Fire pool anti-freezing system and control method thereof

Abstract

The application provides a fire pool anti-freezing system and a control method thereof, which comprises a floating disturbance device, a controller, a sensor module and a submersible heating device; the floating disturbance device is provided with a disturbance stirrer, the disturbance stirrer is fixed in a floating ring, and the floating ring enables the fire pool anti-freezing system to float on the water surface when the fire pool anti-freezing system is placed in water; a fixed support is arranged in the gap between the floating ring and the impeller of the disturbance stirrer, the submersible heating device is arranged on the fixed support, the center of the arc of the submersible heating device is concentric with the axis of the disturbance stirrer; the sensor module comprises a temperature sensor for collecting water surface temperature data in real time; the controller is used for receiving the water surface temperature data reported by the sensor module, controlling the submersible heating device to perform a heating operation and the impeller to perform a disturbance operation if it is determined that the heating start condition is met, and controlling the submersible heating device to stop performing the heating operation and the impeller to stop rotating if it is determined that the heating stop condition is met.

Description

Technical Field

[0001] This disclosure relates to the field of fire water supply technology, and in particular to a fire water tank antifreeze system and its control method. Background Technology

[0002] In frigid regions, outdoor fire-fighting water tanks may freeze in winter. Therefore, it is necessary to protect outdoor fire-fighting water tanks from freezing to prevent them from becoming unusable in emergencies when water is needed.

[0003] In one approach, electric heating cables or submersible heaters are installed on the inner walls of the pool or in the water body to prevent freezing through continuous or intermittent heating. However, heating large areas of water or pool walls results in extremely high operating costs and enormous energy consumption during winter, making it uneconomical.

[0004] In another approach, an insulation layer and a waterproof layer (such as galvanized steel sheet) are added to the outside of the pool wall to isolate moisture from the pool wall and reduce the risk of frost heave. However, laying insulation and waterproof layers is costly, resulting in high initial investment. Furthermore, damage to the internal waterproof layer is extremely difficult to repair and incurs high maintenance costs, making it uneconomical.

[0005] In another approach, clean energy sources such as solar and geothermal energy are used as heat sources, with the water tank kept warm through heat storage plates or heat exchangers. However, solar and geothermal energy are affected by the natural environment. If extreme weather conditions prevent the collection of solar or geothermal energy, power outages and freezing can cause the equipment to seize up. If the system is started directly after power is restored, it is very easy for the motor to burn out, resulting in complete system failure.

[0006] Another approach involves using a fixed underwater mixer or aeration device to circulate the water and prevent freezing. However, fixed aeration devices or mixers cannot automatically adjust their working position according to water level changes. When the water level is too low, the equipment may be exposed above the water surface and run dry, potentially causing damage. When the water level is too high, the equipment may be submerged or its efficiency may be reduced. Summary of the Invention

[0007] In view of the aforementioned problems, this disclosure provides a fire water tank antifreeze system and its control method, which aims to solve the problem of fire water tank freezing in winter and reduce the risk of equipment damage in a low-energy and low-cost manner.

[0008] In conjunction with the first aspect of the present invention, an embodiment of the present invention provides a fire water tank antifreeze system, comprising:

[0009] Floating turbulence control devices, controllers, sensor modules, and underwater heating devices;

[0010] The floating turbulence device is equipped with a turbulence agitator, which is fixed inside the float ring. The float ring enables the fire water tank antifreeze system to float on the water surface when it is placed in the water.

[0011] A fixed bracket is installed in the gap between the float ring and the impeller of the turbulence mixer. The submersible heating device is installed on the fixed bracket. The submersible heating device is arc-shaped, and the center of the arc is concentric with the axis of the turbulence mixer.

[0012] The controller is communicatively connected to the floating turbulence device, the sensor module, and the submersible heating device; the sensor module includes a temperature sensor.

[0013] The sensor module is used to collect water surface temperature data in real time through the temperature sensor.

[0014] The controller is used to receive the water surface temperature data reported by the sensor module, and when it is determined from the water surface temperature data that the conditions for starting heating are met, it controls the submersible heating device to perform heating operation and controls the impeller to rotate to perform turbulence operation; when it is determined from the water surface temperature data that the conditions for stopping heating are met, it controls the submersible heating device to stop performing heating operation and controls the impeller to stop rotating.

[0015] Preferably, the controller is used to control the submersible heating device to perform heating operations and control the impeller to perform turbulence operations when the water surface temperature data determines that the conditions for starting heating are met, including:

[0016] When the controller determines that the water surface freezing heating condition among the start heating conditions is met based on the water surface temperature data, it controls the submersible heating device to perform a heating operation with a first heating power and controls the impeller to be locked in a non-rotating state, and starts a timer. The water surface freezing heating condition includes the impeller being in a non-rotating state and the water surface temperature data indicating that the water surface temperature is lower than the freezing point risk temperature threshold.

[0017] When the preset time is reached, the impeller is controlled to rotate at a first speed to perform a turbulence operation.

[0018] Preferably, before the controller controls the first heating power of the submersible heating device to perform the heating operation and controls the impeller to be in a locked, non-rotating state, it further includes:

[0019] Define a sliding surface function s based on temperature and time, where s = c × (T ref -T cur )+d(T ref-T cur ) / dt, where c is the weight greater than zero, T ref For reference water surface temperature, T cur The water surface temperature is represented by water surface temperature data collected at any point in history.

[0020] We choose the exponential reaching law ds / dt=-ε×sign(s)-k×s, where ε and k are positive numbers used to ensure that the sliding surface is reached in a finite time and to reduce chattering, and sign is a sign function based on s;

[0021] Establish a first-order model of heating power P versus the rate of temperature change: dT cur / dt =aP-b(T cur -T env Combining the inverse solution of the sliding surface derivative with the equivalent control law, T env Let be the ambient temperature, a be the heating power coefficient representing the contribution of unit heating power P to the rate of change of water surface temperature, and b be the heat dissipation coefficient representing the rate of change of temperature caused by the temperature difference between unit water surface and environment.

[0022] According to the overall control law P=Peq+Psw, where Peq is used to maintain the sliding mode motion and Psw=(ε·sign(s)+k·s) / a, the heating power expression is obtained by substituting the actual parameters, and the lower limit of the heating power P is constrained according to the second heating power constraint.

[0023] Based on the real-time sampled water surface temperature data, the sliding surface function s and its derivative are calculated, and substituted into the overall control law to obtain the first heating power.

[0024] Preferably, the controller is further configured to:

[0025] The operating current of the turbulent mixer is collected in real time by the current sensor in the sensor module.

[0026] If it is determined that the impeller of the turbulence mixer is in an abnormal rotation state based on the operating current, the steps of controlling the submersible heating device to perform heating operation with a first heating power and controlling the impeller to be locked and not rotated are repeatedly executed until the preset time is reached, and the impeller is controlled to rotate at a first speed to perform turbulence operation, until it is determined that the impeller of the turbulence mixer is in a normal rotation state based on the operating current.

[0027] If the impeller of the turbulence mixer is determined to be in normal rotation state based on the operating current, then the impeller of the turbulence mixer is controlled to perform turbulence operation at a second rotation speed and the submersible heating device is controlled to perform heating operation at a second heating power, wherein the first rotation speed is less than the second rotation speed and the first heating power is greater than the second heating power.

[0028] Preferably, the controller is further configured to:

[0029] When the submersible heating device is in the heating operation state and / or the impeller is in the rotating turbulence operation state, the liquid level data collected in real time by the liquid level sensor in the sensor module is obtained, and the liquid level sensor is deployed on the bottom surface of the floating turbulence device;

[0030] Determine whether the water level is below the safe rotation threshold of the impeller based on the liquid level data;

[0031] If it is determined that the water level is lower than the safe rotation threshold of the impeller, then the shutdown condition is met, and the power supply to the turbulence mixer and the submersible heating device is turned off to control the submersible heating device to stop performing heating operations and to control the impeller to stop rotating.

[0032] Preferably, the controller is further configured to:

[0033] If the water level data is determined to meet the self-starting conditions, the power supply of the turbulence mixer and the submersible heating device is turned on. The self-starting conditions include that the power supply of the turbulence mixer and the submersible heating device is turned off due to meeting the shutdown conditions, and the water level data indicates that the water level is higher than the preset safe water level.

[0034] Preferably, the controller is further configured to:

[0035] The system acquires real-time ambient relative humidity data collected by the humidity sensor in the sensor module and wind speed data collected by the wind speed sensor in the sensor module.

[0036] Based on the ambient relative humidity data, wind speed data, and water surface temperature data, the predicted probability of water surface freezing is predicted.

[0037] Determine whether the predictive antifreeze conditions are met based on the predicted freezing probability.

[0038] If the predictive antifreeze conditions are met, the submersible heating device is controlled to remain in a non-heating state and the impeller is controlled to perform a turbulence operation at a third rotational speed.

[0039] Preferably, the controller is further configured to predict the probability of water surface freezing based on ambient relative humidity data, wind speed data, and the water surface temperature data, including:

[0040] A logistic regression classification model is constructed with the relative humidity data, wind speed data, and water surface temperature data as input features and the linear score of icing as the dependent variable.

[0041] Substitute the linear score into the logistic function with the linear score as the independent variable and the icing probability as the dependent variable, and determine the probability value of the icing probability based on the historically collected environmental relative humidity data, wind speed data, and water surface temperature data.

[0042] Based on the probability values ​​and the corresponding real event labels, construct a single likelihood for the historically collected environmental relative humidity data, wind speed data, and water surface temperature data at the same collection time as a group;

[0043] Based on the product of the individual likelihoods corresponding to each group, a total likelihood function is constructed, and based on the total likelihood function, the optimal values ​​of the model coefficients are found by maximum likelihood estimation to determine the target logistic regression classification model.

[0044] The real-time collected environmental relative humidity data, wind speed data, and water surface temperature data are substituted into the target logistic regression classification model to obtain the predicted icing probability corresponding to the current collection time.

[0045] Preferably, the submersible heating device is semi-circular, and the fire water tank antifreeze system is equipped with two semi-circular submersible heating devices, which are arranged symmetrically.

[0046] In conjunction with the second aspect of the present invention, an embodiment of the present invention provides a method for preventing freezing of a fire water tank, which is applied to the controller of the fire water tank antifreeze system described in any of the first aspects, wherein the fire water tank antifreeze system includes: a floating turbulence device, a controller, a sensor module, and a submersible heating device;

[0047] The floating turbulence device is equipped with a turbulence agitator, which is fixed inside the float ring. The float ring enables the fire water tank antifreeze system to float on the water surface when it is placed in the water.

[0048] A fixed bracket is installed in the gap between the float ring and the impeller of the turbulence mixer. The submersible heating device is installed on the fixed bracket. The submersible heating device is arc-shaped, and the center of the arc is concentric with the axis of the turbulence mixer.

[0049] The controller is communicatively connected to the floating turbulence device, the sensor module, and the submersible heating device; the sensor module includes a temperature sensor.

[0050] The method includes:

[0051] Acquire the real-time water surface temperature data collected by the temperature sensor in the sensor module;

[0052] If the conditions for starting heating are met based on the water surface temperature data, the submersible heating device is controlled to perform heating operations and the impeller is controlled to rotate to perform turbulence operations.

[0053] If the conditions for stopping heating are met based on the water surface temperature data, the submersible heating device is controlled to stop performing heating operations and the impeller is controlled to stop rotating.

[0054] Through the above-described technical solution, this disclosure can achieve at least the following effective effects:

[0055] The floating turbulence device uses a float to stay afloat on the water surface, while the turbulence mixer generates flow, ensuring uniform water temperature. Combined with a submersible heating device, this provides precise heating and prevents localized overheating or undercooling. The controller uses real-time water surface temperature data collected by sensor modules to manage heating and turbulence operations, activating the equipment only when needed. The heating element heats the water, and the turbulence mixer disperses the heated water, achieving efficient heating with low energy consumption. Simultaneously, the control system prevents prolonged operation, reducing wear and tear, lowering the risk of equipment damage, and extending the equipment's lifespan. In this way, through low-energy and low-cost methods, the problem of ice formation in fire-fighting water tanks in winter is effectively solved, and the risk of equipment damage is reduced.

[0056] Other features and advantages of this disclosure will be described in detail in the following detailed description section. Attached Figure Description

[0057] The accompanying drawings are provided to further illustrate the present disclosure and form part of the specification. They are used together with the following detailed description to explain the present disclosure, but do not constitute a limitation thereof. In the drawings:

[0058] Figure 1 This is a schematic diagram of a fire water tank antifreeze system provided in an embodiment of the present invention.

[0059] Figure 2 This is a schematic diagram of the execution flow of a method for implementing a fire water tank antifreeze system according to an embodiment of the present invention.

[0060] Figure 3 This is one implementation provided by an embodiment of the present invention. Figure 2 A schematic diagram of the execution flow of step S11.

[0061] Figure 4 This is a schematic diagram of the execution flow of another method for implementing a fire water tank antifreeze system provided in an embodiment of the present invention.

[0062] Figure 5 This is a schematic diagram of exemplary hardware and software components of a controller for performing a method for preventing freezing of a fire water tank, provided in an embodiment of the present invention. Detailed Implementation

[0063] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0064] The specific embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit this disclosure.

[0065] This invention provides a fire water tank antifreeze system, see [link / reference]. Figure 1 As shown, the method includes:

[0066] Floating turbulence control devices, controllers, sensor modules, and underwater heating devices;

[0067] The floating turbulence device is equipped with a turbulence agitator, which is fixed inside the float ring. The float ring enables the fire water tank antifreeze system to float on the water surface when it is placed in the water.

[0068] It consists of a float ring and a turbulence mixer. The float ring provides buoyancy to make the system float on the water surface, and the turbulence mixer changes the water flow state by rotating an impeller.

[0069] A fixed bracket is installed in the gap between the float ring and the impeller of the turbulence mixer. The submersible heating device is installed on the fixed bracket. The submersible heating device is arc-shaped, and the center of the arc is concentric with the axis of the turbulence mixer.

[0070] The controller is communicatively connected to the floating turbulence device, the sensor module, and the submersible heating device; the sensor module includes a temperature sensor.

[0071] In step S11, the sensor module collects water surface temperature data in real time through the temperature sensor;

[0072] In step S12, the controller receives the water surface temperature data reported by the sensor module, and if it determines that the conditions for starting heating are met based on the water surface temperature data, it controls the submersible heating device to perform heating operation and controls the impeller to rotate to perform turbulence operation; if it determines that the conditions for stopping heating are met based on the water surface temperature data, it controls the submersible heating device to stop performing heating operation and controls the impeller to stop rotating.

[0073] The float ring can be made of lightweight materials, such as polyethylene foam, which has a density less than water and provides stable buoyancy. The impeller of the turbulence mixer is designed with a curved shape. When the motor drives the impeller to rotate, the water flow is subjected to the thrust and lift of the blades, generating turbulence. This can break the thermal boundary layer on the water surface, accelerate heat transfer, improve the uniformity of water temperature distribution in the fire-fighting water tank, and prevent localized heating and freezing. At the same time, the turbulence effect can increase the contact area between the water and the air, promote heat exchange, and improve the antifreeze effect.

[0074] The temperature sensor can be a high-precision thermistor or a digital temperature sensor, such as one based on the thermoelectric effect or the resistance of semiconductor materials changing with temperature. When the temperature changes, the sensor's resistance or output voltage signal changes accordingly. The weak signal is amplified and filtered by a signal conditioning circuit and then converted into a digital signal. The sensor module then uploads the processed temperature data to the controller via wired or wireless communication.

[0075] The submersible heating device is an equipment that can be submerged in water and heats water by converting electrical energy into heat energy. It uses an electric heating element, which consists of a metal tube, a heating wire, and insulating filler material. When current passes through the heating wire, it generates Joule heat, which is conducted to the surrounding water through the metal tube. The submersible heating device is arc-shaped with its center concentric with the axis of the turbulent mixer, allowing for better alignment between the heating and turbulence areas and more uniform heating. Furthermore, the outer shell of the submersible heating device is made of waterproof and corrosion-resistant materials, ensuring long-term stable operation in water. By rationally controlling the heating power, low-energy heating is achieved.

[0076] In one implementation, the controller collects real-time data from sensors mounted on the float support to monitor the surface water temperature. When the water surface temperature remains below 2°C, the agitator is activated. The agitator impeller generates water spray that spreads outwards at the float position, effectively preventing ice formation in that area, with a power consumption of only 1.5kW. When the air temperature rises and the water surface temperature exceeds 3°C, the agitator is shut off. The controller automatically controls the agitator's start and stop based on changes in water surface temperature, achieving intelligent anti-freeze control. Because the turbulence agitator and temperature sensor are both mounted on the float, they can adjust according to the rise and fall of the water level in the pool, ensuring that the positions of the agitator impeller and temperature sensor remain consistent relative to the water surface.

[0077] The controller connects to the sensor module, submersible heating device, and turbulence mixer via a communication interface. Upon receiving water surface temperature data from the sensor module, the controller compares the real-time temperature with preset start and stop heating thresholds. If the temperature is below the start threshold, the controller outputs a control signal to activate the submersible heating device and simultaneously drive the turbulence mixer impeller to rotate. If the temperature is above the stop threshold, heating and turbulence operation are stopped. This allows for precise adjustment of equipment operation and avoids energy waste.

[0078] The aforementioned technical solution utilizes a floating turbulence device that floats on the water surface, while a turbulent mixer generates flow to ensure uniform water temperature. This, combined with a submersible heating device, provides precise heating, preventing localized overheating or undercooling. The controller, based on real-time water surface temperature data collected by sensor modules, manages the heating and turbulence operations, activating the equipment only when needed. The heating element heats the water, and the turbulent mixer disperses the heated water, achieving efficient heating with low energy consumption. Simultaneously, the control prevents prolonged equipment operation, reducing wear and tear, lowering the risk of equipment damage, and extending the equipment's lifespan. Thus, through low-energy consumption and low cost, this solution effectively solves the problem of ice formation in fire-fighting water tanks during winter and reduces the risk of equipment damage.

[0079] Preferably, the controller is used to control the submersible heating device to perform heating operations and control the impeller to perform turbulence operations when the water surface temperature data determines that the conditions for starting heating are met, including:

[0080] The controller is used to, in step S111, when it is determined from the water surface temperature data that the water surface freezing heating condition among the start heating conditions is met, control the submersible heating device to perform a heating operation with a first heating power and control the impeller to be in a locked non-rotating state, and start a timer, wherein the water surface freezing heating condition includes the impeller being in a non-rotating state, and the water surface temperature data indicates that the water surface temperature is lower than the freezing point risk temperature threshold.

[0081] In this embodiment, when the water surface temperature data collected by the sensor module is transmitted to the controller, the controller determines, based on preset logic, that the conditions for water surface freezing and heating are met. At this time, the controller sends a command to the submersible heating device to operate at a first heating power. This first heating power is set comprehensively based on factors such as the volume of the fire-fighting water tank, the specific heat capacity of water, and the ambient temperature, ensuring rapid water temperature increase without excessive energy waste. Simultaneously, the controller locks the impeller of the turbulent mixer, keeping it stationary to prevent the impeller from consuming additional energy during rotation. The timing function is then activated.

[0082] In step S112, when the timing reaches the preset duration, the impeller is controlled to rotate at a first speed to perform a turbulence operation.

[0083] In this embodiment, when the timer reaches a preset duration, it indicates that the submersible heating device has been operating for a period of time, and a certain temperature gradient may have formed locally on the water surface. At this time, the controller sends a command to the turbulence mixer to rotate its impeller at a first rotational speed. The first rotational speed is determined based on factors such as the viscosity of the water and the size of the fire-fighting water tank, enabling the impeller to generate a suitable turbulence effect. When the impeller rotates, it generates tangential and axial forces on the surrounding water, causing the water to form turbulent flow and up-and-down rolling. This turbulence can break the thermal boundary layer on the water surface, accelerate heat transfer, and make the heat generated by the heating device more evenly distributed throughout the fire-fighting water tank, avoiding local overheating or undercooling, further improving heating efficiency, and effectively preventing the water surface from freezing.

[0084] In one embodiment, after the system is powered on, the controller first reads the water surface temperature data reported by the temperature sensor, for example, -25°C. Then, if the water surface temperature data is determined to be ≤0.5°C, which is considered a freezing point risk temperature threshold, the controller locks the start command for the agitator. The submersible heating device is activated to perform a heating operation at a first heating power (e.g., 2000W) to centrally heat the ice layer tightly surrounding the impeller and shaft system for a preset duration t. After heating is completed, the controller starts the turbulent agitator.

[0085] The above-mentioned technical solution, when meeting the heating conditions for water surface freezing, first heats with an appropriate initial heating power to avoid energy waste, while simultaneously locking the impeller to reduce unnecessary energy consumption. After the preset time is reached, the impeller turbulence is activated to ensure uniform heat distribution and prevent localized freezing. This staged control method precisely adjusts equipment operation according to actual needs, ensuring heating effect while reducing energy consumption. Moreover, the reasonable operating sequence and parameter settings reduce frequent start-ups and shutdowns and excessive operation of the equipment, reducing equipment wear, extending equipment life, and reducing the risk of equipment damage. It effectively solves the problem of water surface freezing in fire-fighting water tanks in winter in a low-energy and low-cost manner.

[0086] Preferably, before the controller controls the first heating power of the submersible heating device to perform the heating operation and controls the impeller to be in a locked, non-rotating state, it further includes:

[0087] In step S11a, a sliding surface function s based on temperature and time is defined, where s = c × (T ref -T cur )+d(T ref -T cur ) / dt, where c is the weight greater than zero, T ref For reference water surface temperature, T cur The water surface temperature is represented by water surface temperature data collected at any point in history.

[0088] Wherein, the sliding surface function s is a function used to describe the relationship between the system state and the desired state, c is a weight greater than zero used to adjust the proportion of temperature deviation and temperature change rate in the sliding surface; T ref It refers to the reference water surface temperature, i.e., the desired water surface temperature; T cur It represents the water surface temperature as measured by water surface temperature data collected at any point in history.

[0089] In this embodiment, the temperature deviation reflects the difference between the current water surface temperature and the desired temperature, while the rate of temperature change reflects the trend of temperature change. When c is large, the temperature deviation dominates in the sliding surface function, focusing more on quickly eliminating the temperature deviation; when c is small, the rate of temperature change has a greater impact, focusing more on the stability of temperature change. In this way, the sliding surface function can comprehensively describe the relationship between the system state and the desired state.

[0090] In step S11b, the exponential reaching law ds / dt=-ε×sign(s)-k×s is selected, where ε and k are positive numbers used to ensure that the sliding surface is reached in a finite time and to reduce chattering, and sign is a sign function based on s;

[0091] Among them, the exponential reaching law ds / dt describes the rate of change of the sliding surface function s with time, and sign is a sign function based on s. When s is greater than 0, sign(s)=1; when s is less than 0, sign(s)=-1; when s is equal to 0, sign(s)=0.

[0092] In this embodiment, -ε×sign(s) is a constant-velocity approaching term, causing the system state to approach the sliding surface at a constant speed; -k×s is an exponential approaching term. As the system state approaches the sliding surface, the value of s gradually decreases, and the effect of this term gradually weakens, but it enables the system state to converge to the sliding surface more quickly. The values ​​of ε and k need to be adjusted according to the specific characteristics of the system. A larger ε can speed up the system's arrival at the sliding surface, but may cause greater chattering; a larger k can reduce chattering, but may increase the time it takes for the system to reach the sliding surface. By reasonably selecting ε and k, chattering can be effectively reduced while ensuring rapid system convergence.

[0093] In step S11c, a first-order model of heating power P versus temperature change rate is established: dT cur / dt =aP-b(T cur -T env Combining the inverse solution of the sliding surface derivative with the equivalent control law, T env Let be the ambient temperature, a be the heating power coefficient representing the contribution of unit heating power P to the rate of change of water surface temperature, and b be the heat dissipation coefficient representing the rate of change of temperature caused by the temperature difference between unit water surface and environment.

[0094] Among them, dT cur / dt represents the rate of change of water surface temperature, a is the heating power coefficient, which is used to represent the contribution of unit heating power P to the rate of change of water surface temperature, and b is the heat dissipation coefficient, which is used to represent the rate of change of temperature caused by the temperature difference between a unit water surface and the environment.

[0095] In this embodiment, based on thermodynamic principles, the water surface temperature is increased by heating power P, and its contribution is related to the heating power coefficient a. The larger the a, the greater the impact of unit heating power on the rate of temperature change. Simultaneously, a temperature difference exists between the water surface and the environment, leading to heat loss. The heat dissipation coefficient b reflects this heat dissipation effect; the larger the b, the greater the rate of temperature change caused by a unit temperature difference. By establishing this first-order model, the relationship between heating power and the rate of change of water surface temperature can be quantified, providing a basis for subsequently solving the equivalent control law. Combining the sliding surface derivative, the equivalent control law can be obtained through inverse solution, thereby determining the heating power required to maintain sliding motion.

[0096] In step S11d, according to the total control law P=Peq+Psw, where Peq is used to maintain the sliding motion and Psw=(ε·sign(s)+k·s) / a, the actual parameters are substituted to obtain the heating power expression, and the lower limit of the heating power P is constrained according to the second heating power constraint.

[0097] In this embodiment, substituting the equivalent control law and sliding mode control term into the overall control law yields an expression for the heating power P. The overall control law comprehensively considers the requirements of maintaining sliding mode motion and ensuring the system state converges quickly to the sliding surface. Simultaneously, to prevent the heating power from being too low to effectively heat the system, a lower limit for the heating power P is constrained based on a second heating power constraint. This ensures that in practical applications, the heating power meets the control requirements without becoming ineffective due to excessively low power, thus improving the system's reliability and stability.

[0098] In step S11e, the sliding surface function s and its derivative are calculated based on the real-time sampled water surface temperature data, and then substituted into the overall control law to obtain the first heating power.

[0099] In this embodiment, after real-time acquisition of water surface temperature data, the value of s is calculated based on the expression of the sliding mode surface function s, and the derivative of s is calculated using numerical methods (such as the finite difference method). Substituting the calculated s and its derivative into the overall control law P=Peq + Psw, the required first heating power at the current moment can be obtained. This enables dynamic adjustment of the heating power based on the real-time system status, allowing the water surface temperature to quickly and stably reach the desired value, thus improving the system's adaptability and control accuracy.

[0100] The aforementioned technical solution, through defining a sliding surface function, selecting an exponential reaching law, establishing a first-order model, and designing a general control law, achieves precise calculation of the first heating power. This power quickly reaches and stabilizes on the sliding surface within a finite time, reducing chattering and improving control stability and robustness. Simultaneously, it dynamically adjusts the heating power based on real-time sampled data, making the heating process more efficient and energy-saving, reducing energy waste, and enabling precise control of the fire water tank's heating power. This solution addresses the winter heating problem of fire water tanks in a low-energy and low-cost manner, effectively preventing water surface freezing.

[0101] Preferably, the controller is further configured to:

[0102] In step S21, the operating current of the turbulent mixer is collected in real time by the current sensor in the sensor module;

[0103] In this embodiment, when the turbulent mixer is powered on, current flows through its internal wires, generating a magnetic field. The magnetic core in the current sensor senses this magnetic field, and according to the law of electromagnetic induction, the change in magnetic flux in the core induces an electromotive force (EMF) in the windings. This induced EMF is converted into a voltage or current signal proportional to the operating current. The voltage or current signal is transmitted to the control system, which performs analog-to-digital conversion and other processing to obtain a precise value of the operating current of the turbulent mixer. By acquiring the operating current in real time, the operating status of the turbulent mixer can be understood promptly.

[0104] In step S22, if it is determined that the impeller of the turbulence mixer is in an abnormal rotation state based on the operating current, the steps of controlling the submersible heating device to perform heating operation with a first heating power and controlling the impeller to be locked and not rotated are repeatedly executed until the preset time is reached, and the impeller is controlled to rotate at a first speed to perform turbulence operation, until it is determined that the impeller of the turbulence mixer is in a normal rotation state based on the operating current.

[0105] Abnormal rotation states can include situations where the impeller rotation becomes stuck or the speed is abnormal due to ice formation on the water surface.

[0106] In this embodiment, when the impeller is determined to be in an abnormal rotation state based on the collected operating current, it indicates that the impeller may be unable to operate normally due to water surface freezing. At this time, the submersible heating device is controlled to perform a heating operation at a first heating power. This first heating power is relatively high and can quickly raise the water temperature to prevent the water surface from freezing. Simultaneously, the impeller is controlled to be locked in a non-rotating state to prevent forced rotation and damage to the equipment. Then, a timer is started, and this operation continues until the preset time is reached.

[0107] Furthermore, after the preset time is reached, the impeller is controlled to rotate at a first speed to perform a turbulence operation. Since the first speed is relatively low, the impeller can be rotated tentatively to see if it can return to normal. If, based on the operating current, the impeller still has not returned to normal rotation, the above process is repeated until the impeller resumes normal rotation. This cyclical operation can gradually troubleshoot and resolve impeller rotation problems while ensuring that the heating function is not significantly affected.

[0108] In step S23, if it is determined that the impeller of the turbulent mixer is in a normal rotating state based on the operating current, then the impeller of the turbulent mixer is controlled to perform turbulence operation at a second rotation speed and the submersible heating device is controlled to perform heating operation at a second heating power, wherein the first rotation speed is less than the second rotation speed and the first heating power is greater than the second heating power.

[0109] Among them, the normal rotation state is when the impeller rotates stably according to the design requirements; the second speed is the speed when the impeller is under normal turbulence; and the second heating power is the heating power of the submersible heating device when the impeller is rotating normally.

[0110] In this embodiment of the disclosure, when the impeller is determined to be in a normal rotating state based on the operating current, it indicates that the turbulence mixer can operate normally. At this time, the control system controls the impeller of the turbulence mixer to perform turbulence operation at a second rotational speed. The second rotational speed is relatively high, which can generate strong turbulence in the water and promote uniform heat distribution.

[0111] Simultaneously, the submersible heating device is controlled to operate at a second heating power. This second heating power is relatively smaller than the first, because heat can be transferred more evenly during normal impeller turbulence, and a higher heating power is not required to maintain the water temperature. By setting a second rotation speed and a second heating power, both heating effect and energy utilization efficiency can be guaranteed, allowing the entire system to operate in a stable and efficient state, meeting the antifreeze and temperature maintenance requirements of the fire water tank in winter.

[0112] In one implementation, the starting current is monitored. The water tank antifreeze monitoring unit integrates the current monitoring units for the mixer and heater, which can monitor current changes in real time. If the current is normal, it indicates successful thawing, and the system switches to normal antifreeze mode; if the current is overloaded, it indicates that there is still seizing, so the heater is restarted and circulated for 5 minutes until thawing is successful.

[0113] The above technical solution collects the operating current of the turbulent mixer in real time, enabling timely and accurate judgment of the impeller rotation status. When the impeller rotates abnormally, it cyclically performs heating and locking operations, preventing equipment damage while ensuring heating function, gradually restoring the impeller to normal rotation. After the impeller resumes normal rotation, the speed and heating power are adjusted appropriately to ensure uniform heat distribution, improving energy utilization efficiency and reducing energy consumption. This allows for phased and intelligent control, enhancing system stability and reliability, effectively preventing the fire water tank surface from freezing, and ensuring the safe and stable operation of the fire water tank during winter.

[0114] Preferably, the controller is further configured to:

[0115] In step S31, when the submersible heating device is in the heating operation state and / or the impeller is in the rotating turbulence operation state, the liquid level data collected in real time by the liquid level sensor in the sensor module is obtained, and the liquid level sensor is deployed on the bottom surface of the floating turbulence device;

[0116] Among them, the liquid level sensor is a sensor used to measure the height of the liquid level. The liquid level sensor is deployed on the bottom surface of the floating turbulence device, which can more accurately sense the water level height.

[0117] In this embodiment of the disclosure, the liquid level sensor starts working when the submersible heating device is in the heating operation state and / or the impeller is rotating in the turbulence operation state. The liquid level sensor is based on the pressure sensing principle; as the water level changes, the water pressure on the bottom surface of the sensor also changes accordingly. The sensor converts the sensed water pressure into an electrical signal. Through internal signal processing circuitry, the electrical signal is amplified, filtered, and then converted into a digital signal proportional to the liquid level height.

[0118] In step S32, it is determined whether the water level is lower than the safe rotation threshold of the impeller based on the liquid level data;

[0119] The safe rotation threshold is the minimum water level height set to ensure the impeller rotates normally and avoids damage. When the water level is below this threshold, the impeller may malfunction due to exposure to air or poor contact with the water surface.

[0120] In this embodiment, after receiving the acquired liquid level data, the controller compares it with a pre-set impeller safe rotation threshold. The safe rotation threshold is determined after comprehensively considering factors such as the impeller's structure, size, rotation method, and working environment. For example, if the impeller's design requires it to be completely submerged in water to a certain depth to rotate normally, then the safe rotation threshold will be set as the water level height corresponding to this minimum submersion depth. The controller implements the comparison logic through programming: if the liquid level data is less than the safe rotation threshold, it is determined that the water level height is below the impeller's safe rotation threshold; otherwise, it is determined that the water level height is normal.

[0121] In step S33, if it is determined that the water level is lower than the safe rotation threshold of the impeller, then the shutdown condition is met, and the power supply of the turbulence mixer and the submersible heating device is turned off to control the submersible heating device to stop performing heating operations and to control the impeller to stop rotating.

[0122] In this embodiment of the disclosure, when the water level is determined to be below the safe rotation threshold of the impeller, the shutdown condition is determined to be met, and the controller can generate a control command. For the submersible heating device, the control command will cut off its power supply, causing it to stop heating operation, preventing damage to the heating device due to dry burning, and also avoiding energy waste. For the impeller, the control command can be sent to the impeller's drive motor to stop the motor from rotating, preventing the impeller from idling in environments with little air or water, reducing mechanical wear and noise.

[0123] The controller transmits control commands accurately to the submersible heating device and the impeller drive components through the corresponding interface circuit, ensuring that they can respond in a timely manner and stop working.

[0124] The aforementioned technical solution acquires real-time liquid level data during the heating process of the submersible heating device and the impeller's turbulence, enabling timely monitoring of water level changes. Based on the liquid level data, it determines whether the water level is below the impeller's safe rotation threshold, providing crucial information for safe equipment operation. When the water level is too low, it quickly controls the submersible heating device to stop heating and the impeller to stop rotating, effectively preventing dry burning of the heating device and impeller idling. This achieves intelligent monitoring and protection of the fire water tank's operating status, extending equipment lifespan and reducing the risk of equipment damage. Simultaneously, it reduces unnecessary energy consumption, improves energy efficiency, and ensures the safe and stable operation of the fire water tank in special environments such as winter.

[0125] Preferably, the controller is further configured to:

[0126] If the water level data is determined to meet the self-starting conditions, the power supply of the turbulence mixer and the submersible heating device is turned on. The self-starting conditions include that the power supply of the turbulence mixer and the submersible heating device is turned off due to meeting the shutdown conditions, and the water level data indicates that the water level is higher than the preset safe water level.

[0127] In this embodiment of the disclosure, if new water is injected into the fire water tank and the liquid level in the fire water tank rises, if it is determined that the water level data meets the self-starting conditions, for example, the liquid level is greater than a preset liquid level threshold, then the working power supply of the turbulence mixer and the submersible heating device is turned on.

[0128] Preferably, the controller is further configured to:

[0129] In step S41, the ambient relative humidity data collected in real time by the humidity sensor in the sensor module and the wind speed data collected by the wind speed sensor in the sensor module are obtained.

[0130] Among them, the humidity sensor is used to collect ambient humidity and convert it into a measurable signal; the ambient relative humidity is the percentage of water vapor pressure in the air to the saturated water vapor pressure at the same temperature; the wind speed sensor is used to measure the air flow speed.

[0131] In this embodiment, the humidity sensor can be a capacitive humidity sensor containing a hygroscopic material. When the relative humidity changes, the hygroscopic material adsorbs or releases water molecules, causing a change in its dielectric constant. Since the capacitance between the sensor electrodes is related to the dielectric constant, the relative humidity data can be obtained by measuring the change in capacitance. The wind speed sensor can employ a cup-type or hot-wire principle. In a cup-type wind speed sensor, when the wind blows, the rotation speed of the cup is proportional to the wind speed. The rotation speed is converted into an electrical signal through a photoelectric or magnetoelectric conversion device, thereby obtaining the wind speed data. These sensors collect data in real time and convert analog signals into digital signals before transmitting them to the controller.

[0132] In step S42, the predicted probability of water surface freezing is predicted based on the ambient relative humidity data, wind speed data, and water surface temperature data.

[0133] In this embodiment, after receiving ambient relative humidity data, wind speed data, and water surface temperature data, the controller uses a pre-established mathematical model to make predictions. This model comprehensively considers the influence of multiple factors on water surface icing. Higher ambient relative humidity means a greater water vapor content in the air, making it easier to reach saturation and condense into ice. Wind speed affects heat exchange on the water surface; high wind speeds accelerate heat loss from the water surface, promoting icing. Water surface temperature is a direct and critical factor for icing; when the water surface temperature is close to or below the freezing point, the probability of icing increases significantly. The model is trained and optimized using extensive experimental data and historical records, and calculates the predicted probability of water surface icing based on the three input parameters.

[0134] In step S43, it is determined whether the predictive antifreeze conditions are met based on the predicted icing probability.

[0135] Among them, predictive antifreeze conditions are pre-set criteria used to determine whether antifreeze measures need to be activated, and are related to the predicted probability of freezing.

[0136] In this embodiment, the controller compares the predicted icing probability with pre-set predictive antifreeze conditions. The predictive antifreeze condition can be a threshold range. For example, when the predicted icing probability exceeds 70%, the predictive antifreeze condition can be determined to be met. The controller implements the comparison logic through programming; if the predicted icing probability is within the threshold range, the predictive antifreeze condition is determined to be met; otherwise, it is determined not to be met. This allows for early detection of the risk of water surface freezing.

[0137] In step S44, if it is determined that the predictive antifreeze conditions are met, the submersible heating device is controlled to remain in a state of not performing heating operation and the impeller is controlled to perform turbulence operation at a third rotational speed.

[0138] The third rotational speed is the specific rotational speed at which the impeller performs turbulence operation when the predictive antifreeze conditions are met.

[0139] In this embodiment of the disclosure, when the predictive antifreeze conditions are determined to be met, the controller issues a control command. For the submersible heating device, the control command keeps it in a state where it does not perform heating operation. This is because when the predicted probability of freezing is high but freezing has not yet occurred, the impeller's turbulence operation can disrupt the ice layer structure that may form on the water surface, while avoiding unnecessary heating and wasting energy. For the impeller, the control command makes it rotate at a third speed to perform the turbulence operation. The third speed is set according to the actual situation to ensure effective turbulence and prevent water surface freezing, without causing excessive equipment wear or noise due to excessive speed.

[0140] The controller can accurately transmit commands to the submersible heating device and the impeller drive components through the corresponding interface circuit to achieve precise control.

[0141] The aforementioned technical solution acquires real-time relative humidity and wind speed data, and combined with water surface temperature data, can comprehensively and accurately predict the probability of water surface freezing. Based on the predicted freezing probability, it determines whether predictive antifreeze conditions are met, allowing for early detection of freezing risks and providing a scientific basis for taking antifreeze measures. When the conditions are met, the submersible heating device is controlled to not heat, and the impeller operates at an appropriate speed to turbulent the airflow, achieving predictive antifreeze control of the fire water tank. This effectively prevents water surface freezing, ensuring the normal use of the fire water tank, while avoiding unnecessary energy consumption and reducing equipment operating costs. Simultaneously, this intelligent control method improves system reliability and stability and reduces manual intervention.

[0142] Preferably, the controller is further configured to predict the probability of water surface freezing based on ambient relative humidity data, wind speed data, and the water surface temperature data, including:

[0143] In step S421, a logistic regression classification model is constructed with the ambient relative humidity data, the wind speed data, and the water surface temperature data as input features and the linear score of icing as the dependent variable.

[0144] Among them, relative humidity data reflects the ratio of water vapor content to saturated water vapor content in the air; wind speed data reflects the air flow speed; water surface temperature data represents the thermal state of the water surface; input features are variables used for model training and prediction; linear score is an intermediate value of the logistic regression classification model output, used to measure the degree of linear relationship between input features and the probability of icing; the logistic regression classification model is a statistical model used for classification problems, which establishes a linear relationship between input features and output categories, and then obtains probability values ​​through the logistic function transformation.

[0145] In this embodiment, the logistic regression classification model is constructed based on linear regression. First, the input features are determined to be ambient relative humidity data, wind speed data, and water surface temperature data, with the dependent variable being the linear score of icing. The model assumes a linear relationship between the input features and the linear score. By collecting a large amount of historical data and using optimization algorithms such as least squares to continuously adjust the coefficients, the linear score output by the model is made to reflect the linear relationship between the input features and icing as accurately as possible, thus constructing the logistic regression classification model to be solved.

[0146] In step S422, the linear score is substituted into the logistic function with the linear score as the independent variable and the icing probability as the dependent variable, and the probability value of the icing probability is determined based on the historically collected environmental relative humidity data, wind speed data, and water surface temperature data.

[0147] The logistic function maps linear scores to probability values. The linear score *z* output by the model is substituted into the logistic function. This function exhibits an S-shaped curve characteristic, mapping the linear score from the real number range to the (0,1) interval, thus obtaining the icing probability. To determine the probability value, historically collected environmental relative humidity, wind speed, and water surface temperature data are used. These data are input into the constructed model to obtain linear scores, which are then substituted into the logistic function for calculation. Through calculation and statistical analysis of a large amount of historical data, the model parameters are continuously adjusted to make the calculated icing probability as close as possible to the actual situation, thereby determining the accurate icing probability value.

[0148] In step S423, based on the probability values ​​and the corresponding real event labels, a single likelihood is constructed for the historically collected environmental relative humidity data, wind speed data, and water surface temperature data that are grouped together at the same collection time.

[0149] Among them, the real event label is the identifier of whether or not ice actually formed in the historical data, such as 1 for ice and 0 for no ice; the single likelihood is a measure of the degree of matching between the ice probability corresponding to a certain set of historical data and the real event label under given model parameters.

[0150] In this embodiment, for each set of historically collected environmental relative humidity, wind speed, and water surface temperature data, the corresponding icing probability value is obtained. Based on the actual event label, if icing actually occurs (label is 1), the individual likelihood is the icing probability value; if no icing actually occurs (label is 0), the individual likelihood is 1 - the icing probability value. For example, if a set of data calculates an icing probability of 0.7 and the actual event label is 1, then the individual likelihood is 0.7; if the actual event label is 0, then the individual likelihood is 1 - 0.7 = 0.3. In this way, the individual likelihood corresponding to a set of historical data collected at the same time is constructed.

[0151] In step S424, a total likelihood function is constructed based on the product of the individual likelihoods corresponding to each group, and the optimal values ​​of the model coefficients are found by maximum likelihood estimation based on the total likelihood function to determine the target logistic regression classification model.

[0152] The total likelihood function is the product of the individual likelihoods of all groups, used to comprehensively measure the model's fit on the entire historical dataset; maximum likelihood estimation is a parameter estimation method that determines the optimal model parameters by finding the model coefficient values ​​that maximize the total likelihood function.

[0153] Detailed technical principle: The total likelihood function is constructed by multiplying the individual likelihoods of each group. To find the optimal model coefficient values, the maximum likelihood estimation method is used. Taking the logarithm of the total likelihood function transforms the product into a summation, facilitating calculation and differentiation. Then, the partial derivatives of the model coefficients are calculated and set to zero, resulting in a set of equations. Through numerical optimization algorithms, such as gradient descent, the model coefficients are iteratively adjusted until the total likelihood function (or log-total likelihood function) reaches its maximum value. The corresponding model coefficient values ​​at this point are the optimal solution, thus determining the target logistic regression classification model.

[0154] In step S425, the real-time collected ambient relative humidity data, wind speed data, and water surface temperature data are substituted into the target logistic regression classification model to obtain the predicted icing probability corresponding to the current collection time.

[0155] Among them, the target logistic regression classification model is a model obtained through training and optimization for predicting the probability of icing; the predicted probability of icing at the current collection time is the icing probability estimate obtained by inputting the real-time collected data into the target model.

[0156] In this embodiment, real-time collected ambient relative humidity data, wind speed data, and water surface temperature data are used as inputs and substituted into a predetermined target logistic regression classification model. Following a pre-defined calculation process, the model first calculates a linear score, then substitutes the linear score into the logistic function, and finally outputs the predicted icing probability corresponding to the current data collection time. The probability value reflects the likelihood of water surface icing under the current environmental conditions.

[0157] The above technical solution constructs and optimizes a logistic regression classification model, which fully considers the influence of multiple factors such as relative humidity, wind speed, and water surface temperature on icing, thus improving the accuracy of prediction. Historical data is used to determine probability values ​​and construct the total likelihood function. The optimal model coefficients are found through maximum likelihood estimation, allowing the model to better fit the actual situation. Substituting real-time data into the target model yields the predicted icing probability, reflecting the icing risk in the current environment in a timely manner. This allows for proactive countermeasures to avoid equipment damage and safety hazards caused by icing, achieving accurate prediction of water surface icing probability, ensuring stable system operation, reducing maintenance costs, and improving overall safety and reliability.

[0158] Preferably, the submersible heating device is semi-circular, and the fire water tank antifreeze system is equipped with two semi-circular submersible heating devices, which are arranged symmetrically.

[0159] In this embodiment, the fire water tank antifreeze system can monitor its own status and issue warnings in real time when it is in operation. If the fire water tank antifreeze system has not been used for a long time (2-3 quarters), it cannot be guaranteed that all sub-units of the system will be able to function normally when it is restarted before winter. After the system is started, the controller actively reads the data of each sensor unit and starts the mixer and heater to perform system self-test. The controller monitors the sensor data and the operating current of the mixer and heater. When the sensor data or the operating current is abnormal, it actively reports the warning information.

[0160] This embodiment abandons the crude goal of preventing freezing throughout the entire system, instead using a low-power mixer to maintain water flow only at key water intake points, achieving ultra-low energy consumption from the source. The combination of the float ring and anti-rotation support enables the core equipment to operate adaptively at all water levels, reducing the risk of cable twisting. The intelligent control process of detecting, thawing, and restarting after power-on, with a built-in thawing cycle, is a core innovation that addresses the risk of seizure during power outages. The annular heater is tightly integrated into the most easily frozen part of the mixer shaft system, maximizing thawing efficiency. The introduction of a liquid level sensor enables low-water-level self-protection of the equipment. System power-on self-testing and real-time status monitoring during operation enhance the system's intelligence level and improve operational and maintenance efficiency. A metal protective mesh is wrapped around the inside and top of the float ring to prevent ice from splashing and puncturing it during agitation, further improving system reliability.

[0161] Compared to traditional electric heating or full-field stirring solutions, this system reduces power consumption and significantly lowers operating costs. Its self-repair capability from frozen states makes it suitable for extremely cold regions with unstable power supplies. The floating design allows it to ignore water level changes, and the liquid level protection function prevents dry-burning damage, making it widely applicable. Through sensor fusion, complex risk assessment, equipment protection, and energy efficiency management are achieved at a lower cost, resulting in excellent system cost-effectiveness. The modular and miniaturized design requires no modification to the water tank, allowing for rapid deployment and easy removal for routine maintenance, significantly reducing lifecycle costs. The inner and top sides of the float are wrapped with metal protective mesh to prevent ice from splashing and puncturing the float, enhancing the system's adaptability to extreme scenarios and improving overall reliability. This enhances the system's adaptability and reliability in extremely harsh environments.

[0162] This invention provides a method for preventing freezing of fire water tanks, applied to the controller of the fire water tank freezing prevention system described in any of the foregoing embodiments. The fire water tank freezing prevention system includes: a floating turbulence device, a controller, a sensor module, and a submersible heating device.

[0163] The floating turbulence device is equipped with a turbulence agitator, which is fixed inside the float ring. The float ring enables the fire water tank antifreeze system to float on the water surface when it is placed in the water.

[0164] A fixed bracket is installed in the gap between the float ring and the impeller of the turbulence mixer. The submersible heating device is installed on the fixed bracket. The submersible heating device is arc-shaped, and the center of the arc is concentric with the axis of the turbulence mixer.

[0165] The controller is communicatively connected to the floating turbulence device, the sensor module, and the submersible heating device; the sensor module includes a temperature sensor.

[0166] The method includes:

[0167] Acquire the real-time water surface temperature data collected by the temperature sensor in the sensor module;

[0168] If the conditions for starting heating are met based on the water surface temperature data, the submersible heating device is controlled to perform heating operations and the impeller is controlled to rotate to perform turbulence operations.

[0169] If the conditions for stopping heating are met based on the water surface temperature data, the submersible heating device is controlled to stop performing heating operations and the impeller is controlled to stop rotating.

[0170] Figure 5 The diagram shows a controller 100, including a processor 1001 and a memory 1003. The processor 1001 and memory 1003 are connected, for example, via a bus 1002. Optionally, the fire water tank antifreeze method 100 may further include a communication component 1004, which can be used for data interaction between the device 100 and other devices, such as data transmission and / or data reception. It should be noted that in actual scheduling, the communication component 1004 is not limited to one, and the structure of this fire water tank antifreeze method 100 does not constitute a limitation on the embodiments of this application.

[0171] Processor 1001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 1001 may also be a combination that implements computing functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0172] Bus 1002 may include a pathway for transmitting information between the aforementioned components. Bus 1002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 1002 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0173] The memory 1003 may be ROM (Read Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, other magnetic storage devices, or any other medium capable of carrying or storing program code and capable of being read by a computer, without limitation herein.

[0174] The memory 1003 is used to store program code for executing the embodiments of this disclosure, and its execution is controlled by the processor 1001. The processor 1001 is used to execute the program code stored in the memory 1003 to implement the steps shown in the aforementioned embodiments of the fire water tank antifreeze method.

[0175] The preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings. However, the present disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present disclosure, various changes, modifications, substitutions and variations can be made to these embodiments, and all such changes, modifications, substitutions and variations fall within the protection scope of the present disclosure.

[0176] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction, and such combinations should also be considered as part of this disclosure. To avoid unnecessary repetition, this disclosure will not further describe the various possible combinations. The technical scope of this application is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A fire-fighting water tank antifreeze system, characterized in that, The system includes: Floating turbulence control devices, controllers, sensor modules, and underwater heating devices; The floating turbulence device is equipped with a turbulence agitator, which is fixed inside the float ring. The float ring enables the fire water tank antifreeze system to float on the water surface when it is placed in the water. A fixed bracket is installed in the gap between the float ring and the impeller of the turbulence mixer. The submersible heating device is installed on the fixed bracket. The submersible heating device is arc-shaped, and the center of the arc is concentric with the axis of the turbulence mixer. The controller is communicatively connected to the floating turbulence device, the sensor module, and the submersible heating device; the sensor module includes a temperature sensor. The sensor module is used to collect water surface temperature data in real time through the temperature sensor. The controller is used to receive the water surface temperature data reported by the sensor module, and when it is determined from the water surface temperature data that the conditions for starting heating are met, it controls the submersible heating device to perform heating operation and controls the impeller to rotate to perform turbulence operation; when it is determined from the water surface temperature data that the conditions for stopping heating are met, it controls the submersible heating device to stop performing heating operation and controls the impeller to stop rotating.

2. The fire water tank antifreeze system according to claim 1, characterized in that, The controller is used to control the submersible heating device to perform heating operations and control the impeller to perform turbulence operations when the water surface temperature data determines that the conditions for starting heating are met, including: When the controller determines that the water surface freezing heating condition among the start heating conditions is met based on the water surface temperature data, it controls the submersible heating device to perform a heating operation with a first heating power and controls the impeller to be locked in a non-rotating state, and starts a timer. The water surface freezing heating condition includes the impeller being in a non-rotating state and the water surface temperature data indicating that the water surface temperature is lower than the freezing point risk temperature threshold. When the preset time is reached, the impeller is controlled to rotate at a first speed to perform a turbulence operation.

3. The fire water tank antifreeze system according to claim 2, characterized in that, Before the controller controls the first heating power of the submersible heating device to perform the heating operation and controls the impeller to be in a locked non-rotating state, it further includes: Define a sliding surface function s based on temperature and time, where s = c × (T ref -T cur )+d(T ref -T cur ) / dt, where c is the weight greater than zero, T ref For reference water surface temperature, T cur The water surface temperature is represented by water surface temperature data collected at any point in history. We choose the exponential reaching law ds / dt=-ε×sign(s)-k×s, where ε and k are positive numbers used to ensure that the sliding surface is reached in a finite time and to reduce chattering, and sign is a sign function based on s; Establish a first-order model of heating power P versus the rate of temperature change: dT cur / dt =aP-b(T cur -T env Combining the inverse solution of the sliding surface derivative with the equivalent control law, T env Let be the ambient temperature, a be the heating power coefficient representing the contribution of unit heating power P to the rate of change of water surface temperature, and b be the heat dissipation coefficient representing the rate of change of temperature caused by the temperature difference between unit water surface and environment. According to the overall control law P=Peq+Psw, where Peq is used to maintain the sliding mode motion and Psw=(ε·sign(s)+k·s) / a, the heating power expression is obtained by substituting the actual parameters, and the lower limit of the heating power P is constrained according to the second heating power constraint. Based on the real-time sampled water surface temperature data, the sliding surface function s and its derivative are calculated, and substituted into the overall control law to obtain the first heating power.

4. The fire water tank antifreeze system according to claim 2, characterized in that, The controller is also used for: The operating current of the turbulent mixer is collected in real time by the current sensor in the sensor module. If it is determined that the impeller of the turbulence mixer is in an abnormal rotation state based on the operating current, the steps of controlling the submersible heating device to perform heating operation with a first heating power and controlling the impeller to be locked and not rotated are repeatedly executed until the preset time is reached, and the impeller is controlled to rotate at a first speed to perform turbulence operation, until it is determined that the impeller of the turbulence mixer is in a normal rotation state based on the operating current. If the impeller of the turbulence mixer is determined to be in normal rotation state based on the operating current, then the impeller of the turbulence mixer is controlled to perform turbulence operation at a second rotation speed and the submersible heating device is controlled to perform heating operation at a second heating power, wherein the first rotation speed is less than the second rotation speed and the first heating power is greater than the second heating power.

5. The fire water tank antifreeze system according to claim 1, characterized in that, The controller is also used for: When the submersible heating device is in the heating operation state and / or the impeller is in the rotating turbulence operation state, the liquid level data collected in real time by the liquid level sensor in the sensor module is obtained, and the liquid level sensor is deployed on the bottom surface of the floating turbulence device; Determine whether the water level is below the safe rotation threshold of the impeller based on the liquid level data; If it is determined that the water level is lower than the safe rotation threshold of the impeller, then the shutdown condition is met, and the power supply to the turbulence mixer and the submersible heating device is turned off to control the submersible heating device to stop performing heating operations and to control the impeller to stop rotating.

6. The fire water tank antifreeze system according to claim 5, characterized in that, The controller is also used for: If the water level data is determined to meet the self-starting conditions, the power supply of the turbulence mixer and the submersible heating device is turned on. The self-starting conditions include that the power supply of the turbulence mixer and the submersible heating device is turned off due to meeting the shutdown conditions, and the water level data indicates that the water level is higher than the preset safe water level.

7. The fire water tank antifreeze system according to claim 1, characterized in that, The controller is also used for: The system acquires real-time ambient relative humidity data collected by the humidity sensor in the sensor module and wind speed data collected by the wind speed sensor in the sensor module. Based on the ambient relative humidity data, wind speed data, and water surface temperature data, the predicted probability of water surface freezing is predicted. Determine whether the predictive antifreeze conditions are met based on the predicted freezing probability. If the predictive antifreeze conditions are met, the submersible heating device is controlled to remain in a non-heating state and the impeller is controlled to perform a turbulence operation at a third rotational speed.

8. The fire water tank antifreeze system according to claim 7, characterized in that, The controller is also used to predict the probability of water surface freezing based on ambient relative humidity data, wind speed data, and the water surface temperature data, including: A logistic regression classification model is constructed with the relative humidity data, wind speed data, and water surface temperature data as input features and the linear score of icing as the dependent variable. Substitute the linear score into the logistic function with the linear score as the independent variable and the icing probability as the dependent variable, and determine the probability value of the icing probability based on the historically collected environmental relative humidity data, wind speed data, and water surface temperature data. Based on the probability values ​​and the corresponding real event labels, construct a single likelihood for the historically collected environmental relative humidity data, wind speed data, and water surface temperature data at the same collection time as a group; Based on the product of the individual likelihoods corresponding to each group, a total likelihood function is constructed, and based on the total likelihood function, the optimal values ​​of the model coefficients are found by maximum likelihood estimation to determine the target logistic regression classification model. The real-time collected environmental relative humidity data, wind speed data, and water surface temperature data are substituted into the target logistic regression classification model to obtain the predicted icing probability corresponding to the current collection time.

9. The fire water tank antifreeze system according to any one of claims 1-8, characterized in that, The submersible heating device is semi-circular, and the fire water tank antifreeze system is equipped with two of the semi-circular submersible heating devices, which are arranged symmetrically.

10. A method for preventing the freezing of a fire-fighting water tank, characterized in that, A controller applied to the fire water tank antifreeze system according to any one of claims 1-9, wherein the fire water tank antifreeze system comprises: a floating turbulence device, a controller, a sensor module, and a submersible heating device; The floating turbulence device is equipped with a turbulence agitator, which is fixed inside the float ring. The float ring enables the fire water tank antifreeze system to float on the water surface when it is placed in the water. A fixed bracket is installed in the gap between the float ring and the impeller of the turbulence mixer. The submersible heating device is installed on the fixed bracket. The submersible heating device is arc-shaped, and the center of the arc is concentric with the axis of the turbulence mixer. The controller is communicatively connected to the floating turbulence device, the sensor module, and the submersible heating device; the sensor module includes a temperature sensor. The method includes: Acquire the real-time water surface temperature data collected by the temperature sensor in the sensor module; If the conditions for starting heating are met based on the water surface temperature data, the submersible heating device is controlled to perform heating operations and the impeller is controlled to rotate to perform turbulence operations. If the conditions for stopping heating are met based on the water surface temperature data, the submersible heating device is controlled to stop performing heating operations and the impeller is controlled to stop rotating.

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