Method and system for predicting and regulating curing strength of mortar under low-temperature curing conditions

Abstract

This invention discloses a method and system for predicting and controlling the curing strength of mortar under low-temperature curing conditions. By real-time monitoring of the resistivity of mortar specimens under different low-temperature environments, a logarithmic resistivity calculation system for mortar with four temperature gradients (0℃, -5℃, -10℃, and -15℃) is established. A linear interpolation method is used to determine the logarithmic resistivity of mortar corresponding to curing temperatures between adjacent temperature gradients. Based on the logarithmic resistivity, a quantitative prediction model of its relationship with mortar compressive strength is constructed to obtain the real-time curing strength within curing time t and the 28-day curing strength. The curing quality is evaluated using the 28-day curing strength of three groups of mortar specimens, and the mortar curing environment parameters are intelligently adjusted based on the evaluation results. This method can predict the strength development of mortar under low-temperature curing in real time, intelligently control the curing environment, ensure that curing quality meets standards, avoid rework, and improve construction efficiency.

Description

Technical Field

[0001] This invention relates to the field of building material maintenance technology, specifically to a method and system for predicting and controlling the curing strength of mortar under low-temperature curing conditions. Background Technology

[0002] The cold, high-altitude regions of western China have average monthly temperatures below zero degrees Celsius, accompanied by harsh environmental characteristics such as oxygen deficiency and drastic diurnal temperature variations. This region has become a key area for the construction of the State Grid. During the construction of transmission line foundations, the extreme low temperatures significantly reduce the hydration rate of cement mortar, slowing down strength development and making it difficult to meet durability requirements. Without effective methods for controlling curing strength, the construction quality of cement mortar-based transmission line foundations will face serious risks, threatening the safe and stable operation of overhead transmission lines and their reliability throughout their entire life cycle, constituting a core obstacle to the construction of power grid infrastructure in cold, high-altitude regions. Traditionally, the quality control of mortar curing in low-temperature environments relies mainly on the experience and judgment of construction personnel combined with compressive strength tests on test blocks after curing. This involves setting curing time and temperature parameters based on subjective experience, and then verifying the strength after the curing stage is completed. Some projects have attempted to use basic temperature monitoring or manual inspection as supplementary methods, but these methods have significant drawbacks: experience-based judgment lacks objective standards, and differences in operation among different construction personnel make it unsuitable for the varying temperature gradients in high-altitude and cold regions; post-construction testing has a significant lag, and when strength fails to meet standards, remedial measures cannot be implemented, requiring rework and resulting in a substantial increase in project costs and construction time; temperature monitoring can only obtain environmental parameter information and cannot directly reflect the internal hydration reaction state and strength development level of the mortar, making it difficult to achieve precise control of curing quality. Resistivity monitoring technology, as an emerging characterization method in the field of building material curing, can indirectly characterize the hydration reaction process and microstructure evolution through the resistivity evolution law of cementitious materials, providing a potential possibility for real-time monitoring of mortar strength development. However, the current application of this technology in low-temperature mortar curing is limited to the simple collection of resistivity data. A quantitative mathematical model between resistivity and mortar compressive strength has not yet been established, making it impossible to accurately predict curing strength based on resistivity data. Furthermore, the resistivity monitoring process is disconnected from the curing environment parameter control process, lacking a complete "monitoring-prediction-control" closed-loop mechanism. Even with resistivity information, it is impossible to dynamically adjust the curing environment according to the strength development trend, thus failing to solve the fundamental problems of slow mortar strength development and insufficient quality assurance in low-temperature environments. The reason for this is that the complex temperature gradients in high-altitude and cold regions cause the correlation between mortar resistivity evolution and strength development to differ significantly from that in normal temperature environments. Existing technologies have neither constructed a dedicated resistivity measurement system for the typical low-temperature range of 0°C to -15°C, nor developed strength prediction methods and curing control strategies based on resistivity data. This prevents resistivity monitoring technology from being transformed into practical control capabilities in low-temperature mortar curing.Therefore, in the foundation engineering of transmission lines in high-altitude and cold regions, it is difficult to monitor the hydration process and strength development of mortar in real time. The traditional maintenance methods have prominent problems of experience dependence and lag. New resistivity monitoring technologies lack supporting prediction models and control systems. There is an urgent need to develop a technical solution that can realize real-time prediction of mortar strength and intelligent control of maintenance quality under low-temperature maintenance conditions. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for predicting and controlling the curing strength of mortar under low-temperature curing conditions. This method can predict the strength development of mortar under low-temperature curing conditions in real time and intelligently control the curing environment based on the prediction results, thereby ensuring that the curing quality meets the standards, avoiding rework, and improving construction efficiency.

[0004] This invention provides a method for predicting and controlling the curing strength of mortar under low-temperature curing conditions, comprising the following steps: By real-time monitoring of the resistivity of mortar test blocks in different low-temperature environments, a system for calculating the logarithmic resistivity of mortar under four temperature gradients of 0℃, -5℃, -10℃, and -15℃ was established. The logarithmic resistivity of the mortar was determined by linear interpolation for the curing temperatures between adjacent temperature gradients. A quantitative prediction model for mortar compressive strength is established based on the logarithmic resistivity to obtain the real-time curing strength and 28-day curing strength of mortar at curing time t. The curing quality was evaluated by measuring the 28-day curing intensity of three groups of mortar test blocks, and the curing environment parameters of the mortar were intelligently controlled based on the evaluation results.

[0005] Furthermore, the establishment of the mortar logarithmic resistivity measurement system under four temperature gradients of 0℃, -5℃, -10℃, and -15℃ includes: For each temperature gradient of 0℃, -5℃, -10℃, and -15℃, the logarithmic resistivity of the mortar at different curing times is calculated using the following formula: At 0℃: (1) At -5℃: (2) At -10℃: (3) At -15℃: (4) in, t represents the resistivity of the mortar under different curing times, in Ω∙m; t represents the mortar curing time, in hours / h.

[0006] Furthermore, the determination of the logarithmic resistivity of the corresponding mortar using linear interpolation for the curing temperatures between adjacent temperature gradients includes: For curing temperatures in the range of 0℃~-5℃~-10℃~-15℃, the resistivity of the corresponding mortar is calculated using a linear interpolation formula. (5) in, For mortar at curing temperature The resistivity of the sample, expressed in Ω∙m; , Given the ambient temperature; , The known resistivity of the mortar at the given ambient temperature.

[0007] Furthermore, the quantitative prediction model for the compressive strength of mortar based on the logarithmic resistivity, and the acquisition of the real-time curing strength of the mortar at curing time t, includes: Substituting the calculated logarithmic resistivity of the mortar into the compressive strength prediction formula, the predicted compressive strength of the mortar at curing time t is calculated. , (6) in, The predicted compressive strength of the mortar at curing time t is expressed in MPa.

[0008] Furthermore, obtaining the 28-day curing strength of the mortar includes: Substituting the curing time t=24×28h into the compressive strength prediction formula, the 28-day curing strength of the mortar under a specific state is calculated.

[0009] Furthermore, the evaluation of curing quality through the 28-day curing strength of three groups of mortar test blocks includes: Calculate the average predicted strength of the 28-day curing strength of the 3 groups of mortar test blocks: (7) (8) in, The average value of the predicted mortar strength of the three test blocks; This refers to the standard value of mortar strength. The maximum predicted strength of the mortar in the test block; This represents the minimum predicted strength of the mortar in the test block.

[0010] Furthermore, the evaluation criteria for the maintenance quality include the matching between the average predicted strength of the mortar and the standard value of the mortar strength specification, and the range of the difference between the maximum and minimum predicted strength of the mortar in the test block; The criteria for evaluating the quality of mortar maintenance are as follows: when the average predicted strength of the mortar is not lower than the standard value of the mortar strength specification, and the difference between the maximum and minimum predicted strength of the mortar is within a preset reasonable range, the mortar maintenance quality is deemed to meet the standard; otherwise, the mortar maintenance quality is deemed to fail to meet the standard.

[0011] Furthermore, the intelligent control of mortar curing environment parameters based on the curing quality evaluation results includes: When the mortar curing quality is determined to be substandard, control measures should be taken to increase the temperature of the curing environment, improve the mortar hydration reaction conditions, and improve the mortar curing quality.

[0012] Furthermore, the resistivity monitoring of the mortar test block is conducted continuously in real time, and the calculation of the logarithmic resistivity of the mortar, the prediction of compressive strength, the evaluation of curing quality, and the control of curing environment parameters are all performed dynamically in real time.

[0013] The present invention also provides a mortar curing strength prediction and control system for realizing the above-mentioned method for predicting and controlling the curing strength of mortar under low-temperature curing conditions. The system includes a resistivity monitoring module, a data processing module, a strength prediction module, a quality evaluation module, and a curing control module. The resistivity monitoring module is signal-connected to the data processing module, the data processing module is signal-connected to the strength prediction module, the strength prediction module is signal-connected to the quality evaluation module, and the quality evaluation module is signal-connected to the curing control module.

[0014] Furthermore, the resistivity monitoring module is used to monitor the resistivity data of mortar test blocks in different low-temperature environments in real time, and transmit the resistivity data to the data processing module; the data processing module is used to establish a four-level temperature gradient calculation system of 0℃, -5℃, -10℃, and -15℃, perform logarithmic transformation on the resistivity data, and complete the logarithmic resistivity data between adjacent temperature gradients using linear interpolation, and transmit the processed logarithmic resistivity data to the strength prediction module; the strength prediction module is used to calculate the real-time curing strength and 28-day curing strength of the mortar at curing time t based on the logarithmic resistivity data using the compressive strength prediction formula, and transmit the strength data to the quality evaluation module; the quality evaluation module is used to calculate the predicted average strength based on the 28-day curing strength of the three groups of mortar test blocks, and perform curing quality evaluation by combining the mortar strength specification standard value, the predicted maximum strength value, and the minimum strength value, and transmit the evaluation result to the curing control module; the curing control module is used to intelligently adjust the mortar curing environment temperature parameters according to the curing quality evaluation results.

[0015] Furthermore, the resistivity monitoring module is equipped with a low-temperature environment-adapted resistivity sensor, which is embedded inside the mortar specimen to collect real-time resistivity signals of the mortar specimen under different curing times and temperature gradients. The data processing module, strength prediction module, and quality evaluation module are integrated into a data computing terminal, which has built-in temperature gradient calculation program, linear interpolation calculation program, and compressive strength prediction program. The curing control module is equipped with a temperature control execution unit, which is connected to the temperature control equipment of the mortar curing environment and is used to adjust the output parameters of the temperature control equipment according to the control command.

[0016] Compared with existing technologies, this invention achieves real-time prediction and dynamic control of mortar strength by real-time monitoring of resistivity, establishing a logarithmic resistivity calculation system under a four-level temperature gradient, using linear interpolation to complete data, constructing a quantitative prediction model to obtain real-time and 28-day strength, evaluating quality based on the strength of multiple test blocks, and intelligently adjusting environmental parameters. It can predict the strength development of mortar under low-temperature curing conditions in real time and intelligently adjust the curing environment according to the prediction results, thereby ensuring that the curing quality meets the standards, avoiding rework, and improving construction efficiency. Attached Figure Description

[0017] Figure 1 A flowchart illustrating a method for predicting and controlling the curing strength of mortar under low-temperature curing conditions, provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a mortar curing strength prediction and control system under low-temperature curing conditions, provided in an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining the present invention and not for limiting the present invention. It should also be noted that, for ease of description, only the parts relevant to the present invention are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as being processed sequentially, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. A process can be terminated when its operation is completed, but it may also have additional steps not included in the drawings. A process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0019] The terms "first," "second," etc., used in the specification and claims of this invention are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0020] like Figure 1 As shown, this invention proposes a method for predicting and controlling the curing strength of mortar under low-temperature curing conditions, comprising the following steps: By real-time monitoring of the resistivity of mortar test blocks in different low-temperature environments, a system for calculating the logarithmic resistivity of mortar under four temperature gradients of 0℃, -5℃, -10℃, and -15℃ was established. The logarithmic resistivity of the mortar was determined by linear interpolation for the curing temperatures between adjacent temperature gradients. A quantitative prediction model for mortar compressive strength was established based on the logarithmic resistivity to obtain the real-time curing strength and 28-day curing strength of mortar at curing time t. The curing quality was evaluated by measuring the 28-day curing intensity of three groups of mortar test blocks, and the curing environment parameters of the mortar were intelligently controlled based on the evaluation results.

[0021] Specifically, this method first involves real-time monitoring of the resistivity of mortar specimens in different low-temperature environments. Resistivity monitoring can be achieved by embedding sensors inside the mortar specimens or by periodic measurements using external contact probes. The collected resistivity data is recorded and stored. Subsequently, based on this monitoring data, a logarithmic resistivity calculation system for mortar under four temperature gradients (0℃, -5℃, -10℃, and -15℃) is established. This system is established through statistical analysis of a large amount of experimental data, fitting the variation law of resistivity with curing time under different temperature gradients, for example, by plotting curves or establishing empirical tables.

[0022] In some implementations, for curing temperatures falling between the four temperature gradients mentioned above, a linear interpolation method is used to determine the corresponding logarithmic resistivity of the mortar. For example, when the curing temperature is between 0°C and -5°C, the logarithmic resistivity at this intermediate temperature can be estimated by simple proportional calculation based on known logarithmic resistivity data at 0°C and -5°C. This method allows for obtaining corresponding resistivity data even under non-standard temperature gradients.

[0023] Based on this, a quantitative prediction model for mortar compressive strength is established using the established logarithmic resistivity of mortar. This model can be built by using regression analysis, neural network training, etc., taking logarithmic resistivity as input and mortar compressive strength as output, thus establishing a mapping relationship between the two. Once the model is established, the logarithmic resistivity obtained through real-time monitoring or interpolation can be substituted into the model to obtain the real-time curing strength of the mortar at any curing time t. For the 28-day curing strength, the curing time can be set to 28 days and then substituted into the prediction model for calculation.

[0024] Therefore, the curing quality was evaluated by assessing the 28-day curing strength of three groups of mortar test blocks. This evaluation involved comparing the predicted 28-day curing strength with preset strength standards through manual comparison and standard review. For example, a minimum strength threshold could be set; if the predicted strength was lower than this threshold, the curing quality was deemed substandard. Subsequently, based on the curing quality evaluation results, the mortar curing environment parameters were intelligently controlled. For instance, when the curing quality was substandard, the temperature setting of the curing equipment could be manually adjusted, or a simple logic judgment system could trigger heating or insulation measures to improve the mortar hydration conditions.

[0025] This method overcomes the subjectivity of traditional experience-based judgments and the lag of post-event testing by real-time monitoring of mortar resistivity and establishing a logarithmic resistivity calculation system under temperature gradients. Through a quantitative prediction model, it achieves real-time and accurate prediction of mortar curing strength, avoiding the problem of unrecoverable insufficient strength. Furthermore, based on the curing quality evaluation results, environmental parameters are intelligently controlled, forming a closed-loop management system of "monitoring-prediction-control," ensuring the controllability of mortar strength development in low-temperature environments in high-altitude and cold regions, and guaranteeing project quality.

[0026] When predicting and controlling the curing strength of mortar under low-temperature curing conditions, a precise system for calculating the logarithmic resistivity of mortar is needed. However, in practice, accurately obtaining the logarithmic resistivity of mortar for different temperature gradients and ensuring the scientific validity and operability of the calculation system are key challenges for achieving accurate prediction and control. Without specific and quantitative calculation methods, the accuracy of subsequent strength predictions will be difficult to guarantee.

[0027] In some implementations, the above-mentioned system for calculating the logarithmic resistivity of mortar under four temperature gradients of 0℃, -5℃, -10℃, and -15℃ is proposed. This includes calculating the logarithmic resistivity of mortar at different curing times for each temperature gradient of 0℃, -5℃, -10℃, and -15℃ according to the following formula. At 0℃: (1) At -5℃: (2) At -10℃: (3) At -15℃: (4) in, t represents the resistivity of the mortar under different curing times, in Ω∙m; t represents the mortar curing time, in / h.

[0028] The purpose of this measurement system is to provide fundamental data for subsequent strength prediction by quantifying the resistivity changes of mortar under specific low-temperature environments. Resistivity, as a macroscopic reflection of ion migration and hydration levels within mortar, has a logarithmic form that better characterizes the nonlinear characteristics of mortar strength development. By collecting data and building models at multiple typical low-temperature points, the applicability and accuracy of the measurement system under different low-temperature conditions can be ensured, providing a solid data foundation for subsequent strength prediction.

[0029] For each specific temperature gradient, independent empirical formulas are used to calculate the logarithmic resistivity of mortar at different curing times. This is based on the scientific fact that the hydration reaction rate and ion migration characteristics of mortar differ significantly at different temperatures. These formulas are usually obtained by fitting a large amount of experimental data, which can accurately capture the change of mortar resistivity over time under specific low-temperature environments. For example, at 0℃, the hydration reaction of mortar can still occur, but at a slower rate, and the resistivity may show a specific increasing trend over time; while at lower temperatures such as -15℃, the hydration reaction may almost stop, but physical processes such as ice crystal formation may affect the resistivity, thus requiring different mathematical models to describe it.

[0030] Formulas (1), (2), (3), and (4) above are obtained by fitting experimental data obtained from long-term real-time resistivity monitoring of mortar specimens under corresponding temperature gradients through regression analysis and other methods. The coefficients and structure of each formula have been optimized to reflect the intrinsic relationship between mortar resistivity and curing time at that temperature to the greatest extent. For example, the formula may contain exponential, logarithmic, or polynomial terms to accurately simulate the rapid change in resistivity in the early stage of curing and its tendency to stabilize in the later stage. Among them, ρ_t represents the real-time resistivity of mortar at a specific curing time t, and its unit is ohmmeter (Ω∙m), which is the internationally accepted unit of resistivity. t represents the curing time of mortar, in hours (h), used to quantify the time that the mortar has experienced from the start of mixing to the current moment. These parameters are the input variables used in the calculation. By obtaining ρ_t through real-time monitoring and combining it with the known curing time t, the logarithmic resistivity of the mortar can be calculated using the corresponding formula.

[0031] In some implementations, a linear interpolation method is proposed to determine the logarithmic resistivity of the mortar for the curing temperature between adjacent temperature gradients. Specifically, for curing temperatures in the range of 0℃ to -5℃ to -10℃ to -15℃, the resistivity of the corresponding mortar is calculated according to the linear interpolation formula. (5) in, For mortar at curing temperature The resistivity of the sample, expressed in Ω∙m; , Given the ambient temperature; , The known resistivity of the mortar at the given ambient temperature.

[0032] This step aims to address the issue that in actual low-temperature curing environments, the curing temperature may not perfectly match the preset discrete gradients of 0℃, -5℃, -10℃, and -15℃. By employing linear interpolation, the resistivity of mortar at any curing temperature between these discrete points can be calculated based on the known resistivity data at these discrete temperature points. This allows the acquisition of resistivity data to no longer be limited to a few specific temperature points, but to cover a continuous temperature range, thus providing more comprehensive and refined data support for subsequent strength prediction. Formula (5) is the specific mathematical model for linear interpolation calculation. Here, represents the mortar resistivity at the target curing temperature, which is the value that needs to be obtained through interpolation calculation. and represent two adjacent known ambient temperatures, such as 0℃ and -5℃, or -5℃ and -10℃, etc. and represent the known resistivity of mortar at these two known ambient temperatures, respectively. These known resistivities can be obtained by real-time monitoring and calculation of the logarithmic resistivity using the aforementioned formula, followed by inverse conversion. This formula allows for the calculation of resistivity at the target temperature based on the relative positions of the target curing temperature and two known temperatures, thus enabling an effective estimation of resistivity at intermediate temperature points.

[0033] In some implementations, a quantitative prediction model for the compressive strength of mortar is proposed based on the logarithmic resistivity to obtain the real-time curing strength of mortar at curing time t. The specific steps include: substituting the calculated logarithmic resistivity of mortar into the compressive strength prediction formula to calculate the predicted compressive strength of mortar at curing time t. , (6) in, The predicted compressive strength of the mortar at curing time t is expressed in MPa.

[0034] This step aims to transform the logarithmic resistivity data of mortar obtained through real-time monitoring and data processing into a compressive strength value with practical engineering significance. The compressive strength prediction formula (6) is a pre-established mathematical model that reflects the quantitative relationship between the logarithmic resistivity of mortar and its compressive strength. This formula is usually obtained by fitting a large amount of experimental data. For example, under different low-temperature environments, while monitoring the resistivity of mortar specimens, compressive strength tests are conducted regularly to establish an empirical relationship between resistivity and compressive strength. The formula can be linear, nonlinear, polynomial, or exponential in form, depending on the characteristics of the mortar material and the curing conditions. By using the real-time measured logarithmic resistivity of the mortar as input, the formula can output the corresponding predicted compressive strength.

[0035] After obtaining the logarithmic resistivity of the mortar at a specific curing time t, its value is substituted into the preset compressive strength prediction formula (6) to calculate the predicted compressive strength of the mortar at that time. This calculation process is usually completed automatically by the data processing terminal or the strength prediction module, ensuring the real-time nature and accuracy of the prediction results. The unit of the predicted compressive strength is MPa, which directly reflects the mechanical properties of the mortar under the current curing conditions and curing time.

[0036] In some implementations, a method for obtaining the 28-day curing strength of mortar is proposed, which includes substituting the curing time t=24×28h into the compressive strength prediction formula to calculate the 28-day curing strength of mortar under a specific state.

[0037] Specifically, the step of substituting the curing time t=24×28h into the compressive strength prediction formula aims to introduce a standardized time parameter into the established compressive strength prediction model. Here, the curing time t=24×28h represents the 28th day of mortar curing, expressed precisely in hours. In the field of construction engineering, the 28-day curing strength is a key indicator for evaluating the performance of concrete or mortar, and is widely used as a benchmark for design strength and quality control. By substituting this specific time into the compressive strength prediction formula established in the above embodiments (as shown in formula (6)), the strength performance of mortar when reaching the standard curing period can be predicted based on real-time monitored resistivity data. The compressive strength prediction formula is usually an empirical or semi-empirical formula that correlates the logarithmic resistivity of mortar with its compressive strength, reflecting the hydration process and strength development patterns of the mortar.

[0038] By substituting the above calculations, the 28-day curing strength of the mortar under specific curing conditions and states can be obtained. Here, "specific states" refers to the degree of hydration and microstructure development of the mortar as reflected by resistivity monitoring in an actual low-temperature curing environment. The calculated 28-day curing strength is a predictive value that can reflect the strength level of the mortar at the end of the standard curing cycle in advance, without waiting for the actual 28-day curing to be completed and for destructive testing to be conducted. This predictive value has important guiding significance for engineering decisions, such as assessing whether the mortar meets design requirements and whether the curing plan needs to be adjusted.

[0039] In some implementations, the curing quality is evaluated by calculating the average predicted strength of the 28-day curing strength of three groups of mortar test blocks. (7) (8) in, The average value of the predicted mortar strength of the three test blocks; This refers to the standard value of mortar strength. The maximum predicted strength of the mortar in the test block; This represents the minimum predicted strength of the mortar in the test block.

[0040] To more comprehensively and accurately assess the curing quality of mortar, this embodiment adopts a method of predicting the strength of multiple groups of mortar test blocks and calculating their average value. Specifically, three groups of mortar test blocks are selected for strength prediction. These three groups of test blocks are usually taken from the same batch or the same construction area to ensure their representativeness. By predicting the 28-day curing strength of these three groups of test blocks respectively and calculating their average predicted strength, the impact of random errors of individual test blocks on the overall evaluation results can be effectively reduced, and the reliability of the curing quality evaluation can be improved. Among them, the average predicted strength of mortar is calculated by formula (7). In this formula, represents the average predicted strength of the mortar of the three groups of test blocks, which represents the overall strength level of the batch of mortar after the 28-day curing period; represents the standard value of mortar strength specification, which is usually derived from relevant national or industry standards and is the benchmark for measuring whether the mortar strength meets the standard. Furthermore, to further evaluate the stability of the curing process, this embodiment also calculates the difference between the maximum and minimum predicted mortar strength in the test block using formula (8), where represents the maximum predicted mortar strength in the test block, and represents the minimum predicted mortar strength in the test block. By calculating the difference between the maximum and minimum values, the dispersion or uniformity of mortar strength among different test blocks can be reflected.

[0041] In some implementations, the criteria for evaluating the curing quality include the matching between the average predicted strength of the mortar and the standard value of the mortar strength specification, and the range of the difference between the maximum and minimum predicted strength of the mortar in the test block. The criteria for evaluating the curing quality are as follows: when the average predicted strength of the mortar is not lower than the standard value of the mortar strength specification, and the difference between the maximum and minimum predicted strength of the mortar is within a preset reasonable range, the mortar curing quality is deemed to meet the standard; otherwise, the mortar curing quality is deemed to fail to meet the standard.

[0042] Specifically, among the evaluation criteria for maintenance quality, the matching between the average predicted strength of the mortar and the standard value of the mortar strength specification aims to assess whether the overall strength level of the mortar meets the expected standard requirements. The average predicted strength of the mortar is calculated based on the predicted strength of multiple test blocks and represents the average performance of that batch of mortar, while the standard value of the mortar strength specification is the minimum strength requirement specified by the industry or engineering design. In actual operation, the data processing terminal compares the calculated average predicted strength of the mortar from three groups of test blocks with the pre-set standard value of the mortar strength specification to determine whether they meet the matching requirements.

[0043] Meanwhile, the judgment index also includes the range of difference between the maximum and minimum predicted mortar strength values ​​in the test blocks, which is mainly used to evaluate the uniformity and stability of mortar curing quality. Mortar test blocks from the same batch and under the same curing conditions should theoretically have relatively similar strengths. If the difference between the maximum and minimum values ​​is too large, it indicates that there may be inhomogeneity in the curing process, such as uneven temperature distribution or improper humidity control, leading to significant differences in mortar strength at different locations. In the data processing terminal, the maximum and minimum predicted mortar strength values ​​of three groups of test blocks are acquired, and their differences are calculated. These differences are then compared with a preset reasonable range, which can be determined based on empirical data, industry standards, or engineering requirements.

[0044] Based on this, the criteria for evaluating the curing quality are set as follows: The mortar curing quality can be deemed satisfactory only when the average predicted strength of the mortar is not lower than the standard value specified in the mortar strength specification, and the difference between the maximum and minimum predicted strength values ​​in the test block is within a preset reasonable range; otherwise, the mortar curing quality is deemed unsatisfactory. This judgment logic is implemented through programming in the quality evaluation module of the data calculation terminal. First, it checks whether the average value meets the standard. If so, it further checks whether the strength difference is within a reasonable range. Only when both conditions are met does the system output the evaluation result of "curing quality meets the standard"; otherwise, it outputs "curing quality does not meet the standard".

[0045] In some implementations, intelligent control of mortar curing environment parameters is proposed based on the curing quality evaluation results, including: when the mortar curing quality is determined to be substandard, taking control measures to increase the curing environment temperature, improving the mortar hydration reaction conditions, and improving the mortar curing quality.

[0046] Specifically, when mortar curing quality is deemed substandard, this condition is based on the results of the aforementioned curing quality evaluation. For example, when the average predicted strength of the mortar is lower than the standard value specified in the mortar strength specification, or when the difference between the maximum and minimum predicted strength exceeds a preset reasonable range, the system will trigger this substandard judgment. This judgment serves as a signal to initiate subsequent control measures, ensuring the targeted and timely nature of the control. Taking control measures to increase the temperature of the curing environment means that the system will actively intervene in the curing environment of the mortar. This control measure can be achieved in various ways, such as increasing the heat input in the curing space by controlling heating equipment (such as electric heaters, warm air blowers, etc.), or adjusting the coverage of insulation materials to reduce heat loss. The core is to increase the temperature around the mortar through external energy input, thereby providing more favorable thermodynamic conditions for the mortar hydration reaction. Improving the mortar hydration reaction conditions is crucial, as the hydration reaction of mortar is an exothermic process, but its reaction rate is significantly affected by temperature. In low-temperature environments, the hydration reaction becomes slow or even stops. Increasing the temperature of the curing environment increases the kinetic energy of water molecules and cement particles, accelerating chemical reactions and promoting the formation of cement hydration products and crystal growth, thereby optimizing the microstructure of the mortar. Improving the quality of mortar curing is the ultimate goal of these control measures. By improving hydration reaction conditions, the mortar can hydrate more fully, forming a dense structure, thus significantly improving its key performance indicators such as compressive strength and durability, ensuring that the actual performance of the mortar meets design requirements and engineering specifications.

[0047] Predicting and controlling the curing strength of mortar under low-temperature curing conditions requires real-time acquisition, processing, and feedback of mortar status information. However, if data acquisition, strength prediction, quality evaluation, and environmental control are not synchronized and continuous, the system response may be delayed, failing to accurately reflect the actual curing status of the mortar. This would affect the timeliness and effectiveness of control, and could even lead to deviations in curing quality.

[0048] To address this, this embodiment proposes an improved scheme, in which the resistivity monitoring of mortar test blocks is set to real-time continuous monitoring, and the calculation of mortar logarithmic resistivity, prediction of compressive strength, evaluation of curing quality, and control of curing environment parameters are all executed dynamically in real time. Specifically, the real-time continuous monitoring of mortar test block resistivity means that the resistivity sensor will continuously collect resistivity signals of mortar test blocks under different curing times and temperature gradients. This continuity ensures the integrity and immediacy of the data stream, providing the latest and most comprehensive basic data for subsequent data processing and strength prediction. For example, by configuring a resistivity sensor with a high sampling frequency and combining it with a stable data transmission link, a millisecond or second-level response to changes in mortar resistivity can be achieved, thereby capturing subtle changes in the mortar hydration process. Simultaneously, the calculation of mortar logarithmic resistivity, prediction of compressive strength, evaluation of curing quality, and control of curing environment parameters are all set to be executed dynamically in real time. This means that once new resistivity data is detected, the system will immediately initiate a series of processing steps, including logarithmic transformation, linear interpolation, compressive strength calculation, and curing quality assessment, and will issue control commands in real time based on the assessment results. This dynamic execution mechanism ensures low latency and high responsiveness throughout the entire predictive control process, enabling the system to quickly make corresponding adjustments based on real-time changes in the mortar's condition. For example, when the predicted strength deviates from the target value, the system can immediately adjust the curing environment temperature to correct the deviation.

[0049] By setting the resistivity monitoring of mortar test blocks to real-time continuous monitoring, and enabling the calculation of mortar logarithmic resistivity, prediction of compressive strength, evaluation of curing quality, and control of curing environment parameters to be executed dynamically in real time, this embodiment ensures a high degree of immediacy and responsiveness throughout the entire chain from data acquisition to final control. This avoids problems such as inaccurate predictions and untimely control caused by data lag or processing delays, allowing the system to continuously and accurately grasp the curing status of the mortar and quickly adjust curing environment parameters according to actual conditions. Therefore, it can significantly improve the accuracy of mortar curing strength prediction and the precision of curing control under low-temperature conditions, thereby effectively ensuring the curing quality of the mortar.

[0050] During the construction of power transmission line foundations in high-altitude and frigid regions, the extreme low temperatures significantly reduce the hydration rate of cement mortar, resulting in slow strength development and difficulty in ensuring durability. Traditional maintenance methods often rely on experience-based judgment combined with post-construction testing, which suffers from strong subjectivity and time lag. Furthermore, new resistivity monitoring technologies have not yet formed a corresponding prediction and control system, lacking a closed-loop logic of "monitoring-prediction-control".

[0051] like Figure 2As shown in the figure, this embodiment proposes a mortar curing strength prediction and control system. The system includes a resistivity monitoring module, a data processing module, a strength prediction module, a quality evaluation module, and a curing control module. The resistivity monitoring module is signal-connected to the data processing module, the data processing module is signal-connected to the strength prediction module, the strength prediction module is signal-connected to the quality evaluation module, and the quality evaluation module is signal-connected to the curing control module.

[0052] Specifically, the resistivity monitoring module monitors the resistivity data of mortar test blocks in different low-temperature environments in real time and transmits the data to the data processing module. The data processing module establishes a four-level temperature gradient calculation system (0℃, -5℃, -10℃, -15℃), performs logarithmic transformation on the resistivity data, and completes the logarithmic resistivity data between adjacent temperature gradients using linear interpolation. The strength prediction module calculates the real-time curing strength and 28-day curing strength of the mortar at curing time t based on the processed logarithmic resistivity data and the compressive strength prediction formula. The quality evaluation module calculates the average predicted strength based on the 28-day curing strength of the three groups of mortar test blocks and evaluates the curing quality in conjunction with the standard value of mortar strength specifications. The curing control module intelligently adjusts the temperature parameters of the mortar curing environment based on the evaluation results.

[0053] The innovation of this embodiment lies in constructing a closed-loop system by connecting the resistivity monitoring module, data processing module, strength prediction module, quality evaluation module, and maintenance control module through signals. This enables real-time perception, accurate prediction, and dynamic control of mortar strength development under low-temperature conditions, effectively solving the problems of subjective experience-based judgment and delayed post-event testing in traditional methods, which lead to unrecoverable substandard strength. This significantly improves the controllability and reliability of power grid infrastructure construction quality in high-altitude and cold regions.

[0054] In response, some implementations have proposed a system for predicting and controlling the curing strength of mortar under low-temperature curing conditions. While this system defines the main functional modules and their signal connections, the specific functional responsibilities of each module, the data processing flow, and the details of how they collaborate to complete the entire prediction and control process are not clearly defined. This may lead to uncertainties in the functional implementation and data interaction efficiency of each module during actual operation, affecting the accuracy and real-time performance of the prediction and control.

[0055] To address the aforementioned issues, this embodiment clarifies the specific functions of each module in the system. Specifically, the resistivity monitoring module is used to monitor the resistivity data of mortar specimens under different low-temperature environments in real time and transmit the resistivity data to the data processing module. This resistivity monitoring module is the sensing layer of the entire system, and its core function is to acquire real-time resistivity data of mortar specimens under different low-temperature environments. By continuously and accurately collecting this raw data, it provides the basic input for subsequent data processing and strength prediction. The resistivity monitoring module typically includes a high-precision sensor and a data acquisition unit, capable of converting physical signals into processable electrical or digital signals and ensuring the stability and reliability of data transmission.

[0056] The data processing module is used to establish a four-level temperature gradient calculation system of 0℃, -5℃, -10℃, and -15℃, perform logarithmic transformation on the resistivity data, and complete the logarithmic resistivity data between adjacent temperature gradients through linear interpolation. The processed logarithmic resistivity data is then transmitted to the intensity prediction module. The data processing module is the data preprocessing center of the system, and its main function is to transform the original resistivity data into standardized data that meets the requirements of the prediction model. Establishing a four-level temperature gradient calculation system means that the module has preset or dynamically loaded a relationship model between mortar resistivity and curing time at a specific low temperature point, for example, through the calculation methods described by formulas (1) to (4). The logarithmic transformation process is to perform logarithmic operations on the real-time monitored resistivity data to match the preset logarithmic resistivity calculation system, thereby eliminating differences in data dimensions or nonlinear relationships, which facilitates subsequent mathematical modeling. When the actual curing temperature is between the preset temperature gradient, the module will use linear interpolation, for example, by using the calculation method shown in formula (5), to estimate and complete the logarithmic resistivity data of adjacent known temperature points, so as to ensure that continuous and accurate logarithmic resistivity data can be obtained at any curing temperature, and to provide a complete data chain for intensity prediction.

[0057] The strength prediction module is used to calculate the real-time curing strength and 28-day curing strength of mortar at curing time t based on the logarithmic resistivity data and the compressive strength prediction formula, and transmits the strength data to the quality evaluation module. The strength prediction module is the core calculation unit of the system, and its function is to convert the processed logarithmic resistivity data into the mortar compressive strength index of concern in engineering. The module has a built-in or loaded quantitative prediction model of mortar logarithmic resistivity and compressive strength, such as the compressive strength prediction formula described by formula (6). By substituting the real-time logarithmic resistivity data output by the data processing module and the current curing time t into the formula, the real-time curing strength of mortar at the current curing time can be calculated. At the same time, in order to evaluate the curing quality, the module will also fix the curing time t to 28 days (i.e., t=24×28h), substitute it into the same compressive strength prediction formula, and calculate the 28-day curing strength of mortar.

[0058] The quality evaluation module is used to calculate the predicted average strength based on the 28-day curing strength of three groups of mortar test blocks, and to evaluate the curing quality by combining the standard value of mortar strength, the maximum value of the predicted strength, and the minimum value of the predicted strength. The evaluation results are then transmitted to the curing control module. The quality evaluation module is the decision support unit of the system. Its function is to comprehensively evaluate the predicted mortar strength and determine whether the curing effect meets the expected standard. The module first calculates the predicted average strength based on the 28-day curing strength of the three groups of mortar test blocks provided by the strength prediction module, according to formulas (7) and (8). Subsequently, the module compares this average value with the preset standard value of mortar strength and analyzes whether the difference between the maximum and minimum values ​​of the predicted strength in the three groups of test blocks is within the preset reasonable range. By comprehensively considering these indicators, the module can objectively and quantitatively evaluate the curing quality of the mortar according to the preset judgment criteria (for example, when the predicted average strength is not lower than the standard value and the difference between the maximum and minimum values ​​is within the reasonable range, it is judged as meeting the standard), and output the evaluation results.

[0059] The curing control module is used to intelligently adjust the temperature parameters of the mortar curing environment based on the curing quality evaluation results. The curing control module is the system's execution control unit, and its function is to intervene in the curing environment in real time and intelligently, forming a closed-loop control, based on feedback from the quality evaluation module. When the quality evaluation module determines that the mortar curing quality is substandard, the curing control module will generate corresponding control commands according to preset control strategies, such as increasing the curing environment temperature. These commands are then sent to the temperature control execution unit, which is connected to the curing environment temperature control equipment, to adjust the output parameters of the temperature control equipment, thereby changing the temperature of the mortar curing environment, improving the hydration reaction conditions of the mortar, and thus improving the curing quality of the mortar.

[0060] In some embodiments, a mortar curing strength prediction and control system under low-temperature curing conditions is proposed. The resistivity monitoring module is equipped with a low-temperature environment-adapted resistivity sensor embedded inside the mortar specimen to collect real-time resistivity signals of the mortar specimen under different curing times and temperature gradients. The data processing module, strength prediction module, and quality evaluation module are integrated into a data computing terminal, which has built-in temperature gradient calculation program, linear interpolation calculation program, and compressive strength prediction program. The curing control module is equipped with a temperature control execution unit, which is signal-connected to the temperature control equipment of the mortar curing environment and is used to adjust the output parameters of the temperature control equipment according to control commands.

[0061] To ensure accurate and stable acquisition of mortar resistivity data in low-temperature environments, the resistivity monitoring module is configured with a low-temperature-adapted resistivity sensor. This sensor, specially designed and using carefully selected materials, maintains measurement accuracy and stability across temperature gradients of 0℃, -5℃, -10℃, and -15℃, effectively resisting the effects of low temperatures on sensor performance, such as preventing drift or damage caused by temperature changes. Furthermore, the resistivity sensor is directly embedded within the mortar specimen, rather than simply placed on the surface or in the external environment. This embedding method allows the sensor to directly contact the mortar interior, sensing changes in ion concentration during the mortar hydration process in real time, thereby acquiring the most accurate real-time resistivity signal reflecting the internal state of the mortar. This approach ensures that the acquired resistivity data is accurate and valid data from the mortar specimen under different curing times and temperature gradients, providing a reliable basis for subsequent strength prediction.

[0062] To improve system integration, computational efficiency, and stability, the data processing module, strength prediction module, and quality evaluation module are integrated into a single data computing terminal. This integration effectively reduces data transmission latency between modules, simplifies system architecture, and facilitates centralized management and maintenance. This data computing terminal can be an industrial-grade computer, embedded controller, or high-performance PLC, and it has pre-built software programs to implement the core algorithms. Specifically, the built-in temperature gradient calculation program handles the calculation of mortar logarithmic resistivity under different temperature gradients; the linear interpolation calculation program performs linear interpolation between curing temperatures of adjacent temperature gradients to determine the corresponding mortar logarithmic resistivity; and the compressive strength prediction program establishes a quantitative prediction model of mortar compressive strength based on logarithmic resistivity. The built-in functionality of these programs ensures that complex calculations can be completed efficiently and accurately locally, providing robust software support for obtaining real-time curing strength and 28-day curing strength.

[0063] To achieve intelligent control of mortar curing environment parameters, the curing control module is equipped with a temperature control execution unit. This unit is a crucial bridge connecting the control logic and the physical actuators. It receives control commands from the quality evaluation module and converts them into signals that can be recognized and executed by the temperature control equipment. The temperature control execution unit connects to the temperature control equipment (e.g., heaters, chillers, constant temperature and humidity chambers) in the mortar curing environment via standard communication interfaces (such as RS485, Ethernet, etc.). When the curing quality evaluation results show that the mortar curing quality is substandard, the temperature control execution unit will precisely adjust the output parameters of the temperature control equipment according to a preset control strategy, such as increasing heating power or decreasing cooling capacity, thereby increasing the curing environment temperature and improving the mortar hydration reaction conditions. This configuration ensures that control commands are executed in a timely and accurate manner, achieving closed-loop control of the curing environment temperature, thus effectively improving the curing quality of the mortar.

[0064] The above description is merely an embodiment of the present invention and is not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for predicting and controlling the curing strength of mortar under low-temperature curing conditions, characterized in that, Includes the following steps: By real-time monitoring of the resistivity of mortar test blocks in different low-temperature environments, a system for calculating the logarithmic resistivity of mortar under multi-level temperature gradients was established. The logarithmic resistivity of the corresponding mortar is determined based on the curing temperature between adjacent temperature gradients. A quantitative prediction model for the compressive strength of mortar is established based on the logarithmic resistivity to obtain the real-time curing strength of mortar at curing time t and the curing strength after a preset number of days. The curing quality is evaluated by setting the curing intensity for a preset number of days for several groups of mortar test blocks, and the curing environment parameters of the mortar are adjusted according to the curing quality evaluation results.

2. The method for predicting and controlling the curing strength of mortar under low-temperature curing conditions according to claim 1, characterized in that, The establishment of a multi-level temperature gradient system for calculating the logarithmic resistivity of mortar includes: For each temperature gradient of 0℃, -5℃, -10℃, and -15℃, the logarithmic resistivity of the mortar at different curing times is calculated according to the following formula; At 0℃: （1） At -5℃: （2） At -10℃: （3） At -15℃: （4） in, t represents the resistivity of the mortar under different curing times, in Ω∙m; t represents the mortar curing time, in hours / h.

3. The method for predicting and controlling the curing strength of mortar under low-temperature curing conditions according to claim 2, characterized in that, The determination of the logarithmic resistivity of the mortar using linear interpolation for the curing temperature between adjacent temperature gradients includes: For curing temperatures in the range of 0℃-5℃, 5℃-10℃, and 10℃-15℃, the resistivity of the corresponding mortar is calculated using a linear interpolation formula. （5） in, For mortar at curing temperature The resistivity of the sample, expressed in Ω∙m; , Given the ambient temperature; , Given the known resistivity of the mortar at the ambient temperature.

4. The method for predicting and controlling the curing strength of mortar under low-temperature curing conditions according to claim 1, characterized in that, The quantitative prediction model for mortar compressive strength based on the logarithmic resistivity, used to obtain the real-time curing strength of the mortar at curing time t, includes: Substituting the calculated logarithmic resistivity of the mortar into the compressive strength prediction formula, the predicted compressive strength of the mortar at curing time t is obtained: （6） in, The predicted compressive strength of the mortar at curing time t is expressed in MPa.

5. The method for predicting and controlling the curing strength of mortar under low-temperature curing conditions according to claim 4, characterized in that, The method for obtaining the preset curing strength of the mortar includes: By substituting the curing time into the compressive strength prediction formula, the preset curing strength of the mortar under a specific condition is calculated.

6. The method for predicting and controlling the curing strength of mortar under low-temperature curing conditions according to claim 5, characterized in that, The evaluation of curing quality through the curing intensity of several groups of mortar test blocks at preset curing days includes: Calculate the average predicted strength of the 28-day curing strength of the 3 groups of mortar test blocks: （7） （8） in, The average value of the predicted mortar strength of the three test blocks; This refers to the standard value of mortar strength. The maximum predicted strength of the mortar in the test block; This represents the minimum predicted strength of the mortar in the test block.

7. The method for predicting and controlling the curing strength of mortar under low-temperature curing conditions according to claim 6, characterized in that, The evaluation criteria for the maintenance quality include the matching between the average predicted strength of the mortar and the standard value of the mortar strength specification, and the range of the difference between the maximum and minimum predicted strength of the mortar in the test block. The criteria for evaluating the quality of mortar maintenance are as follows: when the average predicted strength of the mortar is not lower than the standard value of the mortar strength specification, and the difference between the maximum and minimum predicted strength of the mortar is within a preset reasonable range, the mortar maintenance quality is deemed to meet the standard; otherwise, the mortar maintenance quality is deemed to fail to meet the standard.

8. The method for predicting and controlling the curing strength of mortar under low-temperature curing conditions according to claim 7, characterized in that, The intelligent control of mortar curing environment parameters based on the curing quality evaluation results includes: When the mortar curing quality is determined to be substandard, control measures should be taken to increase the temperature of the curing environment, improve the mortar hydration reaction conditions, and improve the mortar curing quality.

9. The method for predicting and controlling the curing strength of mortar under low-temperature curing conditions according to claim 1, characterized in that, The resistivity monitoring of the mortar test blocks is conducted continuously in real time. The calculation of the logarithmic resistivity of the mortar, the prediction of compressive strength, the evaluation of curing quality, and the control of curing environment parameters are all performed dynamically in real time.

10. A system for predicting and controlling the curing strength of mortar under low-temperature curing conditions, used to execute the method for predicting and controlling the curing strength of mortar under low-temperature curing conditions as described in any one of claims 1 to 9, characterized in that, The system includes: The resistivity monitoring module monitors the resistivity of mortar test blocks in different low-temperature environments in real time. The data processing module is used to establish a mortar log resistivity calculation system under multi-level temperature gradients and determine the corresponding mortar log resistivity based on the curing temperature between adjacent temperature gradients. The strength prediction module is used to establish a quantitative prediction model of mortar compressive strength based on the logarithmic resistivity, and to obtain the real-time curing strength of mortar at curing time t and the curing strength after a preset number of days. The quality evaluation module is used to evaluate the curing quality by using the curing intensity of several groups of mortar test blocks for a preset number of days. The maintenance control module is used to control the mortar curing environment parameters based on the maintenance quality evaluation results.

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