Novel high-ground-temperature tunnel local ventilation cooling system

Abstract

The invention discloses a novel high-ground-temperature tunnel local ventilation cooling system, and relates to the technical field of high-ground-temperature tunnel ventilation, and the novel high-ground-temperature tunnel local ventilation cooling system comprises a temperature monitoring module, a cold air conveying starting module, a cold air output adjusting module, a regional cold air distribution module, an energy efficiency optimization module and a real-time monitoring and emergency response module; and the temperature monitoring module is used for arranging a temperature sensor network in the tunnel. The tunnel temperature is monitored in real time through the temperature sensor network and the model, cold air output is dynamically adjusted, and accurate cooling is ensured. The vortex tube array directly produces cold air by introducing high-pressure air, the cold air is conveyed to a cooling area through an air pipe, and exhausted hot air is subjected to energy recovery through a phase change heat absorption material or a hot air power generation system. The intelligent algorithm predicts the temperature trend, adjusts cold air in advance, and prevents potential safety hazards. And the real-time monitoring platform tracks the temperature and the equipment state, automatically alarms and executes emergency measures to ensure that the system operates in a safe range.

Description

Technical Field

[0001] The invention relates to the technical field of high geothermal tunnel ventilation, and in particular to a novel high geothermal tunnel local ventilation and cooling system. Background Art

[0002] High-temperature tunnel ventilation and cooling refers to the process of using effective ventilation and cooling technologies to reduce the temperature of the working surface during the excavation of high-temperature underground spaces, such as tunnels, coal mines, and deep underground urban spaces, in order to ensure the safety and comfort of the working environment.

[0003] In the existing high-temperature tunnel ventilation technology, cooling is mainly achieved by transporting low-temperature airflow from the outside to the working face. However, when the tunnel is long or the underground space is large, this technology has some limitations. Since the air is gradually heated in the air duct during the process of being transported to the working face, the temperature has risen to a high level when it reaches the working face, and it cannot be effectively cooled. This requires compensation by strengthening ventilation or increasing the power of the fan, but this will bring a lot of energy consumption and low conversion efficiency of cold. In addition, this ventilation and cooling method is greatly affected by the external ambient temperature. If the outside temperature is high, the effect will be even more unsatisfactory. Therefore, in a high-temperature environment, how to design and implement a more efficient ventilation and cooling system is an urgent problem to be solved.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The purpose of the present invention is to provide a new type of local ventilation and cooling system for high-temperature tunnels. By arranging a temperature sensor network and establishing a temperature model, real-time monitoring of the temperature distribution in the tunnel and rapid response to abnormal areas can be achieved. The system dynamically adjusts the output and distribution of cold air according to temperature changes to avoid excessive or insufficient cold air supply. The vortex tube array directly produces cold air by introducing high-pressure air, and transports it to the cooling area through air ducts. The exhausted hot air is recovered through phase change endothermic materials or hot air power generation systems. Intelligent algorithms analyze temperature change patterns, predict future temperature trends, adjust cold air output in advance, and avoid safety hazards. The real-time monitoring platform continuously tracks temperature and equipment status, automatically alarms and performs emergency processing to ensure that the tunnel temperature remains within a safe range, improves the reliability and safety of the system, and solves the problems in the above-mentioned background technology.

[0006] In order to achieve the above-mentioned object, the present invention provides the following technical solutions: a novel local ventilation and cooling system for high ground temperature tunnels, comprising a temperature monitoring module, a cold air delivery start module, a cold air output adjustment module, a regional cold air distribution module, an energy efficiency optimization module, and a real-time monitoring and emergency response module;

[0007] Temperature monitoring module: a temperature sensor network is arranged inside the tunnel to monitor the temperature distribution inside the tunnel in real time. The temperature data collected by the temperature sensor is transmitted to the central control system through the data acquisition system. The temperature data is used to establish a temperature model inside the tunnel and identify abnormal temperature areas.

[0008] The cold air delivery start module starts the cold air delivery mechanism of the vortex tube array based on the preliminary temperature monitoring data. The vortex tube array uses compressed air to generate two airflows of cold air and hot air, and delivers the cold air part to the inside of the tunnel through the pipeline;

[0009] Cold air output adjustment module: when the temperature inside the tunnel changes, the central control system analyzes the current temperature inside the tunnel based on real-time temperature data, dynamically adjusts the output of cold air, and achieves timely temperature response;

[0010] The regional cold air distribution module further subdivides each area in the tunnel during the cold air delivery process, accurately controls the distribution of cold air by adjusting valves and distributors, determines the specific needs of each area based on temperature monitoring data, and accurately controls the distribution amount of cold air to different areas;

[0011] Energy efficiency optimization module: To further optimize energy efficiency, the system uses intelligent algorithms to analyze the temperature change patterns of the tunnel and predict future temperature trends, thereby adjusting the cold air output of the vortex tube array in advance.

[0012] The real-time monitoring and emergency response module continuously tracks the temperature conditions in the tunnel and the working status of the vortex tube array through the real-time monitoring platform. Once an abnormal situation is detected, it automatically issues an alarm and executes emergency treatment measures.

[0013] Preferably, the temperature data is used to establish a temperature model inside the tunnel to identify abnormal temperature areas. The specific steps are as follows:

[0014] A temperature sensor network is arranged in the tunnel, and the temperature sensors collect temperature data at various locations in the tunnel in real time;

[0015] The temperature gradient at each sensor position is calculated through the processed temperature data to reflect the temperature change in space. At the same time, the temperature change rate is calculated to identify the dynamic characteristics of temperature change. The calculation expression of the temperature gradient is: Where, T i(t) is the temperature reading of the ith sensor at time t, T i ′(t) is the processed temperature reading of the ith sensor at time t, is the temperature gradient at the i-th sensor position, reflecting the rate of temperature change in space, R i (t) is the temperature change rate at the i-th sensor position, indicating the change of temperature over time, d i is the distance between adjacent sensors;

[0016] Based on the temperature gradient and temperature change rate, the temperature anomaly factor of each sensor location is calculated to identify the temperature anomaly area. The temperature anomaly factor is a combined function of the temperature gradient and the change rate, reflecting the comprehensive characteristics of temperature changes in space and time. The calculation expression is: F i (t) is the temperature anomaly factor at the i-th sensor position, α and β are adjustment parameters used to balance the influence of temperature gradient and change rate; S i (t) is the weight factor;

[0017] According to the calculated temperature anomaly factor, the temperature anomaly area inside the tunnel is identified, and a threshold is set to distinguish between normal and abnormal areas. A model of the temperature anomaly area is constructed to describe the spatial distribution and variation characteristics of the temperature anomaly, providing support for subsequent ventilation and cooling strategies. The expression for constructing the temperature anomaly area model is: A(t) = {i|F i (t)>F th}, where A(t) represents the set of temperature anomaly areas identified at time t, including all sensor locations where the temperature anomaly factor exceeds the threshold, and F th is the threshold of the temperature anomaly factor.

[0018] Preferably, the output flow rate and temperature of the cold air of the vortex tube array can be preliminarily controlled by adjusting the flow rate and pressure of the compressed air to ensure that the basic cooling requirements are achieved in the initial state.

[0019] Preferably, when the temperature inside the tunnel changes, the central control system analyzes the current temperature inside the tunnel according to the real-time temperature data, dynamically adjusts the output of cold air, and realizes timely temperature response. The specific steps are as follows:

[0020] The temperature change rate of each area is calculated based on the temperature data to determine the area that needs to be cooled first. The temperature change rate can be used to evaluate the rapid change of temperature in the area. The calculation expression is: R i (t) is the temperature change rate of sensor i at time t, and Δt represents the time interval;

[0021] Based on the temperature change rate of each zone, the amount of cold air that needs to be delivered is calculated to ensure a quick response to temperature changes. The calculation expression is: In the formula, Q air (t) represents the output of cold air at time t, κ represents the cold air transmission efficiency coefficient, V x represents the volume of region x, represents the temperature response coefficient, reflecting the sensitivity of temperature to the demand for cold air;

[0022] According to the demand for cold air and the temperature distribution in each area of ​​the tunnel, the output path of cold air is optimized to reduce energy consumption and improve cooling efficiency. At the same time, through the feedback control mechanism, the temperature changes are continuously monitored and the output of cold air is dynamically adjusted. The specific expression is: Where P opt is the optimal cold air output path, L x，P is the transport distance from path P to area x, E x is the energy transmission efficiency of region x, μ is the feedback adjustment coefficient, is the actual cooling air output.

[0023] Preferably, each area in the tunnel is further subdivided, and the distribution of cold air is accurately controlled by adjusting valves and distributors. According to the temperature monitoring data, the specific needs of each area are determined, and the distribution amount of cold air to different areas is accurately controlled. The specific steps are as follows:

[0024] Divide the tunnel into several independent zones according to its length, shape, purpose and internal temperature distribution;

[0025] Based on real-time temperature data, the central control system analyzes the cooling needs of each area, assesses the degree of deviation of each area's temperature from the set safety and comfort range, and the speed and trend of temperature change, to determine the amount of cold air required for each area;

[0026] After the cold air distribution strategy is formulated, the central control system sends instructions to the regulating valves and distributors in each area. The regulating valves and distributors adjust the cold air flow and direction to achieve accurate cold air distribution in each area.

[0027] Once the cold air distribution is completed, the tunnel ventilation system does not stop monitoring, but continues to monitor the temperature changes in each area in real time. Based on the data continuously fed back by the temperature sensor, the central control system promptly identifies temperature anomalies or demand changes in any area.

[0028] Preferably, if the temperature in one area changes suddenly or the cooling demand in other areas changes, the tunnel ventilation system responds immediately and dynamically adjusts the settings of the regulating valves and distributors to redistribute the cold air.

[0029] Preferably, an intelligent algorithm is used to analyze the law of tunnel temperature changes, predict future temperature trends, and adjust the cold air output of the vortex tube array in advance. The specific steps are as follows:

[0030] Intelligent algorithms are used to extract features and recognize patterns from temperature data. Feature extraction refers to extracting key numerical indicators and statistical characteristics from raw data, while pattern recognition refers to identifying the laws and trends of temperature changes in tunnels by analyzing these features.

[0031] Based on the extracted features and identified patterns, temperature trend prediction is performed using machine learning or deep learning algorithms. The prediction model is trained with historical data to learn the complex relationship of temperature changes and the influence of potential factors, and predict the temperature change trend of each area of ​​the tunnel in the future time period;

[0032] According to the results of temperature trend prediction, the cold air output of the vortex tube array is adjusted in advance. By adjusting the working parameters of the vortex tube array, the appropriate cold air output is pre-set to cope with the upcoming temperature changes;

[0033] In the process of implementing prediction and adjustment, the deviation between the actual temperature change and the predicted results is continuously monitored. Through real-time monitoring and data feedback, the accuracy of the prediction model is evaluated, and dynamic adjustments and optimizations are made according to actual conditions.

[0034] Preferably, if it is found that the prediction is inconsistent with the actual situation, the model parameters are automatically updated or a more appropriate algorithm is selected for prediction. Through continuous optimization and feedback adjustment mechanism, it is ensured that the best energy efficiency performance is always maintained in different environments and working conditions.

[0035] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0036] The present invention arranges a temperature sensor network and establishes a temperature model, so that the system can monitor the temperature distribution in the tunnel in real time, identify abnormal temperature areas, and respond quickly to temperature changes. Through this precise monitoring and dynamic adjustment mechanism, the output and distribution of cold air can be adjusted according to actual needs, avoiding excessive or insufficient cold air supply. The vortex tube array directly produces cold air by introducing high-pressure air, and transports it to the cooling area through the air duct. The exhausted hot air is recovered by phase change heat absorption material or hot air power generation system. In addition, the system further subdivides each area in the tunnel, and accurately controls the distribution of cold air by adjusting valves and distributors to ensure that each area can obtain the appropriate cold air flow according to its temperature requirements. This optimized cold air management significantly reduces energy consumption, improves overall energy efficiency, and reduces operating costs, especially in long-term and high-intensity tunnel construction.

[0037] The present invention greatly improves the reliability and safety of the system through intelligent algorithms and real-time monitoring platforms. The intelligent algorithm can analyze the law of temperature changes in the tunnel and predict future temperature trends, thereby adjusting the cold air output in advance to avoid safety hazards caused by sudden temperature changes. The real-time monitoring platform continuously tracks the temperature conditions in the tunnel and the working status of the vortex tube array. Once an abnormal temperature or equipment failure is detected, the system will automatically issue an alarm and execute emergency measures, such as adjusting the cold air output or starting backup equipment. Such real-time monitoring and rapid response capabilities ensure that the system can maintain the temperature in the tunnel within a safe and comfortable range under various working conditions, effectively preventing safety accidents such as heat stroke of workers and overheating of equipment caused by high temperatures. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0039] Figure 1 This is a module schematic diagram of a new type of local ventilation and cooling system for high ground temperature tunnels according to the present invention.

[0040] Figure 2 It is a schematic diagram of an example of local cooling of the tunnel excavation face according to the present invention.

[0041] Figure 3 It is a schematic diagram of the vortex tube refrigeration principle of the present invention. DETAILED DESCRIPTION

[0042] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0043] The present invention provides Figures 1 to 3 A new type of local ventilation and cooling system for high ground temperature tunnels shown in the figure includes a temperature monitoring module, a cold air delivery start module, a cold air output adjustment module, a regional cold air distribution module, an energy efficiency optimization module, and a real-time monitoring and emergency response module;

[0044] Temperature monitoring module: a temperature sensor network is arranged inside the tunnel to monitor the temperature distribution in the tunnel in real time. The temperature data collected by the temperature sensor is transmitted to the central control system through the data acquisition system. The temperature data is used to establish a temperature model inside the tunnel to identify abnormal temperature areas (higher temperature);

[0045] Accurate temperature data collection is the basis for dynamically adjusting the cold air output, which can ensure the real-time performance and response speed of the system.

[0046] Use temperature data to build a temperature model inside the tunnel and identify temperature anomaly areas. The specific steps are as follows:

[0047] A temperature sensor network is arranged in the tunnel, and the temperature sensors collect temperature data at various locations in the tunnel in real time;

[0048] These data are transmitted to the central control system through the data acquisition system. In order to ensure the accuracy and effectiveness of the data, the temperature data is first preprocessed, including noise removal, elimination of outliers and data smoothing.

[0049] The temperature gradient at each sensor position is calculated through the processed temperature data to reflect the temperature change in space. At the same time, the temperature change rate is calculated to identify the dynamic characteristics of temperature change. The calculation expression of the temperature gradient is: Where, T i (t) is the temperature reading of the ith sensor at time t, T i ′(t) is the processed temperature reading of the ith sensor at time t, is the temperature gradient at the i-th sensor position, reflecting the rate of temperature change in space, R i (t) is the temperature change rate at the i-th sensor position, indicating the change of temperature over time, d i is the distance between adjacent sensors;

[0050] Based on the temperature gradient and temperature change rate, the temperature anomaly factor of each sensor location is calculated to identify the temperature anomaly area. The temperature anomaly factor is a combined function of the temperature gradient and the change rate, reflecting the comprehensive characteristics of temperature changes in space and time. The calculation expression is: F i (t) is the temperature anomaly factor at the i-th sensor location, which measures the degree of temperature anomaly at that location. α and β are adjustment parameters used to balance the influence of temperature gradient and change rate; S i (t) is a weighting factor that takes into account the particularities of the sensor location, such as the terrain or wind flow effects in the tunnel;

[0051] According to the calculated temperature anomaly factor, the temperature anomaly area inside the tunnel is identified, a threshold is set to distinguish between normal and abnormal areas, and a model of the temperature anomaly area is constructed. This model is used to describe the spatial distribution and variation characteristics of temperature anomalies, and to provide support for subsequent ventilation and cooling strategies. The expression for constructing the temperature anomaly area model is: A(t) = {i|Fi (t)>F th}, where A(t) represents the set of temperature anomaly areas identified at time t, including all sensor locations where the temperature anomaly factor exceeds the threshold, and F th is the threshold of the temperature anomaly factor. If this value is exceeded, the area is considered to be a temperature anomaly area.

[0052] The cold air delivery start module starts the cold air delivery mechanism of the vortex tube array based on the preliminary temperature monitoring data. The vortex tube array uses compressed air to generate two airflows of cold air and hot air, and delivers the cold air part to the inside of the tunnel through a dedicated pipeline;

[0053] The advantage of the vortex tube array is that it does not require the use of complex refrigerants and compressor systems, is small in size, easy to install, and can work stably in high temperature environments. The output flow rate and temperature of the cold air of the vortex tube array can be initially controlled by adjusting the flow rate and pressure of the compressed air to ensure that the basic cooling requirements are achieved in the initial state.

[0054] Cold air output adjustment module: when the temperature inside the tunnel changes, the central control system analyzes the current temperature inside the tunnel based on real-time temperature data, dynamically adjusts the output of cold air, and achieves timely temperature response;

[0055] When the temperature sensor detects that the temperature in a certain area rises, the system will increase the supply of cold air to that area; conversely, when the temperature drops, the system will reduce the output of cold air. This dynamic adjustment mechanism can quickly respond to temperature changes, avoid energy waste, and ensure that the temperature of the work surface is always within a safe and comfortable range.

[0056] When the temperature inside the tunnel changes, the central control system analyzes the current temperature inside the tunnel based on real-time temperature data, dynamically adjusts the output of cold air, and achieves timely temperature response. The specific steps are as follows:

[0057] The temperature change rate of each area is calculated based on the temperature data to determine the area that needs to be cooled first. The temperature change rate can be used to evaluate the rapid change of temperature in the area. The calculation expression is: R i (t) is the temperature change rate of sensor i at time t, and Δt represents the time interval;

[0058] By calculating the rate of temperature change of each sensor, the system can determine which areas are rising in temperature the fastest and prioritize the delivery of cool air to these areas.

[0059] Based on the temperature change rate of each area, the amount of cold air that needs to be delivered is calculated. The amount of cold air is related to the temperature change rate, the area volume and the current temperature to ensure a quick response to temperature changes. The calculation expression is: In the formula, Q air (t) represents the output of cold air at time t, κ represents the cold air transmission efficiency coefficient, V x represents the volume of region x, represents the temperature response coefficient, reflecting the sensitivity of temperature to the demand for cold air;

[0060] The cold air delivery efficiency coefficient is a parameter that describes the cooling effect of cold air from the source (such as a vortex tube array) to each target area in the tunnel. This coefficient reflects the energy loss of cold air during the delivery process, including factors such as air friction, pipe heat transfer loss, and airflow diffusion. A higher delivery efficiency coefficient means that the cold air maintains a higher cooling capacity during the delivery process and can more effectively reduce the temperature of the target area. On the contrary, if the delivery efficiency coefficient is low, it means that the cold air has lost a lot of cooling effect before reaching the destination, and it may be necessary to increase the air flow or adjust the delivery path to ensure sufficient cooling effect. Therefore, the determination of the cold air delivery efficiency coefficient usually needs to consider the design of the cold air delivery system, material selection, pipeline length, and actual environmental conditions inside the tunnel.

[0061] The volume of zone x refers to the three-dimensional size of a specific area inside the tunnel. This volume is a key physical parameter that determines the amount of cold air required in the zone, as a larger volume requires more cold air to achieve the same temperature reduction. The volumes of different zones in the tunnel may be different, depending on factors such as the shape, size, and distribution of the tunnel. During the cold air distribution process, the system needs to calculate the appropriate cold air flow rate based on the volume of each zone to ensure effective temperature control. For example, a smaller zone may require less cold air flow, while a larger zone may require more cold air to achieve the same cooling effect. Therefore, the zone volume is a key factor affecting the cold air distribution and temperature regulation strategy.

[0062] According to the demand for cold air and the temperature distribution in each area of ​​the tunnel, the output path of cold air is optimized to reduce energy consumption and improve cooling efficiency. At the same time, through the feedback control mechanism, the temperature changes are continuously monitored and the output of cold air is dynamically adjusted. The specific expression is: Where P opt is the optimal cold air output path, L x，P is the transport distance from path P to area x, E x is the energy transmission efficiency of region x, μ is the feedback adjustment coefficient, is the actual cold air output;

[0063] By minimizing energy consumption and output errors, the system is able to achieve efficient cold air delivery and temperature control, ensuring that the temperature in the tunnel is always maintained within a safe and comfortable range.

[0064] The regional cold air distribution module further subdivides each area in the tunnel during the cold air delivery process, accurately controls the distribution of cold air by adjusting valves and distributors, determines the specific needs of each area based on temperature monitoring data, and accurately controls the distribution amount of cold air to different areas;

[0065] This not only improves the utilization efficiency of cold air, but also provides targeted cooling services when the temperature in each area changes, reducing unnecessary cold air consumption.

[0066] Further subdivide each area in the tunnel, accurately control the distribution of cold air by adjusting valves and distributors, determine the specific needs of each area based on temperature monitoring data, and accurately control the distribution amount of cold air to different areas. The specific steps are as follows:

[0067] Divide the tunnel into several independent zones according to its length, shape, purpose and internal temperature distribution;

[0068] The division of these zones is usually based on the distribution of temperature sensors and the working environment requirements in the tunnel. Each zone represents an area that requires separate temperature control, which may have different temperatures due to different geological conditions, construction activities or equipment layout. The purpose of zone division is to achieve more accurate cold air distribution and ensure that each area can obtain the required amount of cold air according to actual needs.

[0069] Based on real-time temperature data, the central control system analyzes the cooling needs of each area. The system evaluates the degree of deviation of the temperature of each area from the set safety and comfort range, as well as the speed and trend of temperature change, to determine the cold air demand of each area.

[0070] High-temperature areas or areas where the temperature rises quickly are given priority, and the system calculates the amount of cold air required based on demand and develops a distribution strategy. This distribution strategy aims to ensure that the temperature of all areas is within a safe and comfortable range with the lowest energy consumption, thereby optimizing the overall environment of the tunnel.

[0071] After the cold air distribution strategy is formulated, the central control system sends instructions to the regulating valves and distributors in each area. The regulating valves and distributors adjust the cold air flow and direction to achieve accurate cold air distribution in each area.

[0072] Each regulating valve and distributor can be operated independently to ensure that cold air can enter each area according to the set strategy. Through this precise control, the system can flexibly adjust the flow and path of cold air according to the specific needs of each area, thereby ensuring that each area is properly supplied with cold air and achieves the best cooling effect.

[0073] Once the cold air distribution is completed, the system does not stop monitoring, but continues to monitor the temperature changes in each area in real time. Through the continuous feedback data from the temperature sensor, the central control system can promptly identify temperature anomalies or demand changes in any area;

[0074] If the temperature in one area changes suddenly or the cooling demand in other areas changes, the system will respond immediately and dynamically adjust the settings of the regulating valves and distributors to redistribute the cold air;

[0075] This dynamic adjustment mechanism ensures that the system can respond quickly to any changes, maintaining a stable and comfortable temperature inside the tunnel while maximizing energy savings and optimizing resource use.

[0076] Energy efficiency optimization module: To further optimize energy efficiency, the system uses intelligent algorithms to analyze the temperature change patterns of the tunnel and predict future temperature trends, thereby adjusting the cold air output of the vortex tube array in advance.

[0077] This predictive adjustment can reduce the system's reaction delay and avoid over-adjustment when the temperature changes suddenly. In addition, by optimizing the use of compressed air, the system can reduce energy consumption, reduce equipment wear, extend the service life of the vortex tube array, and improve the overall energy efficiency of the system.

[0078] Intelligent algorithms are used to analyze the temperature change patterns in the tunnel, predict future temperature trends, and adjust the cold air output of the vortex tube array in advance. The specific steps are as follows:

[0079] Intelligent algorithms are used to extract features and recognize patterns from temperature data. Feature extraction refers to extracting key numerical indicators and statistical characteristics from raw data, such as temperature change amplitude, change rate, and periodic fluctuations. Pattern recognition refers to identifying the laws and trends of temperature changes in tunnels by analyzing these features.

[0080] The system can identify potential factors that affect temperature, such as day-night temperature difference, seasonal changes, and the impact of construction activities. By deeply mining data features and identifying patterns, the system can better understand the temperature variation patterns in the tunnel and provide support for future trend predictions.

[0081] Based on the extracted features and identified patterns, temperature trend prediction is performed using machine learning or deep learning algorithms. The prediction model is trained with historical data to learn the complex relationship of temperature changes and the influence of potential factors, and can predict the temperature change trend of each area of ​​the tunnel in a specific time period in the future;

[0082] The forecast not only takes into account current temperature data, but also combines multiple factors such as time series models, environmental variables and construction plans to improve the accuracy and reliability of the forecast. Predicting future temperature trends in advance allows the system to foresee possible temperature fluctuations and prepare for cold air output.

[0083] According to the results of temperature trend prediction, the cold air output of the vortex tube array is adjusted in advance. By adjusting the working parameters of the vortex tube array, such as the flow rate and pressure of the compressed air, the appropriate cold air output can be set in advance to cope with the upcoming temperature changes;

[0084] This advance adjustment strategy avoids the delay of adjustment after a sudden temperature change, ensuring the timeliness and accuracy of cold air delivery. Adjusting the cold air output in advance can not only improve the temperature control efficiency, but also reduce unnecessary energy consumption and resource waste, and optimize the overall environment in the tunnel.

[0085] In the process of implementing prediction and adjustment, the deviation between actual temperature change and predicted results is continuously monitored. Through real-time monitoring and data feedback, the accuracy of the prediction model is evaluated, and dynamic adjustments and optimizations are made according to actual conditions.

[0086] If the prediction is found to be inconsistent with the actual situation, the system will automatically update the model parameters or select a more appropriate algorithm for prediction. The continuous optimization and feedback adjustment mechanism ensures that the system always maintains the best energy efficiency performance in different environments and working conditions, and provides stable and efficient temperature control services.

[0087] The real-time monitoring and emergency response module continuously tracks the temperature in the tunnel and the working status of the vortex tube array through the real-time monitoring platform. Once an abnormal situation is detected, it automatically issues an alarm and executes emergency treatment measures;

[0088] Through a real-time monitoring platform, the temperature changes in various areas inside the tunnel and the working status of the vortex tube array are continuously tracked, including the output of cold air, the pressure of compressed air, the operating efficiency of the vortex tube array, etc. The monitoring platform is equipped with a variety of sensors and data acquisition equipment, which can timely collect and analyze the environmental data and equipment operation data in the tunnel. When the system detects that the temperature exceeds the preset safety range, or the vortex tube array is in an abnormal working state (such as failure, abnormal reduction in output, unstable compressed air pressure, etc.), the system will automatically issue an alarm to notify the management personnel and immediately start the preset emergency treatment measures. These measures may include adjusting the output of cold air, switching to backup equipment, repairing the faulty vortex tube array or increasing ventilation, etc., to quickly restore the temperature balance in the tunnel and ensure the safety of workers and equipment. Through this intelligent monitoring and emergency response mechanism, the system can identify and deal with potential risks in the first time, effectively prevent safety accidents caused by equipment failure or temperature abnormalities, and improve the overall safety and operating efficiency of tunnel construction. The operation of the real-time monitoring platform ensures that the system can dynamically adjust and maintain the best working state in the complex and changing tunnel environment, ensuring that the working environment of construction personnel is always safe and comfortable.

[0089] At the same time, regular maintenance management plans, including inspection and maintenance of temperature sensors, vortex tube arrays and their piping systems, ensure the long-term stable operation of the entire ventilation system, reduce the occurrence of failures, and improve the reliability and safety of the system.

[0090] The new ventilation system uses efficient vortex tube cold air cooling technology to effectively cool down high-temperature tunnels or other underground spaces. Its working principles include the following aspects:

[0091] First of all, the new ventilation system adds a vortex tube array and compressed air supply system on the basis of traditional fans and air ducts. The fan transports the low-temperature outdoor air to the tunnel excavation surface through the air duct, and the compressed air machine provides compressed air to the vortex tube array. The vortex tube uses the vortex effect of compressed air to generate a low-temperature cold air flow, which is introduced into the tunnel to effectively reduce the temperature of the working surface. The output of the vortex tube cold air is adjusted according to the on-site temperature requirements to ensure that the temperature drops to the set range, usually as low as -40°C. At the outlet of the vortex tube, it is also equipped with a heat recovery system and an energy recovery device to achieve energy saving and efficiency improvement through hot gas discharge and energy conversion.

[0092] The vortex tube array can be placed anywhere in the tunnel. The high-pressure air generated by the air compressor is input into the vortex array to produce high-temperature air and low-temperature air (even minus 10 degrees). The low-temperature air is transported to the cooling area through the air duct, and the high-temperature air is used for energy recovery. The vortex tube uses the vortex tube array to achieve ventilation and cooling, and recovers heat energy through phase change energy storage materials, which significantly improves the overall energy efficiency of the system.

[0093] Secondly, the system is equipped with a multi-point temperature monitoring system in the tunnel to detect temperature changes in the tunnel in real time. Based on these data, the central control system automatically adjusts the cold air output and temperature of the vortex tube to ensure that the temperature of each area remains within the set range, ensuring a safe and comfortable working environment. The system design allows for flexible response to different cooling needs by increasing or decreasing the number of vortex tubes or adjusting the compressed air flow, and is suitable for various underground construction scenarios.

[0094] In general, the new ventilation system provides an efficient, flexible and energy-saving high-temperature tunnel cooling solution by combining vortex tube cold air technology with traditional ventilation methods. It can effectively cope with the high temperature challenges in tunnels and underground spaces and improve the safety and comfort of the construction environment.

[0095] The present invention arranges a temperature sensor network and establishes a temperature model, so that the system can monitor the temperature distribution in the tunnel in real time, identify abnormal temperature areas, and respond quickly to temperature changes. Through this precise monitoring and dynamic adjustment mechanism, the output and distribution of cold air can be adjusted according to actual needs, avoiding excessive or insufficient cold air supply. The use of vortex tube arrays makes cold air delivery more efficient, because cold air can be directly delivered to areas that need cooling through dedicated pipelines, reducing the transmission loss of cold air. In addition, the system further subdivides each area in the tunnel, and accurately controls the distribution of cold air by adjusting valves and distributors to ensure that each area can obtain the appropriate cold air flow according to its temperature requirements. This optimized cold air management significantly reduces energy consumption, improves overall energy efficiency, and reduces operating costs, especially in long-term and high-intensity tunnel construction.

[0096] The present invention greatly improves the reliability and safety of the system through intelligent algorithms and real-time monitoring platforms. The intelligent algorithm can analyze the law of temperature changes in the tunnel and predict future temperature trends, thereby adjusting the cold air output in advance to avoid safety hazards caused by sudden temperature changes. The real-time monitoring platform continuously tracks the temperature conditions in the tunnel and the working status of the vortex tube array. Once an abnormal temperature or equipment failure is detected, the system will automatically issue an alarm and execute emergency measures, such as adjusting the cold air output or starting backup equipment. Such real-time monitoring and rapid response capabilities ensure that the system can maintain the temperature in the tunnel within a safe and comfortable range under various working conditions, effectively preventing safety accidents such as heat stroke of workers and overheating of equipment caused by high temperatures.

[0097] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0098] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0099] It should be noted that, in this article, if there are relational terms such as first and second, etc., they are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or still includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including a..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0100] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0101] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0102] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0103] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0104] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0105] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0106] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0107] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A new type of local ventilation and cooling system for high ground temperature tunnels, characterized in that: It includes temperature monitoring module, cold air delivery start module, cold air output adjustment module, regional cold air distribution module, energy efficiency optimization module and real-time monitoring and emergency response module; Temperature monitoring module: a temperature sensor network is arranged inside the tunnel to monitor the temperature distribution inside the tunnel in real time. The temperature data collected by the temperature sensor is transmitted to the central control system through the data acquisition system. The temperature data is used to establish a temperature model inside the tunnel and identify abnormal temperature areas. The cold air delivery start module starts the cold air delivery mechanism of the vortex tube array based on the preliminary temperature monitoring data. The vortex tube array uses compressed air to generate two airflows of cold air and hot air, and delivers the cold air part to the inside of the tunnel through the pipeline; Cold air output adjustment module: when the temperature inside the tunnel changes, the central control system analyzes the current temperature inside the tunnel based on real-time temperature data, dynamically adjusts the output of cold air, and achieves timely temperature response; The regional cold air distribution module further subdivides each area in the tunnel during the cold air delivery process, accurately controls the distribution of cold air by adjusting valves and distributors, determines the specific needs of each area based on temperature monitoring data, and accurately controls the distribution amount of cold air to different areas; Energy efficiency optimization module: the system uses intelligent algorithms to analyze the temperature change patterns of the tunnel and predict future temperature trends, thereby adjusting the cold air output of the vortex tube array in advance; The real-time monitoring and emergency response module continuously tracks the temperature conditions in the tunnel and the working status of the vortex tube array through the real-time monitoring platform. Once an abnormal situation is detected, it automatically issues an alarm and executes emergency treatment measures.

2. According to the novel high ground temperature tunnel local ventilation and cooling system of claim 1, it is characterized in that: Use temperature data to build a temperature model inside the tunnel and identify temperature anomaly areas. The specific steps are as follows: A temperature sensor network is arranged in the tunnel, and the temperature sensors collect temperature data at various locations in the tunnel in real time; The temperature gradient at each sensor position is calculated through the processed temperature data to reflect the temperature change in space. At the same time, the temperature change rate is calculated to identify the dynamic characteristics of temperature change. The calculation expression of the temperature gradient is: Where, T i (t) is the temperature reading of the ith sensor at time t, T i ′(t) is the processed temperature reading of the ith sensor at time t, is the temperature gradient at the i-th sensor position, reflecting the rate of temperature change in space, R i (t) is the temperature change rate at the i-th sensor position, indicating the change of temperature over time, d i is the distance between adjacent sensors; Based on the temperature gradient and temperature change rate, the temperature anomaly factor of each sensor location is calculated to identify the temperature anomaly area. The temperature anomaly factor is a combined function of the temperature gradient and the change rate, reflecting the comprehensive characteristics of temperature changes in space and time. The calculation expression is: F i (t) is the temperature anomaly factor at the i-th sensor position, α and β are adjustment parameters used to balance the influence of temperature gradient and change rate; S i (t) is the weight factor; According to the calculated temperature anomaly factor, the temperature anomaly area inside the tunnel is identified, and a threshold is set to distinguish between normal and abnormal areas. A model of the temperature anomaly area is constructed to describe the spatial distribution and variation characteristics of the temperature anomaly, providing support for subsequent ventilation and cooling strategies. The expression for constructing the temperature anomaly area model is: A(t) = {i|F i (t)>F th }, where A(t) represents the set of temperature anomaly areas identified at time t, including all sensor locations where the temperature anomaly factor exceeds the threshold, and F th is the threshold of the temperature anomaly factor.

3. According to the novel high ground temperature tunnel local ventilation and cooling system of claim 1, it is characterized in that: The output flow rate and temperature of the cold air from the vortex tube array can be initially controlled by adjusting the flow rate and pressure of the compressed air to ensure that the basic cooling requirements are achieved in the initial state.

4. According to claim 2, a new type of high ground temperature tunnel local ventilation and cooling system is characterized in that: When the temperature inside the tunnel changes, the central control system analyzes the current temperature inside the tunnel based on real-time temperature data, dynamically adjusts the output of cold air, and achieves timely temperature response. The specific steps are as follows: The temperature change rate of each area is calculated based on the temperature data to determine the area that needs to be cooled first. The temperature change rate can be used to evaluate the rapid change of temperature in the area. The calculation expression is: R i (t) is the temperature change rate of sensor i at time t, and Δt represents the time interval; Based on the temperature change rate of each zone, the amount of cold air that needs to be delivered is calculated to ensure a quick response to temperature changes. The calculation expression is: In the formula, Q air (t) represents the output of cold air at time t, κ represents the cold air transmission efficiency coefficient, V x represents the volume of region x, represents the temperature response coefficient, reflecting the sensitivity of temperature to the demand for cold air; According to the demand for cold air and the temperature distribution in each area of ​​the tunnel, the output path of cold air is optimized to reduce energy consumption and improve cooling efficiency. At the same time, through the feedback control mechanism, the temperature changes are continuously monitored and the output of cold air is dynamically adjusted. The specific expression is: Where P opt is the optimal cold air output path, L x，P is the transport distance from path P to area x, E x is the energy transmission efficiency of region x, μ is the feedback adjustment coefficient, is the actual cooling air output.

5. According to the novel high ground temperature tunnel local ventilation and cooling system of claim 1, it is characterized in that: Further subdivide each area in the tunnel, accurately control the distribution of cold air by adjusting valves and distributors, determine the specific needs of each area based on temperature monitoring data, and accurately control the distribution amount of cold air to different areas. The specific steps are as follows: Divide the tunnel into several independent zones according to its length, shape, purpose and internal temperature distribution; Based on real-time temperature data, the central control system analyzes the cooling needs of each area, assesses the degree of deviation of each area's temperature from the set safety and comfort range, and the speed and trend of temperature change, to determine the amount of cold air required for each area; After the cold air distribution strategy is formulated, the central control system sends instructions to the regulating valves and distributors in each area. The regulating valves and distributors adjust the cold air flow and direction to achieve accurate cold air distribution in each area. Once the cold air distribution is completed, the tunnel ventilation system does not stop monitoring, but continues to monitor the temperature changes in each area in real time. Based on the data continuously fed back by the temperature sensor, the central control system promptly identifies temperature anomalies or demand changes in any area.

6. A novel high ground temperature tunnel local ventilation and cooling system according to claim 5, characterized in that: If the temperature in one area changes suddenly or the cooling demand in other areas changes, the tunnel ventilation system responds immediately, dynamically adjusting the settings of the regulating valves and distributors to redistribute the cool air.

7. According to claim 1, a new type of high ground temperature tunnel local ventilation and cooling system is characterized in that: Intelligent algorithms are used to analyze the temperature change patterns in the tunnel, predict future temperature trends, and adjust the cold air output of the vortex tube array in advance. The specific steps are as follows: Intelligent algorithms are used to extract features and recognize patterns from temperature data. Feature extraction refers to extracting key numerical indicators and statistical characteristics from raw data, while pattern recognition refers to identifying the laws and trends of temperature changes in tunnels by analyzing these features. Based on the extracted features and identified patterns, temperature trend prediction is performed using machine learning or deep learning algorithms. The prediction model is trained with historical data to learn the complex relationship of temperature changes and the influence of potential factors, and predict the temperature change trend of each area of ​​the tunnel in the future time period; According to the results of temperature trend prediction, the cold air output of the vortex tube array is adjusted in advance. By adjusting the working parameters of the vortex tube array, the appropriate cold air output is pre-set to cope with the upcoming temperature changes; In the process of implementing prediction and adjustment, the deviation between the actual temperature change and the predicted results is continuously monitored. Through real-time monitoring and data feedback, the accuracy of the prediction model is evaluated, and dynamic adjustments and optimizations are made according to actual conditions.

8. The novel high ground temperature tunnel local ventilation and cooling system according to claim 7 is characterized in that: If it is found that the prediction is inconsistent with the actual situation, the model parameters will be automatically updated or a more appropriate algorithm will be selected for prediction. Through continuous optimization and feedback adjustment mechanism, the best energy efficiency performance is ensured at all times under different environments and working conditions.

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