Cooling system for firefighting robots

Abstract

To provide a cooling system for a firefighting robot that maximizes the efficiency of water spraying activities while ensuring continuous operation in high-temperature environments. [Solution] The robot comprises a water supply unit that receives water supplied from an external water source, a water flow distribution means that distributes the water supplied from the water supply unit for water spraying and cooling, a water discharge means that discharges the distributed water for water spraying toward the fire site, a cooling circulation circuit that circulates the distributed cooling water to heat-generating components inside the robot, a flow control means that controls the flow rate ratio for water spraying and cooling in the water flow distribution means, a temperature sensor that detects the internal temperature of the robot, and a control device that controls the flow control means based on a signal from the temperature sensor.

Description

[Technical Field]

[0001] The present invention relates to a cooling system for a robot used in firefighting activities, and more particularly to a technology for efficiently cooling heat-generating components inside the robot by utilizing water for spraying. [Background technology]

[0002] In recent years, the development of firefighting robots has become more active with the aim of reducing human risks and improving efficiency in firefighting activities. In particular, humanoid robots, which have a shape and movement capabilities similar to that of humans, are expected to be useful in activities in small spaces that are difficult for conventional vehicle-type firefighting robots to perform, and in firefighting activities inside buildings that require climbing stairs.

[0003] However, humanoid robots face serious thermal challenges in the high-temperature environments of firefighting. In particular, the combination of internal heat generated by high-power actuators and control electronics and external radiant heat can lead to a deterioration in the robot's operational performance and equipment failure.

[0004] Conventional firefighting robots typically have been equipped with dedicated cooling systems (fans and heat exchangers), but these systems increase the weight and complexity of the robot, posing practical limitations, especially for humanoid robots where mobility is important.

[0005] Furthermore, there are prior art attempts to use part of the water used for spraying for cooling (for example, Patent Document 1). However, this technology is limited to simply branching the water flow and does not take into consideration dynamic control according to the priority of firefighting activities or optimization for the complex joint structure specific to humanoid robots. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] U.S. Patent No. 8,381,826 Summary of the Invention [Problem to be solved by the invention]

[0007] The present invention solves the above problems, and its purposes are to efficiently utilize the water available for irrigation at fire scenes to reduce the load on dedicated cooling equipment, to properly control the priority of water irrigation and cooling activities to maximize firefighting effectiveness, to provide a cooling system suited to the joint structure unique to humanoid robots, to improve the reliability and continuity of robot operation in high-temperature environments, and to ensure backup functions in the event of system failure and improve safety. [Means for solving the problem]

[0008] The present invention is a cooling system for a robot engaged in firefighting activities, comprising a water supply unit that receives water supplied from an external water source, a water flow distribution means that distributes the water supplied from the water supply unit for use in water spraying and cooling, a water discharge means that discharges the distributed water for water spraying toward the fire site, a cooling circulation circuit that circulates the distributed water for cooling to heat-generating components inside the robot, a flow control means that controls the flow rate ratio for water spraying and cooling in the water flow distribution means, a temperature sensor that detects the internal temperature of the robot, and a control device that controls the flow control means based on a signal from the temperature sensor.

[0009] This configuration enables appropriate flow control that does not interfere with firefighting activities while diverting part of the discharged water for cooling. [Effects of the Invention]

[0010] According to this invention, the load on the dedicated cooling device can be significantly reduced by utilizing an existing water source to improve cooling efficiency, and optimization through dynamic control makes it possible to adaptively adjust the cooling water flow rate according to the conditions of the water discharge activity. Furthermore, weight reduction eliminates the need for a large-capacity dedicated cooling tank, improving the mobility of the robot. Reliability improvement is achieved by multiplexed cooling means, ensuring safety in the event of a system failure. Furthermore, evolution through learning functions has the effect of continuously improving cooling efficiency through the accumulation of operational data. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Basic configuration The firefighting robot of the present invention has a humanoid structure with a torso, head, arms, and legs. The robot is specially designed for firefighting activities in high-temperature environments, and is both heat-resistant and mobile.

[0012] Detailed configuration of the water supply unit: The water supply unit, which receives high-pressure water from external water sources (fire hydrants, fire engine pumps, etc.), consists of a main pipe and branch pipes. The main pipe is made of stainless steel (SUS316L) with an inner diameter of 50 mm and a wall thickness of 5 mm, and can accommodate a maximum water pressure of 2.0 MPa and a flow rate of 5,000 L / min. A check valve is installed at the inlet of the water supply unit to prevent backflow of water. The check valve consists of a spring-loaded check valve and has a minimum operating pressure of 0.05 MPa. The filter, which prevents the intrusion of foreign matter, consists of a 100-mesh stainless steel strainer and is equipped with a regular cleaning mechanism. The water supply unit is equipped with pressure and flow sensors that monitor water pressure and flow rate, and transmits data to the control device in real time.

[0013] Detailed design of the water flow distribution means: The water flow distribution means, which distributes the water flow from the water supply section for discharge and cooling, consists of a T-shaped branch pipe, an electric control valve, and a flow adjustment mechanism. The T-shaped branch pipe has a streamlined internal structure to minimize turbulence, keeping pressure loss to less than 5%. The electric control valve consists of a ball valve driven by a step motor, and is capable of precise control in 0.1% increments over a range of opening from 0-100%. The control valve has a response time of less than 0.3 seconds, allowing for rapid flow rate changes in emergencies. The flow adjustment mechanism is equipped with an orifice-type flow meter installed downstream of each control valve and an automatic flow rate adjustment function using PID control. In addition, to ensure safety in the event of an emergency, a manually operable bypass valve is installed in parallel.

[0014] Advanced water discharge device design: The water discharge device that discharges the distributed water toward the fire site consists of a movable nozzle, a three-axis movable mechanism, and a water discharge pattern control unit. The movable nozzle is a multi-function nozzle that can switch between three modes: straight water discharge, wide-angle spray, and foam spray. Each mode can be switched within 0.5 seconds using an electric actuator. The three-axis movable mechanism has a pan angle of ±180 degrees, a tilt angle of ±90 degrees, and a roll angle of ±45 degrees, and is capable of positioning with an accuracy of ±0.1 degrees. The water discharge pattern control unit automatically selects the optimal water discharge pattern depending on the size and type of fire, and is compatible with a water discharge volume of up to 4000 L / min and a water discharge pressure of up to 1.5 MPa. It also has a function that automatically corrects the water discharge direction in conjunction with a wind direction sensor.

[0015] The detailed configuration of the cooling circulation circuit is an advanced system that circulates distributed cooling water to heat-generating components inside the robot. Its main components include the main heat-generating components, such as servo motors for the joints, a control CPU, a battery, and a power amplifier. A small heat exchanger is placed near each heat-generating component, with an ultra-thin design measuring 10 x 10 mm and 2 mm thick, and an internal microchannel structure that maximizes heat exchange efficiency. The microchannels have grooves 0.5 mm wide and 1 mm deep, arranged at 0.2 mm intervals, increasing the surface area by 300% compared to conventional systems.

[0016] The cooling piping is made of heat-resistant silicone resin, has an inner diameter of 6 mm, an outer diameter of 10 mm, and an operating temperature range of -40°C to +200°C. The inner surface of the piping has spiral grooves to improve cooling efficiency, and the turbulent flow effect improves the heat transfer rate by 20%. Quick connectors are used for the piping connections, improving maintainability.

[0017] The circulation pump is a small electric pump with a maximum flow rate of 50 L / min and a maximum head of 15 m, and the impeller is made of titanium alloy, which has excellent corrosion resistance. The pump control unit uses inverter control to continuously adjust the rotation speed and precisely control the flow rate as needed. It also has a built-in cavitation prevention mechanism, which ensures stable operation even under high temperature conditions.

[0018] The temperature sensors are high-precision sensors that monitor the temperature of each heat-generating component and the cooling water, with a measurement accuracy of ±0.1°C and a response time of 0.1 seconds. The sensors use thermocouple and semiconductor types to ensure redundancy. They also have an alarm function when an abnormal temperature is detected and an emergency stop signal output function.

[0019] High-precision control mechanism for the flow control means: This is a high-precision system that controls the electric control valve in the water flow distribution means and dynamically adjusts the flow rate ratio for discharge and cooling. It achieves a control response time of less than 0.3 seconds and a control accuracy of within ±1% of the set value. The flow control means consists of a main control unit, servo drive unit, and feedback control unit. The main control unit is equipped with a 32-bit microprocessor and executes complex control algorithms at high speed. The servo drive unit drives the control valve with a step motor, achieving a positioning accuracy of 0.01 degrees. The feedback control unit maintains the target flow rate using PID control based on real-time data from the flow sensor.

[0020] The control device has an advanced block configuration and is a control system that integrates multiple specialized functions. The temperature monitoring unit is a multi-channel monitoring system that collects and analyzes signals from temperature sensors, simultaneously monitoring temperatures at up to 32 points, with a data collection cycle of 0.1 seconds. The signal processing unit performs noise filtering, temperature correction, and outlier exclusion, improving data accuracy to ±0.05°C. The temperature trend analysis unit predicts the rate of temperature rise by comparing it with past data, enabling preventative control.

[0021] The priority determination unit is an artificial intelligence system that evaluates the current firefighting activity status and determines the priority of water spraying and cooling. The fire scale evaluation unit integrates data on temperature distribution, smoke density, and wind direction and speed to determine the progress of the fire. The fire extinguishing progress evaluation unit evaluates the effectiveness of water spraying in real time and quantifies the effectiveness of firefighting activities. The rescue priority evaluation unit determines the urgency of life-saving based on building information and on-site conditions. These evaluation results are comprehensively evaluated by the integrated priority calculation unit, and three levels of priority (high, medium, low) are updated every 0.5 seconds.

[0022] The flow rate calculation section is an optimization engine that calculates optimal flow rate distribution based on priority and temperature information. The constraint condition setting section sets constraints such as total water volume limits, minimum water discharge volume, and maximum cooling capacity. The optimization algorithm section combines linear programming and genetic algorithms to derive the optimal solution. The safety margin setting section adds a 10% safety factor to the calculation results to generate practical control values.

[0023] The control signal output unit is a high-precision output system that transmits the calculation results to the control valve. The signal conversion unit converts the digital control value into an analog signal or pulse signal. The communication control unit uses the CAN communication protocol to achieve high-speed data exchange with the control valve. The fail-safe function automatically outputs a safe control value in the event of a communication abnormality. Detailed implementation of priority control function The control device performs priority control according to the following detailed procedure: This control system employs an advanced algorithm that combines real-time processing performance with predictive control capabilities.

[0024] S101 Temperature data acquisition stage: High-speed acquisition of temperature data from temperature sensors. Specifically, data is acquired from 32 temperature sensor channels at 0.1-second intervals and converted into digital data using 16-bit precision A / D conversion. The acquired data is stored in a ring buffer format for the past 60 seconds and used to calculate the temperature change rate. An anomaly detection algorithm is used to remove sensor failures and momentary noise, ensuring highly reliable temperature data.

[0025] S102 Water Discharge Activity Status Evaluation Stage: The current water discharge activity status is evaluated from multiple angles. In the fire scale evaluation, the fire intensity is evaluated on a five-point scale based on the maximum temperature, average temperature, and temperature rise rate. In the fire extinguishing progress evaluation, the fire extinguishing effect is quantified based on the time elapsed since the start of water discharge and the amount of temperature drop. In the surrounding environment evaluation, the risk of fire spread is predicted based on wind direction and speed, humidity, and distribution of combustible materials. In the building structure evaluation, a comprehensive judgment is made on fire resistance, the status of evacuation routes, and the risk of collapse.

[0026] S103 Priority determination stage: The priority of water discharge activities is determined in three stages using detailed criteria. High priority conditions are when the fire temperature is 1000°C or higher, lifesaving is necessary, and there is a high risk of building collapse. Medium priority conditions are when the fire temperature is 500-1000°C, there is a possibility of the fire spreading, and important equipment needs to be protected. Low priority conditions are when the fire temperature is 500°C or lower, the fire is showing signs of extinguishing, and the impact on the surrounding area is limited. The determination results are output along with the reliability, and conservative determinations are used as boundary conditions.

[0027] S104 Flow distribution calculation step: Calculate detailed flow distribution according to priority. Emergency Cooling Mode Operation Details This advanced safety system automatically activates emergency cooling mode if the robot's internal temperature exceeds the danger threshold (80°C). This emergency cooling mode is designed as a multi-stage control system that aims to protect the equipment while allowing firefighting activities to continue.

[0028] Emergency cooling mode activation conditions: The mode is activated when any of the following occurs: the temperature of a major heat-generating component exceeds 80°C, the cooling water temperature exceeds 75°C, the temperature rise rate exceeds 10°C / min, or an abnormality is detected in the cooling system. Activation is determined by majority voting logic of multiple sensors to prevent malfunctions, and the determination is completed within 0.1 seconds.

[0029] Phase 1: Suspension of water spraying: When emergency cooling mode is activated, water spraying is suspended. The standard suspension time is three minutes, but it is automatically adjusted to a range of 1-10 minutes depending on the temperature situation. During the suspension period, the nozzles are retracted to a safe position and all water spraying is diverted for cooling. During this time, fire monitoring continues, and if a rapid spread of fire is detected, water spraying is resumed using the emergency recovery function.

[0030] Stage 2: Maximum cooling mode: The cooling flow rate is set to 100%, and the circulation pump is operated at maximum speed. At the same time, the normally unused auxiliary cooling circuit is operated in parallel, increasing cooling capacity to 150%. To optimize the cooling water flow path, the system switches to high-temperature component priority mode, and cooling is performed in the following order: CPU core, power amplifier, and battery.

[0031] Phase 3: External spray system activation: Activates additional external spray nozzles to spray cooling water directly onto the robot's hull. External spraying achieves rapid temperature reduction through evaporative cooling, working in a complementary manner with internal cooling. The spray pattern is automatically adjusted according to temperature distribution to achieve the most effective cooling. The spray volume is up to 200L / min, maximizing the overall cooling effect in combination with internal cooling.

[0032] Phase 4: Temperature monitoring and recovery determination: Temperature is continuously monitored until it returns to a safe level (below 60°C). A recovery determination is made when all monitoring points reach a safe temperature and the temperature rise rate falls below 2°C / min. During the recovery process, the system gradually transitions to normal control to avoid sudden temperature changes. After recovery is complete, the emergency cooling execution record is saved in a database and used for future control improvements.

[0033] This emergency cooling function prevents thermal damage to equipment, ensuring the continuity of firefighting activities while maintaining the long-term reliability of the robot. Detailed design of multi-stage cooling system To achieve more efficient cooling, a thermodynamically optimized multi-stage cooling system can be employed, an innovative design that uses staged heat recovery to improve overall energy efficiency.

[0034] Detailed specifications of the primary heat exchanger: The primary heat exchanger, which directly cools high-temperature components (CPU core, motor windings), employs an ultra-high-efficiency design. The heat exchange section is made of copper with a micro-fin structure, manufactured through precision machining with a fin height of 2 mm, fin spacing of 0.3 mm, and fin thickness of 0.1 mm. The cooling water flow path uses a serpentine flow path design to maximize contact time, improving heat exchange efficiency by 40% compared to conventional models. It achieves a cooling water temperature rise with a temperature difference of 5-15°C, maintaining high-temperature components at 80°C or below. The primary heat exchanger is made of oxygen-free copper (C1020), which has high thermal conductivity, and the surface is nickel-plated to improve corrosion resistance.

[0035] High-efficiency secondary heat exchanger design: The secondary heat exchanger, which further cools the coolant heated by the primary heat exchanger, achieves a high cooling effect by exchanging heat with outside air. A fan generates forced convection in the outside air intake section, increasing the amount of heat exchange. The heat exchange core has an aluminum plate fin structure that maximizes surface area. Heat exchange with outside air reduces the coolant temperature by 10-20°C, optimizing the supply temperature to the primary heat exchanger. The dehumidification function prevents condensation in high-humidity environments and maintains stable cooling performance.

[0036] Water quality management of the return system: This is an advanced recycling system in which water treated in the secondary heat exchanger is returned to the water supply section and reused as discharge water. The return water treatment section filters, sterilizes, and adjusts the water quality to ensure appropriate quality for discharge water. The flow control section automatically adjusts the amount of return water to optimize the water balance throughout the system. The water quality monitoring section continuously monitors pH, conductivity, and turbidity, and if an abnormality occurs, the return flow is stopped and the water is discharged externally. This return system improves water usage efficiency by 15-25% and reduces the environmental impact. Detailed implementation of a control system with learning capabilities It is possible to configure an advanced control system incorporating machine learning functionality. This system is a next-generation control system that utilizes artificial intelligence technology to achieve continuous performance improvement.

[0037] Advanced data management in the data storage section: For temperature history data, time-series data from all temperature sensors is recorded at 0.1-second intervals to build a database for up to one year. A data compression algorithm improves storage efficiency by 90%. For flow control history, the operation history, response characteristics, and control accuracy of the control valve are recorded in detail to track changes in control performance over time. For firefighting activity patterns, statistical data such as fire type, scale, response time, and water usage is accumulated and used to analyze activity efficiency. For cooling effect data, the temperature difference before and after cooling, cooling time, energy efficiency, etc. are quantified and used as basic data for system optimization.

[0038] Advanced AI technology in the learning processing unit: Analyzes accumulated data using a neural network to derive optimal control parameters. The deep learning algorithm combines a multi-layer perceptron and a convolutional neural network to learn complex nonlinear relationships. The feature extraction unit automatically identifies important control factors using principal component analysis and independent component analysis. The predictive model construction unit uses an LSTM (Long Short-Term Memory) network to predict future temperature changes with high accuracy. The optimization engine combines a genetic algorithm and particle swarm optimization to solve multi-objective optimization problems. Learning convergence is determined using cross-validation to prevent over-learning and ensure generalization performance.

[0039] Adaptive control unit implementation details: The learning results are reflected in the control algorithm to continuously improve cooling efficiency. The parameter update unit extracts optimal control parameters from the learned model and applies them in stages to the existing control system. The performance evaluation unit quantitatively compares control performance before and after the update to verify the improvement effect. The automatic adjustment function automatically adjusts control parameters in response to changes in the operating environment, always maintaining optimal control. The fail-safe function has the ability to automatically return to safe default values ​​if an abnormality is detected in the learning results.

[0040] Quantitative evaluation of learning effects: With the introduction of this learning system, cooling efficiency improved by an average of 25% within six months of operation, and control response time was reduced by 30%. Furthermore, predictive control reduced the frequency of equipment overheating by 80%, significantly improving system reliability. As learning data accumulated, prediction accuracy also improved, and after 12 months, it became possible to converge temperature prediction errors to within ±1°C. Demonstration experiment results To verify the effectiveness of the cooling system of the present invention, a demonstration experiment simulating an actual firefighting environment was conducted at the training facility of the Ichihara City Fire Department with the cooperation of the Fire and Disaster Management Agency of the Ministry of Internal Affairs and Communications.

[0041] The experimental conditions were a high-temperature environment with an ambient temperature of 60°C and a radiant heat intensity of 15kW / m2, in which the robot was made to perform continuous water spraying. A comparison was made between a robot equipped with a conventional air-cooling system and a robot equipped with the water-cooling system of the present invention, and the following improvements were confirmed by the present invention.

[0042] First, in terms of operating time, the conventional system stopped operating after 35 minutes due to overheating, whereas the present invention achieved 180 minutes of continuous operation. As for the internal temperature, the conventional system reached a maximum of 95°C, but the present invention kept it at a maximum of 72°C, enabling operation within the safe operating range.

[0043] Regarding the impact on water discharge performance, it was confirmed that the amount of water discharged in this invention was maintained at 80% or more of the rated amount even when using cooling water, and there was no substantial impact on firefighting effectiveness.In addition, regarding the reuse of cooling water, by reusing cooling water that has passed through a secondary heat exchanger for discharge, the overall water usage efficiency was improved by 15%.

[0044] The system's responsiveness was confirmed to be sufficient to prevent equipment damage due to overheating, with an average of 0.8 seconds between the activation of emergency cooling mode and the start of cooling. Furthermore, as an optimization effect of the learning function, after accumulating 30 hours of operational data, cooling efficiency improved by 25% compared to the initial setting.

[0045] During the experiment, when a part of the cooling system was intentionally made to fail, the backup system operated normally, and a safe shutdown was possible by alternative cooling through external spraying. These experimental results demonstrated the practicality and safety of the present invention. Detailed implementation of a search and rescue system utilizing information from inside buildings In order to enable firefighting robots equipped with the cooling system of this invention to more effectively perform firefighting and rescue operations inside buildings, we have developed an integrated system that utilizes information on the internal structure of buildings. This system is an innovative approach that combines information technology and cooling control technology.

[0046] Detailed collection and management system for building interior information: This system utilizes information on the interior of buildings, including detailed 3D floor plans obtained from a BIM (Building Information Modeling) database, accurate dimensional information from CAD data, the classification of each room's use (living room, office, conference room, warehouse, etc.) and legal occupancy, the coordinates of the locations of evacuation routes and emergency exits based on the Building Standards Act, information on the location of fire extinguishing equipment such as sprinklers, fire hydrants, and smoke detectors, and data on the structural materials of columns, beams, and walls (steel frame, reinforced concrete, wood, etc.) and combustion characteristics data for interior materials (distribution of fire-retardant, semi-fire-resistant, and non-fire-resistant materials). This information is linked to the fire command center's building management database via a high-speed network and is obtained in real time at the same time as a dispatch order is issued. The data format is unified in a standardized XML format, ensuring compatibility between different systems.

[0047] Advanced search path calculation system: The robot uses a multi-objective optimization algorithm based on the acquired building information to calculate the optimal entry path. The route calculation simultaneously considers minimizing travel distance, avoiding high-temperature areas, selecting a structurally safe route, and minimizing the time it takes to reach the rescue target. Combined with fire spread predictions, CFD (computational fluid dynamics) simulations predict smoke and heat diffusion patterns in 3D, generating an efficient search pattern within 0.5 seconds. Prioritizing search areas where people are particularly likely to be trapped, such as living rooms, bedrooms, conference rooms, and facilities for the disabled, and familiarizing itself with the building's structure enables rapid rescue operations. The search pattern is dynamically updated, with the ability to optimize the route based on newly discovered information on-site.

[0048] Advanced collaborative control with the cooling system: The system is equipped with a predictive control function that adjusts the distribution of cooling water in advance based on the predicted temperature distribution within the building. For example, in high-temperature areas near the center of the fire (expected temperature of 800°C or higher), the cooling water flow rate is increased to 60% of the total flow rate to maximize the robot's heat resistance. In relatively low-temperature areas (expected temperature of 300°C or lower), water spraying is prioritized and dynamic control is used to limit the cooling water flow rate to 20% or less. The system also has a route cooling function that optimizes the cooling effect along the building's evacuation routes to support the safe transport of rescued personnel. Cooling strategies tailored to the purpose of each room include enhanced preventative cooling in high-heat-generating areas such as electrical rooms and server rooms, and standard cooling in general living rooms.

[0049] Real-time information integration and update system: The building information system is an advanced information management system that is continuously updated in conjunction with real-time fire conditions. Information collected by the robot, such as on-site temperature data, smoke density distribution, oxygen concentration, structural damage status, and the passability of evacuation routes, is fed back to the building database in real time, helping subsequent rescue teams and other robots develop more precise operation plans. The information reliability evaluation function integrates multiple sensor data to improve information accuracy, quantifying uncertainty and reflecting it in decision-making. Data communication utilizes 5G communication technology to achieve low latency and high reliability, and also features mesh network functionality in case of communication outages during disasters.

[0050] Quantitative effects of improved rescue accuracy: This integrated system enables highly accurate rescue of lives in large buildings and facilities with complex structures, which were previously difficult to achieve with conventional firefighting. In demonstration experiments, the use of building information reduced the time it took to find rescue targets by 70% compared to conventional methods, and the rescue success rate increased from 85% to 95%. It also improved the safety of the robot, reducing the number of malfunctions due to high temperatures by 60%, which is expected to significantly reduce human casualties from fires. Examples of system specifications include a robot height of 1.8m, weight of 180kg (20% lighter than conventional models), maximum operating time of 6 hours (with continuous cooling), maximum cooling water consumption of 200L / h, temperature control accuracy of ±2°C, and control response time of 0.3 seconds.

[0051] Performance data includes a maximum cooling capacity of 15kW (150% compared to conventional dedicated systems), a maximum water discharge capacity of 4000L / min (3200L / min even when using cooling), and system efficiency, achieving an 80% improvement in cooling effect and a 20% weight reduction. When the priority is high, the cooling flow rate is limited to a maximum of 20% of the total flow rate, maximizing water discharge capacity. At this time, minimum cooling of important equipment is maintained and temporary high temperature operation is tolerated. When the priority is medium, the cooling flow rate is limited to a maximum of 40%, achieving a balance between water discharge and cooling. When the priority is low, the cooling flow rate is increased up to a maximum of 70% depending on the temperature, extending the life of the equipment. Correction coefficients are applied to each setting value to account for water pressure fluctuations, piping losses, and control delays.

[0052] S105 Control signal output stage: This outputs a command value to the control valve with high precision. The digital control value is converted into a 4-20mA current signal using 12-bit D / A conversion. This is compared with the control valve's position feedback signal, and PID control continues until the error is within ±0.5%. The communication error detection function detects an error within 0.1 seconds and switches to fail-safe mode. Emergency Cooling Mode Operation Details As shown in Figure 6, this is an advanced safety system that automatically activates emergency cooling mode when the internal temperature of the robot exceeds the danger threshold (80°C). This emergency cooling mode is designed as a multi-stage control system that aims to protect the equipment while also allowing firefighting activities to continue.

[0053] Emergency cooling mode activation conditions: The mode is activated when any of the following occurs: the temperature of a major heat-generating component exceeds 80°C, the cooling water temperature exceeds 75°C, the temperature rise rate exceeds 10°C / min, or an abnormality is detected in the cooling system. Activation is determined by majority voting logic of multiple sensors to prevent malfunctions, and the determination is completed within 0.1 seconds.

[0054] Phase 1: Suspension of water spraying: When emergency cooling mode is activated, water spraying is suspended. The standard suspension time is three minutes, but it is automatically adjusted to a range of 1-10 minutes depending on the temperature situation. During the suspension period, Nozzle 131 is retracted to a safe position and all water spraying is diverted for cooling. During this time, fire monitoring continues, and if a rapid spread of fire is detected, water spraying is resumed using the emergency recovery function.

[0055] Second stage: Maximum cooling mode: The cooling flow rate is set to 100%, and the circulation pump 144 is operated at maximum rotation speed. At the same time, the auxiliary cooling circuit 146, which is not normally used, is also operated in parallel, increasing the cooling capacity to 150%. To optimize the cooling water flow path, the system switches to high-temperature component priority mode, and cooling is performed in the following order: CPU core, power amplifier, and battery.

[0056] Phase 3: External spray system activation: Activate the additional external spray nozzle 147 to spray cooling water directly onto the robot's hull. External spraying achieves rapid temperature reduction through evaporative cooling, working in a complementary manner with internal cooling. The spray pattern is automatically adjusted according to the temperature distribution to achieve the most effective cooling. The spray volume is up to 200 L / min, maximizing the overall cooling effect in combination with internal cooling.

[0057] Phase 4: Temperature monitoring and recovery determination: Temperature is continuously monitored until it returns to a safe level (below 60°C). A recovery determination is made when all monitoring points reach a safe temperature and the temperature rise rate falls below 2°C / min. During the recovery process, the system gradually transitions to normal control to avoid sudden temperature changes. After recovery is complete, the emergency cooling execution record is saved in a database and used for future control improvements.

[0058] This emergency cooling function prevents thermal damage to equipment, ensuring the continuity of firefighting activities while maintaining the long-term reliability of the robot. Detailed design of multi-stage cooling system To achieve more efficient cooling, a thermodynamically optimized multi-stage cooling system can be employed, as shown in Figure 7. This system is an innovative design that improves overall energy efficiency through staged heat recovery.

[0059] Detailed specifications of the primary heat exchanger 147: The primary heat exchanger 147, which directly cools high-temperature components (CPU core, motor windings), employs an ultra-high-efficiency design. The heat exchange section 147a is a copper micro-fin structure manufactured through precision machining with a fin height of 2 mm, fin spacing of 0.3 mm, and fin thickness of 0.1 mm. The cooling water flow path 147b uses a serpentine flow path design to maximize contact time, improving heat exchange efficiency by 40% compared to conventional models. It achieves a cooling water temperature rise with a temperature difference of 5-15°C, maintaining high-temperature components at 80°C or below. The primary heat exchanger is made of oxygen-free copper (C1020), which has high thermal conductivity, and the surface is nickel-plated to improve corrosion resistance.

[0060] High-efficiency design of secondary heat exchanger 148: The secondary heat exchanger 148, which further cools the coolant heated by the primary heat exchanger, achieves a high cooling effect by exchanging heat with outside air. In the outside air intake section 148a, forced convection is generated by fan 148b, increasing the amount of heat exchange. The heat exchange core 148c has an aluminum plate fin structure that maximizes surface area. Heat exchange with outside air reduces the coolant temperature by 10-20°C, optimizing the supply temperature to the primary heat exchanger. The dehumidification function 148d prevents condensation in high-humidity environments and maintains stable cooling performance.

[0061] Water quality management of the return system 149: This is an advanced recycling system in which water treated in the secondary heat exchanger is returned to the water supply unit 110 and reused as discharge water. The return water treatment unit 149a performs filtering, sterilization, and water quality adjustment to ensure appropriate quality for discharge water. The flow rate control unit 149b automatically adjusts the amount of return water to optimize the water balance throughout the system. The water quality monitoring unit 149c continuously monitors pH, conductivity, and turbidity, and if an abnormality occurs, stops the return and discharges the water externally. This return system improves water usage efficiency by 15-25% and reduces environmental impact. Detailed implementation of a control system with learning capabilities It is possible to configure an advanced control system incorporating machine learning functions, as shown in Figure 8. This system is a next-generation control system that utilizes artificial intelligence technology to achieve continuous performance improvement.

[0062] Advanced data management by the data storage unit 170: Temperature history data 170a records time-series data from all temperature sensors at 0.1-second intervals to build a database for up to one year. A data compression algorithm improves storage efficiency by 90%. Flow control history 170b records detailed information on the operation history, response characteristics, and control accuracy of control valves to track changes in control performance over time. Firefighting activity pattern 170c accumulates statistical data on fire type, scale, response time, water consumption, etc., and uses it to analyze activity efficiency. Cooling effect data 170d quantifies the temperature difference before and after cooling, cooling time, energy efficiency, etc., and serves as basic data for system optimization.

[0063] Advanced AI technology of the learning processing unit 171: Analyzes accumulated data using a neural network to derive optimal control parameters. The deep learning algorithm 171a combines a multilayer perceptron and a convolutional neural network to learn complex nonlinear relationships. The feature extraction unit 171b automatically identifies important control factors using principal component analysis and independent component analysis. The prediction model construction unit 171c uses an LSTM (Long Short-Term Memory) network to predict future temperature changes with high accuracy. The optimization engine 171d combines a genetic algorithm and particle swarm optimization to solve multi-objective optimization problems. Convergence of learning is determined by cross-validation to prevent over-learning and ensure generalization performance.

[0064] Implementation details of the adaptive control unit 172: The learning results are reflected in the control algorithm to continuously improve cooling efficiency. The parameter update unit 172a extracts optimal control parameters from the learned model and applies them in stages to the existing control system. The performance evaluation unit 172b quantitatively compares the control performance before and after the update to verify the improvement effect. The automatic adjustment function 172c automatically adjusts the control parameters in response to changes in the operating environment, always maintaining optimal control. The fail-safe function 172d has a function that automatically returns to a safe default value if an abnormality is detected in the learning results.

[0065] Quantitative evaluation of learning effects: With the introduction of this learning system, cooling efficiency improved by an average of 25% within six months of operation, and control response time was reduced by 30%. Furthermore, predictive control reduced the frequency of equipment overheating by 80%, significantly improving system reliability. As learning data accumulated, prediction accuracy also improved, and after 12 months, it became possible to converge temperature prediction errors to within ±1°C. Demonstration experiment results In order to verify the effectiveness of the cooling system of the present invention, a demonstration experiment was conducted simulating an actual firefighting environment.

[0066] The experimental conditions were a high-temperature environment with an ambient temperature of 60°C and a radiant heat intensity of 15kW / m2, in which the robot was made to perform continuous water spraying. A comparison was made between a robot equipped with a conventional air-cooling system and a robot equipped with the water-cooling system of the present invention, and the following improvements were confirmed by the present invention.

[0067] First, in terms of operating time, the conventional system stopped operating after 35 minutes due to overheating, whereas the present invention achieved 180 minutes of continuous operation. As for the internal temperature, the conventional system reached a maximum of 95°C, but the present invention kept it at a maximum of 72°C, enabling operation within the safe operating range.

[0068] Regarding the impact on water discharge performance, it was confirmed that the amount of water discharged in this invention was maintained at 80% or more of the rated amount even when using cooling water, and there was no substantial impact on firefighting effectiveness.In addition, regarding the reuse of cooling water, by reusing cooling water that has passed through a secondary heat exchanger for discharge, the overall water usage efficiency was improved by 15%.

[0069] The system's responsiveness was confirmed to be sufficient to prevent equipment damage due to overheating, with an average of 0.8 seconds between the activation of emergency cooling mode and the start of cooling. Furthermore, as an optimization effect of the learning function, after accumulating 30 hours of operational data, cooling efficiency improved by 25% compared to the initial setting.

[0070] During the experiment, when a part of the cooling system was intentionally made to fail, the backup system operated normally, and a safe shutdown was possible by alternative cooling through external spraying. These experimental results demonstrated the practicality and safety of the present invention. Detailed implementation of a search and rescue system utilizing information from inside buildings In order to enable firefighting robots equipped with the cooling system of this invention to more effectively perform firefighting and rescue operations inside buildings, we have developed an integrated system that utilizes information on the internal structure of buildings. This system is an innovative approach that combines information technology and cooling control technology.

[0071] Detailed collection and management system for building interior information: This system utilizes information on the interior of buildings, including detailed 3D floor plans obtained from a BIM (Building Information Modeling) database, accurate dimensional information from CAD data, the classification of each room's use (living room, office, conference room, warehouse, etc.) and legal occupancy, the coordinates of the locations of evacuation routes and emergency exits based on the Building Standards Act, information on the location of fire extinguishing equipment such as sprinklers, fire hydrants, and smoke detectors, and data on the structural materials of columns, beams, and walls (steel frame, reinforced concrete, wood, etc.) and combustion characteristics data for interior materials (distribution of fire-retardant, semi-fire-resistant, and non-fire-resistant materials). This information is linked to the fire command center's building management database via a high-speed network and is obtained in real time at the same time as a dispatch order is issued. The data format is unified in a standardized XML format, ensuring compatibility between different systems.

[0072] Advanced search path calculation system: The robot uses a multi-objective optimization algorithm based on the acquired building information to calculate the optimal entry path. The route calculation simultaneously considers minimizing travel distance, avoiding high-temperature areas, selecting a structurally safe route, and minimizing the time it takes to reach the rescue target. Combined with fire spread predictions, CFD (computational fluid dynamics) simulations predict smoke and heat diffusion patterns in 3D, generating an efficient search pattern within 0.5 seconds. Prioritizing search areas where people are particularly likely to be trapped, such as living rooms, bedrooms, conference rooms, and facilities for the disabled, and familiarizing itself with the building's structure enables rapid rescue operations. The search pattern is dynamically updated, with the ability to optimize the route based on newly discovered information on-site.

[0073] Advanced collaborative control with the cooling system: The system is equipped with a predictive control function that adjusts the distribution of cooling water in advance based on the predicted temperature distribution within the building. For example, in high-temperature areas near the center of the fire (expected temperature of 800°C or higher), the cooling water flow rate is increased to 60% of the total flow rate to maximize the robot's heat resistance. In relatively low-temperature areas (expected temperature of 300°C or lower), water spraying is prioritized and dynamic control is used to limit the cooling water flow rate to 20% or less. The system also has a route cooling function that optimizes the cooling effect along the building's evacuation routes to support the safe transport of rescued personnel. Cooling strategies tailored to the purpose of each room include enhanced preventative cooling in high-heat-generating areas such as electrical rooms and server rooms, and standard cooling in general living rooms.

[0074] Real-time information integration and update system: The building information system is an advanced information management system that is continuously updated in conjunction with real-time fire conditions. Information collected by the robot, such as on-site temperature data, smoke density distribution, oxygen concentration, structural damage status, and the passability of evacuation routes, is fed back to the building database in real time, helping subsequent rescue teams and other robots develop more precise operation plans. The information reliability evaluation function integrates multiple sensor data to improve information accuracy, quantifying uncertainty and reflecting it in decision-making. Data communication utilizes 5G communication technology to achieve low latency and high reliability, and also features mesh network functionality in case of communication outages during disasters.

[0075] Quantitative effects of improved rescue accuracy: This integrated system enables highly accurate rescue of lives in large buildings and facilities with complex structures, which were previously difficult to achieve with conventional firefighting. In demonstration experiments, the use of building information reduced the time it took to find rescue targets by 70% compared to conventional methods, and the rescue success rate increased from 85% to 95%. It also improved the safety of the robot, reducing the number of malfunctions due to high temperatures by 60%, which is expected to significantly reduce human casualties from fires. Examples of system specifications include a robot height of 1.8m, weight of 180kg (20% lighter than conventional models), maximum operating time of 6 hours (with continuous cooling), maximum cooling water consumption of 200L / h, temperature control accuracy of ±2°C, and control response time of 0.3 seconds.

[0076] Performance data includes a maximum cooling capacity of 15kW (150% compared to conventional dedicated systems), a maximum water discharge capacity of 4000L / min (3200L / min even when used for cooling), and an 80% improvement in cooling efficiency and a 20% reduction in weight. [Industrial Applicability]

[0077] The present invention is expected to be industrially applicable in the following fields:

[0078] In the firefighting industry, unmanned firefighting operations will be possible in urban fires, factory fires, and high-rise building fires, enabling firefighting in areas that are difficult to reach with conventional ladder trucks and chemical trucks. In petrochemical plants, unmanned firefighting operations in hazardous material facilities will protect workers from the dangers of explosions and toxic gases. In nuclear facilities, emergency response operations in high-radiation environments will be possible without the risk of human exposure. In the field of disaster relief, rescue operations following complex disasters such as earthquakes and tsunamis will enable rapid response while minimizing the risk of secondary disasters. In the military and defense sector, unmanned firefighting and rescue missions in combat zones will be expected to be carried out effectively while ensuring the safety of personnel.

[0079] In particular, in firefighting activities in high-temperature and toxic environments that humans cannot approach, robots equipped with the cooling system of this invention enable stable operation for long periods of time, which is difficult to achieve with conventional technology, and contribute to a dramatic improvement in firefighting effectiveness.

[0080] Furthermore, the control technology of the present invention can be applied to robots for working in high-temperature environments other than firefighting (such as for blast furnace work and extravehicular activity in space), and is expected to be used in a wide range of industrial fields.

Claims

1. A cooling system for a robot that performs firefighting activities, comprising: a water supply unit that receives water supplied from an external water source; a water flow distribution means for distributing the water supplied from the water supply unit into a water discharge portion and a water cooling portion; a water discharge means for discharging the distributed water toward the fire site; a cooling circulation circuit that circulates the distributed cooling water to heat-generating components inside the robot; a flow rate control means for controlling a flow rate ratio between the water discharge flow rate and the water cooling flow rate in the water flow distribution means; a temperature sensor that detects the internal temperature of the robot; a control device that controls the flow rate control means based on a signal from the temperature sensor; Equipped with The control device a priority determination means for determining the priority of a water discharge activity; During high-priority water discharge activities, the flow rate of cooling water will be limited. Normally, the flow rate of the cooling water is increased according to the temperature detected by the temperature sensor. A cooling system for a firefighting robot.

2. A cooling system for a robot that performs firefighting activities, comprising: a water supply unit that receives water supplied from an external water source; a water flow distribution means for distributing the water supplied from the water supply unit into a water discharge portion and a water cooling portion; a water discharge means for discharging the distributed water toward the fire site; a cooling circulation circuit that circulates the distributed cooling water to heat-generating components inside the robot; a flow rate control means for controlling a flow rate ratio between the water discharge flow rate and the water cooling flow rate in the water flow distribution means; a temperature sensor that detects the internal temperature of the robot; a control device that controls the flow rate control means based on a signal from the temperature sensor; Equipped with The cooling circulation circuit includes: heat exchange units disposed near the joints of the torso, arms, and legs of the robot; a cooling water pipe connecting each heat exchange unit; a discharge switching means for switching whether the cooled water is returned to the water supply section or discharged to the outside; A cooling system for a firefighting robot, comprising:

3. A cooling control method for a robot that performs firefighting activities, comprising: a distribution step of distributing water supplied from an external water source for use in discharge and cooling; a temperature monitoring step of continuously monitoring the temperature inside the robot; an activity determination step of determining the execution status of the water discharge activity; a flow rate adjusting step of dynamically adjusting the ratio of the flow rates of water for discharge and water for cooling based on the results of the temperature monitoring step and the activity determining step; A method for controlling cooling of a firefighting robot, comprising:

4. 4. The method for controlling cooling of a firefighting robot according to claim 3, a data storage step of storing past cooling control data; A learning process in which the accumulated data is analyzed using machine learning to derive the optimal flow rate distribution pattern; an application step of reflecting the derived optimal pattern in the flow rate adjustment step; The cooling control method for a firefighting robot further comprises: