8988 results about "Thermal source" patented technology

The invention relates to the technical field of heat load prediction, and discloses a heat supply system load prediction method and system, and the method comprises the steps: collecting multi-source sensing data in real time, and collecting outdoor meteorological parameters and building structure information; based on building distribution, a pipe network structure and user load characteristics of a heat supply area, a multi-stage heat supply load prediction model is constructed. And constructing a thermal topological graph model of the heat supply area based on the graph neural network. And periodically collecting parameters of the building-level edge prediction model, the heat exchange station-level aggregation prediction model and the thermal topological graph model, performing global aggregation optimization, and updating and optimizing each edge node model. And obtaining an edge prediction result according to the optimized model, and jointly controlling the heat source output power, the main pump rotating speed and the area valve opening according to the edge prediction result and the heat source level scheduling prediction model. According to the method, the depiction capability of the system on the dynamic load change and the space heat conduction path is improved, and the generalization capability of model updating and the real-time responsiveness of edge deployment are ensured.

The present application belongs to the technical field of material processing, and relates to a mold-free mirror image filament laying method and a mold-free mirror image filament laying system. The method lays a filament ribbon in a mirror image symmetry, without a mold, thereby improving production flexibility and efficiency. The method acquires the temperature and pressure of the filament ribbon in real time, calculates the output power of a heater and the modification value of a filament laying end motion mechanism path by using temperature and pressure differences, and optimizes controller parameters through reinforcement learning, so as to realize stable control of the temperature and pressure. The system comprises a hardware part and a control system. The hardware part includes pressure and heat source components. The control system adjusts through real-time feedback to ensure the quality of filament laying. The present application solves the problem that the temperature and pressure are difficult to accurately control in the process of mold-free mirror image filament laying, and improves the performance of composite products.

The invention discloses a waste heat recovery scheduling method and system for a two-phase cold plate of a data center, and relates to the technical field of refrigeration and heat management. The waste heat recovery scheduling method and system for the two-phase cold plate of the data center comprises the following steps that S1, key thermal parameters and tail end state variables are collected through multiple types of thermal monitoring devices, and thermal state monitoring data are obtained and preprocessed; s2, on the basis of the thermal state monitoring data and in combination with an SLA configuration file, performing priority division on the heat utilization terminals, and constructing a scheduling deviation judgment mechanism to identify thermal state changes; s3, under driving of the regulation and control instruction, accessing multi-source waste heat and distributing the multi-source waste heat to each terminal scene, and evaluating a matching condition of the waste heat and a terminal demand; and S4, based on the change of the heat distribution state and the thermal state monitoring data, identifying an overload risk in combination with a multi-parameter linkage mechanism. The problems that waste heat recovery is insufficient and the energy utilization rate is limited under the light-load and multi-heat-source cooperative working condition are solved.

The invention relates to the technical field of battery safety management, in particular to a battery thermal runaway early warning method and system based on multi-dimensional feature fusion. The method comprises the following steps: collecting thermal characteristic data, gas characteristic data and electrochemical characteristic data of a battery; calculating a temperature gradient vector and an isothermal consistency index by using the thermal characteristic data, and capturing abnormal changes of a battery hot spot region by using a local dynamic sampling increasing method; calculating an internal and external field temperature difference phase difference by utilizing the thermal characteristic data and the gas characteristic data, and judging a heat source attribute by combining a heat contribution ratio model; and calculating a cross-modal early response phase difference, constructing a phase difference feature matrix, combining the temperature gradient vector, the heat source attribute and the phase difference feature matrix to form a fusion feature matrix, and inputting the fusion feature matrix into a dynamic weight fusion discrimination model to calculate a thermal runaway risk probability. According to the invention, based on a multi-dimensional feature fusion method, the thermal runaway risk probability is calculated in real time, and the early-stage accurate early warning of the thermal runaway of the battery is realized.

The invention discloses a heat dissipation driver and electronic equipment, and relates to the technical field of electronic equipment heat dissipation, the heat dissipation driver comprises a frame, a magnetic circuit system, a vibration system and a flow adjusting assembly, the vibration system comprises a vibrating diaphragm and a coil, the coil is located in a magnetic field of the magnetic circuit system, and the outer edge of the vibrating diaphragm is connected with the frame; the vibrating diaphragm, the magnetic circuit system and the frame define a rear cavity, and the vibrating diaphragm is provided with a communication hole communicated with the rear cavity. When the vibrating diaphragm vibrates in the direction close to the magnetic circuit system, the flow adjusting assembly is in an open state, and the flow adjusting assembly is exposed out of the communicating hole so that airflow in the rear cavity can flow out of the rear cavity through the communicating hole. When the vibrating diaphragm vibrates in the direction away from the magnetic circuit system, the flow adjusting assembly is in a closed state, and the flow adjusting assembly blocks the communicating hole, so that airflow in a heat source area of the equipment flows into the rear cavity, and heat dissipation of the equipment is achieved.

The invention discloses a cable tunnel fire risk feature identification system and identification method, and belongs to the technical field of cable tunnel safety monitoring. The whole stage of a fire is covered through multi-class cooperative detection, the target identification precision and scene adaptability are greatly improved, and the safety of the cable tunnel is improved. According to the whole system, a flame and smoke detection unit and a flame / smoke special detection unit are innovatively added to a detection engine module, an original heat source detection unit and an original human body detection unit are combined, a heat source-flame-smoke-human body four-category collaborative detection framework is formed, high-precision recognition is achieved on the basis of a YOLO model framework, and the detection efficiency is improved. Compared with the problems that a traditional system is high in single target detection omission ratio and cannot cover the whole stage of smoldering-initial open fire-violent combustion of a fire, the system has the advantages that the recognition rate of early flame and weak smoke is increased, the false alarm rate is greatly reduced, meanwhile, a heat source of operation and maintenance personnel is prevented from being misjudged as a fire hazard through human body detection, and the safety of the fire hazard is improved. And cable monitoring and personnel safety protection are both considered.

The invention discloses a cable optical fiber temperature measurement monitoring system based on big data AI fusion, particularly relates to the technical field of cable optical fiber temperature measurement monitoring, and aims to realize thermal-electric dynamic coupling monitoring through high-density distributed optical fiber temperature measurement and big data AI fusion modeling and introduction of current load synchronous acquisition, and realize high-density distributed optical fiber temperature measurement and big data AI fusion by means of time synchronization and space relocation processing. The method comprises the following steps: identifying a weak response signal of a thermal inertia hysteresis characteristic and an initial temperature rise stage, constructing a cross-scale time sequence recurrent neural network through multi-dimensional enhancement and vector fusion, outputting a continuous scoring sequence reflecting abnormal credibility, and constructing a risk factor group reflecting a fault evolution path in combination with a scoring fluctuation amplitude, a continuous period and a response delay characteristic, and carrying out positioning offset correction through correlation mapping of risk factors and along-cable temperature distribution and by utilizing a topological relation between optical fiber path coordinates and a cable space, and realizing space reverse projection of an abnormal peak value, thereby recovering an accurate position of a fault heat source and a latent hidden danger section.

The invention discloses a wind-solar complementary energy storage direct current charging method and system based on liquid cooling heat dissipation, and relates to the technical field of energy storage charging. Comprising the following steps: S1, collecting wind-solar complementary energy storage data in real time, and carrying out data preprocessing; s2, converting wind-solar power generation into direct current, judging the flow direction of wind-solar power generation energy, and performing corresponding wind-solar power generation energy transmission power supply; s3, judging the limit of the output power of the charging pile, and controlling and adjusting the output of the charging pile in stages; s4, quantifying the liquid cooling flow required by heat dissipation, and performing heat source heat dissipation on the energy storage system and the charging pile; and S5, carrying out coordinated regulation and control, strategy optimization and multi-dimensional visualization on the flow direction of wind and light power generation energy, charging pile output and heat source heat dissipation. The problems that an existing charging station is difficult to deploy in remote and power transmission difficult areas, high-power charging heat dissipation and energy efficiency bottlenecks are prominent, and the efficiency of traditional air cooling and alternating current conversion is low, so that efficient, safe and green energy supplementation is difficult to achieve are solved.

The invention discloses a new energy automobile hybrid power system cooperative control device and method.The new energy automobile hybrid power system cooperative control device comprises a multi-source data collection module, a cooperative control center and an execution unit, and the multi-source data collection module transmits collected information data to the cooperative control center; the cooperative control center comprises a data fusion unit, an energy management module, a heat management module and a cooperative decision-making unit, the data fusion unit receives data information of the multi-source data acquisition module, carries out fusion processing, and transmits the data information to the energy management module and the heat management module; the energy management module and the heat management module output a control strategy to the collaborative decision-making unit, and the collaborative decision-making unit judges a correction strategy and then sends a control instruction to the execution unit. The method has the advantages that cooperative control of energy management and heat management is achieved, various dimension data of road conditions, driving behaviors, power states and heat source states are fused, the problem of system unbalance caused by single module optimization is solved, and dynamic cooperation of energy management and heat management is achieved.

The present invention relates to the technical field of carbon source preparation, and specifically relates to a carbon source preparation apparatus with a concentration detection function. The carbon source preparation apparatus comprises a frame, a tank body, a stirring system and a detection system, wherein the tank body is fastened and connected to the frame, the tank body being used for dissolution and chain-breaking of kitchen waste slurry; the stirring system is fastened and connected to the tank body; and the detection system is fastened and connected to the stirring system, a built-in sensor of the detection system being used for detecting the carbon source concentration. A heating pipe is provided on the outer side of the tank body, the heating pipe being externally connected to a heat source; the heating pipe maintains the temperature inside the tank body within an appropriate range to ensure the smooth progress of a reaction process, and the heating pipe enables evaporation and concentration of liquid after the reaction is complete. The detection system allows for online real-time monitoring of the carbon source concentration, such that during concentration of a carbon source, the process can be stopped in a timely manner when it is determined that the required concentration is reached after concentration and evaporation for a period of time, thereby reducing energy consumption.

The invention relates to the technical field of compressed carbon dioxide energy storage, and discloses a liquid compressed carbon dioxide energy storage system and method. The system comprises a carbon dioxide circulation system, and the circulation system comprises a first liquid storage tank (1), a first evaporation unit (100), an energy storage unit (200), a second liquid storage tank (6), a second evaporation unit (300), an energy release unit (400) and a condensation unit (500) which are communicated in sequence. According to the system provided by the invention, a liquid compressed carbon dioxide circulating system is deeply coupled with waste heat and waste cold in an ethylene process, so that the problems of a gasification heat source of liquid carbon dioxide on a high-pressure side and a liquefaction cold source of gaseous carbon dioxide on a low-pressure side of a pressure storage system are solved; the bottleneck constraint of heat energy utilization of the conventional adiabatic compression carbon dioxide energy storage system is broken through; elastic distribution of compression heat between industrial steam production and carbon dioxide overheating can be achieved.

The multi-energy complementary heat supply system comprises an external basic heat source, a middle-grade synergistic heat source, a high-grade energy storage heat source, an intelligent heating power mixing center and a central controller, and the intelligent heating power mixing center is used for heating heat source equipment of all levels and operation instructions of associated assemblies according to the operation instructions of the heat source equipment of all the levels and the operation instructions of the associated assemblies. Heat energy of different grades is mixed and allocated, and heat loads meeting the grade requirements of heat consumers are output to the heat consumers; the central controller is used for establishing a multi-target optimization model taking the minimum total operation cost of the system as a core target based on the electricity price prediction data and the different-grade thermal load prediction data, solving the multi-target optimization model and generating a system operation strategy under the condition that preset basic guarantee logic, economic operation logic and peak response and power grid interaction logic are met; and the generated system operation strategy is converted into an operation instruction for the heat source equipment of each level and the associated assembly, so that the reliability and the adaptability of operation control of the heat supply system are effectively improved.

The invention relates to a thermosyphon-assisted natural circulation multistage liquid cooling method, which comprises the following steps of: arranging a double-layer heat exchange interface consisting of a lower high-heat-conduction layer and an upper low-heat-conduction layer in a heat source adjacent area to form a local temperature rise abrupt change area; when the temperature reaches a working liquid boiling threshold value, a local thermosyphon flow jump is generated to drive liquid circulation, and the thermosyphon flow jump has the periodic retriggering capacity by adjusting the material and structure parameters of the double-layer heat exchange interface; a plurality of distributed impedance regulation and control nodes are sequentially arranged along a flowing path of the thermosyphon, so that a flow difference is established between adjacent nodes; multiple stages of thermosyphon cavities are arranged on a flowing path in series, and the starting time sequences of the adjacent thermosyphon cavities are matched to achieve stage-by-stage progressive syphon driving. The condensate is adhered and flows stably in a liquid film form in a condensation outlet area of the last-stage thermosyphon cavity; a liquid turning buffer area is arranged behind a condensation outlet, condensate is guided to a mild backflow path, and closed-loop natural circulation is completed.

The invention belongs to the technical field of drying equipment, and particularly relates to a double-cone vacuum dryer and a silver nitrate drying method.The double-cone vacuum dryer comprises a stock bin, a gas circuit mechanism, a heat source mechanism, a first power mechanism, a blowing adjusting mechanism and a second power mechanism; a second power mechanism drives an arc-shaped plate in a blowing adjusting mechanism to rotate back and forth relative to the transfer bin so as to adjust the direction and the flow speed of the hot nitrogen blown out of an upper opening of the transfer bin, and when the arc-shaped plate rotates clockwise, the silver nitrate wet material which is turned upwards under the action of centrifugal force is blown away; the second power mechanism is matched with the blowing adjusting mechanism to adjust the blowing-out direction and the blowing-out flow speed of hot nitrogen in a reciprocating mode, it can be guaranteed that a dry layer on the surface of the silver nitrate wet material is broken, and the problem that the silver nitrate wet material splashes after the dry layer on the surface of the silver nitrate wet material is broken can be solved; the problems that after a drying layer is formed on the surface of the silver nitrate wet material, the internal heat and mass transfer path is lengthened, and the drying efficiency and the drying time are affected are solved.

The invention provides a heat supply digital twinborn intelligent regulation and control method, and relates to the technical field of intelligent regulation and control, and the method comprises the steps: executing millisecond-level high-concurrency numerical simulation according to a dynamic digital twinborn body, so as to obtain a simulation result; based on the simulation result, coupling the electricity price fluctuation data and the weather prediction data, performing future heat supply system multi-working-condition deduction, and dynamically optimizing a heat source unit start-stop combination and pipe network valve opening strategy to obtain a deduction result and an optimization strategy; generating an equipment regulation and control instruction set according to the deduction result and the optimization strategy; and an equipment regulation and control instruction set is issued to an edge computing node, a variable-frequency circulating pump and an electric control valve executing mechanism are controlled, and dynamic closed-loop regulation of the flow and the pressure of the heat supply pipe network is achieved. According to the invention, the pipe network flow and pressure regulation response time can be shortened to a second level.

The invention belongs to the technical field of electronic equipment thermal management, and discloses an electronic equipment thermal field rapid prediction method for multi-physical field strong coupling. According to the method, a layered heat source intensity distribution model is constructed, a grid mapping relation topological graph technology and a boundary node energy conservation compensation mechanism are developed, a multi-time scale coupling transfer function is designed, and a dynamic adjustment strategy based on phase deviation analysis is introduced. According to the method, the non-uniform heat source distribution and thermal diffusion dynamic characteristics under the high-frequency condition are accurately captured, the energy consistency of multi-physical field coupling is ensured, the thermal field prediction precision is improved, particularly, the method has outstanding advantages in the aspect of phase and amplitude prediction of transient thermal response, and meanwhile calculation resource consumption is greatly reduced.

The invention discloses a hydrogen leakage accident holographic perception and disaster situation dynamic prediction system in a tunnel scene, and belongs to the technical field of hydrogen energy traffic safety and intelligent risk management. According to the system, multi-modal information such as environmental parameters, hydrogen concentration, heat source temperature, leakage acoustic characteristics and vehicle states is collected in real time through a multi-modal sensing unit; abnormal detection, time synchronization and space registration are carried out through the information fusion module to generate fusion data in a unified format; the hazard source analysis module locates a leakage source, estimates a leakage rate, locates an ignition source and extracts disaster characteristics based on the fused data; the disaster dynamic prediction module predicts spatio-temporal evolution of diffusion, combustion and explosion by using an agent model and calculates disaster levels; the feedback early warning unit synchronously outputs the prediction information to the tunnel monitoring platform and issues early warning information; and the data storage and self-optimization module uniformly stores historical data and optimizes the prediction model through incremental learning. The system realizes real-time monitoring, rapid evaluation and intelligent disposal of tunnel hydrogen leakage accidents.

The invention relates to the technical field of electrical digital data processing, and discloses a train ice melting simulation optimization method of an electromagnetic thermal coupling model fused with a deep learning method, which comprises the following steps of: inputting a geometric representation tensor and a physical working condition parameter vector containing an electromagnetic excitation frequency and a reference environment temperature into a feature mapping neural network; outputting a dual-channel space source item tensor containing basic heat source power density and a heat source to temperature change sensitivity distribution matrix through nonlinear convolution operation; constructing a heat conduction discrete numerical value evolution operator configured with an active item linear correction interface; time stepping operation is executed according to the heat conduction time scale, a basic heat source is corrected in real time through the Hadamard product of a sensitivity distribution matrix and temperature deviation, and an operator is substituted for solution. On the premise that electromagnetic-thermal nonlinear coupling characteristics are reserved, decoupling of the time scale is achieved, and the calculation efficiency in high-frequency physical field simulation is effectively improved.

The invention relates to the technical field of process optimization, in particular to a collaborative optimization analysis method for multi-station tower drum welding. In order to solve the problem that cooperative control of tower drum multi-station welding is difficult, firstly, multi-mode sensing data of welding seam vision, arc sensing, thermal field distribution and welding voiceprint are loaded, a fusion evaluation model is constructed to obtain a welding seam deviation value and a sensor confidence score, and the health state of a sensor is judged according to a threshold value; and a corresponding fault-tolerant reconstruction control mode is triggered to obtain welding tracking control parameters, then a multi-station welding heat source model is loaded, thermal interference is decoupled in combination with the control parameters and thermal field data, multiple stations are cooperatively regulated and controlled, a cooperative control instruction is output and executed, and welding process optimization is achieved.

The invention discloses an intelligent fault diagnosis method, device and equipment and a storage medium, and relates to the technical field of new energy automobile thermal management, and the method comprises the steps: obtaining a sensor collection parameter, vibration feature information and a heat source coupling parameter; inputting the sensor acquisition parameters, the vibration characteristic information and the heat source coupling parameters into a reinforcement learning model to predict a potential fault, and determining a fault type, a fault confidence coefficient and fault evolution trend information; performing fault identification based on the fault type and the fault confidence, and determining fault type information; and generating a corresponding fault correction report based on the fault category information and the fault evolution trend information. According to the method, the potential fault is predicted in advance through the reinforcement learning model, the type, confidence and evolution trend of the potential fault are accurately deduced, a dynamic fault correction report is generated, the fault is intervened in advance, the diagnosis accuracy is improved, and fault diagnosis from passive response to active prevention and considering reliability and energy efficiency is realized.

Disclosed in the present application are a dual-sided laser synchronous welding heat source model establishment method, a dual-sided laser synchronous welding heat source simulation method, a dual-sided laser synchronous welding system, and a medium. Firstly, combined heat sources each comprising a Gaussian cylindrical heat source attenuation model and a Gaussian surface heat source correction model are established, and a dual-sided laser synchronous welding heat source model is established by means of a rotating coordinate system; a three-dimensional geometric model and a three-dimensional mesh model of a T-joint are established; and the consistency between simulated molten metal morphology and an actual weld shape is used as a criterion for determining whether parameter settings of the dual-sided laser synchronous welding heat source model are rational, so as to obtain an optimal finite element simulation heat source model. By establishing two heat sources each obtained by combining a Gaussian cylindrical heat source attenuation model and a Gaussian surface heat source correction model, and symmetrically applying the two heat sources to two sides of a T-joint to act on the interior and surface of a weld, the present invention realizes the accurate simulation of a weld penetration zone in a T-shaped thin-plate weldment, and thus enables the prediction of residual stress and welding deformation during a design phase, thereby optimizing the welding process, improving the welding quality and efficiency, and reducing material waste and production costs.

The invention discloses a hybrid model driving-based space-time consistency regulation and control method for a central heating system, which comprises the following steps of: performing hydraulic equilibrium analysis on the central heating system, and performing hydraulic analysis on a space structure of a heating pipe network by using a graph theory method based on an energy conservation law, simulating the hydraulic working condition of the official website by using a basic loop analysis method; based on an energy conservation and mass conservation heat balance equation, a heat source and a heat user are indirectly connected through heat exchanger transition, a dynamic physical model of each subsystem is established based on a lumped heat capacity method, a refined model of the heat supply system is established, and the thermal dynamic characteristics of the system are researched and analyzed; based on a Pearson's correlation function, considering thermal inertia of equipment such as a pipe network of the central heating system and a building fence structure, and determining a regulation and control period and time of the regulation and control model; according to the method, by controlling the opening degree of the regulating valve of the heat exchange station, the suitability degree of the room temperature of a heat user is guaranteed.

The invention relates to the technical field of optical communication, in particular to a vapor chamber and an optical module. Heat generated by a heat source is absorbed through the lower shell, then heat absorbed by the lower shell is absorbed by the heat dissipation working medium in the steam cavity, the heat dissipation working medium is changed into a gas state from a liquid state after absorbing heat, and the gas-state heat dissipation working medium is adsorbed on the inner surface of the upper shell, is cooled into a liquid state again and returns to the bottom of the steam cavity again. Therefore, heat dissipation of a heat source in the optical module is realized. The interface contact thermal resistances are only between the heat source and the lower shell and between the upper shell and the external environment, the number of the interface contact thermal resistances on a heat transfer path is greatly reduced, the uniform temperature plate is arranged as a part of the optical module, an integrated enhanced heat dissipation structure is formed, the interface contact thermal resistances caused by split design are prevented from being increased, and the heat dissipation efficiency is improved. The heat dissipation performance of the whole optical module is improved, and the heat dissipation requirement of the high-speed optical module is met.

The invention discloses a permanent magnet synchronous motor temperature monitoring method based on digital-analog hybrid drive, and the method specifically comprises the steps: dividing a motor into a plurality of heat source nodes, including a stator winding, a stator tooth part, a rotor core and the like, connecting the nodes through a thermal resistance and thermal capacity network, building a thermal network model of the motor, and carrying out the thermal network model; calculating the initial values of thermal resistance and thermal capacity of each component of the motor, and optimizing parameters in a thermal network model by using a differential evolution algorithm based on the lumped parameter thermal network model and in combination with a data-driven strategy. Furthermore, temperature rise prediction is dynamically adjusted according to motor state data (such as stator current, rotating speed and the like) collected in real time so as to realize real-time temperature estimation. The method is high in temperature estimation precision, does not affect the performance of the motor, is simple in calculation, is good in real-time performance, and has physical interpretability. The temperature rise of the motor can be predicted in real time under different working conditions, early warning is given out, motor faults caused by too high temperature rise are effectively avoided, and the reliability and safety of the motor are improved.

The invention relates to a heat pipe energy pile, a heat pipe ground source heat pump system and an operation management method of the heat pipe ground source heat pump system, and solves the technical problems that an existing ground source heat pump needs extra power, is high in energy consumption and is difficult to adapt to winter and summer two-way energy supply, and the system comprises a pile foundation, a heat pipe, a heat exchanger and a heat pump unit. The heat pipe is combined with the pile foundation, is a vacuumized closed pipe body which is provided with a capillary core and filled with a phase change working medium, and is divided into an evaporation section at the lower part / side part of the pile foundation and a condensation section at the upper part of the pile foundation; the evaporation section exchanges heat with soil, the condensation section is connected with a heat exchanger, and the heat pump ground source side is connected with the heat exchanger; the capillary core drives a working medium to flow back autonomously through capillary force, and heat transfer or release is achieved. The system has the following effects that the contradiction between low consumption and annual energy supply in the prior art is solved, no extra power is achieved, two-way efficient energy supply in winter and summer is achieved, and energy consumption of a building cold and heat source system is greatly reduced.

The invention provides an intelligent heat dissipation system of an oil-free digital energy air compression station, which relates to the technical field of heat dissipation of air compression stations and comprises a sensor module, a correlation analysis module and a heat dissipation execution module which are in communication connection. Statistical correlation, causal correlation and time correlation between each operation parameter and temperature are analyzed, a physical mechanism is introduced, a hybrid correlation model is constructed, a predicted temperature change trend is combined, specific operation parameters influencing the temperature change at the current moment are analyzed, specific equipment is positioned according to the operation parameters, and a heat dissipation strategy is executed. Through a closed loop of model prediction, parameter attribution, equipment positioning and accurate heat dissipation, data-driven correlation analysis and causal reasoning of a physical mechanism are combined, rapid positioning from temperature abnormity to a specific heating source is realized, and low efficiency of traditional equipment-by-equipment troubleshooting is avoided.