for allowing signals to pass through in a specified frequency range while suppressing signals below a lower limit frequency and above an upper limit frequency, while retaining only signals related to the vibration of the stirring blade, noted as stirring blade vibration signals. The function of the method is to keep the target frequency component (such as the characteristic frequency of the vibration of the stirring blade) and remove high-frequency noise and low-frequency interference at the same time;
acquiring vibration signal data of the stirring blade during initial operation, recording the vibration signal data as an initial vibration signal, and obtaining a vibration difference value of each moment according to a difference value of the vibration signal of the stirring blade and the initial vibration signal at each moment;
Clustering the vibration difference values at each moment, and calculating according to the clustering result to obtain the abrasion degree of the stirring blade;
acquiring the current rotating speed of the mixing building, the current internal temperature of the mixing building, the standard rotating speed of the mixing building, the ideal operating temperature of equipment and the highest internal temperature allowed by the equipment in real time;
According to the abrasion degree of the stirring blade, the rotating speed of the stirring building and the temperature evaluation inside the stirring building, the equipment influence coefficient is obtained, and the specific acquisition mode is as follows:
;
In the formula, Represented as a device influence coefficient,Expressed as the degree of wear of the stirring vanes,The standard rotating speed of the mixing tower is shown,In order to mix the current rotational speed of the building,Indicated as the current internal temperature of the mixing plant,Indicated as the ideal operating temperature of the device,Expressed as the highest internal temperature allowed by the device.
When the rotational speed reduces, stirring vane's cutting speed and mixed effort weaken, and aggregate and thick liquids's distribution in the concrete is inhomogeneous, and lower rotational speed can lead to stirring time to need prolong in order to compensate efficiency decline to increase equipment burden, when the current rotational speed of mix the building is less than mix building standard rotational speed, the relative motion between concrete thick liquids and the aggregate weakens, can not intensive mixing, and the blade can't cover all regions of agitator in the unit time, leads to partial material to be detained or stir inadequately.
When the current temperature in the mixing building is equal to the ideal running temperature of the equipment, the influence of the temperature on the equipment is minimum, and when the current temperature in the mixing building is greater than the highest allowable internal temperature of the equipment, the influence of the temperature on the equipment is extremely great.
In this embodiment, it should be specifically described that the clustering step for the vibration difference value at each moment is:
Step 1.1, taking the vibration difference values as clustering characteristics, taking the vibration difference values at all moments in the detection time as a data set, and taking each vibration difference value in the data set as a data point;
step 1.2, determining an optimal cluster number K of the data set by using an elbow method;
The elbow method is an algorithm for determining the optimal cluster number of a data set, and forms an inflection point similar to an elbow by calculating the sum of squares of total errors under different cluster numbers, namely the sum of squares of distances from each point to the cluster center of the data set, and drawing a relation curve of the cluster number and the sum of squares of total errors, wherein when the cluster number is increased, the sum of squares of total errors is gradually reduced, but is slowed down at a certain point. The cluster number at this inflection point is the optimal cluster number, since the increase in cluster number after that brings less error reduction, indicating that the model has described the data structure better;
Step 1.3, randomly selecting K data points in a data set as initial clustering centers, and calculating Euclidean distance from each data point to each initial clustering center according to the specific acquisition mode:
;
In the formula, Expressed as Euclidean distance of data point to cluster center, whereinRepresented as data points of a data set,The method comprises the steps of representing initial cluster centers, traversing K initial cluster centers for each data point, and distributing the K initial cluster centers to cluster clusters corresponding to the initial cluster centers closest to the initial cluster centers;
Euclidean distance is a geometric distance calculation method for measuring the distance of a straight line between two points, defined as the square root of the sum of squares of the differences in the corresponding dimensions of the coordinates of the two points in a multidimensional space. For a two-dimensional space, it is a straight line distance formula between two points on a plane, and in a three-dimensional or higher-dimensional space, it is extended to the shortest distance between two points in a multi-dimensional space.
Step 1.4, traversing all data points to obtain initial clustering clusters, and calculating the average value of the data points in each initial clustering cluster to obtain a new clustering center;
And 1.5, repeating the step 1.3 and the step 1.4 until the clustering center is not changed any more, and obtaining a final clustering cluster and a final clustering center.
In this embodiment, it should be specifically described that the step of calculating the wear degree of the stirring blade according to the clustering result is as follows:
Calculating the ratio of the number of data points in each final cluster to the total number of data sets to obtain the weight of each final cluster;
Weighting and summing the weight of each final cluster and the final cluster center to obtain the abrasion degree of the stirring blade, wherein the calculation formula is as follows WhereinExpressed as the degree of wear of the stirring vanes,Expressed as the weight of the j-th final cluster,Denoted as the j-th final cluster center, K is the best cluster number for the dataset.
Step 2, raw material data are obtained, wherein the raw material data comprise aggregate moisture content, cement temperature and aggregate size distribution degree, and material influence coefficients are obtained according to raw material data evaluation;
in this embodiment, it should be specifically described that the step of obtaining the material influence coefficient according to the raw material data evaluation is:
installing a moisture sensor in the aggregate conveying belt, and monitoring the moisture content of the aggregate in real time through the moisture sensor;
the cement temperature is monitored in real time by using an infrared thermometer, which is non-contact temperature measuring equipment, and the surface temperature of an object is calculated and displayed by receiving infrared radiation emitted by the surface of the object and utilizing the relation between the wavelength of the infrared radiation and the temperature of the object. The method is characterized by being quick and accurate, and is suitable for use in high-temperature, dangerous or inconvenient contact environments. The infrared thermometer is commonly used for monitoring the temperature of materials such as cement, aggregate and the like in real time, can effectively avoid errors and inconvenient operation caused by contact temperature measurement, and is widely applied to the fields of building material production and quality control;
Diameter data of aggregate is obtained through screening experiments, the size distribution degree of the aggregate is obtained according to the diameter data evaluation of the aggregate, the screening experiments are a common particle classification and size distribution testing method, and aggregate samples are separated according to particle sizes through a series of standard screens with different apertures. In the experiment, the aggregate sequentially passes through the screen meshes under the vibration screen or manual operation, the aggregate mass trapped by each screen mesh is recorded, and the mass ratio and the accumulated passing rate of each particle size range are calculated;
according to the aggregate moisture content, the cement temperature and the aggregate size distribution degree, the material influence coefficient is obtained by evaluation, and the concrete obtaining mode is as follows:
;
In the formula, Expressed as a coefficient of influence of the material,For the degree of size distribution of the aggregate,The water content of the aggregate is the water content of the aggregate,Is the cement temperature.
In this embodiment, the step of obtaining diameter data of the aggregate through the sieving experiment is specifically described as follows:
selecting a certain amount of aggregate samples from the aggregate, and drying the aggregate samples;
sequentially stacking the screens according to the screen mesh specification from large to small, placing a receiving tray at the bottommost part, and pouring the aggregate sample into the screen mesh with the largest aperture;
Starting a screen vibrating machine to screen the aggregate samples, sequentially weighing the residual aggregate mass of each layer of screen from the screen at the top after screening, and calculating the ratio of the residual aggregate mass of each layer of screen to the total mass of the aggregate samples to obtain the corresponding mass ratio of each layer of screen.
In this embodiment, it should be specifically described that the step of obtaining the aggregate size distribution degree according to the diameter data evaluation of the aggregate includes:
the average particle size of the aggregate is calculated, and the specific acquisition mode is as follows:
;
In the formula, Expressed as the average particle size of the aggregate,Represented as the pore size of the ith screen,Represented as the corresponding mass fraction of the i-th screen;
the discrete degree of the particle size distribution is calculated, and the specific acquisition mode is as follows:
;
In the formula, Expressed as the degree of dispersion of the particle size distribution, the larger the value, the more dispersed the particle size distribution,Expressed as the average particle size of the aggregate;
The particle size with the cumulative passing rate of sixty percent is obtained from the sieving curve, and the particle size uniformity coefficient is obtained by calculation with the particle size with the cumulative passing rate of ten percent, wherein the specific obtaining mode is as follows:
;
In the formula, The smaller the particle diameter uniformity coefficient is, the more uniform the particle diameter distribution is, the larger the particle diameter uniformity coefficient is, the more nonuniform the particle diameter distribution is,Expressed as a particle size with a cumulative pass of sixty percent,Particle size expressed as ten percent of cumulative pass rate;
the particle size distribution index is obtained by evaluating the average particle size of aggregate and the discrete degree of the particle size distribution, and the specific acquisition mode is as follows:
;
In the formula, Expressed as a particle size distribution index, the larger the particle size distribution index, the more dispersed the aggregate particle size distribution,Expressed as the average particle size of the aggregate,Expressed as the degree of dispersion of the particle size distribution;
According to the discrete degree of particle size distribution, the particle size uniformity coefficient and the particle size distribution index, the aggregate size distribution degree is obtained by evaluation, and the concrete obtaining mode is as follows:
;
In the formula, The aggregate size distribution degree is shown as the aggregate size distribution degree, the larger the aggregate size distribution degree is, the more uneven the particle size distribution is, the larger the influence on the mixing time is,Expressed as the degree of dispersion of the particle size distribution, reflects the dispersion of the particle size range,Expressed as a particle size uniformity coefficient, the ratio of large particles to small particles is measured,Expressed as particle size distribution index, for further modifying the effect of the distribution on the mixing properties.
Step 3, acquiring the temperature and the humidity of a mixing workshop through a temperature and humidity sensor, and evaluating according to the temperature and the humidity of the mixing workshop to obtain an environmental influence coefficient;
In this embodiment, it should be specifically described that the step of obtaining the environmental impact coefficient according to the temperature and humidity evaluation of the mixing plant is as follows:
acquiring real-time temperature data of a mixing workshop through a temperature sensor, and acquiring the allowable maximum workshop temperature;
Acquiring real-time humidity data of a mixing workshop through a humidity sensor, and acquiring allowable maximum workshop humidity;
according to the real-time temperature data and the real-time humidity data, the environmental influence coefficient is obtained by evaluation, and the specific acquisition mode is as follows:
;
In the formula, Represented as an environmental impact coefficient,Represented as real-time temperature data,Expressed as the maximum allowable shop temperature,Represented as real-time humidity data,Expressed as the maximum allowable plant humidity.
And 4, comprehensively evaluating the equipment influence coefficient, the material influence coefficient and the environment influence coefficient to obtain a mixing time adjustment index, wherein the equipment influence coefficient, the material influence coefficient and the environment influence coefficient are subjected to normalization treatment, so that units are kept consistent, and the mixing time adjustment index is obtained by the following steps:
;
in the middle of Expressed as a blending time adjustment index,Expressed as the equipment influence factor, the equipment performance status directly influences the adjustment requirement of the concrete mixing time, and when the equipment condition is deteriorated, the mixing time needs to be prolonged to ensure the mixing uniformity. When the abrasion of the stirring blade is serious, the stirring efficiency of the equipment is reduced to influence the full mixing of materials in the concrete, at the moment, the influence coefficient of the equipment is increased, the stirring time is correspondingly prolonged to compensate the insufficient performance of the equipment, otherwise, when the equipment is in a good state, the influence coefficient of the equipment is lower, the shorter stirring time can be maintained, the temperature rise or the performance reduction of the concrete caused by over stirring is avoided,The method is characterized in that the method is represented as a material influence coefficient, the change of the material characteristics directly influences the adjustment range of the concrete mixing time, when the concrete mixing difficulty caused by the material characteristics is increased, the material influence coefficient is increased, the mixing time is prolonged at the moment, the cement paste can be ensured to uniformly wrap the aggregate to avoid layering or segregation, and conversely, when the material performance is in an ideal state, the influence coefficient is lower, the mixing time can be properly shortened, so that energy sources are saved, and the production efficiency is improved. The proportional relation is beneficial to dynamically adjusting the mixing time by monitoring the material state in real time, reducing unnecessary resource consumption while ensuring the mixing quality of the concrete, is particularly suitable for concrete production control under complex construction environments such as high temperature, high humidity and the like,Expressed as an environmental impact coefficient, the more the environmental conditions deviate from the standard, the higher the impact coefficient thereof, which requires compensating for the adverse effect on the blending effect by extending the blending time. In a high-temperature environment, hydration reaction of concrete is accelerated, fluidity of mixing is reduced, materials can not be fully mixed, so that environmental impact coefficient is increased, mixing time is required to be increased to ensure uniformity, excessive moisture can be attached to the surface of aggregate in a high-humidity environment, water-cement ratio is fluctuated, and the full combination of slurry and aggregate can be improved by prolonging the mixing time. Meanwhile, under the low temperature or dry environment, the water on the surface of the concrete is quickly lost, the mixing time is also required to be properly prolonged to ensure the workability,、、Weight coefficients expressed as device influence coefficient, material influence coefficient, and environmental influence coefficient, and,、、The specific values are dependent on the actual situation, and are determined by the expert, for example,、、May be 0.4, 0.2.
And 5, obtaining actual mixing time according to the mixing time adjustment index, and controlling the concrete mixing time according to the actual mixing time.
In this embodiment, it should be specifically described that the step of obtaining the actual blending time according to the blending time adjustment index is as follows:
Setting an initial mixing time and a mixing time threshold, and when the mixing time adjustment index is equal to the mixing time threshold, setting the mixing time as the initial mixing time;
calculating the ratio of the mixing time adjustment index to the mixing time threshold value to obtain a time adjustment coefficient, wherein the time adjustment coefficient is obtained in the following manner:
;
In the formula, Represented as a time adjustment coefficient,Expressed as a blending time adjustment index,Expressed as a blending time threshold;
the actual mixing time is obtained by multiplying the time adjustment coefficient and the initial mixing time, and the actual mixing time is obtained by the following steps:
;
In the formula, Expressed as the actual mixing time, is given,Expressed as the initial mix time, is indicated,Represented as a time adjustment coefficient.
Finally, the foregoing description of the preferred embodiment of the invention is provided for the purpose of illustration only, and is not intended to limit the invention to the particular form disclosed, but on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Although the embodiments of the present invention and the accompanying drawings have been disclosed for illustrative purposes, those skilled in the art will appreciate that various substitutions, changes and modifications are possible without departing from the spirit and scope of the invention and the appended claims, and thus the scope of the invention is not limited to the embodiments and the disclosure of the drawings.
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| CN101266197A (en) * | 2007-03-12 | 2008-09-17 | 斯奈克玛 | Method of detecting damage to an antifriction bearing of a motor |
| CN110877016A (en) * | 2019-10-11 | 2020-03-13 | 南京绿新能源研究院有限公司 | Wind power generation blade detection device and detection method |
| CN114323290A (en) * | 2021-12-28 | 2022-04-12 | 中国水利水电科学研究院 | Information collection method of aggregate temperature and outlet concrete temperature of concrete mixing building |
| KR20240018218A (en) * | 2022-08-02 | 2024-02-13 | 주식회사 에스에이치엘에이비 | Method and system for uniformly controlling production temperature of ready-mixed concrete |
| CN119017544A (en) * | 2024-08-15 | 2024-11-26 | 山东大学 | A method and system for controlling temperature of concrete mixing for intelligent temperature control nuclear power |
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2024
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101266197A (en) * | 2007-03-12 | 2008-09-17 | 斯奈克玛 | Method of detecting damage to an antifriction bearing of a motor |
| CN110877016A (en) * | 2019-10-11 | 2020-03-13 | 南京绿新能源研究院有限公司 | Wind power generation blade detection device and detection method |
| CN114323290A (en) * | 2021-12-28 | 2022-04-12 | 中国水利水电科学研究院 | Information collection method of aggregate temperature and outlet concrete temperature of concrete mixing building |
| KR20240018218A (en) * | 2022-08-02 | 2024-02-13 | 주식회사 에스에이치엘에이비 | Method and system for uniformly controlling production temperature of ready-mixed concrete |
| CN119017544A (en) * | 2024-08-15 | 2024-11-26 | 山东大学 | A method and system for controlling temperature of concrete mixing for intelligent temperature control nuclear power |
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