Adaptive control method of temperature and humidity parameters in the demoulding process of precast concrete parts

Abstract

The present invention relates to the field of intelligent control of concrete prefabricated parts production processes and discloses a method for adaptively controlling temperature and humidity parameters during the demoulding process of concrete prefabricated parts. The method comprises: obtaining an electrical fingerprint signal representing the internal hydration state of concrete and an external ambient temperature change rate signal through a pre-embedded sensing unit; dynamically determining the current temperature and humidity parameter tolerance domain boundaries through a preset two-dimensional lookup table based on the dual-signal coupling relationship; and controlling the operation of environmental conditioning equipment accordingly. The present invention realizes a transition from fixed threshold control to dynamic tolerance domain regulation through real-time coupling analysis of the electrical fingerprint and thermal disturbance, enabling the system to adaptively adjust the control boundary according to the actual state of the component, significantly improving control robustness and resource utilization efficiency while ensuring quality.

Description

Technical Field

[0001] The invention relates to a temperature and humidity parameter adaptive control method for a demoulding process of a prefabricated concrete part, and belongs to the technical field of intelligent control of a production process of a prefabricated concrete part. Background Art

[0002] In the production process of precast concrete parts, the current mainstream control methods are mainly divided into two categories: one is switch control based on fixed thresholds, which starts and stops environmental conditioning equipment through preset temperature and humidity thresholds; the other is to use fuzzy control or neural network algorithms to optimize set values ​​in an attempt to improve environmental stability. Although these methods can achieve basic regulation, their core logic is still limited to independent monitoring and lag compensation of environmental parameters, and they fail to fundamentally solve the core contradiction of the equivalent compensation relationship between temperature and humidity during the concrete hydration process.

[0003] In a typical large-scale prefabricated component stacking and maintenance scenario, the boundary layer microenvironment formed by uneven air circulation on the component surface varies significantly. If existing technologies pursue precise control, they need to deploy dense sensor networks and complex actuators, resulting in high system costs and frequent failures. If extensive strategies are adopted, it is difficult to avoid the components being in a sub-healthy state for a long time, inducing microcracks that are invisible to the naked eye and posing durability risks. The essential problem is that the control system lacks the ability to perceive the internal hydration state of the components in real time, and is forced to adopt a passive environment-response mode, unable to dynamically adjust the control strategy according to the actual needs of the components.

[0004] In recent years, the industry has attempted to introduce online monitoring technologies (such as embedded strain sensors) to optimize control, but two major bottlenecks remain: monitoring data is only used to correct fixed thresholds, without a dynamic mapping mechanism between state signals and environmental tolerances; and the reliance on a central processing unit to run complex algorithms leads to poor real-time performance and scalability in large-scale scenarios. Therefore, the technical challenge addressed by this invention is to develop an adaptive temperature and humidity tolerance range generation mechanism based on real-time feedback from the controlled object's internal state, significantly improving system economics and adaptability to operating conditions while ensuring quality. Summary of the Invention

[0005] The present invention provides a method for adaptively controlling temperature and humidity parameters during the demoulding process of precast concrete parts. The main purpose of the method is to solve the problems of existing control systems that lack coupling cognition between the concrete hydration state and environmental disturbances, resulting in regulation lag, resource waste and insufficient controllability of quality risks.

[0006] To achieve the above object, the present invention provides a method for adaptively controlling temperature and humidity parameters during a demoulding process of a precast concrete part, the method comprising the following steps:

[0007] Step a, acquiring a signal from a sensing unit formed by at least one bipolar resistor embedded in a precast concrete component; applying a pulse excitation voltage to the sensing unit; and analyzing the relaxation time of the current waveform of the sensing unit after the pulse excitation is released as an electrical fingerprint signal representing the hydration state of the precast concrete component.

[0008] Step b: collecting temperature data of the environment in which the precast concrete part is located in real time, and calculating the rate of change of the temperature data as a temperature change rate signal representing the degree of thermal disturbance of the environment to which the precast concrete part is subjected;

[0009] Step c: Based on the coupling relationship between the electrical fingerprint signal and the temperature change rate signal, a calibrated two-dimensional lookup table is used to dynamically determine the temperature and humidity parameter tolerance range allowed for the current precast concrete component. The temperature and humidity parameter tolerance range includes an upper limit of the temperature fluctuation range and a lower limit of the humidity fluctuation range. The input of the two-dimensional lookup table is the discretized electrical fingerprint signal level and the temperature change rate signal level, and the output of the two-dimensional lookup table is the value of the temperature and humidity parameter tolerance range.

[0010] Step d: monitor the actual temperature and humidity of the environment in which the precast concrete parts are located in real time through external environmental sensors; when the actual temperature and humidity reach the boundary of the temperature and humidity parameter tolerance range, start or stop the corresponding environmental conditioning equipment to cause the actual temperature and humidity to return to within the tolerance range.

[0011] Preferably, the relaxation time analysis step includes: after the pulse excitation is released, capturing, by the microcontroller, the time required for the response current to decay from a peak value to a stable value.

[0012] Preferably, the two-dimensional lookup table divides the control process into at least one high-tolerance stage and one low-tolerance stage according to the concrete hydration stage represented by the electrical fingerprint signal; in the low-tolerance stage, the upper limit of the temperature fluctuation range and the lower limit of the humidity fluctuation range output by the lookup table are stricter than those in the high-tolerance stage.

[0013] Preferably, the environmental conditioning equipment includes a humidifying device, a ventilation device, and a heating device, and the environmental conditioning equipment is started or stopped by a switch quantity control method.

[0014] Preferably, the bipolar resistor is a bipolar resistor having a resistance value in the range of one hundred ohms to one thousand ohms.

[0015] Preferably, the step of acquiring the electrical fingerprint signal also includes: between regular sampling periods, alternately applying a high-frequency AC excitation signal with a frequency of 8 kHz to 12 kHz and a low-frequency AC excitation signal with a frequency of 80 Hz to 120 Hz to the sensing unit; determining a compensation coefficient based on the ratio of the measured high-frequency electrical impedance value to the low-frequency electrical impedance value; and using the compensation coefficient to correct the electrical fingerprint signal, and then using it to determine the temperature and humidity parameter tolerance domain in a two-dimensional lookup table.

[0016] Preferably, the step of calculating the time second derivative of the temperature change rate signal includes: calculating the time second derivative of the temperature change rate signal in real time to obtain the temperature change acceleration signal When it is determined that the precast concrete part is in the stress accumulation risk stage and the absolute value of the temperature change acceleration signal is continuously lower than the threshold value of 0.05 degrees Celsius per square hour, the ventilation equipment in the environmental conditioning equipment is controlled to operate continuously at a low power level of 10% to 15% of the rated power.

[0017] Preferably, during the acquisition of the electrical fingerprint signal, the frequency characteristics of the relaxation oscillation signal contained in the response current waveform are synchronously analyzed; and when the frequency characteristics continue to decrease, the lower limit of the humidity fluctuation range determined by the two-dimensional lookup table is dynamically adjusted upward.

[0018] Preferably, the frequency of temperature data collection is once every five minutes to once every ten minutes.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. By coupling and analyzing the electrical fingerprint signal of the internal hydration state of concrete with the ambient temperature change rate signal, the system can dynamically generate and maintain a temperature and humidity parameter tolerance domain based on the real-time assessment of the controlled object's own state and the external disturbances it is experiencing. This abandons the rigid pursuit of fixed environmental target values ​​in traditional control and transforms it into a flexible adjustment of control boundaries based on the actual bearing capacity of the component. This gives the system an inherent adaptive adjustment capability in the face of environmental fluctuations, effectively avoiding control deviations and resource waste caused by hysteresis compensation.

[0021] 2. As the core representation of the hydration state, combined with real-time monitoring of the temperature change rate, coupled mapping is performed through a preset two-dimensional decision model. This dual-factor input mechanism enables the control strategy to automatically adapt to the electrical signal baseline offset caused by changes in aggregate characteristics or proportions in different batches, while accurately responding to varying degrees of environmental thermal shock, ensuring the stability and universality of control decisions and reducing the risk of control failure due to material or environmental uncertainties.

[0022] 3. The two-dimensional decision-making model can distinguish between high-tolerance and low-tolerance phases, and output stricter temperature and humidity fluctuation range limits during low-tolerance phases, such as the initial setting period, during sensitive windows. This on-demand focused control method allows limited regulatory resources to be concentrated on the periods most critical to component quality, avoiding unnecessary energy consumption caused by full-process high-voltage control while ensuring the stability of environmental parameters during the highest-risk periods. Its input is a discrete signal level, and its output is a specific tolerance boundary value. This mechanism avoids the resource consumption of complex online calculations and the difficulty of model maintenance. Combined with the switch control method to operate the environmental conditioning equipment, the entire system has a simple structure, rapid response, and flexible deployment. Each prefabricated component unit can make independent decisions based on its own status, facilitating distributed large-scale applications, greatly improving the system's engineering feasibility and cost-effectiveness.

[0023] 4. The system can identify potential internal stress accumulation risks under the appearance of a stable environment at specific stages, such as the stress accumulation risk period. At this time, the system can trigger preset micro-disturbance strategies such as low-power continuous ventilation to gently promote uniform surface heat dissipation and water evaporation. Without significantly changing the macro temperature and humidity tolerance range, the system can homogenize the internal stress gradient in advance and suppress the formation of hidden quality risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 This is a timing diagram of the electrical fingerprint signal acquisition process inside the precast concrete part of the present invention;

[0025] Figure 2 This is a comparison chart of the cumulative energy consumption of the experimental group and the control group under different curing times;

[0026] Figure 3 Schematic diagram of the temperature and humidity tolerance range of concrete during the hydration stage of the present invention;

[0027] Figure 4 This is a comparison diagram of typical attenuation curves of the response current changing with time at different hydration stages of the present invention.

[0028] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0029] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0030] The present invention provides a method for adaptively controlling temperature and humidity parameters during the demolding process of precast concrete components. In a large-scale intelligent production base for prefabricated building components, hundreds of newly cast precast concrete components, such as bridge T-beams or building wall panels, are densely stacked within a constant temperature and humidity curing workshop. To ensure optimal mechanical properties and prevent premature cracking during the critical curing period before demolding, the temperature and humidity of the curing environment must be precisely and efficiently regulated. The provided method for adaptively controlling temperature and humidity parameters operates in this scenario through a distributed control system with autonomous decision-making capabilities. The specific implementation process is as follows. The core of this method is to abandon the traditional approach of setting fixed target values ​​for ambient temperature and humidity. Instead, a temperature and humidity tolerance range that each individual precast concrete component can safely withstand is dynamically established. Intervention is initiated only when environmental conditions reach the boundaries of this tolerance range. This process relies on real-time perception of both the component's internal hydration state and external environmental disturbances.

[0031] First, the hydration state fingerprint acquisition step of the controlled object is performed. Before pouring concrete, at least one sensor unit needs to be embedded at the key stress or geometric center position inside the prefabricated part. The sensor unit is composed of a bipolar resistor. This resistor itself is a mature and cost-controlled component. Its resistance value is preferably in the range of 100 ohms to 1,000 ohms. The selection of this range is an engineering trade-off based on a deep understanding of the electrical properties of concrete materials: if the resistance value is too low, in the early stage of hydration, when the resistivity of the concrete itself is low, the signal of the sensor unit is easily submerged by the matrix signal, resulting in a poor signal-to-noise ratio; conversely, if the resistance value is too high, in the later stage of hydration, as the concrete As the density increases and the resistivity rises sharply, the response current passing through the sensor unit will become extremely weak, making it difficult to measure accurately. After the sensor unit is embedded, its lead wires are connected to a microcontroller deployed near the prefabricated part or integrated into its mold. During the control cycle, the microcontroller applies a short pulse excitation voltage to the sensor unit through the drive circuit it controls, such as a 5-volt DC voltage for 100 milliseconds. The key measurement occurs at the moment the pulse excitation is released. After the pulse excitation is released, a gradually decaying response current will be generated at both ends of the sensor unit because the polarization state formed by the ions inside the concrete under the action of the electric field will not disappear immediately.The microcontroller captures this response current waveform through a high-precision current sampling circuit and an analog-to-digital converter. The so-called relaxation time, its physical meaning is to characterize the time required for internal ions to recover from an ordered polarized state to a disordered state. This is directly related to the existence form of water and ion mobility in the internal pore structure of concrete, and thus constitutes an ideal electrical fingerprint signal to characterize its internal hydration state. In the specific analysis step, the microcontroller starts the internal timer immediately after the pulse excitation is released, and continuously monitors the response current value. When the current value decays from the peak value at the moment of excitation release to a preset stable value, such as a percentage of the peak value When the temperature reaches 10 or an absolute threshold close to the system noise floor, the timing is stopped for this period of time, which is quantified as the relaxation time of this measurement. At the same time, the environmental thermal disturbance feature recognition step is performed. One or more temperature sensors, such as NTC thermistors, are placed in the external environment of the prefabricated component, but as close to its surface as possible to accurately reflect the temperature field actually experienced by the component. The microcontroller collects environmental temperature data at a fixed frequency, preferably once every five to ten minutes. The setting of this collection frequency is also an engineering trade-off: too frequent collection will introduce a large amount of meaningless data noise caused by small air convection. The noise is detected and the computational burden is increased; however, too sparse sampling may miss short-term and drastic temperature fluctuations that have a significant impact on component quality. The microcontroller compares the current and previous temperature readings based on continuous sampling time intervals, calculates the difference and divides it by the time interval to obtain an accurately quantified temperature change rate signal. Next, the core decision-making link of the entire control method is entered, that is, the determination of the dual-factor coupled dynamic tolerance domain. The implementation of this step relies on a calibrated and solidified two-dimensional lookup table in the non-volatile memory of the microcontroller. The data of this two-dimensional lookup table is not generated in real time during the control process, but is generated by the calculation of the temperature. It is established through a one-time typical experimental calibration or by domain experts based on material science principles. Once established, it does not need to be changed during the actual control process, which greatly reduces the computational complexity and maintenance requirements of the field controller. The two input dimensions of the two-dimensional lookup table are the discretized electrical fingerprint signal level and the temperature change rate signal level. For example, the relaxation time can be divided into several levels, such as less than 200 milliseconds, 200 milliseconds to 800 milliseconds, 800 milliseconds to 2000 milliseconds, and greater than 2000 milliseconds, corresponding to the key stages of concrete hydration, such as the plastic state, initial setting, final setting and hardening.Similarly, the absolute value of the temperature change rate signal can also be divided into multiple levels such as less than 0.1 degrees Celsius per hour, 0.1 to 0.5 degrees Celsius per hour, and greater than 0.5 degrees Celsius per hour. Each cell of the lookup table stores a specific output value, that is, the temperature and humidity parameter tolerance range allowed under the current working conditions. The tolerance range is specifically manifested as an upper limit of the temperature fluctuation range and a lower limit of the humidity fluctuation range. The design logic of the two-dimensional lookup table embodies the idea of ​​intelligent focusing. Based on the concrete hydration stage represented by the electrical fingerprint signal, the control process is clearly divided into at least one high-tolerance stage and a low tolerance stage. For example, when the electrical fingerprint signal indicates that the concrete is in the low tolerance stage of the initial setting period, its internal structure is rapidly forming and is extremely sensitive to temperature and humidity fluctuations. At this time, even if a smaller temperature change rate signal is input, the upper limit of the temperature fluctuation range and the lower limit of the humidity fluctuation range output by the lookup table will be stricter than in the high tolerance stage, such as the late hardening stage. In the high tolerance stage of the hardening stage in the late hydration stage, the component has a certain strength and is more resistant to environmental fluctuations. The lookup table will output a looser tolerance domain, thereby avoiding unnecessary energy consumption.

[0032] Finally, the system enters a continuous operation state of adaptive maintenance of the tolerance domain boundary. The microcontroller monitors the actual temperature and humidity of the environment in which the prefabricated parts are located in real time through external environmental sensors, such as digital temperature and humidity sensors. It continuously compares these actual readings with the tolerance domain boundary dynamically determined from the two-dimensional lookup table. When the actual temperature reaches or is about to exceed the upper limit of the temperature fluctuation range of the tolerance domain, the microcontroller outputs a switch signal through its input and output ports to turn off the heating equipment or turn on the ventilation equipment in a switch control manner; when the actual humidity reaches or is about to fall below the lower limit of the humidity fluctuation range of the tolerance domain, the humidification equipment is started. Once the environmental parameters return to the tolerance domain, the corresponding environmental conditioning equipment is stopped. This tolerance domain-based boundary control replaces the tracking control based on fixed set points; the method also includes several preferred in-depth technical paths, one of which is a compensation correction mechanism for electrical fingerprint signals, taking into account the possibility that different batches of aggregates, cement or admixtures may cause mixing. Due to the difference in the electrical benchmark of concrete, the system will alternately apply a high-frequency AC excitation signal with a frequency of 8 kHz to 12 kHz and a low-frequency AC excitation signal with a frequency of 80 Hz to 120 Hz to the sensor unit between the conventional pulse excitation sampling cycles. The high-frequency AC impedance mainly reflects the resistance of the pore solution, while the low-frequency AC impedance is more affected by the solid-liquid interface polarization effect. The ratio of the two can more deeply reflect the microstructural characteristics of concrete. The system determines a compensation coefficient based on the ratio of the measured high-frequency electrical impedance value to the low-frequency electrical impedance value, and uses this compensation coefficient to correct the original electrical fingerprint signal measured by the relaxation time method. The corrected signal is then used to query the two-dimensional lookup table, thereby effectively avoiding the interference of raw material variation on the hydration state judgment. Secondly, it is based on the predictive intervention of temperature change acceleration. The microcontroller not only calculates the temperature change rate signal, but also calculates its second-order time derivative to obtain the temperature change acceleration signal. At certain critical stages, for example, when the system determines based on electrical fingerprints that a precast concrete component is at a risk stage where the internal and external temperature difference may cause stress accumulation after the hydration heat peak, even if the current temperature change rate is still within the tolerance range, if the system determines that the absolute value of the temperature change acceleration signal continues to be lower than a small threshold, such as 0.05 degrees Celsius per square hour, this often indicates a dangerous trend of seemingly stable but actually accumulating internal stress. At this time, the system will actively intervene and control the ventilation equipment in the environmental conditioning equipment to continuously operate at a low power level of 10% to 15% of its rated power. This mild micro-disturbance is intended to break the static air boundary layer on the surface of the component and promote uniform heat dissipation, thereby homogenizing the internal stress in advance without drastically changing the macro-environmental parameters. Gradient, thirdly, is the dynamic compensation of humidity based on the frequency domain analysis of the response current waveform; in the process of obtaining the electrical fingerprint signal, the microcontroller not only pays attention to the time domain feature of the relaxation time, but also performs fast Fourier transform on the collected complete response current waveform, and simultaneously analyzes the frequency characteristics of the relaxation oscillation signal contained therein. According to material research, these oscillation frequencies are related to the generation of early hydration products and the initiation of microcracks. When the system observes a continuous downward trend in these frequency characteristics, this is often a precursor to internal microdamage, which is usually related to rapid surface water loss. Once this feature is identified, the system will immediately execute a compensation logic to dynamically increase the lower limit of the humidity fluctuation range currently determined by the two-dimensional lookup table to enhance moisturizing and inhibit further development of damage.

[0033] Example 1: In a typical large-scale production scenario of prefabricated building components, hundreds of prefabricated concrete components coexist in the same large-scale curing workshop. Due to the differences in the components' own hydration heat release and the boundary layer effect caused by the uneven air circulation inside the workshop, the temperature and humidity of the local microenvironment of each component are significantly and dynamically different. The traditional centralized control system copes with this difference by maintaining the environmental parameters of the entire workshop at a constant value, which physically leads to a fundamental mismatch between the control instructions and the actual needs of the components. The operation of this method in this scenario first uses a bipolar resistor embedded in each prefabricated component and a temperature sensor arranged on its outside to synchronously obtain an electrical fingerprint signal representing the internal hydration process and a temperature change rate signal representing the external thermal environment disturbance. These two independent signal streams are logically realized in the system through a solidified two-dimensional lookup table. Specifically, when a sharp temperature change rate signal appears, the system does not respond directly. Instead, it uses the current hydration stage of the component determined by the electrical fingerprint signal as a key premise to determine its response mode. If the component is in the low-tolerance stage at the beginning of hydration, this temperature change rate signal will be judged as a high-risk thermal shock, and the lookup table will then output an extremely narrow tolerance range for temperature and humidity parameters, forcing the environmental conditioning equipment to make immediate adjustments. On the contrary, if the component has entered the hardening stage at the end of hydration, that is, the high-tolerance stage, the temperature change rate signal of the same intensity may be judged by the system as a tolerable fluctuation, and the tolerance range boundary will be relaxed accordingly, thereby avoiding equipment startup. The system's response mode to external disturbances is fundamentally determined by the prerequisite of its internal hydration state, thereby deterministically directing limited control resources to components in the critical maintenance stage.

[0034] This dynamic decision-making mechanism based on dual-signal coupling resolves the inherent contradiction between quality assurance and energy efficiency that has long existed in this field. To ensure quality, traditional methods require maintaining high standards of constant temperature and humidity throughout the entire maintenance cycle, resulting in significant energy consumption. If the standards are relaxed to save costs, it is impossible to avoid quality risks caused by environmental instability during the critical hydration stage. This method uses the electrical fingerprint signal as the fundamental basis for determining the system operation mode, and realizes autonomous switching between the two modes within a single architecture. When the electrical fingerprint signal indicates that the component has entered a sensitive low-tolerance stage, the system's operating logic automatically focuses on quality assurance, and its behavior is manifested as active maintenance of a strict tolerance domain; when the signal indicates that the component has entered a robust high-tolerance stage, its operating logic automatically switches to focusing on energy efficiency, and its behavior is transformed into passive monitoring of a loose tolerance domain. This deterministic, physical-state-based priority switching makes quality and efficiency no longer two opposing ends of mutual compromise, but is dynamically and holistically maintained throughout the component's life cycle. Furthermore, this method redefines the traditional control problem by introducing the core concept of the tolerance domain of temperature and humidity parameters. The core challenge faced by traditional control technologies is how to track a preset environmental target value with high precision and frequency. This method restructures the control task from tracking a set point to managing an allowable boundary. Most of the time, as long as the actual environmental parameters fluctuate naturally within the wide tolerance domain dynamically generated by the system, the control system does not need to take any action, thus avoiding the energy consumption and computational load incurred by suppressing harmless fluctuations. Control actions are triggered only when the environmental parameters reach the tolerance domain boundary, a low-probability event. This architectural shift reduces the original complex, continuous tracking problem to a simple, intermittent boundary monitoring problem. The system can thus use the saved monitoring and computing resources for deeper risk prediction. For example, by analyzing the acceleration signal of temperature changes, potential stress accumulation risks can be identified and intervened, realizing the possibility of transitioning from passive response to proactive prevention.

[0035] Example 2: In order to verify the actual effectiveness of the temperature and humidity parameter adaptive control method disclosed in the present invention in ensuring component quality and improving resource utilization efficiency, the following comparative test was designed and performed. The purpose of the test is to simulate a real industrial maintenance environment and quantitatively compare the differences in key performance indicators and system energy consumption of the controlled object when the method of the present invention is used and the fixed high-standard temperature and humidity setting value control method commonly used in the industry is used. The test platform is constructed in a high-precision environmental simulation cabin. The cabin is accurately divided into two independent spaces with temperature, humidity and airflow isolated from each other, corresponding to the test group A and the control group B respectively. In each space, a 400m2 C30 concrete cast from the same batch and the same mix ratio is placed. mx400mmx100mm prefabricated test blocks, both of which have identical bipolar resistors with a resistance of 500 ohms embedded in their geometric center positions as sensing units, the environmental conditioning equipment consists of an industrial-grade electric heating system and an ultrasonic humidification system independently connected to the two spaces, and energy consumption is recorded by separate electricity meters. The entire test process is set to 72 hours to fully cover the critical hydration cycle of concrete from initial setting to stable hardening after final setting. A core parameter in the test is the sampling period of pulse excitation, which is set according to the decision logic of balancing data real-time performance with system processing load. The setting of this period mainly depends on the monitored electrical fingerprint signal, namely the relaxation time, which changes during the hydration process. In the early stage of hydration, the relaxation time changes dramatically. In order to ensure that the key turning point can be captured, a shorter sampling period is required; in the later stage of hydration, the signal tends to be stable, and the period can be appropriately extended to reduce the system load. Based on this rule and targeting the typical hydration characteristics of C30 concrete, this experiment adopted a variable sampling strategy: within the first 12 hours, the sampling period was set to 5 minutes, and then adjusted to 10 minutes. After the experiment was started, the control system of the control group B was strictly operated according to the fixed high-standard curing procedures, with the goal of maintaining the ambient temperature at 20±0.5℃ and the relative humidity at 95±2%RH. The test group A started the adaptive control method of the present invention. Within the first 8 hours of the experiment, it was observed that the environmental conditioning equipment of the two groups The start-stop frequencies are very close, indicating that the early hydration stage identified by the electrical fingerprint signal of test group A makes the tolerance range of its dynamically generated temperature and humidity parameters quite strict, and its control behavior converges with the high-standard fixed control mode. However, after about 12 hours of test operation, the control behavior of test group A shows a clear change. The operating frequency of its environmental conditioning equipment begins to drop significantly, and the temperature and humidity in the cabin show a gentle fluctuation over a larger range, while the equipment of control group B still maintains a high frequency of start and stop. This phenomenon shows that the system of test group A has determined that the test block has entered the high tolerance stage based on the change in the relaxation time signal and has relaxed the control boundary accordingly. See Table 1: Comparison of the average start-stop frequency of environmental conditioning equipment in the test group and control group in different time periods.

[0036] Table 1:

[0037]

[0038] The underlying mechanism behind these data trends lies in the fact that the present method does not pursue absolute environmental stability, but rather ensures that environmental fluctuations never exceed the physical limits of the component's current safety. In the late hydration stage, the component's internal structure is relatively stable, and its tolerance to temperature and humidity fluctuations is enhanced. At this point, continued high-precision, constant environmental control is of no practical value in improving quality and instead results in continuous energy consumption. It is precisely through precise perception of this internal state that the present invention achieves the targeted allocation of control effort.

[0039] After the 72-hour test period, the final results of the two groups were statistically analyzed and tested. Energy consumption data showed that the total energy consumption of test group A was 38.7% of that of control group B. To assess the quality of the components, an ultrasonic detector was used to measure the sound velocity of the two test blocks to characterize the uniformity and density of their internal structure, and dye penetrant testing was performed on their surfaces to observe the distribution of microcracks. The test results showed no significant difference in the ultrasonic sound velocity of the two test blocks, and the surface microcrack density was at the same extremely low level. This shows that test group A significantly reduced energy consumption without affecting the final molding quality of component C. See Table 2: Comparison of energy consumption and quality indicators of concrete precast components in the test and control groups.

[0040] Table 2:

[0041]

[0042] The results of this experiment objectively confirm that the adaptive temperature and humidity parameter control method proposed in the present invention can construct and maintain a dynamic parameter tolerance domain that matches the actual needs of the component through real-time coupling analysis of the internal hydration state of concrete and external environmental disturbances. The present invention can significantly reduce energy consumption and improve resource utilization efficiency, thereby providing a technically feasible and economically superior implementation path for resolving the long-standing quality and cost contradictions in large-scale prefabricated component production.

[0043] Example 3: This example combines Figures 1 to 4 , the realization of the adaptive control method of temperature and humidity parameters in the demoulding process of precast concrete parts is explained. Figure 1As shown in the figure, the timer module first sends a sampling cycle arrival instruction, triggering the microcontroller to execute the preparation pulse excitation operation. Subsequently, the driver circuit applies a 5V pulse (100ms) to the bipolar resistor. After the pulse ends, the pulse excitation is immediately released, causing the bipolar resistor to respond to the current and produce a pulse response. The microcontroller then synchronously starts the internal timer and starts continuous ADC sampling. The ADC sampler continuously collects the current waveform to record the complete relaxation process. During this period, the sampling requirements must be met: high-precision current waveform sampling to capture the relaxation process. When the current decays to 10% of the peak value, the microcontroller stops the timer and transmits the current waveform data to the processing module through the ADC sampler. The signal processor then calculates the relaxation time and can further perform FFT frequency domain analysis to extract the frequency domain characteristics and determine the concrete hydration state stage. The system supports the following relaxation time ranges: less than 200ms for plastic state, 200-800ms for initial setting period, 800-2000ms for final setting period, and greater than 2000ms for hardening period. Finally, the electrical fingerprint level signal is returned to determine the current concrete state level.

[0044] like Figure 2 As shown in the figure, the curves are represented by dashed circles for test group A (adaptive control) and solid squares for control group B (fixed control). As curing time increases from 0 to 60 hours, the figure shows that the energy consumption of control group B (fixed control) at 60 hours is 55.8 kWh, while the corresponding value for test group A (adaptive control) is 21.6 kWh, forming a significant energy-saving region between the two groups. The figure also specifically marks the 61.3% energy consumption reduction in the energy-saving region, clearly indicating that the proposed adaptive temperature and humidity parameter control method based on the coupling mechanism of concrete hydration state and temperature perturbations significantly reduces the start-stop frequency and operating energy consumption of environmental conditioning equipment compared to traditional fixed setpoint control strategies, while ensuring component molding quality.

[0045] like Figure 3 As shown, the curve in the upper half of the figure shows the temperature fluctuation range within the temperature tolerance range ( ) changes, where the tolerance region boundary is represented by a thick solid line and the actual parameter fluctuation is represented by a dotted line. In the critical stage of initial setting, the system sets ±1 The safety tolerance boundary is extended to ±5 The safety tolerance region is highlighted with gray filling, and the lower half shows the change in the lower limit of the humidity tolerance region. The diagram shows that during the initial setting period, the system sets the lower limit of humidity to >92%. As hydration progresses to the final setting period and hardening period, the lower limit of humidity tolerance gradually decreases, eventually reaching >70%.

[0046] like Figure 4As shown in the figure, three typical curves are drawn, corresponding to the initial setting period ( <200ms), final setting period (200ms< <800ms) and hardening period ( >800ms) three key hydration stages, among which the initial setting period ( <200ms) is marked with a dotted line, with the fastest decay rate. The current drops rapidly to near 0 in a short time, indicating that the ion mobility is high and the hydration structure has not yet formed. The final setting period (200ms< <800ms) is represented by the middle dashed line, and the response current decay trend is moderate, reflecting that the condensation structure is forming; while the hardening period ( >800ms) is represented by a solid line, and the current decay is the most gentle, indicating that the internal structure is dense and the ion migration is restricted.

[0047] Example 4: This example uses C50 high-strength concrete for prefabricated components as the object to establish a standardized laboratory reference system. For example, in an intelligent production base for prefabricated building components, when a new C50 high-strength concrete mix is ​​introduced, its hydration characteristics are significantly different from those of conventional concrete. Directly applying the existing control model will face the dual risks of quality instability and uncontrolled energy consumption. To meet this challenge, it is necessary to accurately construct a dedicated control logic core for this specific material before large-scale production starts.

[0048] This process begins with the preparation of a set of standard test blocks. The geometric centers of the test blocks are pre-embedded with bipolar resistor sensor units with resistance values ​​ranging from 100 ohms to 1,000 ohms, which are exactly the same as those used in future practical applications. The test blocks are placed in a high-precision programmable environmental simulation chamber to ensure that the temperature and humidity environment is controllable and reproducible. During the standard maintenance period of 72 hours, the system performs measurement cycles at a dynamic frequency, that is, sampling every five minutes in the first 12 hours, and then extending the sampling interval to 10 minutes. In each measurement cycle, the microcontroller not only measures the original relaxation time by the pulse excitation method, but also obtains the original relaxation time. , and alternately apply a high-frequency AC excitation signal with a frequency of 10,000 Hz and a low-frequency AC excitation signal with a frequency of 100 Hz, and measure the high-frequency electrical impedance values ​​respectively. and low frequency electrical impedance At the same time, through non-invasive detection methods such as Vicat instrument, the actual initial and final setting times of the test blocks were synchronously measured and recorded, and their compressive strength growth curves were measured at regular intervals, thereby obtaining a benchmark data set characterizing the evolution of the macroscopic physical state of the C50 concrete.

[0049] After data collection is completed, the offline data analysis and model building phase begins. The first step is to establish an electrical fingerprint signal correction mechanism that can eliminate the impact of raw material batch differences. This correction mechanism relies on a compensation coefficient. The calculation procedure is as follows: First, based on the physical test benchmark data, the high-frequency and low-frequency impedance ratio of the concrete in the final setting state measured by the Vicat instrument is determined as the benchmark impedance ratio. Secondly, to determine the formula The dimensionless sensitivity factor in , a calibration procedure is required. The procedure iteratively adjusts a value between 0.1 and 0.3. value, and use it to calculate a series of corrected electrical fingerprint signals The signal value sequence is then correlated with the normalized compressive strength growth curve extracted from the physical test benchmark data, and the one that maximizes the correlation coefficient between the two sequences is finally selected. In other words, this procedure transforms a parameter selection problem that relies on experience into a repeatable calculation process with a clear optimization goal.

[0050] Next, the core data of the two-dimensional lookup table is constructed. This process divides the state of the controlled object into different risk cells and assigns a certain temperature and humidity parameter tolerance range to each cell. The two dimensions of the lookup table are discretized based on the calibration results: the first dimension is the corrected electrical fingerprint signal The threshold of the grade is strictly anchored to the initial setting time and final setting time of the C50 concrete measured by the Vicat instrument. The second dimension is the temperature rate of change signal level, which is categorized based on risk assessment. For example, a rate of change of less than 0.1°C per hour is defined as a steady state, 0.1 to 0.5°C per hour as a mild disturbance, and greater than 0.5°C per hour as a severe thermal shock. The output value of each cell in the lookup table is determined through a rigorous iterative optimization process. For each cell in the lookup table, the corresponding hydration stage and environmental disturbance level are first replicated in an environmental simulation chamber, and an initial, stringent temperature and humidity tolerance range is set. Then, after curing, the test specimens under these conditions are tested to see if they meet the pre-set engineering targets of a strength of at least 98% of the design value and a surface microcrack density of less than 0.02 per square centimeter. If these conditions are met, the tolerance range boundaries are relaxed by a fixed step size in the next test, for example, by increasing the upper limit of the temperature fluctuation range by 0.1°C, and the test is repeated. This iterative process continues until the test result after relaxing the boundary just fails to meet the engineering goal. At this time, the tolerance domain boundary value that was more stringent than the previous one that met the goal is solidified into the cell as the final result. This procedure is systematically applied to each cell of the lookup table until the entire lookup table is fully calibrated.

[0051] Finally, the parameters in the predictive intervention logic are solidified in principle. When the system determines that the component is in the stress accumulation risk stage caused by the internal and external temperature difference, the temperature change acceleration signal is used to trigger low-power continuous ventilation. , and its absolute value threshold is set to 0.05 degrees Celsius per square hour. The principle of setting this value is that it is significantly higher than the measurement noise floor of the precision temperature sensor, and at the same time lower than the temperature change acceleration corresponding to the minimum stress accumulation rate that causes internal micro-damage in the hydration stage calculated based on the material fracture mechanics theory, thereby ensuring the early and safe intervention. For the humidity dynamic compensation mechanism based on the frequency domain analysis of the response current waveform, the continuous decline in the frequency characteristic is clearly defined as the main oscillation frequency extracted by the fast Fourier transform, which decreases monotonically in three consecutive measurement cycles and the cumulative decrease exceeds five percent. Once this condition is met, the system will perform a dynamic upward adjustment on the lower limit of the humidity fluctuation range currently determined by the two-dimensional lookup table, increasing the lower limit by three percent relative humidity to actively combat the risk of dehydration microcracks.

[0052] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for adaptively controlling temperature and humidity parameters during the demoulding process of precast concrete parts, characterized in that: The method comprises the following steps: Step a, acquiring a signal from a sensing unit formed by at least one bipolar resistor embedded in a precast concrete component; applying a pulse excitation voltage to the sensing unit; and analyzing the relaxation time of the current waveform of the sensing unit after the pulse excitation is released as an electrical fingerprint signal representing the hydration state of the precast concrete component. Step b: collecting temperature data of the environment in which the precast concrete part is located in real time, and calculating the rate of change of the temperature data as a temperature change rate signal representing the degree of thermal disturbance of the environment to which the precast concrete part is subjected; Step c: Based on the coupling relationship between the electrical fingerprint signal and the temperature change rate signal, a calibrated two-dimensional lookup table is used to dynamically determine the temperature and humidity parameter tolerance range allowed for the current precast concrete component. The temperature and humidity parameter tolerance range includes an upper limit of the temperature fluctuation range and a lower limit of the humidity fluctuation range. The input of the two-dimensional lookup table is the discretized electrical fingerprint signal level and the temperature change rate signal level, and the output of the two-dimensional lookup table is the value of the temperature and humidity parameter tolerance range. Step d: monitor the actual temperature and humidity of the environment in which the precast concrete parts are located in real time through external environmental sensors; when the actual temperature and humidity reach the boundary of the temperature and humidity parameter tolerance range, start or stop the corresponding environmental conditioning equipment to cause the actual temperature and humidity to return to within the tolerance range.

2. The method for adaptively controlling temperature and humidity parameters during the demoulding process of a precast concrete part according to claim 1, characterized in that: The relaxation time analysis step includes: after the pulse excitation is released, the microcontroller captures the time required for the response current to decay from the peak value to the stable value.

3. The method for adaptively controlling temperature and humidity parameters during the demoulding process of a precast concrete part according to claim 1, characterized in that: The two-dimensional lookup table divides the control process into at least one high-tolerance stage and one low-tolerance stage according to the concrete hydration stage represented by the electrical fingerprint signal. In the low-tolerance stage, the upper limit of the temperature fluctuation range and the lower limit of the humidity fluctuation range output by the lookup table are stricter than those in the high-tolerance stage.

4. The method for adaptively controlling temperature and humidity parameters during the demoulding process of a precast concrete part according to claim 1, characterized in that: Environmental conditioning equipment includes humidifying equipment, ventilation equipment and heating equipment. The starting or stopping of environmental conditioning equipment adopts switch quantity control method.

5. The method for adaptively controlling temperature and humidity parameters in a demoulding process of a precast concrete part according to claim 1, characterized in that: The bipolar resistor is a bipolar resistor having a resistance value ranging from one hundred ohms to one thousand ohms.

6. The method for adaptively controlling temperature and humidity parameters during the demoulding process of a precast concrete part according to claim 1, characterized in that: The step of acquiring the electrical fingerprint signal also includes: between regular sampling periods, alternately applying a high-frequency AC excitation signal with a frequency of 8 kHz to 12 kHz and a low-frequency AC excitation signal with a frequency of 80 Hz to 120 Hz to the sensing unit; determining a compensation coefficient based on the ratio of the measured high-frequency electrical impedance value to the low-frequency electrical impedance value; and using the compensation coefficient to correct the electrical fingerprint signal, which is then used in a two-dimensional lookup table to determine the temperature and humidity parameter tolerance domain.

7. The method for adaptively controlling temperature and humidity parameters during the demoulding process of a precast concrete part according to claim 1, characterized in that: The calculation step of the time second derivative of the temperature change rate signal includes: calculating the time second derivative of the temperature change rate signal in real time to obtain the temperature change acceleration signal When it is determined that the precast concrete part is in the stress accumulation risk stage and the absolute value of the temperature change acceleration signal is continuously lower than the threshold value of 0.05 degrees Celsius per square hour, the ventilation equipment in the environmental conditioning equipment is controlled to operate continuously at a low power level of 10% to 15% of the rated power.

8. The method for adaptively controlling temperature and humidity parameters during the demoulding process of a precast concrete part according to claim 1, characterized in that: During the acquisition of the electrical fingerprint signal, the frequency characteristics of the relaxation oscillation signal contained in the response current waveform are synchronously analyzed; and when the frequency characteristics continue to decline, the lower limit of the humidity fluctuation range determined by the two-dimensional lookup table is dynamically adjusted upward.

9. The method for adaptively controlling temperature and humidity parameters in a demoulding process of a precast concrete part according to claim 1, characterized in that: The frequency of temperature data collection is every five to ten minutes.

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