Water absorption determination method and device applied to recycled aggregate

Abstract

The invention relates to the technical field of water absorption determination, in particular to a water absorption determination method and device applied to recycled aggregate, and the method comprises the following steps: selecting a plurality of to-be-determined samples from the recycled aggregate, obtaining particle size distribution data of each to-be-determined sample, generating a particle size distribution curve, drying the soaked to-be-determined samples, and determining the water absorption of the recycled aggregate according to the particle size distribution curve. Collecting the mass of each sample to be detected at each moment in the drying process; calculating the distribution deviation degree of each sample to be detected; obtaining a potential moment; calculating a relative difference degree and a judgment coefficient of each potential moment, and obtaining a target moment; compensating the mass at the target moment to obtain the saturated surface dry mass of each sample to be detected; and correcting the saturated surface dry mass, calculating the water absorption rate of each sample to be measured, and measuring the water absorption rate of the recycled aggregate. According to the method, the influence of particle size distribution difference on water absorption determination is reduced, and the determination accuracy of the water absorption of the recycled aggregate is improved.

Description

Technical Field

[0001] This application relates to the field of water absorption rate determination technology, specifically to a method and apparatus for determining the water absorption rate of recycled aggregates. Background Technology

[0002] In the field of building materials, processing waste concrete into recycled aggregates not only achieves the goal of resource utilization of construction waste but also alleviates the current pressure of resource shortages. As a key material for the resource utilization of construction waste, the water absorption rate of recycled aggregates is a core parameter affecting the workability and durability of concrete. Typically, due to the presence of old mortar on the surface and numerous internal cracks, the water absorption rate of recycled aggregates is three to ten times that of natural aggregates. Accurate measurement of the water absorption rate of recycled aggregates is crucial for concrete mix design.

[0003] In traditional methods using the saturated surface-drying method, the uneven particle size distribution of recycled aggregates leads to varying adsorption capacities for water surface tension. For example, small particles tend to trap more non-absorbed water, while larger particles have larger pores and poorer water adsorption, thus affecting the accuracy of the saturated surface-drying mass measurement. Furthermore, during the drying process, the non-absorbed water adsorbed on the surface of the recycled aggregates drips due to gravity, but this dripping is accompanied by evaporation, causing significant deviations in the measured saturated surface-drying mass and resulting in inaccurate determination of the water absorption rate of the recycled aggregates. Summary of the Invention

[0004] To address the aforementioned technical problems, a method and apparatus for determining the water absorption rate of recycled aggregates are provided to solve the existing issues.

[0005] The solution to the technical problem of this application is to provide a method and apparatus for determining the water absorption rate of recycled aggregates, including the following steps: In a first aspect, embodiments of this application provide a method for determining the water absorption rate of recycled aggregates, the method comprising the following steps: Multiple samples were selected from the recycled aggregate to obtain the particle size distribution data of each sample and generate a particle size distribution curve. The samples were dried after soaking and the mass of each sample was collected at each time point during the drying process. Analyze the deviation of the particle size distribution curve from the Gaussian distribution, as well as the asymmetric distribution of the particle size distribution curve, and calculate the distribution deviation of each sample to be tested. Curve fitting and abrupt change detection were performed on the mass of each sample at different times during the initial drying stage. The trend of mass change on the fitted curve was analyzed, as well as the situation of abnormal mass change, to obtain the potential time. For each sample to be tested, the differences in mass fluctuations and mass change trends between the left and right sides at each potential time point are analyzed, the relative difference is calculated, and the judgment coefficient of each potential time point is determined by combining the correlation of mass changes between the left and right sides. The potential time points are then screened to obtain the target time point. Based on the rate of mass change of each sample after the target time, the mass at the target time is compensated to obtain the saturated surface dry mass of each sample. By analyzing the skewed distribution and deviation of the particle size distribution curve, the saturated surface dry mass is corrected, and the water absorption rate of each sample is calculated. The deviation of the water absorption rate of all samples is analyzed, and the water absorption rate of the recycled aggregate is determined.

[0006] Preferably, the calculation of the distribution deviation of each sample to be tested includes: For each sample, the particle size distribution data is fitted with a Gaussian distribution to obtain the fitted Gaussian distribution curve; the area of ​​integral of the difference between the particle size distribution curve and the fitted Gaussian distribution curve is calculated. The difference between the median and the mean of the particle size distribution data for each sample is calculated and denoted as the relative difference. The relative difference is then negatively mapped. The distribution deviation is the normalized result of the ratio between the integral area and the result of the negative mapping.

[0007] Preferably, the process of obtaining the potential time is as follows: obtain all inflection points on the fitting curve corresponding to each sample in the initial stage of drying; and perform abrupt change point detection on the quality at all times in the initial stage of drying to obtain all abrupt change points; and record the time corresponding to the inflection point and the time corresponding to the abrupt change point in the initial stage of drying as the potential time.

[0008] Preferably, the calculation of relative difference includes: For each sample to be tested, the multiple times before each potential time and the multiple times after each potential time in the initial stage of drying are respectively recorded as the left local time period and the right local time period. The difference between the dispersion of quality at all times within the left local time interval and the dispersion of quality at all times within the right local time interval is calculated as the fluctuation difference at each potential time. The difference between the test statistic of the tangent slope of each potential time point on the fitted curve at all times in the left local time interval and the test statistic of the tangent slope of each potential time point in the right local time interval is calculated as the trend difference of each potential time point. The relative difference is the product of the fluctuation difference and the trend difference.

[0009] Preferably, determining the judgment coefficients for each potential time point includes: Calculate the correlation of quality across all times between the left and right local time intervals, and perform a positive mapping on the absolute value of the correlation. The judgment coefficient is the ratio of the relative difference to the result of the positive mapping.

[0010] Preferably, the process of obtaining the target time is as follows: sort the judgment coefficients of all potential times of each sample in the initial drying stage in descending order, select the judgment coefficients of the top-ranked potential times for clustering, count the number of potential times contained in each cluster, and select the potential time corresponding to the cluster center of the cluster with the largest number, which is recorded as the target time.

[0011] Preferably, obtaining the saturated surface-dry mass of each sample to be tested includes: Linear fitting is performed on the mass of each sample at all times after the target time, and the slope of the fitted line is taken as the evaporation rate; the interval time from the start of drying to the target time is calculated; the product of the interval time and the evaporation rate is taken as the compensation mass. The saturated surface dry mass is the sum of the mass corresponding to the target time and the compensation mass.

[0012] Preferably, the correction of the saturated surface dry mass includes: Calculate the skewness of the particle size distribution curve for each sample to be tested. If the skewness is positive, assign a sign value of 1 to each sample to be tested; otherwise, assign a sign value of -1. No. Corrected saturated surface dry mass of the test sample The calculation formula is: ,in, For the first The saturated surface dry mass of the test sample before correction. For the first The sign value of each sample to be tested. For the first Distribution deviation of the test samples This is the preset scaling factor.

[0013] Preferably, the determination of the water absorption rate of the recycled aggregate includes: recording the difference between the water absorption rate of each sample to be tested and the average water absorption rate of all samples to be tested as the relative deviation; removing the sample to be tested with the largest relative deviation, and taking the average water absorption rate of all remaining samples to be tested as the water absorption rate of the recycled aggregate.

[0014] Secondly, embodiments of this application also provide a water absorption rate measuring device for recycled aggregates, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any of the above-described methods for measuring the water absorption rate of recycled aggregates.

[0015] This application has at least the following beneficial effects: This application calculates the distribution deviation of each test sample by measuring the degree of deviation of its particle size distribution curve from a normal distribution. Its advantage lies in considering the uneven particle size distribution of recycled aggregate to assess the error in measuring saturated surface-dry mass. It obtains potential moments, calculates relative differences, determines the judgment coefficient for each potential moment, and obtains the target moment. Its advantage lies in analyzing the important moments of mass change during the drying process after the recycled aggregate in the test sample has been soaked and removed. Furthermore, by analyzing the differences in mass change between the left and right sides, the potential moments are judged, selecting the turning point where the state of dominance by water droplets transitions to a state of dominance by evaporation after the droplets have finished. The mass at this moment, when the droplets have finished but the main evaporation has not yet begun, is closest to the saturated surface-dry mass. Secondly, the mass at the target moment is compensated to obtain the saturated surface-dry mass of each test sample. Its advantage lies in considering the simultaneous occurrence of water droplet drop and evaporation processes, and by using only samples containing… The rate of mass reduction during evaporation is assessed to evaluate the rate of water evaporation and compensate for the water lost during the dripping process, thus more accurately reflecting the true saturated surface-dry state of the recycled aggregate in the test sample. Furthermore, the skewness and deviation of the particle size distribution curve are used to correct the saturated surface-dry mass. The deviation in water absorption rate of all test samples is analyzed, and the water absorption rate of the recycled aggregate is measured. The beneficial effect is that it considers the influence of particle size distribution deviation on the measurement of saturated surface-dry mass. When there are many small particles, it reduces the possibility of an overestimation of the saturated surface-dry mass due to the large amount of non-absorbed water carried by small particles; conversely, when there are many large particles, it reduces the possibility of an underestimation of the saturated surface-dry mass due to the poor water adsorption effect of large particles. The water absorption rate of each test sample is calculated, thereby reducing the influence of particle size distribution differences on the water absorption rate measurement. This allows for a more accurate assessment of the water absorption characteristics of the recycled aggregate and improves the accuracy of the water absorption rate measurement. Attached Figure Description

[0016] The following is a detailed description of a method for determining the water absorption rate of recycled aggregates according to the present application, with reference to the accompanying drawings.

[0017] Figure 1 A flowchart illustrating the steps of a method for determining the water absorption rate of recycled aggregates, provided in an embodiment of this application; Figure 2A flowchart illustrating the steps of the modified method for obtaining saturated surface dry mass provided in this application embodiment. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description, in conjunction with the accompanying drawings and embodiments, provides a method and apparatus for determining the water absorption rate of recycled aggregates. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a method for determining the water absorption rate of recycled aggregate according to an embodiment of this application. The method includes the following steps: Step 1: Select multiple test samples from the recycled aggregate, obtain the particle size distribution data of each test sample, and generate a particle size distribution curve. Dry the test samples after soaking and collect the mass of each test sample at each time point during the drying process.

[0021] With the rapid development of infrastructure construction, a large amount of waste concrete is generated during the construction, reconstruction, expansion, and demolition of some highways, railways, water conservancy, and other infrastructure projects. This results in the accumulation of concrete building waste, occupying a large amount of land and causing certain environmental pollution. By processing waste concrete building waste into recycled aggregates, which can partially or completely replace traditional artificial aggregates in concrete engineering, not only can the goal of resource utilization of construction waste be achieved, but the pressure of current resource shortages can also be alleviated.

[0022] Aggregate water absorption rate is a key parameter in calculating material usage in concrete mix design, directly reflecting the aggregate's ability to absorb and retain moisture. Recycled aggregates typically originate from construction waste, and their composition and structure may differ from natural aggregates. Due to residual mortar on their surface or micro-cracks present after crushing, recycled aggregates often have higher water absorption rates. This increased absorption capacity leads to decreased strength, necessitating the use of large amounts of water and cement in the production of recycled concrete, making it difficult to achieve the required performance standards. Therefore, after crushing waste concrete to obtain recycled aggregates, it is necessary to determine their water absorption rate.

[0023] The saturated surface-dry water absorption rate of recycled aggregate was tested. The main process involved weighing a fixed amount of recycled aggregate, completely immersing it in a soaking tank, and rotating and shaking it at fixed intervals of 30 minutes for 24 hours to allow the recycled aggregate to saturate and absorb water. After soaking, the recycled aggregate was placed on a weighing instrument in a drying oven and weighed to measure the saturated surface-dry mass of the recycled aggregate. The recycled aggregate was dried to a constant weight using a drying oven at a temperature of 120℃~150℃, and the mass of the dried aggregate was measured. Therefore, the water absorption rate of recycled aggregate is... ,in, This represents the water absorption rate of the recycled aggregate.

[0024] However, during the determination of water absorption rate of recycled aggregate, there are differences in water adsorption by recycled aggregates of different fine particle sizes. For example, fine particles have a larger specific surface area and a significantly higher proportion of surface adsorbed water and pore water, while coarse aggregates have a smaller specific surface area and therefore lower water absorption capacity, but can provide higher strength. Therefore, it is necessary to screen the particle size of recycled aggregates in the same batch.

[0025] The recycled aggregates used in this experiment were all crushed from C40 concrete test blocks mixed in the laboratory by a jaw crusher. The water absorption rate of recycled aggregates with a particle size range of 5mm to 13mm was determined. The recycled aggregates were divided into multiple portions, which were recorded as each sample to be tested. In this embodiment, medium-sized recycled aggregate is selected for measurement and analysis. The recycled aggregate is divided into three parts. As for other implementation methods, the implementer can set them according to the actual situation.

[0026] Secondly, there may be differences in particle size distribution among the recycled aggregates in the test samples. For example, for recycled aggregates with a particle size range of 5mm to 13mm, smaller aggregates have a stronger ability to trap water. During the saturation adsorption process, they can trap water from the non-absorbed portion. This water may evaporate during the drying process, resulting in the measured saturated surface dry mass being greater than the actual saturated surface dry mass, which leads to a large deviation in the measured water absorption rate.

[0027] Therefore, in order to measure the impact of differences in particle size distribution, it is necessary to obtain the particle size distribution of recycled aggregate in the sample to be tested, specifically: The particle size distribution data of each sample is obtained using a particle size analyzer, and a particle size distribution curve is generated. It should be noted that particle size analyzers can obtain particle size distribution data, specifically the percentage of each particle size. By plotting the percentage of all particle sizes in each sample, a particle size distribution curve can be obtained.

[0028] Each sample to be tested was immersed in a soaking tank for soaking and adsorption. After soaking, the recycled aggregate was placed on a weighing instrument in a drying oven, and the mass of each sample to be tested was collected in real time at each moment during the entire drying process. In this embodiment, the data acquisition time interval is 1Hz. As for other implementation methods, the implementer can set it according to the actual situation. The accuracy of the weighing instrument is required to be within 0.1g.

[0029] Thus, the particle size distribution curve of each sample and the mass of each sample at each time point during the entire drying process are obtained.

[0030] Step 2: Analyze the deviation of the particle size distribution curve from the Gaussian distribution, as well as the asymmetric distribution of the particle size distribution curve, and calculate the distribution deviation of each sample to be tested.

[0031] Furthermore, the more concentrated the particle size distribution of the recycled aggregate in the test sample, the more uniform the size of the aggregate particles in the test sample, and the less affected by the adsorption differences of the aggregate. However, if the particle size distribution of the recycled aggregate in the test sample has a large deviation, due to the influence of the surface tension of water, the small aggregate particles are more likely to carry away excess water, and this part of the water is not the actual amount of water adsorbed by the aggregate, which leads to the measured saturated surface dry mass being too large, thus affecting the determination of the water absorption rate.

[0032] Ideally, the particle size distribution of recycled aggregate basically conforms to a normal distribution. Therefore, we analyze the deviation of the particle size distribution curve of each sample from the normal distribution and calculate the degree of distribution deviation. Specifically: Gaussian distribution fitting was performed on the particle size distribution data of each sample to obtain the fitted Gaussian distribution curve; In this embodiment, a Gaussian distribution is fitted using the nonlinear least squares method, where the Gaussian distribution is the same as the normal distribution. The nonlinear least squares method and the Gaussian distribution are well-known techniques and will not be described in detail here.

[0033] Calculate the area of ​​integral between the particle size distribution curve and the fitted Gaussian distribution curve; In this embodiment, the formula for calculating the integral area is: ,in, The function representing the particle size distribution curve. This represents the Gaussian function corresponding to the Gaussian distribution curve. Indicates the minimum particle size. Indicates the maximum particle size. ∫ represents the differential element in the integral, and ∫ represents the integral sign.

[0034] Obtain the median and mean of the particle size distribution data for each sample to be tested; In this embodiment, the median and average of all particle sizes in each sample are represented in the particle size distribution curve. hour, The value represents the median. The value represents the average.

[0035] Calculate the difference between the median and the mean, denoted as the relative difference, and perform a negative mapping on the relative difference; In this embodiment, the absolute value of the difference between the median and the mean is calculated and denoted as the relative difference; secondly, the specific process of negative mapping is as follows: assuming the relative difference is denoted as... ,Will The result is used as the result of the negative mapping, where, It is an exponential function with the natural constant as the base.

[0036] The normalized result of the ratio between the integral area and the result of the negative mapping is used as the distribution deviation of each sample to be tested. In this embodiment, the tanh function is used for normalization. The tanh function is a well-known technique and will not be described in detail here. As other implementation methods, implementers can use other methods of the prior art, such as the sigmoid function, etc. This embodiment does not impose any special restrictions on this.

[0037] It should be noted that the larger the integral area, the more the aggregate particle size distribution of the sample deviates from the Gaussian distribution, i.e., the normal distribution, reflecting the poorer uniformity of the aggregate particles in the sample; the larger the relative difference, the smaller the negative mapping result, indicating a more significant asymmetry in the aggregate particle size distribution, reflecting a possible skewness in the particle size distribution, with more small or large particles; the larger the distribution deviation, the more disordered the aggregate particle size distribution of the sample, the poorer its uniformity, and the higher the error in the water absorption rate measurement, thus requiring more correction.

[0038] Thus, the distribution deviation of each sample to be tested is obtained.

[0039] Step 3: Perform curve fitting and abrupt change detection on the mass of each sample at different times during the initial drying stage. Analyze the trend of mass change on the fitted curve and the situation of abnormal mass change to obtain potential times. For each sample, analyze the differences in mass fluctuation and mass change trend between the left and right sides of each potential time, calculate the relative difference, and determine the judgment coefficient of each potential time by combining the correlation of mass change between the left and right sides. Screen the potential times to obtain the target time.

[0040] Furthermore, when determining the water absorption rate of recycled aggregate using the saturated surface-dry method, the accuracy of the measurement is mainly affected by the saturated surface-dry mass of the recycled aggregate. and the quality of recycled aggregate after drying The accuracy is affected, among which, the dry mass of the saturated surface This indicates the mass of the recycled aggregate when it has fully absorbed moisture and reached saturation, and the mass of the recycled aggregate after drying. The weight of the recycled aggregate is the weight of the aggregate itself. During the drying process, only the water adsorbed in the aggregate is evaporated, and the chemical structure of the aggregate itself is not affected. Therefore, the difference between the two weights represents the saturated water absorption capacity of the recycled aggregate.

[0041] Secondly, when the recycled aggregate is taken out of the soaking tank, the aggregate particles will adsorb some water film, so the mass is much greater than the actual saturated surface dry mass. The surface tension of some water film is broken by gravity, causing it to quickly detach from the aggregate in the form of water droplets. At the same time, some adsorbed water evaporates as water, which makes it difficult to determine the saturated surface dry mass.

[0042] In traditional methods, the mass of recycled aggregate at the time of soaking and removal is directly taken as the saturated surface-dry mass. There is also the practice of taking the mass of recycled aggregate after it has been removed and dried until it is no longer dripping water as the saturated surface-dry mass. However, since dripping water and water evaporation occur simultaneously, and due to the adsorption tension between aggregate particles on water, more unsaturated adsorbed water is retained, resulting in a deviation in the determination of saturated surface dry mass and affecting the accuracy of water absorption rate measurement.

[0043] Based on the above analysis, in the initial stage of drying, a layer of water film will be adsorbed on the surface of the aggregate after it is removed. This water film will drip off due to gravity. At this time, the water lost is non-absorbed surface water. The dripping phenomenon usually occurs within a short period after the aggregate is removed, and the measured mass change rate is relatively high and fluctuates greatly. As the dripping phenomenon weakens, evaporation begins to appear. Evaporation is a slow process. The mass change during the evaporation stage is mainly caused by the evaporation of moisture from the internal pores of the aggregate. The water lost at this time is adsorbed moisture in the aggregate, and the mass change rate is relatively lower. The period between dripping and evaporation refers to when the dripping phenomenon weakens and evaporation has not yet significantly affected the aggregate mass. At this time, the aggregate mass is closest to the saturated surface-dry mass. Therefore, the saturated surface-dry mass should be within the mass range measured in the initial stage of drying. By analyzing the mass changes at different times in the initial stage of drying, potential times can be screened, specifically: The initial drying phase is defined as multiple moments at the start of drying for each sample. In this embodiment, the initial drying time is 50% of the total drying time. As for other implementation methods, the implementer can set the time according to the actual situation.

[0044] Curve fitting was performed on the mass at all times during the initial drying phase to obtain all inflection points of the fitted curve. In this embodiment, the least squares method is used for curve fitting. The least squares method and the acquisition of inflection points are well-known techniques and will not be described in detail here.

[0045] The quality at all times during the initial drying phase was analyzed to identify all abrupt changes. In this embodiment, the Pettite detection algorithm is used to detect mutation points. The Pettite detection algorithm is a well-known technology and will not be described in detail here. As other implementation methods, implementers may use other methods of existing technology, such as the BG algorithm, Bayesian mutation detection, etc. This embodiment does not impose any special restrictions on this.

[0046] The time corresponding to the inflection point in the initial stage of drying and the time corresponding to the mutation point are recorded as potential times. It should be noted that if a potential moment falls between the dripping and evaporation, the mass change before and after the dripping will differ. Therefore, the mass change is assessed by inflection points and abrupt change points to screen potential moments for further evaluation.

[0047] Secondly, if the potential moment is the true inflection point between the end of water droplet falling and the beginning of evaporation dominance, then the mass change on the left side of this potential moment is a rapid decrease due to the simultaneous influence of water droplet penetration and evaporation, resulting in significant fluctuations in mass change. Conversely, the mass change on the right side of this potential moment is mainly a slow decrease due to water evaporation, with relatively smaller fluctuations compared to the left side. Furthermore, if the potential moment is the true inflection point between the end of water droplet falling and the beginning of evaporation dominance, then the rate of mass change on the left side gradually decreases, while the rate of mass decrease on the right side is relatively stable due to the influence of the evaporation rate. Therefore, analyzing the differences in mass changes on both sides at each potential moment and calculating the judgment coefficient are as follows: For each sample to be tested, multiple times before each potential time point in the initial drying stage are selected and recorded as the left local time period; multiple times after each potential time point in the initial drying stage are selected and recorded as the right local time period. In this embodiment, the duration of the left local time period and the right local time period is 30s. It should be noted that if there is a time interval between two potential moments that is less than 30s, then all moments between the two potential moments will be used as the left local time period or the right local time period. The left local time period or the right local time period will be selected as the minimum value between the time interval between the two potential moments and 30s.

[0048] The difference between the dispersion of quality at all times within the left local time interval and the dispersion of quality at all times within the right local time interval is calculated as the fluctuation difference at each potential time. In this embodiment, the dispersion is measured by calculating the standard deviation of the quality of all times within the left local time period and the standard deviation of the quality of all times within the right local time period. As other implementation methods, implementers may use other methods of the prior art, such as variance, coefficient of variation, etc. This embodiment does not impose any special restrictions on this. Secondly, the absolute value of the difference between the dispersion of the quality of all times within the left local time period and the dispersion of the quality of all times within the right local time period is calculated as the fluctuation difference of each potential time.

[0049] It should be noted that the greater the fluctuation difference, the greater the difference in mass change on both sides of the potential moment, and the more likely it is to be a turning point of state transition.

[0050] Calculate the test statistic of the slope of the tangent line at each potential time point on the fitted curve at all times within the left local time interval; Calculate the test statistic of the tangent slope of each potential time point on the fitted curve at all times within the right local time interval; In this embodiment, the Mann-Kendall trend test algorithm is used to calculate the test statistic. The Mann-Kendall trend test algorithm and the calculation of the tangent slope are well-known techniques and will not be described in detail here. The difference in the test statistic between the left and right local time intervals at each potential time point is taken as the trend difference at each potential time point; In this embodiment, the absolute value of the difference between the test statistic between the left local time period and the right local time period of each potential time is taken as the trend difference of each potential time.

[0051] Calculate the product of the fluctuation difference and the trend difference as the relative degree of difference at each potential moment; It should be noted that the greater the trend difference, the greater the difference in the rate of mass change on the left and right sides of the potential moment, reflecting that the potential moment is more likely to be a turning point of state transition; the greater the relative difference, the more likely the potential moment is to be a turning point of state transition.

[0052] Calculate the correlation of quality across all times between the left and right local time intervals, and perform a positive mapping on the absolute value of the correlation. In this embodiment, the correlation is measured by calculating the Pearson correlation coefficient of the quality of all times between the left and right local time periods. The Pearson correlation coefficient is a well-known technique and will not be elaborated upon here. As for other implementations, implementers can use other methods from the prior art, such as cosine similarity, etc. This embodiment does not impose any special restrictions on this. Secondly, the specific process of the positive mapping is as follows: a positive mapping is performed using an exponential function. Let the absolute value of the correlation be denoted as... Then The result is taken as the result of the positive mapping, where, It is an exponential function with the natural constant as the base; through the process of positive mapping, the result of the positive mapping is made to be greater than 0.

[0053] It should be noted that the smaller the absolute value of the correlation, that is, the smaller the result of the positive mapping, the smaller the linear correlation between the quality changes on the left and right sides, the more different the quality changes on the left and right sides are, and the more likely the potential moment is to be the turning point of the state transition.

[0054] The ratio of the relative difference to the result of the positive mapping is used as the judgment coefficient for each potential time point; It should be noted that the larger the judgment coefficient, the more the characteristics of the potential moment match the characteristics of the state transition point.

[0055] Furthermore, the judgment coefficients for individual potential moments may contain a certain degree of randomness and error. Therefore, clustering the judgment coefficients reduces the impact of randomness on individual potential moments, thereby filtering potential moments. Specifically: For each sample to be tested, the judgment coefficients of all potential moments in the initial drying stage are sorted in descending order, and the judgment coefficients of the top-ranked potential moments are selected for clustering. Count the number of potential moments contained in each cluster; select the potential moment corresponding to the cluster center of the cluster with the largest number of potential moments, and denote it as the target moment; In this embodiment, 10% of the decision coefficients at all potential moments are selected for clustering, and the DBSCAN clustering algorithm is used for clustering. The K-means clustering algorithm is a well-known technology and will not be described in detail here. As other implementation methods, implementers can use other methods of existing technology, such as the K-means clustering algorithm, etc. This embodiment does not impose any special restrictions on this.

[0056] It should be noted that the cluster with the largest number of potential moments contains the most potential moments, indicating that these moments appear most frequently in the data and are more reliable. The cluster center represents the average characteristics of all potential moments within the cluster and has higher stability and representativeness. Therefore, the cluster center is taken as the state transition inflection point, and the quality of this target moment is closest to the saturated surface dry quality.

[0057] At this point, the target time has been obtained.

[0058] Step 4: Based on the rate of mass change of each sample after the target time, compensate for the mass at the target time to obtain the saturated surface-dry mass of each sample; correct the saturated surface-dry mass by analyzing the skewness and deviation of the particle size distribution curve, and calculate the water absorption rate of each sample; analyze the deviation of the water absorption rate of all samples, and determine the water absorption rate of the recycled aggregate.

[0059] Furthermore, the mass change of aggregate before the target time is not only affected by water droplets but also by the evaporation process. The saturated surface-dry mass should be the mass at saturated adsorption when there are no water droplets but before evaporation. Therefore, the mass at the target time may be lower than the saturated surface-dry mass. Thus, it is necessary to compensate for the mass of water evaporated between the target time points, specifically as follows: A linear fit is performed on the mass of each sample after the target time at all time points, and the slope of the fitted line is used as the evaporation rate. In this embodiment, the least squares method is used for linear fitting. The least squares method and the slope calculation are well-known techniques and will not be described in detail here.

[0060] The time interval between the start of drying and the target time is calculated; the product of the time interval and the evaporation rate is used as the compensation mass. The sum of the mass corresponding to the target time and the compensation mass is taken as the saturated surface dry mass of each sample to be tested. It should be noted that the saturated adsorption mass at this point can be used to assess the mass of the aggregate during the transition between the droplet falling and the evaporation of water.

[0061] Furthermore, due to the influence of aggregate particle size distribution in each sample, the adsorption tension of aggregate particles on water varies. This causes small particles to trap non-absorbed water, while large particles have lower water absorption capacity, leading to deviations in the measured water absorption rate. Correction to the saturated surface-dry mass needs to be made based on the particle size distribution deviation. When there are many small particles in the particle size distribution, they trap more non-absorbed water. This water evaporates during the drying process but is not considered actual adsorbed water within the aggregate pores. To balance the effects of evaporation and small particle size, the saturated surface-dry mass needs to be reduced. Conversely, when there are many large particles in the particle size distribution, the pores between particles are larger, resulting in poor water adsorption. In this case, it is more difficult for the aggregate particles to store water, leading to a lower measured saturated surface-dry mass, requiring an appropriate increase in the saturated surface-dry mass. Therefore, by analyzing the skewness of the particle size distribution curve for each sample and combining it with the distribution deviation, the saturated surface-dry mass is corrected, specifically as follows: Calculate the skewness of the particle size distribution curve for each sample to be tested. If the skewness is positive, assign a sign value of 1; otherwise, assign a sign value of -1. It should be noted that the calculation process of skewness is a well-known technique and will not be elaborated here; secondly, a positive skewness indicates that the particle size distribution curve is right-skewed, and the sample contains more large particles, while a negative skewness indicates that the particle size distribution curve is left-skewed, and the sample contains more small particles.

[0062] The formula for calculating the corrected saturated surface dry mass of each sample is as follows: in, For the first The corrected saturated surface dry mass of each sample to be tested. For the first The saturated surface dry mass of the test sample before correction. For the first The sign value of each sample to be tested. For the first Distribution deviation of the test samples Preset scaling factor; In this embodiment, the preset scaling factor is set to 5. The purpose is to adjust the correction strength for the saturated surface dry mass, avoiding excessive amplification or reduction of the saturated surface dry mass. The range of values ​​is ,but The range of values ​​is , The range of values ​​is ,but The range of values ​​is .

[0063] It should be noted that when the sign value is positive, the aggregate in the sample contains more large particles, requiring an amplification of the saturated surface-dry mass; when the sign value is negative, the aggregate in the sample contains more small particles, requiring a reduction of the saturated surface-dry mass. The flowchart of the method for obtaining the corrected saturated surface-dry mass provided in this application embodiment is shown below. Figure 2 As shown.

[0064] Furthermore, based on the corrected saturated dry mass and the mass after drying, the water absorption rate of each sample is calculated according to the formula for calculating water absorption rate, specifically: Obtain the mass of each sample at the last moment during the entire drying process, and use it as the mass of each sample after drying. In this embodiment, if the mass reduction of each sample to be tested is less than 0.3g within 10 minutes during the drying process, the drying is considered to be over. The mass at the last moment of the entire drying process is taken as the mass after drying. As another implementation method, the implementer can set it according to the actual situation.

[0065] The formula for calculating the water absorption rate of each sample is as follows: in, For the first The water absorption rate of the sample to be tested. For the first The corrected saturated surface dry mass of each sample to be tested. For the first The mass of each sample to be tested after drying.

[0066] The difference between the water absorption rate of each sample and the mean water absorption rate of all samples is denoted as the relative deviation. In this embodiment, the absolute value of the difference between the water absorption rate of each sample and the mean water absorption rate of all samples is denoted as the relative deviation.

[0067] The sample with the largest relative deviation is removed, and the average water absorption rate of all remaining samples is taken as the water absorption rate of the recycled aggregate, thus realizing the determination of the water absorption rate of the recycled aggregate.

[0068] Based on the same inventive concept as the above method, this application embodiment also provides a water absorption rate measuring device for recycled aggregate, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described methods for measuring the water absorption rate of recycled aggregate.

[0069] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0070] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0071] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application. Therefore, any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of this application, without departing from the content of the technical solution of this application, shall fall within the protection scope of the technical solution of this application.

Claims

1. A method for determining the water absorption rate of recycled aggregate, characterized in that, The method includes the following steps: Multiple samples were selected from the recycled aggregate to obtain the particle size distribution data of each sample and generate a particle size distribution curve. The samples were dried after soaking and the mass of each sample was collected at each time point during the drying process. Analyze the deviation of the particle size distribution curve from the Gaussian distribution, as well as the asymmetric distribution of the particle size distribution curve, and calculate the distribution deviation of each sample to be tested. Curve fitting and abrupt change detection were performed on the mass of each sample at different times during the initial drying stage. The trend of mass change on the fitted curve was analyzed, as well as the situation of abnormal mass change, to obtain the potential time. For each sample to be tested, the differences in mass fluctuations and mass change trends between the left and right sides at each potential time point are analyzed, the relative difference is calculated, and the judgment coefficient of each potential time point is determined by combining the correlation of mass changes between the left and right sides. The potential time points are then screened to obtain the target time point. Based on the rate of mass change of each sample after the target time, the mass at the target time is compensated to obtain the saturated surface dry mass of each sample. By analyzing the skewed distribution and deviation of the particle size distribution curve, the saturated surface dry mass is corrected, and the water absorption rate of each sample is calculated. The deviation of the water absorption rate of all samples is analyzed, and the water absorption rate of the recycled aggregate is determined.

2. The method for determining the water absorption rate of recycled aggregate as described in claim 1, characterized in that, The calculation of the distribution deviation of each sample to be tested includes: For each sample, the particle size distribution data is fitted with a Gaussian distribution to obtain the fitted Gaussian distribution curve; the area of ​​integral of the difference between the particle size distribution curve and the fitted Gaussian distribution curve is calculated. The difference between the median and the mean of the particle size distribution data for each sample is calculated and denoted as the relative difference. The relative difference is then negatively mapped. The distribution deviation is the normalized result of the ratio between the integral area and the result of the negative mapping.

3. The method for determining the water absorption rate of recycled aggregate as described in claim 1, characterized in that, The process of obtaining the potential time is as follows: obtain all inflection points on the fitting curve corresponding to each sample in the initial stage of drying; detect the mutation points of the quality at all times in the initial stage of drying and obtain all mutation points; record the time corresponding to the inflection point and the time corresponding to the mutation point in the initial stage of drying as the potential time.

4. The method for determining the water absorption rate of recycled aggregate as described in claim 1, characterized in that, The calculation of the relative difference includes: For each sample to be tested, the multiple times before each potential time and the multiple times after each potential time in the initial stage of drying are respectively recorded as the left local time period and the right local time period. The difference between the dispersion of quality at all times within the left local time interval and the dispersion of quality at all times within the right local time interval is calculated as the fluctuation difference at each potential time. The difference between the test statistic of the tangent slope of each potential time point on the fitted curve at all times in the left local time interval and the test statistic of the tangent slope of each potential time point in the right local time interval is calculated as the trend difference of each potential time point. The relative difference is the product of the fluctuation difference and the trend difference.

5. The method for determining the water absorption rate of recycled aggregate as described in claim 4, characterized in that, The determination of the judgment coefficients for each potential time point includes: Calculate the correlation of quality across all times between the left and right local time intervals, and perform a positive mapping on the absolute value of the correlation. The judgment coefficient is the ratio of the relative difference to the result of the positive mapping.

6. The method for determining the water absorption rate of recycled aggregate as described in claim 1, characterized in that, The process of obtaining the target time is as follows: sort the judgment coefficients of all potential times of each sample in the initial drying stage in descending order, select the judgment coefficients of the top-ranked potential times for clustering, count the number of potential times contained in each cluster, and select the potential time corresponding to the cluster center of the cluster with the largest number, which is recorded as the target time.

7. The method for determining the water absorption rate of recycled aggregate as described in claim 1, characterized in that, The process of obtaining the saturated surface-dry mass of each sample to be tested includes: Linear fitting is performed on the mass of each sample at all times after the target time, and the slope of the fitted line is taken as the evaporation rate; the interval time from the start of drying to the target time is calculated; the product of the interval time and the evaporation rate is taken as the compensation mass. The saturated surface dry mass is the sum of the mass corresponding to the target time and the compensation mass.

8. The method for determining the water absorption rate of recycled aggregate as described in claim 1, characterized in that, The correction of the saturated surface dry mass includes: Calculate the skewness of the particle size distribution curve for each sample to be tested. If the skewness is positive, assign a sign value of 1 to each sample to be tested; otherwise, assign a sign value of -1. No. Corrected saturated surface dry mass of the test sample The calculation formula is: ,in, For the first The saturated surface dry mass of the test sample before correction. For the first The sign value of each sample to be tested. For the first The distribution deviation of the test samples. This is the preset scaling factor.

9. The method for determining the water absorption rate of recycled aggregate as described in claim 1, characterized in that, The determination of the water absorption rate of the recycled aggregate includes: recording the difference between the water absorption rate of each sample and the mean water absorption rate of all samples as the relative deviation; removing the sample with the largest relative deviation, and taking the mean water absorption rate of all remaining samples as the water absorption rate of the recycled aggregate.

10. A device for measuring the water absorption rate of recycled aggregate, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for determining the water absorption rate of recycled aggregate as described in any one of claims 1-9.

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