Skirting line heater, skirting line heating control method and device and computer equipment

Abstract

The invention relates to a skirting line heater, a skirting line heating control method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring historical use information of a user for the skirting line heater; performing heating prediction based on a historical use time period and a historical heating temperature in the historical use information to obtain a predicted starting time period and a predicted heating temperature of a heating assembly of the skirting line heater; acquiring indoor environment information at a target moment before the predicted opening time period; in combination with the indoor environment information and the predicted heating temperature, the heating power of the heating assembly at the target moment is determined; in the process that the heating assembly works according to the heating power, the foreign matter falling risk degree of the heating assembly is determined based on the working information of the heating assembly; and executing risk management and control measures related to the foreign matter falling risk degree. By adopting the method, the safety of the skirting line heater in the using process can be improved.

Description

Technical Field

[0001] This application relates to the field of smart home technology, and in particular to a skirting board heater, a skirting board heating control method, a device, a computer equipment, a computer-readable storage medium, and a computer program product. Background Technology

[0002] With the rapid development of smart home technology, intelligent control of home appliances has become a core direction for improving user experience and achieving energy conservation and environmental protection. Among them, skirting board heaters, as commonly used equipment for indoor heating in winter, are evolving from traditional mechanical operation to intelligent and adaptive control.

[0003] Traditional skirting board heaters lack real-time monitoring of their operating status, making it impossible to identify potential risks such as localized overheating, efficiency reduction, or short circuits caused by falling foreign objects, which could lead to equipment damage or even fire hazards. Therefore, traditional skirting board heaters present safety issues. Summary of the Invention

[0004] Therefore, it is necessary to address the technical problem of poor safety of traditional skirting board heaters by providing a skirting board heater, skirting board heating control method, device, computer equipment, computer-readable storage medium, and computer program product.

[0005] Firstly, this application provides a method for controlling the heating of baseboards. The method includes:

[0006] Obtain user's historical usage information regarding the baseboard heater;

[0007] Based on the historical usage time period and historical heating temperature in the historical usage information, heating prediction is performed to obtain the predicted start time period and predicted heating temperature of the heating component for the skirting board heater.

[0008] At a target time before the predicted start time, obtain indoor environmental information for the target time.

[0009] Based on the indoor environmental information and the predicted heating temperature, the heating power of the heating component at the target time is determined;

[0010] During the operation of the heating component according to the heating power, the degree of risk of foreign objects falling into the heating component is determined based on the operating information of the heating component;

[0011] Implement risk management measures related to the degree of risk of the foreign object falling.

[0012] In one embodiment, the number of heating components is multiple; the operating information includes acceleration information, vibration information, and sound information; determining the foreign object drop risk level of the heating components based on the operating information includes:

[0013] If at least one of the acceleration information, vibration information, and sound information of multiple heating components is obtained simultaneously, then information correlation analysis is performed on the information of each heating component to determine the foreign object falling state of each heating component.

[0014] For each heating component, if the foreign object falling status of the heating component is "already fallen", the obtained information of the heating component is analyzed to determine the degree of risk of foreign object falling of the heating component.

[0015] If the foreign object falling from the heating component is not detected, the risk level of the foreign object falling from the heating component is determined to be no risk.

[0016] In one embodiment, the heating prediction based on the historical usage periods and historical heating temperatures in the historical usage information to obtain the predicted start-up period and predicted heating temperature for the heating component of the skirting board heater includes:

[0017] Based on the historical usage period and historical heating temperature in the historical usage information, heating prediction is performed to obtain the predicted start-up period and initial predicted temperature of the heating component for the skirting board heater.

[0018] Obtain the temperature during the predicted start-up period;

[0019] Based on the temperature during the specified time period, the initial predicted temperature is adjusted to obtain the predicted heating temperature.

[0020] Secondly, this application also provides a skirting board heater, including a control component and a heating component connected to each other;

[0021] The control component is used to acquire historical usage information of the user regarding the skirting board heater;

[0022] Based on the historical usage time period and historical heating temperature in the historical usage information, heating prediction is performed to obtain the predicted start time period and predicted heating temperature of the heating component for the skirting board heater.

[0023] At a target time before the predicted start time, obtain indoor environmental information for the target time.

[0024] Based on the indoor environmental information and the predicted heating temperature, the heating power of the heating component at the target time is determined;

[0025] During the operation of the heating component according to the heating power, the degree of risk of foreign objects falling into the heating component is determined based on the operating information of the heating component;

[0026] Implement risk management measures related to the degree of risk of the foreign object falling.

[0027] In one embodiment, there are multiple heating components; each heating component has a coupler on at least one side for connecting to other heating components via the coupler.

[0028] In one embodiment, a magnet is also provided around the periphery of the coupler;

[0029] The magnet is used to attract magnets on the periphery of couplers on other heating components to connect the heating component to which the magnet belongs to the other heating components.

[0030] In one embodiment, the skirting board heater further includes a current sensing component; the current sensing component is connected to the control component;

[0031] The current sensing component is used to detect the operating current of the heating component when it is working;

[0032] The control component is used to acquire the operating current and, if the operating current is higher than a current threshold, to turn off the heating component.

[0033] Thirdly, this application also provides a skirting board heating control device. The device includes:

[0034] The historical usage information acquisition module is used to acquire the user's historical usage information for the skirting board heater;

[0035] The heating prediction module is used to predict the heating based on the historical usage period and historical heating temperature in the historical usage information, so as to obtain the predicted start-up period and predicted heating temperature of the heating component for the skirting board heater.

[0036] The indoor environment information acquisition module is used to acquire indoor environment information at a target time before the predicted start time period.

[0037] A heating power determination module is used to determine the heating power of the heating component at the target time by combining the indoor environment information and the predicted heating temperature;

[0038] The risk level determination module is used to determine the risk level of foreign object falling from the heating component based on the working information of the heating component during the operation of the heating component according to the heating power.

[0039] The control measures execution module is used to execute risk control measures related to the degree of risk of the foreign object falling.

[0040] Fourthly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described above.

[0041] Fifthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the method described above.

[0042] Sixthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the method described above.

[0043] The aforementioned skirting board heater, skirting board heating control method, device, computer equipment, computer-readable storage medium, and computer program products, through deep integration of user behavior analysis and environmental adaptive control technology, achieve a comprehensive upgrade of the skirting board heater control method: First, the heating prediction function based on historical usage information can accurately mine users' heating habits and generate dynamic start-up times and temperature parameters, completely eliminating the cumbersome and lagging nature of the traditional manual setting mode and significantly improving ease of use; Second, the real-time power adjustment mechanism combined with indoor environmental information at the target time can automatically optimize heating power according to environmental changes, reducing ineffective energy consumption while ensuring comfort, and significantly improving energy saving compared to the traditional fixed power mode; Furthermore, through a foreign object falling risk assessment system constructed by continuously monitoring the working information of the heating components, it can proactively identify local overheating or efficiency reduction problems caused by dust accumulation, loose parts, etc., and trigger graded control measures such as early warning prompts, automatic power reduction, or shutdown, effectively avoiding equipment damage or even fire hazards, and improving the safety of skirting board heater use. Attached Figure Description

[0044] Figure 1 This is an application environment diagram of a skirting board heating control method in one embodiment;

[0045] Figure 2 This is a flowchart illustrating a skirting board heating control method in one embodiment;

[0046] Figure 3 This is a flowchart illustrating the steps for determining the state of a falling foreign object in one embodiment;

[0047] Figure 4This is a flowchart illustrating the temperature adjustment steps in one embodiment;

[0048] Figure 5 This is a schematic diagram of the structure of the skirting board heater in one embodiment;

[0049] Figure 6 This is a schematic diagram of the skirting board heater in another embodiment;

[0050] Figure 7 This is a flowchart illustrating the skirting board heating control method in another embodiment;

[0051] Figure 8 This is a structural block diagram of a skirting board heating control device in one embodiment;

[0052] Figure 9 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0054] The skirting board heating control method provided in this application embodiment can be applied to, for example... Figure 1In the application environment shown, the control component 102 communicates with the heating component 104 via a network. The control component 102 can be a terminal or a server. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart vehicle devices. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server can be a standalone server or a server cluster consisting of multiple servers. The heating component 104 is the core component for the device to provide heating; its function is to convert electrical energy or other energy into heat energy and release heat into the room through heat conduction, convection, or radiation. Specifically, during the process of controlling the skirting board heating, the control component 102 acquires the user's historical usage information for the skirting board heater; based on the historical usage time period and historical heating temperature in the historical usage information, it makes a heating prediction to obtain the predicted start time period and predicted heating temperature for the heating component 104 of the skirting board heater; at the target time before the predicted start time, it acquires the indoor environmental information at the target time; combining the indoor environmental information and the predicted heating temperature, it determines the heating power of the heating component 104 at the target time; during the process of the heating component 104 operating according to the heating power, it determines the degree of foreign object falling risk of the heating component 104 based on the working information of the heating component 104; and it implements risk control measures related to the degree of foreign object falling risk.

[0055] In one embodiment, such as Figure 2 As shown, a method for controlling the heating of skirting boards is provided, which is applied to... Figure 1 Taking control component 102 as an example, the following steps are included:

[0056] Step S202: Obtain the user's historical usage information for the skirting board heater.

[0057] The skirting board heater is a heating device that uses thermally superconducting materials as its basic heating unit and is designed in the form of a skirting board. Historical usage information is a record of operational data generated when users have used the skirting board heater in the past, which may include key information such as turn-on time, turn-off time, usage period, heating temperature, running time, and power level selection.

[0058] Specifically, the complete operation process of each use of the skirting board heater can be recorded during its various uses. For example, when a user clicks the "Turn On" button via the app, the control component records the current time (e.g., 18:00 on October 15, 2023) and associates it with the user-set heating temperature (e.g., 25℃). During heater operation, the control component continuously records the actual running time (e.g., continuous operation for 4 hours) and power level (e.g., medium). When the user clicks "Turn Off," the control component records the shutdown time again (e.g., 22:00). This data is stored in a timeline format on the device's local storage or a cloud server, forming a database of the user's historical usage information. To protect privacy, data transmission and storage can employ encryption technology, accessible only to the user or authorized service providers. Through long-term accumulation, historical usage information can reflect patterns in the user's heating habits (e.g., turning on daily from 18:00 to 22:00 in winter), temperature preferences (e.g., preference for 25℃), and other patterns, providing a basis for subsequent heating predictions.

[0059] Step S204: Based on the historical usage period and historical heating temperature in the historical usage information, heating prediction is performed to obtain the predicted start-up period and predicted heating temperature of the heating component for the skirting board heater.

[0060] Historical usage periods refer to the specific time periods during which users have used the heater in the past, such as 18:00-22:00 daily. Historical heating temperatures are the target temperatures set by users in the past, such as 22℃ or 25℃. Heating prediction infers future user behavior patterns by analyzing historical data. Predicted activation periods are the time periods during which the heater is likely to be turned on in the future, predicted based on historical patterns. Predicted heating temperatures are the target temperatures that the heater may be set to in the future, predicted based on historical patterns.

[0061] Specifically, the control component can access data from a historical usage database and first perform statistical analysis on historical usage periods. For example, it can extract the specific times when users turned on the heater within the past 30 days, calculate the average and standard deviation of daily operating times. A smaller standard deviation indicates strong regularity in user operating times; a larger deviation requires further analysis in conjunction with other factors. Optionally, the control component can perform cluster analysis on historical heating temperatures to identify commonly used temperature settings and their frequency of occurrence. Based on these analyses, the control component uses time series forecasting algorithms or machine learning models, inputting external variables such as the current date, season, and weather forecast, to generate predicted operating periods and predicted heating temperatures. If there are anomalies in historical user behavior, the control component will use an anomaly detection algorithm to eliminate interference and ensure prediction accuracy. Optionally, the control component can also perform heating prediction based on historical usage periods and historical heating temperatures in the historical usage information to obtain the predicted operating period and initial predicted temperature for the heating components of the skirting board heater. It can then obtain the temperature during the predicted operating period and adjust the initial predicted temperature based on the temperature during that period to obtain the predicted heating temperature.

[0062] Step S206: At the target time before the predicted start time, obtain the indoor environmental information for the target time.

[0063] The target time is a specific point in time before the predicted start time; for example, the target time could be 30 minutes before the predicted start time. Indoor environmental information refers to the physical parameters of the current indoor environment, including temperature, humidity, air quality, and wind speed.

[0064] Specifically, the control component sets a target time before the predicted start-up period and collects indoor environmental data in real time through the multi-sensor module built into the baseboard heater or a networked smart home environmental monitoring device. For example, a temperature sensor measures the current room temperature, a humidity sensor measures relative humidity, and an air quality sensor detects PM2.5 concentration. If the heater is not equipped with all sensors, the control component can also obtain more comprehensive environmental information by sharing data with other smart devices in the user's home. All data is transmitted to the control component via Wi-Fi or Bluetooth and is marked with a collection timestamp to ensure data timeliness. For example, if the target time is 17:30, the control component only uses data collected between 17:25 and 17:35 to avoid using outdated information that may affect subsequent decisions.

[0065] Step S208: Combine indoor environmental information and predicted heating temperature to determine the heating power of the heating component at the target time.

[0066] Among them, heating power is the electrical energy consumed by the heating component per unit time, which directly affects the heating speed and energy consumption.

[0067] Specifically, the control component first calculates the temperature difference based on the indoor environmental information at the target time and the predicted heating temperature (e.g., 25°C). If the temperature difference is large, it indicates that rapid heating is needed, and the control component will increase the heating power to a high power level to shorten the time to reach the target temperature; if the temperature difference is small, the power can be reduced to a low power level to maintain the temperature and reduce energy consumption. Simultaneously, the control component can further consider the impact of humidity. High humidity environments reduce the human body's perception of temperature, potentially requiring an appropriate increase in the target temperature or power; the opposite is true in low humidity environments. Furthermore, the control component can dynamically adjust the power; if the actual temperature rises too quickly, the power is reduced; if it rises too slowly, the power is increased. The final determined power level can be fed back to the user through the heater display screen, and the user can also manually adjust it.

[0068] Step S210: During the operation of the heating component according to the heating power, the degree of risk of foreign objects falling into the heating component is determined based on the working information of the heating component.

[0069] The operating information refers to real-time data of the heating component during operation, which may include temperature distribution, current, voltage, vibration, etc. The risk of foreign object falling is the likelihood that the heating component will malfunction or pose a safety hazard due to external foreign objects.

[0070] Specifically, during operation, the heating component is continuously monitored by multiple built-in sensors. For example, temperature sensors collect real-time temperature data for each area; if a certain area's temperature is more than 10°C higher than others, it may be due to dust accumulation clogging the heat dissipation vents, leading to localized overheating. Current sensors monitor the input current; a sudden increase in current may indicate a short circuit risk due to loose components. Vibration sensors detect the overall vibration frequency of the heater; abnormal vibration may indicate mechanical failure due to loose internal screws or foreign objects lodged. Optionally, the control component can compare this data with preset normal operating ranges and assess the risk of foreign objects falling into the heater using fuzzy logic algorithms. For example, if only the temperature is abnormal, the risk level is "medium risk"; if both temperature and current are abnormal, the risk level is upgraded to "high risk." The assessment results are updated every minute to ensure timely detection of potential problems. Optionally, if at least one of the acceleration information, vibration information, and sound information of multiple heating components is acquired simultaneously, the control component can also perform information correlation analysis on the acquired information of each heating component to determine the foreign object falling status of each heating component; for each heating component, if the foreign object falling status of the heating component is "already fallen", the acquired information of the heating component is analyzed to determine the degree of foreign object falling risk of the heating component; if the foreign object falling status of the heating component is "not fallen", the degree of foreign object falling risk of the heating component is determined to be "no risk".

[0071] Step S212: Implement risk control measures related to the degree of risk of foreign object falling.

[0072] Risk management measures are preventive or responsive actions taken for different risk levels in order to reduce safety hazards.

[0073] Specifically, the control component can automatically implement tiered control measures based on the level of risk of foreign object falling. If the risk is low, the control component can push a reminder message via software, reduce the heating power to a safe range, continue operation, and continuously monitor. If the risk is medium, the control component can trigger an audible alarm and a visual warning, while reducing the heating power to the lowest level to prevent the fault from escalating; if the user does not respond within 10 minutes, the control component automatically shuts off the heater and sends an emergency notification. If the risk is high, the control component immediately cuts off the power, stops the heating component, and notifies the user via both software and SMS, while recording the fault code for maintenance personnel. Furthermore, the control component can upload risk events to a cloud server to generate a fault report, providing data support for subsequent product improvements. Through tiered control, the control component ensures safety while minimizing interference with normal user operation.

[0074] The aforementioned skirting board heating control method achieves a comprehensive upgrade of skirting board heater control by deeply integrating user behavior analysis and environmental adaptive control technology. Firstly, the heating prediction function based on historical usage information can accurately identify user heating habits and generate dynamic start-up times and temperature parameters, completely eliminating the cumbersome and delayed nature of traditional manual setting modes and significantly improving ease of use. Secondly, the real-time power adjustment mechanism, combined with indoor environmental information at the target time, can automatically optimize heating power according to environmental changes, reducing ineffective energy consumption while ensuring comfort, resulting in significantly improved energy efficiency compared to traditional fixed power modes. Furthermore, the foreign object falling risk assessment system, built by continuously monitoring the working information of the heating components, can proactively identify localized overheating or efficiency degradation caused by dust accumulation, loose components, etc., and trigger graded control measures such as early warning prompts, automatic power reduction, or shutdown, effectively avoiding equipment damage and even fire hazards, and improving the safety of skirting board heater use.

[0075] In one embodiment, such as Figure 3 As shown, there are multiple heating components; the operating information includes acceleration, vibration, and sound information; based on the operating information of the heating components, the risk level of foreign object falling into the heating components is determined, including:

[0076] Step S302: If at least one of the acceleration information, vibration information, and sound information of multiple heating components is obtained simultaneously, then information correlation analysis is performed on the information of each heating component to determine the foreign object falling state of each heating component.

[0077] The heating element is the part of the skirting board heater responsible for generating heat. Operating information may include, for example, acceleration, vibration, and sound information. Acceleration information reflects the motion state of the heating element, vibration information reflects its vibration pattern, and sound information reflects the sound characteristics of the heating element during operation. Information correlation analysis examines whether there are correlations between different pieces of information to determine the status of foreign object fall onto the heating element. The foreign object fall status refers to whether a foreign object has fallen onto the heating element, categorized as "fallen" or "not fallen."

[0078] Specifically, when the control component simultaneously acquires at least one of the acceleration, vibration, and sound information from multiple heating components, it analyzes the correlation between the information from each heating component. For example, if only the acceleration information of heating component a is acquired among heating component a, heating component b, and heating component c, and the sound from heating component a is very loud while the sounds from heating components b and c are very quiet, then it is possible that no foreign object fell onto heating components b and c; rather, the sound of a foreign object falling onto heating component a was captured by the sensors of heating components b and c.

[0079] For each heating component, in step S304, if the foreign object falling status of the heating component is "fallen", the obtained information of the heating component is analyzed to determine the degree of risk of foreign object falling into the heating component.

[0080] Specifically, for each heating component, if the state of the foreign object falling is determined to be that it has fallen, the system will conduct in-depth analysis based on the acquired information such as the acceleration, vibration, and sound of the heating component. For example, it will analyze the magnitude and direction of the acceleration, the frequency and amplitude of the vibration, and the frequency and intensity of the sound to determine the degree of risk caused by the falling foreign object to the heating component.

[0081] Step S306: If the foreign object falling status of the heating component is "not fallen", determine that the risk level of the foreign object falling of the heating component is "no risk".

[0082] Specifically, if the foreign object falling status of the heating component is "not fallen", then the control component will directly determine that the risk level of foreign object falling of the heating component is no risk, that is, there is no need to worry about the problems caused by foreign object falling.

[0083] In this embodiment, by comprehensively analyzing various working information of the heating component, the state of foreign object falling into the heating component and the degree of risk can be accurately determined, thereby taking timely measures to prevent malfunctions or safety accidents and improving the safety and reliability of the skirting board heater.

[0084] In one embodiment, such as Figure 4As shown, heating prediction is performed based on historical usage periods and historical heating temperatures from historical usage information to obtain the predicted start-up periods and predicted heating temperatures for the heating components of the skirting board heater, including:

[0085] Step S402: Based on the historical usage period and historical heating temperature in the historical usage information, heating prediction is performed to obtain the predicted start-up period and initial predicted temperature of the heating component for the skirting board heater.

[0086] Historical usage information includes records of past use of the baseboard heater, such as usage periods and heating temperatures. Heating prediction forecasts future heater usage based on this information. Predicted on-time periods indicate the likely future on-time periods for the baseboard heater. The initial predicted temperature is a target temperature for the heater, preliminarily predicted based on historical heating temperatures.

[0087] Specifically, the control components predict heating based on the user's historical usage time and historical heating temperature of the baseboard heater. For example, by analyzing when the user used the heater each day and what the typically set heating temperature was, the system can predict the likely time periods and initial predicted temperatures for the baseboard heater's heating components in the future.

[0088] Step S404: Obtain the temperature of the predicted start-up period.

[0089] Among them, the time-period temperature is the predicted indoor ambient temperature during the opening period.

[0090] Specifically, the control component will obtain the predicted temperature during the start-up period, that is, the actual indoor temperature during that period.

[0091] Step S406: Based on the time period temperature, adjust the initial predicted temperature to obtain the predicted heating temperature.

[0092] The predicted heating temperature is the heater target temperature adjusted based on the temperature over a given time period.

[0093] Specifically, the control unit adjusts the initial predicted temperature based on the temperature during a given time period. For example, if the temperature during the predicted heating period is already high, the control unit may lower the initial predicted temperature to prevent the indoor temperature from becoming too high; conversely, if the temperature during a given time period is low, the control unit may raise the initial predicted temperature to ensure the indoor temperature is warm. Through this adjustment, the final predicted heating temperature is obtained.

[0094] In this embodiment, by combining historical usage information and real-time ambient temperature for heating prediction, the usage of the skirting board heater can be predicted more accurately, improving heating comfort and energy efficiency while avoiding unnecessary energy waste.

[0095] In one embodiment, such as Figure 1 As shown, a skirting board heater is also provided, including a control component 102 and a heating component 104 connected to each other; the control component 102 is used to acquire historical usage information of the skirting board heater by the user; perform heating prediction based on the historical usage period and historical heating temperature in the historical usage information to obtain the predicted start-up period and predicted heating temperature of the heating component 104 for the skirting board heater; acquire indoor environmental information at a target time before the predicted start-up period; determine the heating power of the heating component 104 at the target time by combining the indoor environmental information and the predicted heating temperature; determine the degree of foreign object falling risk of the heating component 104 based on the working information of the heating component 104 during the operation of the heating component 104 according to the heating power; and implement risk control measures related to the degree of foreign object falling risk.

[0096] Specifically, the control component 102 first acquires the user's historical usage information for the baseboard heater, and then performs heating prediction based on this information to obtain the predicted start-up time and predicted heating temperature of the heating component 104. At a target time before the predicted start-up time, the control component 102 acquires indoor environmental information, such as indoor temperature. Next, the control component 102 combines the indoor environmental information and the predicted heating temperature to determine the heating power of the heating component 104 at the target time to ensure the indoor temperature reaches the expected level. During the operation of the heating component 104 at the predicted heating power, the control component 102 determines the risk level of foreign object falling onto the heating component 104 based on its operating information, such as acceleration, vibration, and sound. Finally, the control component 102 executes risk control measures related to the risk level of foreign object falling, such as issuing an alarm, reducing power, or shutting down the heating component 104.

[0097] In this embodiment, through the overall control process, the skirting board heater can achieve intelligent and automated heating control, improve heating comfort and energy efficiency, and ensure safety and reliability during use.

[0098] In one embodiment, such as Figure 5 As shown, there are multiple heating components 104; each heating component 104 has a coupler 106 on at least one side for connecting to other heating components 104 via the coupler 106.

[0099] The coupler 106 is a component used to connect the heating assembly 104, realizing electrical and mechanical connection.

[0100] Specifically, in this embodiment, the skirting board heater has multiple heating components 104, and each heating component 104 has a coupler 106 on at least one side. These couplers 106 are used to connect other heating components 104 together to form a complete heating system. For example, the right-side coupler 106 of one heating component 104 can be connected to the left-side coupler 106 of another heating component 104, thereby realizing the series or parallel connection between the heating components 104.

[0101] In this embodiment, the heating component 104 is connected via coupler 106, which can easily expand the heating area and power of the skirting board heater to meet heating needs in different scenarios. At the same time, this connection method also facilitates the installation, maintenance, and replacement of the heating component 104.

[0102] In one embodiment, such as Figure 6 As shown, a magnet 108 is also provided on the periphery of the coupler 106; the magnet 108 is used to attract the magnets 108 on the periphery of the coupler 106 on other heating components 104, so as to connect the heating component 104 to which the magnet 108 belongs to other heating components 104.

[0103] Among them, magnet 108 is a component used to attract and connect coupler 106.

[0104] Specifically, the coupler 106 is also provided with magnets 108 on its periphery. These magnets 108 are used to attract each other to the magnets 108 on the periphery of the coupler 106 of other heating components 104, thereby tightly connecting the heating component 104 to which the magnet 108 belongs to other heating components 104 together. For example, when the magnet 108 on the periphery of the coupler 106 of one heating component 104 comes close to the magnet 108 on the periphery of the coupler 106 of another heating component 104, they will automatically attract each other and form a stable connection.

[0105] In this embodiment, the connection process between the heating components 104 is simplified and the connection efficiency and stability are improved by using the magnet 108 to attract and connect the coupler 106. At the same time, this connection method also offers a degree of flexibility, facilitating the disassembly and reassembly of the heating components 104.

[0106] In one embodiment, the skirting board heater further includes a current sensing component (not shown in the figure); the current sensing component is connected to the control component; the current sensing component is used to detect the operating current when the heating component is working; the control component is used to acquire the operating current and turn off the heating component when the operating current is higher than the current threshold.

[0107] The current sensing component is used to detect the operating current of the heating element during operation. The operating current is the actual current consumed by the heating element when it is working. The current threshold is a preset safe current upper limit.

[0108] Specifically, in this embodiment, the skirting board heater further includes a current sensing component connected to the control component. The current sensing component detects the operating current of the heating component in real time and transmits the detection results to the control component. The control component acquires this operating current data and compares it with a preset current threshold. If the operating current exceeds the current threshold, it indicates a potential malfunction or overload in the heating component. In this case, the control component immediately shuts down the heating component to prevent safety accidents or equipment damage caused by excessive current.

[0109] In this embodiment, through a current protection mechanism, the skirting board heater can promptly cut off the power supply when the operating current is abnormal, protecting the safety of the equipment and the user. This protection mechanism can improve the reliability and service life of the skirting board heater, and reduce maintenance costs and safety risks.

[0110] In a specific embodiment, such as Figure 7 As shown, a method for controlling the heating of baseboards is also provided, including:

[0111] Step S701: Obtain the user's historical usage information for the skirting board heater;

[0112] Step S702: Based on the historical usage period and historical heating temperature in the historical usage information, perform heating prediction to obtain the predicted start-up period and initial predicted temperature of the heating component for the skirting board heater;

[0113] Step S703: Obtain the temperature of the predicted start-up period;

[0114] Step S704: Based on the time period temperature, adjust the initial predicted temperature to obtain the predicted heating temperature;

[0115] Step S705: At the target time before the predicted start time, obtain the indoor environmental information at the target time;

[0116] Step S706: Combine indoor environmental information and predicted heating temperature to determine the heating power of the heating component at the target time;

[0117] The number of heating components is multiple;

[0118] Step S707: During the operation of the heating components according to the heating power, if at least one of the acceleration information, vibration information and sound information of multiple heating components is obtained at the same time, then information correlation analysis is performed on the information of each heating component to determine the foreign object falling state of each heating component.

[0119] Step S708: For each heating component, if the foreign object falling status of the heating component is "fallen", analyze the obtained information of the heating component to determine the degree of risk of foreign object falling into the heating component.

[0120] Step S709: If the foreign object falling status of the heating component is "not fallen", determine that the risk level of the foreign object falling of the heating component is "no risk".

[0121] Step S710: Implement risk control measures related to the degree of risk of foreign object falling.

[0122] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0123] Based on the same inventive concept, this application also provides a skirting board heating control device for implementing the skirting board heating control method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more skirting board heating control device embodiments provided below can be found in the limitations of the skirting board heating control method described above, and will not be repeated here.

[0124] In one embodiment, such as Figure 8 As shown, a skirting board heating control device 800 is provided, including: a historical usage information acquisition module 802, a heating prediction module 804, an indoor environment information acquisition module 806, a heating power determination module 808, a risk level determination module 810, and a control measure execution module 812, wherein:

[0125] The historical usage information acquisition module 802 is used to acquire the user's historical usage information for the skirting board heater;

[0126] The heating prediction module 804 is used to make heating predictions based on historical usage periods and historical heating temperatures in historical usage information, so as to obtain the predicted start-up period and predicted heating temperature of the heating component for the skirting board heater.

[0127] The indoor environment information acquisition module 806 is used to acquire indoor environment information at a target time before the predicted start time.

[0128] The heating power determination module 808 is used to determine the heating power of the heating component at a target time by combining indoor environmental information and predicted heating temperature.

[0129] The risk level determination module 810 is used to determine the risk level of foreign object falling from the heating component based on the working information of the heating component during the operation of the heating component according to the heating power.

[0130] The control measures execution module 812 is used to execute risk control measures related to the degree of risk of foreign object falling.

[0131] In one embodiment, the number of components is multiple; the operating information includes acceleration information, vibration information, and sound information. In this embodiment, the risk level determination module 810 is specifically used for:

[0132] If at least one of the acceleration information, vibration information, and sound information of multiple heating components is obtained at the same time, then information correlation analysis is performed on the information of each heating component to determine the foreign object falling state of each heating component.

[0133] For each heating component, if the foreign object in the heating component is in the state of "fallen", the information obtained from the heating component is analyzed to determine the degree of risk of foreign object falling into the heating component.

[0134] If the foreign object falling from the heating component is not detected, the risk level of the foreign object falling from the heating component is determined to be no risk.

[0135] In one embodiment, the heating prediction module 804 is specifically used for:

[0136] Heating prediction is made based on historical usage periods and historical heating temperatures from historical usage information to obtain the predicted start-up period and initial predicted temperature of the heating components for the skirting board heater.

[0137] Obtain the temperature during the predicted start time period;

[0138] Based on the temperature over a given period, the initial predicted temperature is adjusted to obtain the predicted heating temperature.

[0139] Each module in the aforementioned skirting board heating control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0140] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 9 As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for controlling the heating of baseboards. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0141] Those skilled in the art will understand that Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0142] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0143] Obtain user's historical usage information regarding the baseboard heater;

[0144] Heating prediction is made based on historical usage periods and historical heating temperatures from historical usage information to obtain the predicted start-up period and predicted heating temperature of the heating components for the skirting board heater.

[0145] At the target time before the predicted start time, obtain indoor environmental information for the target time.

[0146] By combining indoor environmental information and predicted heating temperature, the heating power of the heating components at the target time is determined;

[0147] During the operation of the heating component according to the heating power, the degree of risk of foreign objects falling into the heating component is determined based on the operating information of the heating component.

[0148] Implement risk management measures related to the degree of risk of foreign object falling.

[0149] In one embodiment, the number of heating components is multiple; the operating information includes acceleration information, vibration information, and sound information. In this embodiment, the processor, when executing the computer program, further performs the following steps:

[0150] If at least one of the acceleration information, vibration information, and sound information of multiple heating components is obtained at the same time, then information correlation analysis is performed on the information of each heating component to determine the foreign object falling state of each heating component.

[0151] For each heating component, if the foreign object in the heating component is in the state of "fallen", the information obtained from the heating component is analyzed to determine the degree of risk of foreign object falling into the heating component.

[0152] If the foreign object falling from the heating component is not detected, the risk level of the foreign object falling from the heating component is determined to be no risk.

[0153] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0154] Heating prediction is made based on historical usage periods and historical heating temperatures from historical usage information to obtain the predicted start-up period and initial predicted temperature of the heating components for the skirting board heater.

[0155] Obtain the temperature during the predicted start time period;

[0156] Based on the temperature over a given period, the initial predicted temperature is adjusted to obtain the predicted heating temperature.

[0157] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0158] Obtain user's historical usage information regarding the baseboard heater;

[0159] Heating prediction is made based on historical usage periods and historical heating temperatures from historical usage information to obtain the predicted start-up period and predicted heating temperature of the heating components for the skirting board heater.

[0160] At the target time before the predicted start time, obtain indoor environmental information for the target time.

[0161] By combining indoor environmental information and predicted heating temperature, the heating power of the heating components at the target time is determined;

[0162] During the operation of the heating component according to the heating power, the degree of risk of foreign objects falling into the heating component is determined based on the operating information of the heating component.

[0163] Implement risk management measures related to the degree of risk of foreign object falling.

[0164] In one embodiment, the number of heating components is multiple; the operating information includes acceleration information, vibration information, and sound information. In this embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0165] If at least one of the acceleration information, vibration information, and sound information of multiple heating components is obtained at the same time, then information correlation analysis is performed on the information of each heating component to determine the foreign object falling state of each heating component.

[0166] For each heating component, if the foreign object in the heating component is in the state of "fallen", the information obtained from the heating component is analyzed to determine the degree of risk of foreign object falling into the heating component.

[0167] If the foreign object falling from the heating component is not detected, the risk level of the foreign object falling from the heating component is determined to be no risk.

[0168] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0169] Heating prediction is made based on historical usage periods and historical heating temperatures from historical usage information to obtain the predicted start-up period and initial predicted temperature of the heating components for the skirting board heater.

[0170] Obtain the temperature during the predicted start time period;

[0171] Based on the temperature over a given period, the initial predicted temperature is adjusted to obtain the predicted heating temperature.

[0172] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0173] Obtain user's historical usage information regarding the baseboard heater;

[0174] Heating prediction is made based on historical usage periods and historical heating temperatures from historical usage information to obtain the predicted start-up period and predicted heating temperature of the heating components for the skirting board heater.

[0175] At the target time before the predicted start time, obtain indoor environmental information for the target time.

[0176] By combining indoor environmental information and predicted heating temperature, the heating power of the heating components at the target time is determined;

[0177] During the operation of the heating component according to the heating power, the degree of risk of foreign objects falling into the heating component is determined based on the operating information of the heating component.

[0178] Implement risk management measures related to the degree of risk of foreign object falling.

[0179] In one embodiment, the number of heating components is multiple; the operating information includes acceleration information, vibration information, and sound information. In this embodiment, when the computer program is executed by the processor, it further performs the following steps:

[0180] If at least one of the acceleration information, vibration information, and sound information of multiple heating components is obtained at the same time, then information correlation analysis is performed on the information of each heating component to determine the foreign object falling state of each heating component.

[0181] For each heating component, if the foreign object in the heating component is in the state of "fallen", the information obtained from the heating component is analyzed to determine the degree of risk of foreign object falling into the heating component.

[0182] If the foreign object falling from the heating component is not detected, the risk level of the foreign object falling from the heating component is determined to be no risk.

[0183] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0184] Heating prediction is made based on historical usage periods and historical heating temperatures from historical usage information to obtain the predicted start-up period and initial predicted temperature of the heating components for the skirting board heater.

[0185] Obtain the temperature during the predicted start time period;

[0186] Based on the temperature over a given period, the initial predicted temperature is adjusted to obtain the predicted heating temperature.

[0187] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0188] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0189] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0190] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for controlling the heating of skirting boards, characterized in that, The method includes: Obtain user's historical usage information regarding the baseboard heater; Based on the historical usage time period and historical heating temperature in the historical usage information, heating prediction is performed to obtain the predicted start time period and predicted heating temperature of the heating component for the skirting board heater. At a target time before the predicted start time, obtain indoor environmental information for the target time. Based on the indoor environmental information and the predicted heating temperature, the heating power of the heating component at the target time is determined; During the operation of the heating component according to the heating power, the degree of risk of foreign objects falling into the heating component is determined based on the operating information of the heating component; Implement risk management measures related to the degree of risk of the foreign object falling.

2. The method according to claim 1, characterized in that, The number of heating components is multiple; the operating information includes acceleration information, vibration information, and sound information; determining the risk level of foreign object falling from the heating components based on the operating information includes: If at least one of the acceleration information, vibration information, and sound information of multiple heating components is obtained simultaneously, then information correlation analysis is performed on the information of each heating component to determine the foreign object falling state of each heating component. For each heating component, if the foreign object in the heating component has fallen, the obtained information about the heating component is analyzed to determine the degree of risk of foreign object falling into the heating component. If the foreign object falling from the heating component is not detected, the risk level of the foreign object falling from the heating component is determined to be no risk.

3. The method according to claim 1, characterized in that, The heating prediction based on the historical usage periods and historical heating temperatures in the historical usage information, to obtain the predicted start-up period and predicted heating temperature for the heating component of the skirting board heater, includes: Based on the historical usage period and historical heating temperature in the historical usage information, heating prediction is performed to obtain the predicted start-up period and initial predicted temperature of the heating component for the skirting board heater. Obtain the temperature during the predicted start-up period; Based on the temperature during the specified time period, the initial predicted temperature is adjusted to obtain the predicted heating temperature.

4. A skirting board heater, characterized in that, This includes interconnected control and heating components; The control component is used to acquire historical usage information of the user regarding the skirting board heater; Based on the historical usage time period and historical heating temperature in the historical usage information, heating prediction is performed to obtain the predicted start time period and predicted heating temperature of the heating component for the skirting board heater. At a target time before the predicted start time, obtain indoor environmental information for the target time. Based on the indoor environmental information and the predicted heating temperature, the heating power of the heating component at the target time is determined; During the operation of the heating component according to the heating power, the degree of risk of foreign objects falling into the heating component is determined based on the operating information of the heating component; Implement risk management measures related to the degree of risk of the foreign object falling.

5. The skirting board heater according to claim 4, characterized in that, The number of heating components is multiple; each heating component has a coupler on at least one side for connecting to other heating components via the coupler.

6. The skirting board heater according to claim 5, characterized in that, The coupler is also surrounded by a magnet; The magnet is used to attract magnets on the periphery of couplers on other heating components to connect the heating component to which the magnet belongs to the other heating components.

7. The skirting board heater according to claim 4, characterized in that, The skirting board heater also includes a current sensing component; the current sensing component is connected to the control component; The current sensing component is used to detect the operating current of the heating component when it is working; The control component is used to acquire the operating current and, if the operating current is higher than a current threshold, to turn off the heating component.

8. A skirting board heating control device, characterized in that, The device includes: The historical usage information acquisition module is used to acquire the user's historical usage information for the skirting board heater; The heating prediction module is used to make heating predictions based on the historical usage time period and historical heating temperature in the historical usage information, so as to obtain the predicted start-up time period and predicted heating temperature of the heating component for the skirting board heater. The indoor environment information acquisition module is used to acquire indoor environment information at a target time before the predicted start time period. A heating power determination module is used to determine the heating power of the heating component at the target time by combining the indoor environment information and the predicted heating temperature; The risk level determination module is used to determine the risk level of foreign object falling from the heating component based on the working information of the heating component during the operation of the heating component according to the heating power. The control measures execution module is used to execute risk control measures related to the degree of risk of the foreign object falling.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 3.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 3.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 3.

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