Intelligent mass concrete temperature control system

Abstract

The invention discloses an intelligent mass concrete temperature control system, and relates to the technical field of concrete pouring temperature control. Comprising a temperature monitoring system, a central control system, a temperature regulation execution system, an intelligent water supplementing system, a fault diagnosis system and a remote control terminal, and the central control system comprises a shell located in the central control system. The internal temperature of concrete is collected in real time through temperature sensors which are distributed at multiple points and are high in precision in the temperature monitoring system, and the central control system accurately judges, regulates and controls the temperature by using a self-adaptive intelligent temperature control algorithm and integrating multiple factors such as concrete pouring time, environment temperature, internal temperature change rate and environment humidity; the temperature adjusting execution system achieves efficient cooling and heating operation through a refrigerator, a cold water pump and heating pipe equipment according to the instruction, it is ensured that concrete is hardened at the proper temperature, the concrete quality is greatly improved, and the risk of crack quality hidden danger caused by the temperature problem is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature control for concrete pouring, and in particular to an intelligent temperature control system for large-volume concrete. Background Art

[0002] In modern infrastructure construction, large-scale projects such as hydropower and highways widely utilize mass concrete pouring technology. Due to the enormous volume of concrete poured at once, the cement hydration reaction releases a significant amount of heat during the pouring process, causing the concrete's internal temperature to rise sharply. If temperature control is not effective, a large temperature difference will occur between the concrete's interior and surface, leading to thermal stress. When thermal stress exceeds the concrete's tensile strength, cracks will form, seriously affecting the strength, durability, and waterproofing of the concrete structure, increasing safety risks and subsequent maintenance costs.

[0003] Traditional concrete temperature control methods have numerous limitations. Different cements have distinct hydration heat release curves. Low-heat cement releases heat more slowly and in a lower amount, while ordinary Portland cement releases heat more quickly and in a higher amount. Construction environments are also extremely complex and variable, with ambient temperature, humidity, and wind speed all significantly impacting concrete heat dissipation. Existing temperature control systems often focus on adding various types of automatic control and detection equipment. However, in actual production practice, especially in hydropower or highway construction, improving the efficiency, reliability, and maintainability of construction methods and equipment is more critical. Some current temperature control equipment suffers from low device integration and weak data processing capabilities. This lack of effective coordination between various monitoring and control devices prevents comprehensive, real-time, and precise control of concrete temperature. Furthermore, traditional systems lack fault diagnosis and resolution capabilities. When equipment fails, it is difficult to promptly detect and accurately locate the fault point, resulting in extended equipment downtime, impacting the continuity and stability of temperature control, and negatively affecting concrete quality. Furthermore, construction management lacks convenient remote monitoring and management methods. Construction workers and managers have difficulty obtaining real-time key data such as the temperature and humidity inside the concrete, and are unable to adjust temperature control strategies according to on-site conditions. This makes project quality control very difficult and makes it difficult to meet the requirements of modern engineering construction for efficient, precise, and intelligent construction. Therefore, it is urgent to develop an intelligent large-volume concrete temperature control system to solve the problems of traditional temperature control methods and improve the construction quality and engineering safety of large-volume concrete. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent mass concrete temperature control system, which solves the technical problems raised in the background technology.

[0005] To achieve the above objectives, the present invention provides the following technical solutions: an intelligent mass concrete temperature control system, comprising a temperature monitoring system, a central control system, a temperature adjustment execution system, an intelligent water replenishment system, a fault diagnosis system, and a remote control terminal, wherein the central control system comprises a housing located within the central control system, a cover plate being mounted on the surface of the housing by screws, a microprocessor, a data storage module, and a built-in algorithm program being fixedly mounted inside the housing, and a display screen being fixedly mounted on the surface of the cover plate; The temperature adjustment execution system includes a movable plate located within the temperature adjustment execution system, a water tank is fixedly installed on the top of the movable plate, a refrigerator is fixedly installed inside the water tank, a cold water pump is fixedly installed on the top of the movable plate, a cooling pipe is fixedly installed at the water outlet of the cold water pump through a flange, a heat sink is fixedly installed on the surface of the water tank, a return pipe is plugged into the interior of the heat sink, and three heating pipes are fixedly installed on the inner wall of the water tank; The intelligent water replenishment system includes a humidity sensor and a water replenishment device.

[0006] Preferably, the water replenishment device includes a support plate fixedly installed on the top of the water tank, a rotating rod is rotatably installed inside the support plate, a turntable is fixedly installed on the surface of the rotating rod, a connecting rod is connected to the surface of the turntable, a tooth plate is slidably installed on the top of the support plate, a rotating rod is rotatably installed on the top of the support plate, a gear is fixedly installed on the surface of the rotating rod, a frame is fixedly installed on the surface of the rotating rod, six water spray heads are provided on the surface of the frame, and a water pump is fixedly installed on the top of the water tank.

[0007] Preferably, a water pipe is fixedly installed inside the frame, the water pipe is connected to several sprinkler heads, and a water inlet pipe extending to the inside of the water tank is fixedly installed at the water inlet of the water pump, and a delivery pipe fixedly connected to the water pipe is fixedly installed at the water outlet of the water pump.

[0008] Preferably, one end of the connecting rod away from the turntable is movably connected to one end surface of the tooth plate, and the surface of the tooth plate is meshed with the surface of the gear.

[0009] Preferably, the cooling pipe is designed as a serpentine pipe, one end of the cooling pipe away from the cold water pump is threadedly connected to one end of the return pipe, and the end of the return pipe away from the cooling pipe extends to the interior of the water tank.

[0010] Preferably, the fault diagnosis system includes a data acquisition module, a data fusion processor, a machine learning algorithm operation module and an alarm; The data acquisition module includes a flow sensor, a current sensor, and a voltage sensor; A flow sensor is fixedly installed on the surface of the cooling tube, and a current sensor and a voltage sensor are fixedly installed on the surfaces of the three heating tubes respectively.

[0011] Preferably, the built-in algorithm program adopts an adaptive intelligent temperature control algorithm based on multivariate regression analysis and fuzzy control theory; specifically: The algorithm uses the time after concrete pouring, ambient temperature, the rate of change of temperature inside the concrete, and ambient humidity as input variables. It establishes an initial temperature control strategy model through multivariate regression analysis. The formula is as follows: in, is the initial temperature control strategy parameter, is the regression coefficient, which is obtained through training with historical data.

[0012] Preferably, the temperature monitoring system includes a temperature sensor and a wireless transmission module, and the machine learning algorithm operation module uses a support vector machine (SVM) algorithm to perform fault diagnosis. The algorithm uses the flow sensor data collected by the data acquisition module to , current sensor data , voltage sensor data And temperature sensor data , humidity sensor data As input feature vector In the training phase, a large amount of feature vector data under normal operating conditions and various fault conditions is collected and divided into training sets and test sets. The training set data is used to train the SVM model. By optimizing the kernel function (such as the radial basis kernel function) and parameters (such as the penalty factor and the kernel coefficient ), so that the model achieves the best classification performance; During the actual operation, the feature vector collected in real time is input into the trained SVM model, and the model outputs the fault type label. The fault types include but are not limited to sensor failure, cooling pipe blockage, and heating pipe failure. At the same time, combined with the multi-source data processed by the data fusion processor, by calculating the distance between the characteristic vector and the center of each type of fault mode, the location of the fault point can be further determined to achieve fast and accurate fault diagnosis.

[0013] Preferably, the remote control terminal and the central control system use a communication method based on the MQTT protocol; this protocol has the characteristics of being lightweight, low power consumption, and highly reliable, and is suitable for data transmission in an Internet of Things environment; The central control system acts as an MQTT client, encapsulating the temperature data collected by the temperature monitoring system, the humidity data collected by the humidity sensor, and the fault information data of the fault diagnosis system into messages according to the MQTT protocol format, and publishing them to the designated MQTT topic; the remote control terminal acts as another MQTT client, subscribes to the corresponding topic, receives the data, and displays it in real time on the interface; The remote control terminal can send control instructions to the central control system, such as adjusting the operating parameters of the temperature regulation execution system and setting the water replenishment threshold of the intelligent water replenishment system; these instructions are also sent to the designated topic in the form of MQTT messages. The central control system subscribes to the topic, receives and parses the instructions, and executes the corresponding operations to realize remote monitoring and control of the temperature control system.

[0014] Compared with related technologies, the intelligent mass concrete temperature control system provided by the present invention has the following beneficial effects: 1. The present invention provides an intelligent large-volume concrete temperature control system. The internal temperature of the concrete is collected in real time by multi-point distributed and high-precision temperature sensors in the temperature monitoring system. The central control system uses an adaptive intelligent temperature control algorithm to comprehensively consider multiple factors such as concrete pouring time, ambient temperature, internal temperature change rate, and ambient humidity to accurately determine and regulate the temperature. The temperature regulation execution system uses refrigerators, cold water pumps, and heating pipe equipment according to instructions to achieve efficient cooling and heating operations, ensuring that the concrete hardens at an appropriate temperature, greatly improving the quality of the concrete and effectively reducing the risk of cracks and quality hazards caused by temperature problems.

[0015] 2. The present invention provides an intelligent large-volume concrete temperature control system. The fault diagnosis system uses a data acquisition module to collect multi-source data such as flow, current, voltage, temperature and humidity. After integration by a data fusion processor, the fault point and type are quickly and accurately located with the help of a machine learning algorithm operation module, and an alarm is issued in a timely manner. At the same time, the remote control terminal communicates with the central control system based on the MQTT protocol. Users can remotely view data and adjust system parameters anytime and anywhere, realizing intelligent operation and maintenance and convenient management of the temperature control system, greatly improving work efficiency, reducing equipment downtime, and ensuring the continuity and stability of temperature control work. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a three-dimensional diagram of the structure of the intelligent mass concrete temperature control system of the present invention; Figure 2 This is an exploded diagram of the central control system structure of the present invention; Figure 3 This is a three-dimensional diagram of the cooling pipe structure of the present invention; Figure 4 This is a structural perspective diagram of the water replenishment device of the present invention; Figure 5 This is a schematic diagram of the temperature sensor and humidity sensor structure installation of the present invention; Figure 6 This is a cross-sectional view of the interior of the water tank structure of the present invention; Figure 7 This is the structural circuit diagram of the intelligent large-volume concrete temperature control system of the present invention.

[0017] In the figure: 1. Temperature monitoring system; 101. Temperature sensor; 102. Wireless transmission module; 2. Central control system; 201. Shell; 202. Cover; 203. Microprocessor; 204. Data storage module; 205. Built-in algorithm program; 206. Display screen; 3. Temperature adjustment execution system; 301. Moving plate; 302. Water tank; 303. Refrigerator; 304. Cold water pump; 305. Cooling pipe; 306. Return pipe; 307. Heat sink; 308. Heating pipe; 4. Intelligent water replenishment system; 401. Humidity sensor; 402. Support plate; 403. Rotating rod; 404. Turntable; 405. Connecting rod; 406. Gear plate; 407. Rotating rod; 408. Gear; 409. Frame; 410. Sprinkler head; 411. Water pump; 5. Fault diagnosis system; 6. Remote control terminal. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0019] Example 1: See also Figure 1-Figure 7 , the present invention provides a technical solution: an intelligent mass concrete temperature control system, comprising a temperature monitoring system 1, a central control system 2, a temperature adjustment execution system 3, an intelligent water supply system 4, a fault diagnosis system 5 and a remote control terminal 6; It should be noted that the intelligent mass concrete temperature control system consists of a temperature monitoring system 1, a central control system 2, a temperature adjustment execution system 3, an intelligent water supply system 4, a fault diagnosis system 5 and a remote control terminal 6; The temperature monitoring system 1 includes a temperature sensor 101 and a wireless transmission module 102; In this embodiment, the temperature sensors 101 are distributed at different locations inside the concrete. Due to the complex temperature field distribution inside large-volume concrete, multi-point arrangement of sensors can comprehensively capture temperature changes in different areas. At the same time, the temperature sensor 101 adopts a high-precision temperature sensor 101 design. Its high-precision measurement capability, such as up to ±0.1°C, ensures the accuracy of the acquired temperature data; the wireless transmission module 102 is responsible for quickly and stably transmitting the collected temperature data to the central control system 2, providing the original basis for subsequent temperature analysis and control decisions, so that the entire temperature control system can respond to the dynamic changes in the temperature inside the concrete in a timely manner.

[0020] The central control system 2 includes a housing 201 located in the central control system 2. A cover plate 202 is mounted on the surface of the housing 201 by screws. A microprocessor 203, a data storage module 204, and a built-in algorithm program 205 are fixedly mounted inside the housing 201. A display screen 206 is fixedly mounted on the surface of the cover plate 202. In this embodiment, the microprocessor 203 has a powerful data processing capability. After receiving data from the temperature monitoring system 1 and other related systems, it uses the built-in algorithm program 205 to perform in-depth analysis. For example, through the adaptive intelligent temperature control algorithm, it determines whether the concrete temperature is in an appropriate range based on multiple factors such as the time after concrete pouring, ambient temperature, and the rate of change of the temperature inside the concrete; if the temperature is abnormal, it immediately sends a corresponding instruction to the temperature adjustment execution system 3 to adjust the concrete temperature; the data storage module 204 is used to store a large amount of historical temperature data information, which is convenient for later review and analysis of the concrete temperature control process, and provides data support for project quality tracing and optimization of temperature control strategies; the display screen 206 provides the operator with an intuitive data display interface, making it easy to understand the system operation status and key data at any time.

[0021] The temperature adjustment execution system 3 includes a movable plate 301 located within the temperature adjustment execution system 3, a water tank 302 is fixedly mounted on the top of the movable plate 301, a refrigerator 303 is fixedly mounted inside the water tank 302, a cold water pump 304 is fixedly mounted on the top of the movable plate 301, a cooling pipe 305 is fixedly mounted at the water outlet of the cold water pump 304 via a flange, a heat sink 307 is fixedly mounted on the surface of the water tank 302, a return pipe 306 is plugged into the interior of the heat sink 307, and three heating pipes 308 are fixedly mounted on the inner wall of the water tank 302; In this embodiment, when the central control system 2 determines that the temperature of the concrete is too high, the cold water pump 304 is started, and the refrigerator 303 works to cool the water in the water tank 302. The low-temperature cooling water circulates into the concrete through the cooling pipe 305, removing heat to achieve cooling. The cooling pipe 305 adopts a serpentine tube design, which can increase the contact area with the concrete and improve the heat dissipation efficiency. When the temperature is too low, the heating pipe 308 is energized and heated to heat the water in the water tank 302. The concrete is heated through water circulation, ensuring that the concrete hardens at an appropriate temperature and guaranteeing the quality and performance of the concrete.

[0022] The intelligent water replenishment system 4 includes a humidity sensor 401 and a water replenishment device; The water replenishment device includes a support plate 402 fixedly mounted on the top of the water tank 302, a rotating rod 403 is rotatably mounted inside the support plate 402, a rotating disk 404 is fixedly mounted on the surface of the rotating rod 403, a connecting rod 405 is connected to the surface of the rotating disk 404, a gear plate 406 is slidably mounted on the top of the support plate 402, a rotating rod 407 is rotatably mounted on the top of the support plate 402, a gear 408 is fixedly mounted on the surface of the rotating rod 407, a frame 409 is fixedly mounted on the surface of the rotating rod 407, and no less than six water spray heads 410 are provided on the surface of the frame 409. A water pump 411 is fixedly mounted on the top of the water tank 302; In this embodiment, during the curing process of large-volume concrete, water evaporation may affect its temperature control effect and strength development; the humidity sensor 401 monitors the humidity of the concrete surface in real time. When the humidity is lower than the set value, the water replenishment device is activated; the water replenishment device drives the frame 409 and the sprinkler head 410 above it to swing through a series of mechanical structures such as the rotating rod 403, the turntable 404, the connecting rod 405, the gear plate 406, and the gear 408. The water pump 411 pumps water from the water tank 302 and evenly sprays it onto the concrete surface from the sprinkler head 410 through the water pipe, thereby maintaining the humidity of the concrete stable and creating a good humidity environment for temperature control and strength growth of the concrete.

[0023] Example 2: See also Figure 1-Figure 7 As shown, based on the first embodiment, the present invention provides a technical solution: the fault diagnosis system 5 includes a data acquisition module, a data fusion processor, a machine learning algorithm operation module and an alarm; The data acquisition module includes flow sensor, current sensor and voltage sensor; A flow sensor is fixedly mounted on the surface of the cooling tube 305, and a current sensor and a voltage sensor are fixedly mounted on the surfaces of the three heating tubes 308 respectively; In this embodiment, the flow sensor, current sensor, and voltage sensor in the data acquisition module respectively monitor the water flow rate of the cooling pipe 305 and the current and voltage equipment operating status parameters of the heating pipe 308. Combined with the data from the temperature sensor 101 and the humidity sensor 401, the data fusion processor integrates and analyzes the multi-source data.

[0024] In this embodiment, the machine learning algorithm operation module uses these fused data to judge the system operation status through specific algorithms such as the support vector machine algorithm. When a fault is detected, such as sensor failure, blockage of the cooling pipe 305, or abnormality of the heating pipe 308, it can quickly and accurately locate the fault point and fault type, and promptly notify maintenance personnel through an alarm, thereby reducing equipment downtime, ensuring the continuous and stable operation of the temperature control device, and avoiding concrete quality problems caused by equipment failure.

[0025] In this embodiment, the remote control terminal 6 provides a convenient remote operation channel for construction personnel and management personnel; through a mobile phone APP or a computer client, users can log in to the remote control terminal 6 anytime and anywhere, view the internal temperature and humidity data of the concrete in real time, and understand the operating status of the temperature control system; at the same time, various parameters of the temperature control system can be remotely set and adjusted, such as setting the target temperature range of the temperature adjustment execution system 3 and the humidity threshold of the intelligent water replenishment system 4.

[0026] The built-in algorithm program 205 adopts an adaptive intelligent temperature control algorithm based on multivariate regression analysis and fuzzy control theory; specifically: The algorithm is based on the time after concrete pouring , ambient temperature , the rate of change of temperature inside concrete and ambient humidity As input variables, the initial temperature control strategy model is established through multivariate regression analysis, and the formula is as follows: in, is the initial temperature control strategy parameter, is the regression coefficient, obtained through historical data training; On this basis, fuzzy control theory is introduced to adjust the initial temperature control strategy in real time, and the deviation between the internal temperature of the concrete and the preset suitable temperature range is adjusted. and the rate of change of deviation , define fuzzy rules; for example, when For "righteousness" and When it is “positively small”, increase the cooling water flow rate or increase the heating power; through the fuzzy reasoning and defuzzification process, output the final temperature control strategy to achieve precise control of the temperature regulation execution system 3.

[0027] In this embodiment, the time after concrete pouring, ambient temperature, rate of change of temperature inside concrete, and ambient humidity are used as input variables. An initial temperature control strategy model is first established through multivariate regression analysis. Then, fuzzy control theory is used to define fuzzy rules based on the deviation between the internal temperature of concrete and the preset suitable temperature range and the rate of change of the deviation. After fuzzy reasoning and defuzzification, the final temperature control strategy is output to accurately control the temperature regulation execution system 3 to ensure that the concrete is at a suitable temperature.

[0028] The machine learning algorithm operation module uses the support vector machine (SVM) algorithm for fault diagnosis. The algorithm uses the flow sensor data collected by the data acquisition module to , current sensor data , voltage sensor data and temperature sensor 101 data , humidity sensor 401 data As input feature vector In the training phase, a large amount of feature vector data under normal operating conditions and various fault conditions is collected and divided into training sets and test sets. The training set data is used to train the SVM model. By optimizing the kernel function (such as the radial basis kernel function) and parameters (such as the penalty factor and the kernel coefficient ), so that the model achieves the best classification performance; During the actual operation, the feature vector collected in real time is input into the trained SVM model, and the model outputs the fault type label. The fault types include but are not limited to sensor failure, cooling tube 305 blockage, and heating tube 308 failure. At the same time, combined with the multi-source data processed by the data fusion processor, by calculating the distance between the characteristic vector and the center of each type of fault mode, the location of the fault point can be further determined to achieve fast and accurate fault diagnosis.

[0029] In this embodiment, data from a flow sensor, a current sensor, a voltage sensor, a temperature sensor 101, and a humidity sensor 401 are used as input feature vectors. During the training phase, a large amount of normal and fault state feature vector data is used to train the model, and the kernel function and parameters are optimized to improve the classification performance. During actual operation, real-time feature vectors are input, and fault type labels are output. The distance between the feature vector and the center of the fault mode is calculated by combining multi-source data to determine the location of the fault point, thereby achieving fast and accurate fault diagnosis.

[0030] The remote control terminal 6 and the central control system 2 use a communication method based on the MQTT protocol; this protocol has the characteristics of being lightweight, low power consumption, and highly reliable, and is suitable for data transmission in the Internet of Things environment; The central control system 2 acts as an MQTT client, encapsulating the temperature data collected by the temperature monitoring system 1, the humidity data collected by the humidity sensor 401, and the fault information data of the fault diagnosis system 5 into messages according to the MQTT protocol format, and publishing them to the designated MQTT topic; the remote control terminal 6 acts as another MQTT client, subscribes to the corresponding topic, receives the data, and displays it in real time on the interface; The remote control terminal 6 can send control instructions to the central control system 2, such as adjusting the operating parameters of the temperature regulation execution system 3 and setting the water replenishment threshold of the intelligent water replenishment system 4; these instructions are also sent to the designated topic in the form of MQTT messages. The central control system 2 subscribes to the topic, receives and parses the instructions, and executes the corresponding operations to realize remote monitoring and control of the temperature control system.

[0031] In summary, the intelligent large-volume concrete temperature control system collects the internal temperature of the concrete in real time through the multi-point distributed and high-precision temperature sensors 101 in the temperature monitoring system 1. The central control system 2 uses an adaptive intelligent temperature control algorithm to comprehensively consider multiple factors such as concrete pouring time, ambient temperature, internal temperature change rate, and ambient humidity to accurately judge and regulate the temperature. The temperature adjustment execution system 3 uses the refrigerator 303, cold water pump 304, and heating pipe 308 equipment according to instructions to achieve efficient cooling and heating operations, ensuring that the concrete hardens at an appropriate temperature, greatly improving the quality of the concrete, and effectively reducing the risk of cracks and quality hazards caused by temperature problems.

[0032] In addition, the fault diagnosis system 5 uses the data acquisition module to collect multi-source data such as flow, current, voltage, temperature and humidity, which are integrated by the data fusion processor and quickly and accurately locate the fault point and type with the help of machine learning algorithm operation modules such as support vector machine algorithm, and timely alarm; at the same time, the remote control terminal 6 communicates with the central control system 2 based on the MQTT protocol. Users can remotely view data and adjust system parameters anytime and anywhere, realizing intelligent operation and maintenance and convenient management of the temperature control system, greatly improving work efficiency, reducing equipment downtime, and ensuring the continuity and stability of temperature control work.

[0033] Working principle: At a large-volume concrete pouring construction site, the temperature monitoring system 1 is first installed. Multiple high-precision temperature sensors 101 are evenly distributed at key locations inside the concrete at a certain spacing and depth, such as the center area of the pouring body, areas close to the surface, and between different structural layers. These locations can fully capture the temperature changes in different areas inside the concrete and ensure the integrity of temperature data collection. The temperature sensor 101 has high-precision measurement capabilities with an accuracy of up to ±0.1°C, ensuring the accuracy of the collected temperature data. At the same time, it is connected to the wireless transmission module 102, which is responsible for stably and quickly transmitting the data collected by the temperature sensor 101 to the central control system 2, realizing real-time data transmission; The central control system 2 is installed in the control room of the construction site. The shell 201 is fixed on the operating table, and the cover plate 202 is installed with screws. Inside the shell 201, the microprocessor 203, the data storage module 204 and the built-in algorithm program 205 have been pre-installed and debugged. The microprocessor 203 uses a high-performance chip with strong data processing capabilities and can quickly process a large amount of temperature, humidity and equipment operation data. The data storage module 204 uses a large-capacity storage device to store historical temperature data, equipment operation records and system setting parameters, etc., to facilitate subsequent review and analysis of the concrete temperature control process and project quality tracing. A display screen 206 is installed on the surface of the cover plate 202 to facilitate operators to view system operation status, concrete temperature data and equipment working parameters in real time; The temperature regulation execution system 3 is installed near the concrete pouring area to facilitate rapid adjustment of the concrete temperature. The movable plate 301 is installed on a movable bracket to facilitate adjustment of the position according to construction requirements. A water tank 302 is fixed on the top of the movable plate 301. A refrigerator 303 and three heating pipes 308 are installed inside the water tank 302 to reduce and increase the temperature of the water in the water tank respectively. A cold water pump 304 is also installed on the top of the movable plate 301, and its outlet is connected to the serpentine cooling pipe 305 through a flange. The cooling pipe 305 is made of metal with good thermal conductivity and moderate wall thickness to ensure good heat exchange effect. The serpentine design increases the contact area with the concrete and improves the heat dissipation efficiency. A heat sink 307 is installed on the surface of the water tank 302, and a return pipe 306 is inserted inside. One end of the return pipe 306 is threadedly connected to the cooling pipe 305, and the other end extends to the inside of the water tank 302 to form a complete water circulation cooling system. The humidity sensor 401 of the intelligent water replenishment system 4 is installed on the concrete surface for real-time monitoring of the humidity of the concrete surface. The water replenishment device is installed on the top of the water tank 302, the support plate 402 is fixed on the top of the water tank 302, the rotating rod 403 is rotatably installed inside the support plate 402, the turntable 404 is fixed on the surface of the rotating rod 403, one end of the connecting rod 405 is connected to the turntable 404, and the other end is movably connected to the tooth plate 406, the tooth plate 406 is slidably installed on the top of the support plate 402 and meshes with the gear 408 on the rotating rod 407, the surface of the rotating rod 407 is fixed with a frame 409, a water pipe is installed inside the frame 409, the water pipe is connected with six sprinkler heads 410, and a water pump 411 is installed on the top of the water tank 302, its water inlet pipe extends into the water tank 302, and the water outlet pipe is connected to the water pipe inside the frame 409, to ensure that water can be replenished in time when the humidity of the concrete surface is insufficient; The flow sensor of the fault diagnosis system 5 is installed on the surface of the cooling pipe 305 to monitor the water flow rate in the cooling pipe. The current sensor and voltage sensor are installed on the surface of the three heating pipes 308 to monitor the current and voltage of the heating pipes. The data acquisition module collects these sensor data, integrates and analyzes them through the data fusion processor, and then the machine learning algorithm operation module uses the support vector machine (SVM) algorithm to perform fault diagnosis. The alarm is installed in a conspicuous location on the construction site to promptly issue an alarm when a fault is detected. The remote control terminal 6 can use a mobile phone APP or a computer client. Construction personnel and management personnel can log in to the remote control terminal 6 to remotely monitor and control the entire temperature control system. The central control system 2 and the remote control terminal 6 use a communication method based on the MQTT protocol to ensure the efficiency, stability and security of data transmission. During the concrete pouring process, the temperature monitoring system 1 starts working. The temperature sensor 101 collects the internal temperature data of the concrete in real time and sends the data to the central control system 2 through the wireless transmission module 102. At the same time, the humidity sensor 401 collects the surface humidity data of the concrete. The flow sensor, current sensor and voltage sensor respectively collect the water flow rate of the cooling pipe 305 and the current and voltage data of the heating pipe 308. These data are also transmitted to the central control system 2. After receiving the data, the microprocessor 203 of the central control system 2 uses the built-in algorithm program 205 to process it. First, according to the adaptive intelligent temperature control algorithm, the time after the concrete pouring is used to calculate the temperature of the concrete. , ambient temperature , concrete internal temperature change rate ΔtΔTint and ambient humidity As input variables, the initial temperature control strategy model is established through multivariate regression analysis: in, is the initial temperature control strategy parameter, The regression coefficient is obtained through historical data training. On this basis, the fuzzy control theory is introduced to calculate the deviation between the internal temperature of the concrete and the preset suitable temperature range. and the rate of change of deviation , define fuzzy rules, for example, when For "righteousness" and When it is “positively small”, increase the cooling water flow rate or increase the heating power; through the fuzzy reasoning and defuzzification process, output the final temperature control strategy to achieve precise control of the temperature regulation execution system 3; If the microprocessor 203 determines that the temperature of the concrete is too high, it sends a cooling instruction to the temperature control execution system 3, the cold water pump 304 is started, the refrigerator 303 starts working, and the water in the water tank 302 is cooled. The low-temperature cooling water circulates into the concrete through the cooling pipe 305, taking away heat to achieve cooling. The cooled water flows back to the water tank 302 through the return pipe 306, completing the water cycle. If the concrete temperature is determined to be too low, the microprocessor 203 controls the heating pipe 308 to be energized and heated, heating the water in the water tank 302. The hot water heats the concrete through the water circulation, ensuring that the concrete hardens at an appropriate temperature. During the concrete curing process, humidity sensor 401 monitors the concrete surface humidity in real time. When the humidity falls below a set value, intelligent water replenishment system 4 activates, pumping pump 411 draws water from water tank 302, transports it through a water pipe to frame 409, and sprays it evenly onto the concrete surface from sprinkler head 410. Simultaneously, a motor drives rotating rod 403, which in turn rotates turntable 404. Connecting rod 405 causes toothed plate 406 to slide across the top of support plate 402. Toothed plate 406 rotates gear 408, which in turn rotates rotating rod 407. This causes frame 409 and sprinkler head 410 to swing accordingly, expanding the water spray coverage area and maintaining a stable concrete humidity. The data acquisition module of the fault diagnosis system 5 continuously collects data from the flow sensor, current sensor, voltage sensor, temperature sensor 101, and humidity sensor 401, and transmits it to the data fusion processor for integration. The machine learning algorithm operation module adopts the support vector machine (SVM) algorithm, using this fused data as the input feature vector X = (Q, I, V, T, H) for fault diagnosis. During the training phase, a large amount of feature vector data under normal operating conditions and various fault conditions is collected and divided into training sets and test sets for training the SVM model. The kernel function (such as the radial basis kernel function) and parameters (such as the penalty factor C and the kernel coefficient γ) are optimized to achieve optimal classification performance. During actual operation, the real-time collected feature vectors are input into the trained SVM model, and the model outputs a fault type label y. Fault types include but are not limited to sensor failure, cooling pipe 305 blockage, heating pipe 308 failure, etc. At the same time, combined with the multi-source data processed by the data fusion processor, the distance between the feature vector and the center of each fault mode is calculated to further determine the location of the fault point. If a fault is detected, the alarm promptly issues an alarm to notify maintenance personnel. The remote control terminal 6 communicates with the central control system 2 through the MQTT protocol. The central control system 2 encapsulates the temperature data collected by the temperature monitoring system 1, the humidity data collected by the humidity sensor 401, and the fault information data of the fault diagnosis system 5 into messages in the MQTT protocol format and publishes them to the designated MQTT topic. The remote control terminal 6 subscribes to the corresponding topic, receives these data, and displays them in real time on the interface. Construction personnel and management personnel can send control instructions to the central control system 2 through the remote control terminal 6, such as adjusting the operating parameters of the temperature regulation execution system 3 (refrigerator power, cold water pump flow, heating pipe temperature, etc.), setting the water replenishment threshold of the intelligent water replenishment system 4, etc. These instructions are also sent to the designated topic in the form of MQTT messages. The central control system 2 subscribes to the topic, receives and parses the instructions, and executes the corresponding operations to realize remote monitoring and control of the temperature control system.

[0034] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include," "comprise," or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, the phrase "includes an element defined by..." does not exclude the presence of other identical elements in the process, method, article, or device that includes the element.

[0035] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent mass concrete temperature control system, comprising a temperature monitoring system (1), a central control system (2), a temperature regulation execution system (3), an intelligent water supply system (4), a fault diagnosis system (5) and a remote control terminal (6), characterized in that: The central control system (2) comprises a housing (201) located in the central control system (2), a cover plate (202) being mounted on the surface of the housing (201) by screws, a microprocessor (203), a data storage module (204) and a built-in algorithm program (205) being fixedly mounted inside the housing (201), and a display screen (206) being fixedly mounted on the surface of the cover plate (202); The temperature regulation execution system (3) comprises a movable plate (301) located in the temperature regulation execution system (3), a water tank (302) is fixedly installed on the top of the movable plate (301), a refrigerator (303) is fixedly installed inside the water tank (302), a cold water pump (304) is fixedly installed on the top of the movable plate (301), a cooling pipe (305) is fixedly installed at the water outlet of the cold water pump (304) through a flange, a heat sink (307) is fixedly installed on the surface of the water tank (302), a return pipe (306) is plugged into the interior of the heat sink (307), and three heating pipes (308) are fixedly installed on the inner wall of the water tank (302); The intelligent water replenishment system (4) comprises a humidity sensor (401) and a water replenishment device.

2. The intelligent mass concrete temperature control system according to claim 1, characterized in that: The water replenishing device comprises a support plate (402) fixedly mounted on the top of the water tank (302); a rotating rod (403) is rotatably mounted inside the support plate (402); a rotating disk (404) is fixedly mounted on the surface of the rotating rod (403); a connecting rod (405) is connected to the surface of the rotating disk (404); a tooth plate (406) is slidably mounted on the top of the support plate (402); a rotating rod (407) is rotatably mounted on the top of the support plate (402); a gear (408) is fixedly mounted on the surface of the rotating rod (407); a frame (409) is fixedly mounted on the surface of the rotating rod (407); six water spray heads (410) are provided on the surface of the frame (409); and a water pump (411) is fixedly mounted on the top of the water tank (302).

3. The intelligent mass concrete temperature control system according to claim 2, characterized in that: A water pipe is fixedly installed inside the frame (409), and the water pipe is connected to a plurality of water spray heads (410). A water inlet pipe extending to the inside of the water tank (302) is fixedly installed at the water inlet of the water pump (411), and a delivery pipe fixedly connected to the water pipe is fixedly installed at the water outlet of the water pump (411).

4. The intelligent mass concrete temperature control system according to claim 2, characterized in that: One end of the connecting rod (405) away from the rotating disk (404) is movably connected to the surface of one end of the tooth plate (406), and the surface of the tooth plate (406) is meshed with the surface of the gear (408).

5. The intelligent mass concrete temperature control system according to claim 1, characterized in that: The cooling pipe (305) is designed as a serpentine pipe. One end of the cooling pipe (305) away from the cold water pump (304) is threadedly connected to one end of the return pipe (306), and the end of the return pipe (306) away from the cooling pipe (305) extends to the interior of the water tank (302).

6. The intelligent mass concrete temperature control system according to claim 1, characterized in that: The fault diagnosis system (5) includes a data acquisition module, a data fusion processor, a machine learning algorithm operation module and an alarm; The data acquisition module includes a flow sensor, a current sensor, and a voltage sensor; A flow sensor is fixedly mounted on the surface of the cooling tube (305), and a current sensor and a voltage sensor are respectively fixedly mounted on the surfaces of the three heating tubes (308).

7. The intelligent mass concrete temperature control system according to claim 1, characterized in that: The built-in algorithm program (205) adopts an adaptive intelligent temperature control algorithm based on multivariate regression analysis and fuzzy control theory; specifically: The algorithm uses the time after concrete pouring, ambient temperature, the rate of change of temperature inside the concrete, and ambient humidity as input variables. It establishes an initial temperature control strategy model through multivariate regression analysis. The formula is as follows: in, is the initial temperature control strategy parameter, is the regression coefficient, which is obtained through training with historical data.

8. The intelligent mass concrete temperature control system according to claim 1, characterized in that: The temperature monitoring system (1) includes a temperature sensor (101) and a wireless transmission module (102). The machine learning algorithm operation module uses a support vector machine (SVM) algorithm to perform fault diagnosis. The algorithm uses the flow sensor data collected by the data acquisition module to , current sensor data , voltage sensor data and temperature sensor (101) data 、Humidity sensor (401) data As input feature vector In the training phase, a large amount of feature vector data under normal operating conditions and various fault conditions is collected and divided into training sets and test sets. The training set data is used to train the SVM model. By optimizing the kernel function (such as the radial basis kernel function) and parameters (such as the penalty factor and the kernel coefficient ), so that the model achieves the best classification performance; During the actual operation, the feature vector collected in real time is input into the trained SVM model, and the model outputs the fault type label. , the fault types include but are not limited to sensor failure, cooling pipe (305) blockage, and heating pipe (308) failure; at the same time, combined with the multi-source data processed by the data fusion processor, by calculating the distance between the characteristic vector and the center of each type of fault mode, the location of the fault point is further determined to achieve fast and accurate fault diagnosis.

9. The intelligent mass concrete temperature control system according to claim 1, characterized in that: The remote control terminal (6) and the central control system (2) use a communication method based on the MQTT protocol; the protocol has the characteristics of being lightweight, low power consumption, and highly reliable, and is suitable for data transmission in an Internet of Things environment; The central control system (2) acts as an MQTT client, encapsulating the temperature data collected by the temperature monitoring system (1), the humidity data collected by the humidity sensor (401), and the fault information data of the fault diagnosis system (5) into messages according to the MQTT protocol format, and publishing them to a designated MQTT topic; the remote control terminal (6) acts as another MQTT client, subscribes to the corresponding topic, receives the data, and displays them in real time on the interface; The remote control terminal (6) can send control instructions to the central control system (2), such as adjusting the operating parameters of the temperature control execution system (3) and setting the water replenishment threshold of the intelligent water replenishment system (4); these instructions are also sent to a designated topic in the form of MQTT messages. The central control system (2) subscribes to the topic, receives and parses the instructions, and executes corresponding operations to achieve remote monitoring and control of the temperature control system.

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