High-temperature tunnel intelligent cooling device and method

Abstract

The present application relates to the technical field of tunnel engineering construction equipment, in particular to a high-geothermal-tunnel intelligent cooling device and method, the device comprising a pry-mounted refrigeration module, an intelligent control system and a dual-mode refrigeration terminal; the pry-mounted refrigeration module comprises an integrated pry-mounted unit and a circulating water tank; the circulating water tank is provided with a temperature sensor and a water level monitor for real-time monitoring of the temperature and water level of the circulating water and transmitting the monitoring data to the intelligent control system; the intelligent control module comprises a frequency conversion adjustment module, a cloud communication module and a fault diagnosis module; the dual-mode refrigeration terminal is connected to the integrated pry-mounted unit through a pipeline, comprising an independent air cooling device and a ventilation pipeline interface, and can switch between independent air cooling mode and collaborative work with the construction ventilation system. The device and method significantly improve the construction efficiency and safety of high-geothermal-tunnel, reduce the operation and maintenance cost, and provide reliable technical support for high-geothermal-tunnel construction.

Description

Technical Field

[0001] This invention relates to the field of tunnel construction equipment technology, specifically to an intelligent cooling device and method for high-temperature tunnels. Background Technology

[0002] Since the mid-19th century, high-temperature heat hazards have gradually become a significant challenge in the field of tunnel engineering. Early construction projects in Europe, such as the Sannes and Simplon tunnels, already faced construction difficulties due to the high temperature and humidity environment. With the construction of deep-buried, long tunnels like Mont Blanc and Anfang in the 20th century, heat hazards have intensified, severely deteriorating the construction environment and causing secondary problems such as cracking of the lining structure, posing a serious threat to the construction safety, structural stability, and health of personnel in tunnel engineering.

[0003] In my country, since the first recorded rock temperature of 35-40℃ in the Chengdu-Kunming Railway tunnel project in the 1960s, extreme cases have emerged in engineering practice in western China during the 21st century. For example, the rock temperature in the Sangzhuling Tunnel reached as high as 89.9℃, and the Bulunkou-Gonger Hydropower Station Tunnel experienced an ultra-high temperature environment of 105℃. According to the requirements of the "Railway Tunnel Design Code," the ambient temperature during construction must be strictly controlled below 28℃; exceeding this standard will directly threaten construction safety, structural stability, and the health of personnel.

[0004] The causes of high ground temperatures are complex, involving the coupled effects of multiple factors such as geological structure and geothermal activity. During the construction phase, the core strategy lies in implementing effective cooling measures. Traditionally, physical cooling methods such as ventilation and water spraying are widely used, but they suffer from insufficient cooling supply and low heat dissipation efficiency, making it difficult to meet the systemic cooling needs of ultra-long tunnels. While mechanical refrigeration technology can achieve efficient cooling replenishment, current equipment has significant limitations: its split structure, designed for coal mine environments, makes movement difficult, and cold water transport requires additional insulation, increasing energy consumption and construction costs. Furthermore, 15°C cold water experiences a significant temperature rise after passing through a high-temperature environment, and the equipment's protective shutdown is triggered when the circulating water temperature reaches 36°C, severely impacting its continuous operation capability.

[0005] Furthermore, the existing equipment lacks sufficient intelligence and cannot meet the intelligent control requirements of complex tunnel conditions, which further restricts the construction efficiency and safety of high-temperature tunnels. Therefore, developing an efficient, intelligent, and portable cooling device and method suitable for high-temperature tunnel environments is of great significance for improving tunnel construction efficiency, ensuring construction safety, and protecting personnel health. Summary of the Invention

[0006] To address the aforementioned issues, this invention provides an intelligent cooling device for high-temperature tunnels. This device significantly improves the construction efficiency and safety of high-temperature tunnels and reduces operation and maintenance costs through technologies such as skid-mounted design, high-efficiency cooling, intelligent control, dual-mode cooling, remote monitoring, safety protection, and environmental adaptability, thus providing reliable technical support for the construction of high-temperature tunnels.

[0007] The technical solution of the present invention is as follows:

[0008] A smart cooling device for high-temperature tunnels includes a skid-mounted refrigeration module, an intelligent control system, and a dual-mode refrigeration terminal.

[0009] Skid-mounted refrigeration modules include integrated skid-mounted units and circulating water tanks;

[0010] The circulating water tank is equipped with a temperature sensor and a water level monitor to monitor the temperature and water level of the circulating water in real time and transmit the monitoring data to the intelligent control system.

[0011] The intelligent control module includes:

[0012] The variable frequency control module is used to dynamically adjust the power of the chiller unit and the circulating water flow rate;

[0013] The cloud communication module is used for remote data transmission and device cluster management;

[0014] The fault diagnosis module triggers a graded protection mechanism based on sensor data;

[0015] The dual-mode cooling terminal is connected to the integrated skid-mounted unit via piping, including an independent air-cooling device and ventilation duct interface, and can switch to independent air-cooling mode or work in conjunction with the construction ventilation system.

[0016] Integrated skid-mounted units include:

[0017] Refrigeration unit: It consists of a semi-hermetic twin-screw compressor, a high-efficiency condenser, and an evaporator connected in sequence through refrigerant piping. A circulating water pump is installed between the high-efficiency condenser and the circulating water tank.

[0018] Expansion valve: installed on the refrigerant line between the condenser and the evaporator;

[0019] Heat dissipation unit: includes an air cooler and a fan, with the air cooler connected to the evaporator via a chilled water pump;

[0020] Filter: Installed between the condenser and the expansion valve.

[0021] The overall dimensions of the intelligent cooling equipment for high-temperature tunnels are compatible with standard tunnel transportation equipment.

[0022] The ventilation duct interface of the dual-mode cooling terminal is equipped with an air volume-water temperature coupling controller.

[0023] The intelligent control system is equipped with:

[0024] a) Water temperature adaptive adjustment algorithm, which automatically adjusts the compressor frequency based on the real-time monitored temperature inside the cave;

[0025] b) Automatic switching function between cooling and dehumidification modes;

[0026] c) Water temperature over-limit protection mechanism: when the return water temperature is >50℃, the system will be shut down.

[0027] A smart cooling method for high-temperature tunnels includes the following steps:

[0028] Step 1: System initialization, collecting temperature and humidity parameters inside the cave through the environmental sensing module;

[0029] Step 2: The intelligent decision-making module selects either independent cooling or combined ventilation and cooling mode based on the parameters;

[0030] Step 3: Dynamically adjust the compressor power and circulating water flow rate to maintain the outlet water temperature within the set range;

[0031] Step 4: Remotely set parameters and monitor operational status through a cloud-based monitoring platform;

[0032] Step 5: When an abnormal water temperature or equipment malfunction is detected, the protection program will be automatically executed and an alarm message will be sent.

[0033] Step three includes:

[0034] The variable frequency control module monitors the water temperature and level in the circulating water tank and the operating parameters of each device in the system in real time.

[0035] Based on the preset temperature range and equipment performance curve, the operating frequency of each device in the integrated skid-mounted unit is automatically adjusted;

[0036] Closed-loop feedback control ensures that the outlet water temperature remains stable within the set range.

[0037] Step two includes:

[0038] Real-time monitoring of temperature and humidity parameters inside the cave;

[0039] The preset cooling / dehumidification mode switching threshold will prioritize the cooling mode when the air temperature is higher than the set temperature threshold and the relative humidity is lower than the humidity threshold.

[0040] When the air temperature is within a certain range and the relative humidity is higher than the humidity threshold, switch to dehumidification mode or ventilation combined with cooling mode.

[0041] Step five includes:

[0042] The temperature sensor in the circulating water tank continuously monitors the return water temperature in real time;

[0043] When the return water temperature exceeds the set shutdown threshold, the intelligent control system immediately triggers the system shutdown protection mechanism;

[0044] Meanwhile, the system sends alarm information through the cloud monitoring platform or local alarm device to notify maintenance personnel to handle the situation in a timely manner.

[0045] Step three includes adaptive water temperature control. The steps to implement adaptive water temperature control are as follows:

[0046] Data Acquisition and Preprocessing: A dedicated data acquisition module is set up in the intelligent control system. It is connected to the water temperature sensor and the ambient temperature and humidity sensor through the communication interface. The module collects water temperature, ambient temperature and humidity data at certain time intervals and performs preprocessing operations such as filtering and calibration on the collected data to remove noise and outliers, thereby improving the accuracy and reliability of the data.

[0047] Parameter initialization: Based on the actual conditions of the tunnel and the design requirements of the refrigeration system, set initial parameters such as the target water temperature range, the upper and lower limits of the compressor frequency, and the frequency adjustment step size, and store these parameters in the memory of the intelligent control system.

[0048] Model training and optimization: During the system installation and debugging phase and subsequent operation, historical data on the water temperature regulation process are continuously collected. This data is used to train and optimize the water temperature regulation model. Machine learning algorithms are used to continuously adjust the model's parameters to improve the model's prediction accuracy and adaptability.

[0049] Real-time adjustment and feedback control: During system operation, the intelligent control system collects water temperature data at set time intervals and inputs it into the water temperature adjustment model. Based on the output of the model, the operating frequency of the compressor is adjusted in real time through the frequency conversion adjustment module. At the same time, the changes in water temperature are continuously monitored. If the adjusted water temperature still does not reach the target range or an abnormality occurs, the compressor frequency is recalculated and adjusted in time to form a closed-loop feedback control to ensure that the water temperature is stable within the set range.

[0050] The beneficial effects of this invention are as follows:

[0051] 1. This invention discloses an intelligent cooling device for high-temperature tunnels. This intelligent cooling device and method for high-temperature tunnels integrates a refrigeration unit (cooling capacity ≥1000kW) and a circulating water tank (volume 20m3) into the same skid-mounted chassis (size / weight can be customized) to form a compact device that can be quickly moved, realizing the integrated function of "cooling-water storage-air supply". The device is easy to move, the response speed is improved by 50%, and it can be quickly deployed to an area 50-100m away from the working face to flexibly meet the cooling needs of different sections of the tunnel. It reduces the cold loss of pipelines in traditional split equipment (cold loss rate ≤5% / 100m) and improves the overall energy efficiency by 40%.

[0052] 2. The present invention discloses an intelligent cooling device for high-temperature tunnels. This intelligent cooling device and method for high-temperature tunnels uses 30℃±2℃ circulating water, combined with a high-efficiency heat exchange design (heat exchange efficiency ≥85%), to reduce the need for pipe insulation. By raising the shutdown protection threshold to 50℃ (the industry standard is 36℃), the continuous operation time is extended. The construction cost of insulation pipelines is reduced by 30%, and the energy consumption for cooling per kilometer is reduced by 25%. The equipment can operate continuously until the circulating water temperature reaches 50℃, and the operation time in high-temperature environments is extended by more than 3 times.

[0053] 3. This invention discloses an intelligent cooling device for high-temperature tunnels. This intelligent cooling device and method for high-temperature tunnels achieves dual-mode intelligent air supply and dynamic energy efficiency management: In independent cooling mode, 15℃ cold water is transported through insulated pipes, and the cooling power consumption per unit area is ≤0.8kWh / m². 2 This reduces the working face temperature from 38℃ to below 28℃; in the ventilation duct combined mode, the construction ventilation duct enhances heat dissipation, increasing the system's overall energy efficiency ratio (EER) by 30%; the dual modes can be switched according to site requirements, covering the needs of the entire tunnel construction cycle, with a cooling gradient of ≥10℃, effectively ensuring the working environment.

[0054] 4. This invention discloses an intelligent cooling device for high-temperature tunnels, which integrates an intelligent system with adaptive heat load adjustment, cloud-based cluster control, and a three-level early warning system: based on a multi-source sensor network (temperature accuracy ±0.5℃, humidity accuracy ±3%RH), it adjusts the compressor frequency in real time and dynamically optimizes energy consumption by 15%–25%; it supports cluster management of 100 devices (data latency <1s), and provides accurate remote fault diagnosis.

[0055] The efficiency is ≥95%. It achieves unattended automated operation, reducing manual intervention by 40%; fault response time is ≤2 seconds, ensuring construction continuity and reducing operation and maintenance costs by 38%. Attached Figure Description

[0056] Figure 1 This is a structural schematic diagram of an intelligent cooling device for high-temperature tunnels.

[0057] Figure 2 This is a schematic diagram of a separate cooling measurement point for the mechanical refrigeration unit in Embodiment 1 of the present invention;

[0058] Figure 3 This is a graph showing the changes in air temperature and air velocity at the air outlet of the refrigeration unit in Embodiment 1 of the present invention;

[0059] Figure 4 This is a graph showing the change in ambient humidity after the refrigeration unit of Embodiment 1 of the present invention is turned on;

[0060] Figure 5 This is a comparison chart of ambient temperatures after the refrigeration unit is turned on according to Embodiment 1 of the present invention.

[0061] Figure 6 This is a graph showing the environmental temperature and humidity variation patterns in Embodiment 2 of the present invention.

[0062] Figure 7 This is a histogram showing the temperature drop in Embodiment 2 of the present invention.

[0063] Figure 8 This is a schematic diagram of a numerical simulation of the high-efficiency intelligent cooling and temperature reduction in Embodiment 3 of the present invention;

[0064] Figure 9 This is a comparison chart of numerical simulation and field measurement results of tunnel environmental temperature in Embodiment 3 of the present invention;

[0065] Figure 10 This is a comparison diagram of the effects of mechanical refrigeration and non-mechanical refrigeration in Embodiment 3 of the present invention;

[0066] The components represented by the various reference numerals in the diagram are:

[0067] This invention comprises: 1. An integrated skid-mounted unit, 1-1. A semi-hermetic twin-screw compressor, 1-2. A high-efficiency condenser, 1-3. An evaporator, 1-4. An expansion valve, 1-5. An air cooler, 1-6. A fan, 1-7. A chilled water pump, 1-8. A circulating water pump, 1-9. A filter, 2. A circulating water tank, 2-1. A temperature sensor, 2-2. A water level monitor, 3. An intelligent control system, 3-1. A frequency converter module, 3-2. A cloud communication module, 3-3. A fault diagnosis module, 3-4. An environmental sensing module, 3-5. An intelligent decision-making module, 4. A dual-mode refrigeration terminal, 4-1. An independent air-cooling device, 4-2. A ventilation duct interface, 4-2a. An airflow-water temperature coupling controller. Detailed Implementation

[0068] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of this application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to this application are not shown or described in the specification. This is to avoid obscuring the core parts of this application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0069] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0070] like Figure 1 As shown, the intelligent cooling equipment for high-temperature tunnels measures 9.0m long × 1.6m wide × 2.7m high. It adopts an integrated skid-mounted design, integrating the refrigeration unit and the circulating water tank into a movable module. By optimizing the water circulation path, it can deliver 25℃ circulating water for cooling, with a cooling capacity of 1000kW, an installed power of 280kW, and the cold air temperature controlled at 15-20℃ with an air volume of 20-25m / s.

[0071] This innovative dual-mode cooling terminal allows for flexible selection of independent air cooling or operation in conjunction with the construction ventilation system. The intelligent control system integrates frequency conversion regulation, cloud monitoring, and fault diagnosis functions, raising the shutdown protection threshold to 50℃. Compared to traditional cooling solutions, this cooling equipment eliminates the need for special insulation treatment on the circulating water pipes, reducing cooling loss by over 40%, making it particularly suitable for the complex conditions of ultra-long, high-temperature tunnels.

[0072] The equipment includes an integrated skid-mounted unit 1, a circulating water tank 2, an intelligent control system 3, and a dual-mode refrigeration terminal 4.

[0073] The integrated skid-mounted unit 1 includes a semi-hermetic twin-screw compressor 1-1, a high-efficiency condenser 1-2, an evaporator 1-3, an expansion valve 1-4, an air cooler 1-5, a fan 1-6, a chilled water pump 1-7, a circulating water pump 1-8, and a filter 1-9 integrated module, which is combined and installed with the circulating water tank 2 through detachable connectors.

[0074] The circulating water tank 2 is equipped with a temperature sensor 2-1 and a water level monitor 2-2. The working water temperature is always maintained in the range of 40℃ through the external water supply pipe.

[0075] The intelligent control system 3 includes a frequency conversion adjustment module 3-1, a cloud communication module 3-2, and a fault diagnosis module 3-3; the dual-mode cooling terminal 4 includes an independent air-cooling device 4-1 and a ventilation duct interface 4-2.

[0076] Furthermore, the frequency converter module 3-1 adopts advanced frequency converter technology, which uses sensors to monitor the water temperature and level in the circulating water tank 2 in real time, as well as the operating parameters of various devices in the system, such as the current and voltage of the compressor 1-1. Based on these parameters, the frequency converter automatically adjusts the operating frequency of devices such as the compressor 1-1, the fan 1-6, the chilled water pump 1-7, and the circulating water pump 1-8.

[0077] The frequency converter module 3-1 is equipped with an intelligent algorithm that accurately calculates the optimal operating frequency required by each device under different loads based on the preset temperature range and equipment performance curve, so as to achieve energy saving and stable operation.

[0078] The implementation steps of the frequency converter regulation module 3-1 are as follows:

[0079] 1) Install the frequency converter at the power input terminal of each device that needs to be regulated, and connect the corresponding sensor.

[0080] 2) Calibrate the sensors to ensure that the collected data is accurate and reliable.

[0081] 3) Program and set the inverter's adjustment parameters, including target temperature, equipment performance curves, etc.

[0082] 4) Start the system and allow the frequency converter to automatically adjust the equipment operating frequency based on real-time data, continuously monitor the system operating status, and make dynamic adjustments as needed.

[0083] Furthermore, the cloud communication module 3-2 utilizes wireless communication technologies, such as 4G / 5G and Wi-Fi, to connect the intelligent control system 3 to the cloud server. Through a communication terminal installed locally, it uploads system operation data, including equipment status, temperature, water level, and other information, to the cloud in real time. The cloud platform has data storage, analysis, and display functions. Users can remotely access system information anytime and anywhere through mobile apps, web pages, and other terminals, view equipment operation status and historical data, and receive system alarm information.

[0084] The implementation steps for cloud communication module 3-2 are as follows:

[0085] 1) Select a suitable wireless communication module, install it in the intelligent control system 3, and configure the network so that it can connect to the Internet.

[0086] 2) Build a server in the cloud, deploy data storage and management software, and design a corresponding database structure to store various types of data uploaded by the system.

[0087] 3) Develop user-side access interfaces, such as mobile apps and web pages, to enable data visualization and remote control functions.

[0088] 4) Conduct system integration testing to ensure that local data can be uploaded to the cloud accurately and stably, and that cloud data can be fed back to the user terminal in a timely manner, so as to realize remote monitoring and management.

[0089] Furthermore, the fault diagnosis module 3-3 collects real-time operating parameters of the equipment, such as vibration, temperature, and pressure, by installing sensors in various key parts of the system. Using fault diagnosis algorithms, such as neural networks and expert systems, the collected data is analyzed and processed, and compared with the parameter model under normal operating conditions. When abnormal parameters are detected, the system automatically determines the fault type and location, promptly issues an alarm signal, and provides corresponding fault handling suggestions.

[0090] The implementation steps of fault diagnosis module 3-3 are as follows:

[0091] 1) Conduct a comprehensive assessment of the possible fault types of each device in the system, and determine the key parameters that need to be monitored and the locations where sensors are installed.

[0092] 2) Purchase and install the corresponding sensors, and debug and calibrate the sensors to ensure the accuracy and stability of data acquisition.

[0093] 3) Select a suitable fault diagnosis algorithm, train and optimize the algorithm so that it can accurately identify various fault characteristics.

[0094] 4) Integrate the fault diagnosis algorithm into the intelligent control system 3, set the fault alarm threshold and processing flow, conduct system testing, and verify the accuracy and reliability of fault diagnosis.

[0095] Furthermore, environmental sensing modules 3-4 are equipped with environmental sensors, such as temperature sensors, humidity sensors, smoke sensors, and gas sensors (e.g., carbon monoxide, carbon dioxide), installed inside the tunnel and around the system to monitor environmental parameters in real time. Through data fusion technology, data collected from different sensors is integrated and analyzed to construct a comprehensive perception model of the system's environment. Based on this environmental sensing information, the system automatically adjusts its operating mode and parameters to adapt to different environmental conditions, ensuring effective cooling and safe operation of the equipment.

[0096] The implementation steps for environmental perception module 3-4 are as follows:

[0097] 1) Determine the environmental parameters to be monitored and the locations of the environmental sensors to be installed based on the actual application scenarios and requirements of the system.

[0098] 2) Purchase and install the corresponding environmental sensors, and debug and calibrate the sensors to ensure the accuracy and stability of data acquisition.

[0099] 3) Develop data fusion algorithms to integrate and analyze data from different sensors and build an environmental perception model.

[0100] 4) Integrate the environmental perception model into the intelligent control system 3, set the system operation mode and parameter adjustment strategy, automatically optimize and adjust according to environmental changes, and conduct system testing and verification.

[0101] Furthermore, the integrated skid-mounted unit 1 adopts a modular design, with each functional unit connected by quick-connect pipes, and its overall size is compatible with standard tunnel transportation equipment.

[0102] Furthermore, the intelligent control system 3 is equipped with:

[0103] 1) Water temperature adaptive adjustment algorithm, which automatically adjusts the compressor frequency based on the real-time monitored temperature inside the cave;

[0104] 2) Automatic switching function between cooling and dehumidification modes;

[0105] 3) Water temperature over-limit protection mechanism: when the return water temperature is >50℃, the system will be shut down.

[0106] The water temperature adaptive adjustment algorithm is as follows:

[0107] 1) Data acquisition and preprocessing: A dedicated data acquisition module is set up in the intelligent control system 3. It is connected to the water temperature sensor 2-1 and the ambient temperature and humidity sensors through the communication interface. It collects water temperature, ambient temperature and humidity data at certain time intervals, such as every minute or every second. The collected data is preprocessed by filtering, calibration and other operations to remove noise and outliers and improve the accuracy and reliability of the data.

[0108] 2) Parameter initialization: Based on the actual conditions of the tunnel and the design requirements of the refrigeration system, set initial parameters such as the target water temperature range of 40℃, the upper and lower limits of the compressor frequency, and the frequency adjustment step size, and store these parameters in the memory of the intelligent control system 3.

[0109] 3) Model Training and Optimization: During the system installation and commissioning phase and subsequent operation, historical data on water temperature regulation is continuously collected, including the correlation between compressor frequency adjustment and water temperature changes under different environmental conditions. This data is used to train and optimize the water temperature regulation model. Machine learning algorithms such as neural networks and support vector machines are employed to continuously adjust the model's parameters, improving its prediction accuracy and adaptability.

[0110] 4) Real-time adjustment and feedback control: During system operation, the intelligent control system 3 collects water isothermal data at set time intervals and inputs it into the water temperature regulation model. Based on the model's output, the operating frequency of compressor 1-1 is adjusted in real time via the frequency converter module 3-1. Simultaneously, changes in water temperature are continuously monitored. If the adjusted water temperature still does not reach the target range, or if temperature changes occur, the compressor frequency is recalculated and adjusted promptly, forming a closed-loop feedback control to ensure the water temperature remains stable within the 40℃ range.

[0111] The automatic switching function between cooling and dehumidification modes is as follows:

[0112] 1) Arrange temperature and humidity sensors appropriately in the tunnel to ensure accurate monitoring of air temperature and humidity in different areas.

[0113] 2) Based on the actual conditions of the tunnel and usage requirements, set the switching thresholds for cooling and dehumidification modes. When the air temperature is higher than the set temperature threshold of 28℃ and the relative humidity is lower than 65%, the cooling mode should be used first; when the air temperature is within a certain range, such as 22-28℃ and the relative humidity is higher than the humidity threshold of 65%, switch to dehumidification mode.

[0114] The water temperature over-limit protection mechanism is as follows:

[0115] 1) The temperature sensor 2-1 in the circulating water tank 2 continuously monitors the return water temperature in real time, and collects water temperature data at a high frequency, such as multiple times per second, and transmits the data to the intelligent control system 3 in real time.

[0116] 2) After receiving the water temperature data transmitted by the temperature sensor 2-1, the intelligent control system 3 immediately processes and judges the data. It compares the real-time water temperature with the set shutdown threshold of 50℃. If the water temperature exceeds 50℃, it is determined that the water temperature exceeds the limit, triggering the system shutdown protection mechanism.

[0117] Furthermore, the ventilation duct interface 4-2 of the dual-mode cooling terminal 4 is equipped with an air volume-water temperature coupling controller 4-2a, which can automatically adjust the circulating water flow rate according to the ventilation volume.

[0118] The method for using intelligent cooling equipment for high-temperature tunnels includes the following steps:

[0119] Step 1: System initialization, collecting temperature and humidity parameters inside the cave through environmental sensing modules 3-4;

[0120] Step 2: The intelligent decision-making module 3-5 selects either independent cooling or combined ventilation and cooling mode based on the parameters;

[0121] Step 3: Dynamically adjust the compressor power and circulating water flow rate to maintain the outlet water temperature within the set range;

[0122] Step 4: Remotely set parameters and monitor operational status through a cloud-based monitoring platform;

[0123] Step 5: When an abnormal water temperature or equipment malfunction is detected, the protection program will be automatically executed and an alarm message will be sent.

[0124] Example 1: Field Measurement of Independent Cooling by Refrigeration Equipment

[0125] In a high-risk section of the tunnel with high ground temperature, the high-efficiency intelligent cooling equipment was placed 200m away from the tunnel face. First, water was supplied to the water tank of the mechanical high-efficiency intelligent cooling equipment, and simultaneously all intelligent temperature and humidity sensors were placed within 30m in front of the air outlet of the high-efficiency intelligent cooling equipment to simulate the working conditions of placing the equipment within the influence range of the tunnel face.

[0126] Temperature and humidity sensors and anemometers are positioned along the left sidewall, tunnel centerline, and right sidewall, respectively. Next, as the sensor temperatures gradually rise to match the tunnel ambient temperature, the temperature and humidity change curves of all sensors are monitored in the monitoring system; this process takes half an hour. Finally, the high-efficiency intelligent cooling equipment is activated to lower the temperature, and the temperature and humidity changes of all sensors are simultaneously monitored in the monitoring system. The sensor arrangement is as follows: Figure 2 As shown.

[0127] like Figure 3 The figure shown is a graph illustrating the changes in air temperature and air velocity at the air outlet of the refrigeration unit. Figure 3 This indicates that the outlet air temperature and velocity of the mechanical refrigeration equipment exhibit specific trends during unit operation. The outlet temperature gradually decreased from its initial maximum of 37.8℃, dropping to 23.9℃ after about half an hour, with a cumulative decrease of 36.8%. During the same period, the outlet air velocity fluctuated, with the average velocity remaining stable at around 10m / s, indicating that the unit is operating well.

[0128] Figure 4 This is a graph showing the change in ambient humidity after the refrigeration unit is turned on. Figure 4This reflects the impact of the cooling fan's operation on the tunnel's ambient humidity. Before the fan was turned on, the tunnel humidity was significantly higher than the set standard of 45%–65%, and the humidity curve fluctuated wildly with poor stability. After the fan started, the humidity dropped rapidly and stabilized within the target range, and the fluctuation amplitude of the curve decreased. However, when the fan was turned off, the humidity rose rapidly, exceeding the specified range again, and the curve fluctuation intensified.

[0129] Figure 5 This is a comparison chart of ambient temperatures after the refrigerator was turned on. From Figure 5 As can be seen from (a), the tunnel ambient temperature dropped significantly after the mechanical refrigeration equipment was turned on. After 20 minutes, the tunnel ambient temperature reached its lowest point, forming a distinct trough, with the rate of temperature drop varying slightly at different locations and time points. Figure 5 (b) It can be seen that the temperature drop ranges from 6 to 16°C, with an average maximum drop of 11.6°C. Among them, the proportion of the drop ranges from 6 to 10°C is about 16%, and the proportion of the drop ranges from 10 to 14°C is about 70%. Field measurements show that mechanical refrigeration equipment can significantly reduce the ambient temperature, providing reliable technical support for improving the construction environment of high-temperature tunnels.

[0130] Example 2: Cooling equipment in conjunction with ventilation ducts

[0131] Connect the refrigeration equipment to the construction ventilation duct, adjust the main fan power to 30%, and record the changes in temperature and humidity within the tunnel environment. The results are as follows: Figure 6 As shown.

[0132] from Figure 6 It can be seen that after the refrigeration equipment was turned on, the ambient temperature curve inside the cave showed a rapid decline, stabilizing at around 36℃. The relative humidity curve showed a rapid increase. This is because as the temperature decreases, the saturated water vapor content decreases, while the actual water vapor content remains relatively stable for a short period, leading to a corresponding increase in relative humidity, eventually stabilizing between 50% and 60%. Further statistical analysis of the temperature drop yielded the following results: Figure 7 As shown, the temperature drop in the tunnel ranged from 6 to 11°C, with an average drop of 8.9°C. Connecting the refrigeration unit to the ventilation duct also significantly improved the temperature and humidity inside the tunnel.

[0133] Example 3: Numerical Simulation of Mechanical Refrigeration Effect

[0134] 3D model such as Figure 8As shown, the model is 520m long, 50m wide, and 40m high, representing the surrounding rock area. The tunnel excavation length is 500m, and the ventilation duct is 20m from the working face. Field surveys revealed that axial flow fans were installed at distances of 220m and 375m from the working face. The mechanical cooling interface is located at 250m from the working face, lagging behind the secondary lining structure by approximately 100m. Field monitoring showed that the tunnel rock temperature was 65℃, and the air temperature in the main ventilation duct reached 30℃. After the distribution of fresh airflow across multiple working faces, the air velocity in the working face ventilation ducts was only 18m³ / s. The output airflow of the high-efficiency intelligent cooling equipment was 20m³ / s when its power was at 70%.

[0135] The temperature, air volume, and air temperature collected on-site were used as boundary conditions for the numerical simulation. The distribution and magnitude of the ambient temperature within the tunnel were then compared to verify the accuracy of the numerical simulation in predicting actual working conditions. Since the on-site monitoring data showed the cooling equipment not being turned on, a comparison was needed between the on-site monitoring and the operating condition of the high-efficiency intelligent cooling equipment with the equipment turned on before conducting parameter optimization research. Specifically, the input air volume of the high-efficiency intelligent cooling equipment was adjusted to 0 m³ / s. The comparison results are as follows: Figure 9 As shown, the numerical simulation results are basically consistent with the field measurement results, proving that the selection of numerical model parameters is reasonable, and the mechanical refrigeration cooling effect can be further studied.

[0136] Figure 10 The study demonstrates the environmental temperature variation patterns near the tunnel face with and without efficient intelligent cooling. It shows that the temperature at the excavation face decreased from 38.6℃ to 29.5℃, a reduction of 9.1℃. Within a 200m radius of the tunnel excavation face, the average temperature decreased by 8.9℃, demonstrating a significant cooling effect. The overall tunnel ambient temperature decreased by an average of 7.0℃, an average reduction of 18.4%. Numerical simulations indicate that the efficient intelligent cooling equipment played a significant role in cooling the tunnel, particularly at the fan outlet (near the tunnel face), where the temperature dropped significantly.

[0137] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0138] The above examples illustrate the present invention only to aid in understanding it and are not intended to limit the scope of the invention. Those skilled in the art can make various simple deductions, modifications, or substitutions based on the principles of this invention.

Claims

1. A smart cooling method for high-temperature tunnels, characterized in that, The method is implemented based on a high-temperature tunnel intelligent cooling device, which includes a skid-mounted refrigeration module, an intelligent control system (3), and a dual-mode refrigeration terminal (4). The skid-mounted refrigeration module includes an integrated skid-mounted unit (1) and a circulating water tank (2); The circulating water tank (2) is equipped with a temperature sensor (2-1) and a water level monitor (2-2) to monitor the temperature and water level of the circulating water in real time and transmit the monitoring data to the intelligent control system (3). The intelligent control system (3) includes: The variable frequency control module (3-1) is used to dynamically adjust the power of the chiller unit and the circulating water flow rate; The cloud communication module (3-2) is used for remote data transmission and device cluster management; The fault diagnosis module (3-3) triggers a graded protection mechanism based on sensor data; The dual-mode cooling terminal (4) is connected to the integrated skid-mounted unit (1) via a pipeline, including an independent air-cooling device (4-1) and a ventilation duct interface (4-2), which can switch to independent air-cooling mode or work in conjunction with the construction ventilation system; The integrated skid-mounted unit (1) includes: Refrigeration unit: It consists of a semi-hermetic twin-screw compressor (1-1), a high-efficiency condenser (1-2), and an evaporator (1-3) connected in sequence through refrigerant pipelines. A circulating water pump (1-8) is provided between the high-efficiency condenser (1-2) and the circulating water tank (2). Expansion valve (1-4): installed on the refrigerant line between the condenser (1-2) and the evaporator (1-3); Heat dissipation unit: includes air cooler (1-5) and fan (1-6), air cooler (1-5) and evaporator (1-3) are connected by chilled water pump (1-7); Filter (1-9): Installed between condenser (1-2) and expansion valve (1-4); The overall dimensions are compatible with standard tunnel transport equipment; The ventilation duct interface (4-2) of the dual-mode cooling terminal (4) is equipped with an air volume-water temperature coupling controller (4-2a). The intelligent control system (3) is equipped with: a) Water temperature adaptive adjustment algorithm, which automatically adjusts the compressor frequency based on the real-time monitored temperature inside the cave; b) Automatic switching function between cooling and dehumidification modes; c) Over-temperature protection mechanism: the system will shut down when the return water temperature is greater than 50°C. The method includes the following steps: Step 1: System initialization, collecting temperature and humidity parameters inside the cave through the environmental sensing module (3-4); Step 2: The intelligent decision-making module (3-5) selects either independent cooling or combined ventilation and cooling mode based on the parameters; Step 3: Dynamically adjust the compressor power and circulating water flow rate to maintain the outlet water temperature within the set range; Step 4: Remotely set parameters and monitor operational status through a cloud-based monitoring platform; Step 5: When an abnormal water temperature or equipment malfunction is detected, the protection program will be automatically executed and an alarm message will be sent. in: Step three includes: The variable frequency control module monitors the water temperature and level in the circulating water tank and the operating parameters of each device in the system in real time. Based on the preset temperature range and equipment performance curve, the operating frequency of each device in the integrated skid-mounted unit is automatically adjusted; Closed-loop feedback control ensures that the outlet water temperature remains stable within the set range; Step two includes: Real-time monitoring of temperature and humidity parameters inside the cave; The preset cooling / dehumidification mode switching threshold will prioritize the cooling mode when the air temperature is higher than the set temperature threshold and the relative humidity is lower than the humidity threshold. When the air temperature is within a certain range and the relative humidity is higher than the humidity threshold, switch to dehumidification mode or ventilation combined with cooling mode. Step five includes: The temperature sensor in the circulating water tank continuously monitors the return water temperature in real time; When the return water temperature exceeds the set shutdown threshold, the intelligent control system immediately triggers the system shutdown protection mechanism; At the same time, the system sends alarm information through the cloud monitoring platform or local alarm device to notify maintenance personnel to handle it in a timely manner; Step three includes adaptive water temperature adjustment, and the steps to implement adaptive water temperature adjustment are as follows: Data Acquisition and Preprocessing: A data acquisition module is set up in the intelligent control system. It is connected to the water temperature sensor and the ambient temperature and humidity sensor through the communication interface. The water temperature, ambient temperature and humidity data are collected at certain time intervals. The collected data is preprocessed by filtering and calibration to remove noise and outliers, thereby improving the accuracy and reliability of the data. Parameter initialization: Based on the actual conditions of the tunnel and the design requirements of the refrigeration system, set the initial parameters of the target water temperature range, the upper and lower limits of the compressor frequency, and the frequency adjustment step size, and store these parameters in the memory of the intelligent control system. Model training and optimization: During the system installation and debugging phase and subsequent operation, historical data on the water temperature regulation process are continuously collected. This data is used to train and optimize the water temperature regulation model. Machine learning algorithms are used to continuously adjust the model's parameters to improve the model's prediction accuracy and adaptability. Real-time adjustment and feedback control: During system operation, the intelligent control system collects water temperature data at set time intervals and inputs it into the water temperature adjustment model. Based on the output of the model, the operating frequency of the compressor is adjusted in real time through the frequency conversion adjustment module. At the same time, the changes in water temperature are continuously monitored. If the adjusted water temperature still does not reach the target range or an abnormality occurs, the compressor frequency is recalculated and adjusted in time to form a closed-loop feedback control to ensure that the water temperature is stable within the set range.

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