Notebook computer intelligent heat dissipation control system based on multi-modal sensors

Abstract

The application belongs to the technical field of computer control, and discloses a notebook computer intelligent heat dissipation control system based on a multi-modal sensor, which comprises the following steps: collecting multi-modal thermal sensing data of a notebook computer; identifying a current running scene type and obtaining user heat dissipation preferences based on the multi-modal thermal sensing data; calculating a thermal trend index of each hardware component of the notebook computer according to historical multi-modal thermal sensing data and the current running scene type; generating a heat dissipation regulation scheme with scene adaptability based on the thermal trend index, the current running scene type and the user heat dissipation preferences; and realizing notebook computer intelligent heat dissipation control in a progressive regulation mode according to the heat dissipation regulation scheme, so that the stability of the notebook computer performance is greatly improved and the hardware service life is prolonged.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer control, more particularly, the present application relates to a notebook computer intelligent heat dissipation control system based on multi-modal sensors. BACKGROUND

[0002] With the continuous improvement of the performance of portable computing devices, the power consumption and heat generation of notebook computer processors and graphics cards have increased significantly, which puts higher requirements on the heat dissipation system; effective heat dissipation management is crucial to maintaining hardware performance and prolonging device life, so an intelligent heat dissipation control system is needed to balance device performance and user experience; the use scenarios of notebook computers show significant diversity characteristics, that is, some scenarios, such as gaming or video rendering, require high-performance operation, at which time the heat dissipation system must provide sufficient cooling capacity to prevent hardware overheating and frequency reduction; while some scenarios, such as meetings or office work in a library environment, require a quiet user experience, at which time the fan noise should be appropriately controlled to improve user comfort.

[0003] The existing method monitors the hardware temperature in real time, then judges the device load state, and then adjusts the fan speed in real time to complete heat dissipation control; in the traditional notebook computer heat dissipation system, the control of the fan speed usually relies on the adjustment of the cooling intensity by the hardware temperature threshold, this method will respond frequently according to the temperature change, and the adjustment range of the fan speed is too large, which will cause additional stress and wear to the fan motor, resulting in a shortened service life of the heat dissipation system; secondly, this frequent change in fan noise may cause auditory interference to the user, increasing the fatigue of use, thereby reducing the work or entertainment experience, and the existing heat dissipation control strategy often uses a general heat dissipation mode, which cannot meet the individual needs of different users in different scenarios.

[0004] In view of this, the present application proposes a notebook computer intelligent heat dissipation control system based on multi-modal sensors to solve the above problems. SUMMARY

[0005] In order to overcome the above-mentioned defects of the prior art, in order to achieve the above-mentioned purpose, the present application provides the following technical scheme: a notebook computer intelligent heat dissipation control system based on multi-modal sensors, comprising:

[0006] A data acquisition module acquires multi-modal thermal perception data of the notebook computer;

[0007] A scene recognition module identifies the current running scene type based on the multi-modal thermal perception data and obtains the user's heat dissipation preference;

[0008] An analysis module calculates the heat trend index of each hardware component of the notebook computer according to the historical multi-modal thermal perception data and the current running scene type;

[0009] A scheme construction module: generating a heat dissipation regulation scheme with scene adaptability based on the heat trend index, the current running scene type and the user heat dissipation preference;

[0010] A regulation module: implementing the notebook computer intelligent heat dissipation control in a progressive adjustment mode according to the heat dissipation regulation scheme.

[0011] Further, the current running scene type is identified based on the multi-modal heat perception data, and the user heat dissipation preference is obtained, including:

[0012] Extracting a state feature vector representing a current use state based on the multi-modal heat perception data;

[0013] Calculating the similarity of the state feature vector and a preset context template, the context template including a high-performance computing context, an office document processing context, a video playing context, a webpage browsing context and a silent standby context;

[0014] Determining the current running scene type according to the context template with the highest similarity;

[0015] Recording the temperature tolerance and noise sensitivity of the user under the current running scene type to form the user heat dissipation preference.

[0016] Further, the state feature vector representing the current use state is extracted based on the multi-modal heat perception data, including:

[0017] Separating the multi-modal heat perception data into a hardware temperature stream, a hardware usage rate stream and an environment perception stream;

[0018] Performing time series filtering on the hardware temperature stream to extract a temperature mean value, a temperature change gradient and a temperature fluctuation variance as thermal inertia features;

[0019] Performing load mode analysis on the hardware usage rate stream to extract a central processing unit utilization rate peak value, a graphics processing unit load rate change slope and a memory occupancy rate duration as load intensity features;

[0020] Performing spatial modeling on the environment perception stream to extract a heat dissipation bottom surface contact area proportion and an environment temperature and body temperature difference value as heat conduction efficiency features;

[0021] Normalizing and fusing the thermal inertia features, the load intensity features and the heat conduction efficiency features to generate a multi-dimensional state feature vector, wherein the load intensity features are given the highest weight factor to preferentially respond to a computing task mutation.

[0022] Further, the heat trend index of each hardware component of the notebook computer is calculated, including:

[0023] segmenting the historical multi-modal thermal perception data according to time sequence to obtain historical running scenarios;

[0024] extracting the temperature change rate and the temperature peak of each hardware component in the historical running scenarios to form a temperature change pattern;

[0025] combining the current running scenario type and the temperature change pattern in the historical same scenario to predict the temperature change trend of each hardware component in the future period;

[0026] taking the ratio of the predicted temperature change trend and the temperature threshold of each hardware component as a thermal trend index, the thermal trend index representing the urgency of the hardware component reaching the temperature threshold.

[0027] Further, the generation of the scenario-adaptive heat dissipation regulation scheme comprises:

[0028] determining the hardware components requiring key heat dissipation and the heat dissipation urgency based on the thermal trend index, and determining a heat dissipation priority strategy according to the current running scenario type;

[0029] combining the user heat dissipation preference and the heat dissipation priority strategy to calculate the heat dissipation response intensity and response timing, and constructing a heat dissipation regulation scheme; the heat dissipation regulation scheme comprises fan speed adjustment parameters and processor performance adjustment parameters.

[0030] Further, the determination of the hardware components requiring key heat dissipation and the heat dissipation urgency based on the thermal trend index comprises:

[0031] dividing the thermal trend index of each hardware component into an urgency level, setting three heat dissipation urgency levels: if the thermal trend index is greater than a first urgency threshold, the hardware is divided into an emergency heat dissipation level; if the thermal trend index is greater than or equal to a second urgency threshold and less than or equal to the first urgency threshold, the hardware is divided into a proactive heat dissipation level; if the thermal trend index is less than the second urgency threshold, the hardware is divided into a regular heat dissipation level;

[0032] correcting the thermal trend index based on the function weight coefficient of each hardware component to obtain a corrected thermal trend index; sorting the corrected thermal trend index from high to low, and marking the top M hardware components as key heat dissipation objects and marking their corresponding urgency levels.

[0033] Further, the notebook computer intelligent heat dissipation control is realized in a progressive adjustment mode, which comprises the control of the notebook computer fan speed, the control of the notebook computer processor performance, and the heat dissipation adjustment based on environmental adaptability.

[0034] Further, the control of the notebook computer fan speed comprises:

[0035] Setting the minimum change unit and minimum time interval of fan speed adjustment;

[0036] According to the fan speed adjustment parameters in the heat dissipation regulation scheme, the difference between the target fan speed and the current fan speed is calculated;

[0037] The difference is decomposed into multiple gradual adjustment steps according to the minimum change unit;

[0038] Each gradual adjustment step is executed in sequence according to the minimum time interval, realizing the smooth change of fan speed;

[0039] After each adjustment step is executed, the fan noise level is collected, and if it exceeds the user noise sensitivity threshold, the execution speed of the subsequent adjustment step is delayed.

[0040] Further, the control of the notebook computer processor performance includes:

[0041] Setting the minimum adjustment unit and minimum adjustment time interval of processor frequency, voltage and power consumption limit;

[0042] According to the processor performance adjustment parameters in the heat dissipation regulation scheme, the difference between the target performance state and the current performance state is calculated;

[0043] The difference is decomposed into multiple gradual adjustment steps according to the minimum adjustment unit;

[0044] Each gradual adjustment step is executed in sequence according to the minimum adjustment time interval, realizing the smooth change of processor performance parameters;

[0045] Monitor the temperature change rate after each adjustment step is executed, when the temperature drop rate reaches the preset threshold, suspend the subsequent frequency reduction step to maintain performance;

[0046] In high temperature conditions, the processor power consumption limit is adjusted first, followed by the frequency, and finally the voltage, forming a multi-level performance adjustment mechanism.

[0047] Further, the heat dissipation adjustment based on environmental adaptability includes:

[0048] Detecting the placement environment of the notebook computer, including the desktop material, surrounding space limit and environmental temperature;

[0049] Based on the placement environment, evaluate the effectiveness and heat dissipation efficiency of the heat dissipation channel, and detect the environmental conditions based on the effectiveness and heat dissipation efficiency of the heat dissipation channel;

[0050] When detecting a heat dissipation limited environment, adjust the heat dissipation strategy and strengthen internal heat dispersion and processor power consumption control;

[0051] When a favorable heat dissipation environment is detected, the fan speed is reduced, reducing noise and energy consumption.

[0052] The notebook computer intelligent heat dissipation control system based on multi-modal sensors has the following technical effects and advantages:

[0053] The notebook computer intelligent heat dissipation control system based on multi-modal sensors has the following technical effects and advantages: Through the collection and analysis of multi-modal thermal perception data, the system realizes comprehensive perception and precise control of the notebook computer's heat dissipation state, integrates multi-dimensional data such as temperature, environment, load, user behavior, and noise into a unified heat dissipation decision basis, thereby enhancing the adaptability of the system. Through scene recognition module and heat trend index calculation, the system can intelligently identify the current running scene and predict the temperature change trend of each hardware component, realizing forward-looking control of heat dissipation. This scene-based predictive control strategy ensures the coordinated operation of hardware components in different use scenarios, significantly improves heat dissipation efficiency, and avoids noise interference and performance fluctuations caused by traditional heat dissipation methods. Through the cooperative work of the multi-modal sensor array, the system can comprehensively perceive the internal temperature distribution and external environmental conditions of the notebook computer, cope with diversified heat dissipation needs in different use scenarios, and improve the individualization degree and user satisfaction of the system through learning and adaptation of user heat dissipation preferences. By introducing a gradual adjustment mechanism, the system realizes smooth changes in fan speed and processor performance, avoiding sudden changes in traditional heat dissipation control and improving user experience comfort. Based on environmental adaptability, the heat dissipation adjustment can automatically adjust the heat dissipation strategy according to the actual placement environment of the notebook computer, ensuring efficient heat management in different environmental conditions, significantly prolonging hardware life and improving system stability. Thus, for the complex and variable use scenarios and environmental conditions of notebook computers, the system realizes automated and intelligent heat dissipation control, ensuring hardware performance while optimizing noise control and energy consumption, ensuring stable system operation while providing better user experience. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 The notebook computer intelligent heat dissipation control system based on multi-modal sensors has the following technical effects and advantages:

[0055] Figure 2 The notebook computer intelligent heat dissipation control system based on multi-modal sensors has the following technical effects and advantages: DETAILED DESCRIPTION

[0056] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0057] Embodiment 1

[0058] Referring to Figure 1 As shown in the figure, the embodiment is a notebook computer intelligent heat dissipation control system based on a multi-modal sensor, which comprises:

[0059] A data acquisition module, a scene recognition module, an analysis module, a scheme construction module and a regulation and control module. The data flow and functional cooperation among the modules realize intelligent control of notebook computer heat dissipation, effectively solving the problems of traditional heat dissipation schemes that cannot adapt to different scene requirements, poor user experience and low heat dissipation efficiency, etc.

[0060] The data acquisition module: acquires multi-modal thermal perception data of the notebook computer;

[0061] A variety of sensors are integrated in the notebook computer system to form a complete thermal state perception network, and various types of data related to heat management are comprehensively collected. These data collectively constitute the thermal characteristics and use environment characteristics of the notebook computer, providing comprehensive data support for subsequent intelligent heat dissipation control.

[0062] Preferably, in some possible implementation manners of the embodiment, the collection content of the multi-modal thermal perception data includes: collecting real-time temperature data of the notebook computer processor, graphics card, memory and battery through a temperature sensing array to obtain hardware temperature; collecting notebook computer surrounding environment temperature, humidity and airflow condition through an environment perceiver to form environment data; collecting processor utilization rate, memory occupancy rate and graphics card load rate through a performance monitoring component to form processor load; recording user input frequency, application program switching frequency and running program type through a user behavior capture unit to form user operation behavior; measuring environment background noise level and notebook computer fan noise level through an acoustic perceiver to form environment noise level.

[0063] It should be noted that the temperature sensing array adopts a high-precision digital temperature sensor, which is arranged at each main heat source position of the notebook computer, and the sampling frequency is 10 times per second; the environment perceiver is arranged at the notebook computer air inlet and air outlet positions for real-time monitoring of environment parameter changes; the performance monitoring component obtains hardware resource occupancy data based on an operating system API; the user behavior capture unit records user interaction mode by monitoring system events and application state changes; the acoustic perceiver is realized by a built-in microphone array, and distinguishes environment noise and fan noise through spectrum analysis.

[0064] In one implementation manner of the embodiment, the collection period of various types of data is set to 1 second to ensure that the system can respond to the thermal state changes of the hardware in a timely manner. The collected raw data is preprocessed through filtering, normalization and the like to form a standardized multi-modal thermal perception data matrix for subsequent analysis and processing.

[0065] a scene recognition module, which recognizes a current running scene type based on multi-modal thermal perception data and obtains a user heat dissipation preference;

[0066] The demand for heat dissipation of a notebook computer varies significantly in different use scenarios, for example, performance is prioritized in a gaming scenario, and noise control is more important in an office scenario. By recognizing the current running scene, combined with the user's personalized preference for heat dissipation, a more accurate heat dissipation strategy can be formulated.

[0067] Preferably, in some possible implementation manners of the embodiment of the present application, the implementation method of scene recognition comprises: extracting a state feature vector representing a current use state based on multi-modal thermal perception data; calculating the similarity of the state feature vector and a preset context template, the context template comprising a high-performance computing context, an office document processing context, a video playing context, a webpage browsing context and a silent standby context; determining the current running scene type according to the context template with the highest similarity; and recording the temperature tolerance and noise sensitivity of the user in the current running scene type to form the user heat dissipation preference.

[0068] Preferably, in some possible implementation manners of the embodiment of the present application, the extraction of the state feature vector representing the current use state comprises: separating the multi-modal thermal perception data into a hardware temperature stream, a hardware usage rate stream and an environment perception stream; performing time series filtering on the hardware temperature stream to extract the temperature mean value, temperature change gradient and temperature fluctuation variance as thermal inertia features; performing load mode analysis on the hardware usage rate stream to extract the central processing unit utilization rate peak value, graphics processing unit load rate change slope and memory occupancy rate duration as load intensity features; performing spatial modeling on the environment perception stream to extract the heat dissipation bottom surface contact area ratio and the temperature difference between the environment and the body as heat conduction efficiency features; and performing normalized fusion of the thermal inertia features, load intensity features and heat conduction efficiency features to generate a multi-dimensional state feature vector, wherein the load intensity features are given the highest weight factor to respond to the calculation task mutation preferentially.

[0069] The state feature vector contains multi-dimensional features such as hardware temperature and environment, and comprehensively represents the current running state of the notebook computer. The preset context template is a typical use scenario feature set obtained based on a large amount of user use data statistical analysis, and each context template contains a feature vector standard mode in the scenario.

[0070] In one implementation manner of the embodiment of the present application, the cosine similarity is used to calculate the matching degree of the current state feature vector and the preset context template, and the context template with the highest similarity is taken as the current running scene type. To improve the recognition accuracy, the system combines the recognition results of consecutive multiple time windows, adopts a majority voting mechanism to determine the final scene type, and avoids frequent jumping of scene recognition.

[0071] The user heat dissipation preference is obtained by analyzing the manual intervention behavior of the user to the automatic adjustment of the system in a specific scenario, for example, the user frequently manually reduces the fan speed in the video playing scenario, indicating that the user is sensitive to noise in this scenario. The system continuously learns and updates the user preference data to form a personalized user heat dissipation preference model.

[0072] The analysis module calculates the heat trend index of each hardware component of the notebook computer according to the historical multi-modal heat perception data and the current running scenario type;

[0073] The heat trend index reflects the temperature rising trend and potential risk of each hardware component, and is a key basis for formulating accurate heat dissipation strategies. By analyzing the temperature change pattern in the similar scenario in the historical data, the temperature change trend of each component in the current scenario can be predicted, and heat dissipation measures can be taken in advance.

[0074] Preferably, in some possible implementation manners of the embodiment of the present application, the calculation method of the heat trend index comprises: segmenting the historical multi-modal heat perception data according to time sequence for heat pattern analysis to obtain historical running scenarios; extracting the temperature change rate and temperature peak value of each hardware component in the historical running scenarios to form a temperature change pattern; combining the current running scenario type and the temperature change pattern in the historical similar scenarios to predict the temperature change trend of each hardware component in the future period; and taking the ratio of the predicted temperature change trend and the temperature threshold value of each hardware component as the heat trend index, and the heat trend index represents the urgency of the hardware component reaching the temperature threshold value.

[0075] The heat pattern analysis adopts a sliding window technology, and the historical data is segmented and processed, and the length of each window is 5 minutes, and adjacent windows overlap by 50%. The data in each window is subjected to feature extraction and scenario labeling to form a historical running scenario database. The temperature change pattern includes multiple characteristic parameters such as temperature rising rate, duration, peak temperature and the like, and comprehensively describes the heat behavior characteristics of the hardware component in a specific scenario.

[0076] In one implementation manner of the embodiment of the present application, a time series prediction model is used to predict the temperature change trend of each hardware component in the next 10 minutes. The model input includes the current temperature, the load state, the historical temperature change pattern and the like, and the output is the temperature change curve in the prediction period. The ratio of the predicted maximum temperature to the temperature threshold value of the component is taken as the heat trend index, and the closer the heat trend index is to 1, the closer the component is to the temperature threshold value, and the more urgent the heat dissipation demand is.

[0077] It should be noted that the temperature threshold values of different hardware components are different, and the processor is usually 90℃, the graphics card is 85℃, the memory is 80℃, and the battery is 45℃. The system will automatically adjust these threshold values according to the hardware specifications to ensure the accuracy of the heat trend index.

[0078] A scheme construction module: based on the heat trend index, the current running scene type and the user heat dissipation preference, a heat dissipation regulation scheme with scene adaptability is generated;

[0079] The heat dissipation regulation scheme is a specific guidance scheme for the system to perform heat dissipation operation, including fan rotating speed, processor performance state and other regulation parameters. By comprehensively considering the heat trend index, scene demand and user preference, the optimal heat dissipation regulation scheme is generated to achieve the balance between heat dissipation effect and user experience.

[0080] Preferably, in some possible implementation manners of the embodiment of the present application, the heat dissipation regulation scheme generation method comprises: based on the heat trend index, determining the hardware components needing to be focused on heat dissipation and the heat dissipation urgency degree and determining the heat dissipation priority strategy according to the current running scene type; combining the user heat dissipation preference and the heat dissipation priority strategy to calculate the heat dissipation response intensity and response timing, and constructing the heat dissipation regulation scheme; the heat dissipation regulation scheme includes fan rotating speed adjustment parameters and processor performance adjustment parameters.

[0081] The heat dissipation urgency degree is divided based on the heat trend index, and the specific process is to set three levels of heat dissipation urgency: if the heat trend index is greater than a first urgency threshold, the hardware is divided into an emergency heat dissipation level; if the heat trend index is greater than or equal to a second urgency threshold and less than or equal to the first urgency threshold, the hardware is divided into a proactive heat dissipation level; and if the heat trend index is less than the second urgency threshold, the hardware is divided into a regular heat dissipation level;

[0082] The heat trend index is corrected based on the function weight coefficient of each hardware component to obtain a corrected heat trend index; for example, the function weight coefficient of the central processing unit and the graphics processing unit is set to the highest value 1.0, the function weight coefficient of the memory module and the hard disk component is set to 0.7, and the function weight coefficient of other peripheral chips is set to 0.4; the corrected heat trend index is the product of the original heat trend index and the function weight coefficient; the hardware components in the top M positions are marked as the heat dissipation focus according to the order from high to low of the corrected heat trend index, and the corresponding urgency degree level is marked;

[0083] In one implementation manner of the embodiment of the present application, the value of the first urgency threshold is set to 0.8, the value of the second urgency threshold is set to 0.5, and the value of M is set to 4.

[0084] The heat dissipation priority strategy formulates different heat dissipation focuses according to the characteristics of different scenes: in the high-performance computing context, the hardware performance and temperature control are preferentially guaranteed, and a higher fan noise level is allowed; in the office document processing context, the temperature control and noise control are balanced, and a medium fan rotating speed is maintained; in the video playing context, the fan noise tolerance is dynamically adjusted according to the video volume; in the webpage browsing context, a low-noise environment is preferentially guaranteed, and a mild heat dissipation control strategy is adopted; and in the silent standby context, the fan rotating speed is minimized to reduce the energy consumption and noise level.

[0085] In one implementation of the embodiment of the present application, the heat dissipation response strength is calculated using a fuzzy logic control algorithm, the input variables include a heat trend index, a heat dissipation urgency, whether it is a key heat dissipation object, user noise sensitivity and scene priority, and the output variables are fan speed increment and processor performance adjustment amplitude.

[0086] The fan speed adjustment parameters in the heat dissipation regulation scheme include target speed, speed change step and speed change interval; the processor performance adjustment parameters include frequency adjustment value, power consumption limit value and voltage adjustment value. These parameters together constitute a complete set of heat dissipation regulation instructions to guide the system to perform specific heat dissipation operations.

[0087] The regulation module: according to the heat dissipation regulation scheme, the notebook computer intelligent heat dissipation control is realized in a progressive adjustment mode;

[0088] The traditional heat dissipation control usually adopts step adjustment, which leads to poor user experience and unstable heat dissipation effect. The present application adopts a progressive adjustment mode, which makes the heat dissipation control more smooth and natural, improves the user experience and optimizes the heat dissipation effect. The progressive adjustment includes control of notebook computer fan speed, control of notebook computer processor performance and heat dissipation adjustment based on environmental adaptability.

[0089] Preferably, in some possible implementations of the embodiment of the present application, the control method of notebook computer fan speed includes: setting the minimum change unit and the minimum time interval of fan speed adjustment; calculating the difference between the target fan speed and the current fan speed according to the fan speed adjustment parameters in the heat dissipation regulation scheme; decomposing the difference into multiple progressive adjustment steps according to the minimum change unit; sequentially executing each progressive adjustment step according to the minimum time interval to realize the smooth change of fan speed; after each adjustment step is executed, the fan noise level is collected, and if it exceeds the user noise sensitivity threshold, the execution speed of the subsequent adjustment step is delayed.

[0090] In one implementation of the embodiment of the present application, the minimum change unit of fan speed is set to 50 RPM and the minimum time interval is set to 200 milliseconds. For example, when the fan speed needs to be increased from 2000 RPM to 2500 RPM, the system will decompose the difference of 500 RPM into 10 adjustment steps of 50 RPM, execute the adjustment every 200 milliseconds, and complete the whole speed increasing process in 2 seconds. This progressive adjustment method avoids the noise impact caused by sudden speed change and improves the user experience.

[0091] The control method for notebook computer processor performance includes: setting minimum adjustment unit and minimum adjustment time interval of processor frequency, voltage and power consumption limit; calculating difference value between target performance state and current performance state according to processor performance adjustment parameter in heat dissipation regulation scheme; decomposing the difference value into multiple progressive adjustment steps according to the minimum adjustment unit; sequentially executing each progressive adjustment step according to the minimum adjustment time interval to realize smooth change of processor performance parameter; monitoring temperature change rate after each adjustment step is executed, and when the temperature drop rate reaches a preset threshold, suspending subsequent frequency reduction steps to maintain performance; in the case of high temperature, the processor power consumption limit is adjusted first, then the frequency is adjusted, and finally the voltage is adjusted, forming a multi-level performance adjustment mechanism.

[0092] In an implementation manner of the embodiment of the present application, the minimum adjustment unit of the processor frequency is 100 MHz, and the minimum adjustment time interval is 300 milliseconds; the minimum adjustment unit of the power consumption limit is 1 W, and the minimum adjustment unit of the voltage is 0.01 V. The system adopts a hierarchical control strategy, first realizes rapid cooling by adjusting the power consumption limit, and then gradually adjusts the frequency and voltage when the temperature is still not effectively controlled, to ensure that the necessary performance is maintained while the temperature is effectively controlled.

[0093] The heat dissipation regulation based on environmental adaptability includes: detecting the placement environment of the notebook computer, including the desktop material, the surrounding space limitation and the environmental temperature; based on the placement environment, evaluating the effectiveness and heat dissipation efficiency of the heat dissipation channel, detecting the environmental condition based on the effectiveness and heat dissipation efficiency of the heat dissipation channel; when a heat dissipation limited environment is detected, adjusting the heat dissipation strategy to strengthen internal heat dispersion and processor power consumption control; when a favorable heat dissipation environment is detected, reducing the fan speed to reduce noise and energy consumption.

[0094] In an implementation manner of the embodiment of the present application, the system judges the heat dissipation environmental condition by analyzing the air flow state and temperature gradient of the air inlet and outlet. For example, when the air outlet temperature is abnormally high and the air volume is small, it may indicate that the heat dissipation channel is blocked; when the environmental temperature is low and the air flow is smooth, the system can appropriately reduce the fan speed to reduce noise while maintaining good heat dissipation effect.

[0095] It should be noted that after each heat dissipation regulation operation is executed, the system records the regulation effect and user feedback, continuously optimizes the heat dissipation strategy and control parameter, forms a self-adaptive learning mechanism, and makes the heat dissipation control effect continuously improve with the increase of use time.

[0096] In other embodiments of the present application, multi-modal thermal perception data can also be input into a pre-trained deep learning model, and the model directly outputs the optimal heat dissipation regulation scheme, simplifying the heat dissipation control process and improving the system response speed.

[0097] By the above technical solution, the notebook computer intelligent heat dissipation control system based on a multi-modal sensor can automatically adjust the heat dissipation strategy according to different use scenarios and user preferences, achieve the best balance between heat dissipation effect and user experience, effectively solve the problems existing in the traditional heat dissipation scheme, and improve the use experience and heat dissipation efficiency of the notebook computer.

[0098] The embodiment realizes comprehensive perception and precise control of the notebook computer heat dissipation state through the collection and analysis of multi-modal thermal perception data, can integrate multi-dimensional data such as temperature, environment, load, user behavior and noise into a unified heat dissipation decision basis, thereby enhancing the adaptability of the system. Through the scene recognition module and the heat trend index calculation, the system can intelligently identify the current running scene and predict the temperature change trend of each hardware component, realizing the forward-looking control of heat dissipation. This scene-based predictive control strategy can ensure the coordinated operation of hardware components in different use scenarios, greatly improving the heat dissipation efficiency and avoiding the noise interference and performance fluctuation problems caused by traditional heat dissipation methods. Through the cooperative work of the multi-modal sensor array, the system can comprehensively perceive the internal temperature distribution and external environment of the notebook computer, cope with diversified heat dissipation needs in different use scenarios, and improve the individualization degree and user satisfaction of the system through the learning and adaptation of user heat dissipation preferences. By introducing the gradual adjustment mechanism, the system realizes the smooth change of fan speed and processor performance, avoiding the mutation problem in traditional heat dissipation control, and improving the comfort of user experience. Based on the environmental adaptability of heat dissipation adjustment, the system can automatically adjust the heat dissipation strategy according to the actual placement environment of the notebook computer, ensuring efficient heat management under different environmental conditions, significantly prolonging the hardware life and improving the system stability. Thus, for the complex and variable use scenarios and environmental conditions of the notebook computer, the automatic and intelligent heat dissipation control is realized, which not only guarantees the performance of hardware, but also optimizes the noise control and energy consumption, ensuring the stable operation of the system while providing better user experience.

[0099] Embodiment 2

[0100] Please refer to Figure 2 The embodiment does not describe some parts in detail, see the description of embodiment 1, the notebook computer intelligent heat dissipation control method based on multi-modal sensor includes:

[0101] Step S1: collecting multi-modal thermal perception data of the notebook computer;

[0102] Step S2: identifying the current running scene type based on the multi-modal thermal perception data and obtaining the user heat dissipation preference;

[0103] Step S3: calculating the heat trend index of each hardware component of the notebook computer according to the historical multi-modal thermal perception data and the current running scene type;

[0104] Step S4: generating a heat dissipation regulation scheme with scene adaptability based on the heat trend index, the current running scene type and the user heat dissipation preference;

[0105] Step S5: implementing the notebook computer intelligent heat dissipation control in a progressive adjustment manner according to the heat dissipation regulation scheme.

[0106] The above merely provides the preferred embodiments of the present application but should not be used to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, the skilled in the art should understand that the technical solutions described in the foregoing embodiments can be modified or equivalent replaced, and any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0107] It should be noted that in this document, the terms "comprise", "comprising", or any other variant thereof are intended to cover a non-exclusive inclusion, such that a process, method, article or apparatus that comprises a list of elements does not include only those elements recited, but can also include other elements not expressly listed or inherent to such process, method, article or apparatus. Without more limitations, an element defined by the statement "comprising a" does not exclude the existence of additional identical elements in the process, method, article or apparatus that includes the element.

[0108] In the description of the present application, it should be understood that the terms "first", "second" and the like are only used to distinguish different descriptions, and cannot be understood as indicating or implying relative importance.

[0109] In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0110] In the description of the present application, the meaning of "several" is one or more, and the meaning of "a large number" is two or more.

[0111] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0112] The formula of the present specification is a value calculated by de-dimensioning, the formula is obtained by collecting a large amount of data to simulate a formula of the most recent real situation, and preset parameters and threshold values in the formula are set by a person skilled in the art according to actual conditions.

[0113] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the claims and their equivalents.

Claims

1. A multi-modal sensor based smart thermal control system for a notebook computer, characterized in that, The application comprises: a data acquisition module: collecting multi-modal thermal perception data of a notebook computer; a scene recognition module; identifying the current running scene type and obtaining the user's heat dissipation preference based on the multi-modal thermal perception data; an analysis module: calculating the thermal trend index of each hardware component of the notebook computer according to the historical multi-modal thermal perception data and the current running scene type; a scheme construction module: generating a heat dissipation regulation scheme with scene adaptability based on the thermal trend index, the current running scene type and the user's heat dissipation preference; a regulation module: realizing the notebook computer's intelligent heat dissipation control in a gradual adjustment mode according to the heat dissipation regulation scheme; the notebook computer's intelligent heat dissipation control in a gradual adjustment mode comprises: control of the notebook computer's fan speed, control of the notebook computer's processor performance and environment-adaptive heat dissipation adjustment; the control of the notebook computer's fan speed comprises: setting the minimum change unit and the minimum time interval of fan speed adjustment; calculating the difference between the target fan speed and the current fan speed according to the fan speed adjustment parameter in the heat dissipation regulation scheme; decomposing the difference into multiple gradual adjustment steps according to the minimum change unit; sequentially executing each gradual adjustment step according to the minimum time interval to realize the smooth change of the fan speed; after the execution of each adjustment step, collecting the fan noise level, and if it exceeds the user's noise sensitivity threshold, delaying the execution speed of the subsequent adjustment step.

2. The multi-modal sensor based smart thermal control system for a notebook computer of claim 1, wherein, the identification of the current running scene type and the obtaining of the user's heat dissipation preference based on the multi-modal thermal perception data comprise: extracting a state feature vector representing the current use state based on the multi-modal thermal perception data; calculating the similarity between the state feature vector and a preset context template, wherein the context template includes a high-performance computing context, an office document processing context, a video playing context, a web browsing context and a silent standby context; determining the current running scene type according to the context template with the highest similarity; recording the user's temperature tolerance and noise sensitivity under the current running scene type to form the user's heat dissipation preference.

3. The multi-modal sensor based smart thermal control system for a notebook computer of claim 2, wherein, the extraction of the state feature vector representing the current use state based on the multi-modal thermal perception data comprises: separating the multi-modal thermal perception data into hardware temperature flow, hardware usage rate flow and environment perception flow; performing time series filtering on the hardware temperature flow to extract the temperature mean value, temperature change gradient and temperature fluctuation variance as thermal inertia features; performing load pattern analysis on the hardware usage rate flow to extract the central processing unit utilization rate peak value, graphics processing unit load rate change slope and memory occupancy rate duration as load intensity features; performing spatial modeling on the environment perception flow to extract the heat dissipation bottom surface contact area ratio and the environment temperature and body temperature difference value as heat conduction efficiency features; normalizing and fusing the thermal inertia features, load intensity features and heat conduction efficiency features to generate a multi-dimensional state feature vector, wherein the load intensity features are given the highest weight factor to respond to the calculation task mutation preferentially.

4. The multi-modal sensor based smart thermal control system for a notebook computer of claim 1, wherein, the calculation of the thermal trend index of each hardware component of the notebook computer comprises: performing segmented thermal mode analysis on the historical multi-modal thermal perception data according to the time sequence to obtain the historical running scene; extracting temperature change rates and temperature peaks of each hardware component in historical running scenarios to form temperature change patterns; combining the current running scenario type and the temperature change patterns in historical similar scenarios to predict the temperature change trend of each hardware component in the future period; taking the ratio of the predicted temperature change trend and the temperature threshold of each hardware component as the heat trend index, which represents the urgency of the hardware component reaching the temperature threshold.

5. The multi-modal sensor based smart thermal control system for a notebook computer of claim 1, wherein, The generation of the scenario-adaptive heat dissipation regulation scheme includes: based on the heat trend index, determining the hardware components that need to be cooled and the cooling urgency, and determining the cooling priority strategy according to the current running scenario type; combining the user cooling preference and the cooling priority strategy to calculate the cooling response intensity and response timing, and constructing the cooling regulation scheme; the cooling regulation scheme includes fan speed adjustment parameters and processor performance adjustment parameters.

6. The multi-modal sensor based smart thermal control system for a notebook computer of claim 5, wherein, The determination of the hardware components that need to be cooled and the cooling urgency based on the heat trend index includes: dividing the heat trend index of each hardware component into three levels of cooling urgency: if the heat trend index is greater than the first urgency threshold, the hardware is divided into an emergency cooling level; if the heat trend index is greater than or equal to the second urgency threshold and less than or equal to the first urgency threshold, the hardware is divided into a proactive cooling level; if the heat trend index is less than the second urgency threshold, the hardware is divided into a regular cooling level; based on the functional weight coefficient of each hardware component, the heat trend index is corrected to obtain a corrected heat trend index; according to the corrected heat trend index from high to low, the first M hardware components are selected as the key cooling objects, and their corresponding urgency levels are marked.

7. The multi-modal sensor based smart thermal control system for a notebook computer of claim 1, wherein, The control of the notebook computer processor performance includes: setting the minimum adjustment unit and the minimum adjustment time interval of the processor frequency, voltage and power consumption limit; calculating the difference value between the target performance state and the current performance state according to the processor performance adjustment parameter in the cooling regulation scheme; decomposing the difference value into multiple gradual adjustment steps according to the minimum adjustment unit; sequentially executing each gradual adjustment step according to the minimum adjustment time interval to realize the smooth change of the processor performance parameters; monitoring the temperature change rate after each adjustment step is executed, and pausing the subsequent frequency reduction step when the temperature drop rate reaches the preset threshold to maintain the performance; in the case of high temperature, the processor power consumption limit is adjusted first, followed by the frequency, and finally the voltage, forming a multi-level performance adjustment mechanism.

8. The multi-modal sensor based smart thermal control system for a notebook computer of claim 1, wherein, The environment-adaptive cooling adjustment includes: detecting the placement environment of the notebook computer, including the desktop material, the surrounding space limitation and the environment temperature; based on the placement environment, evaluating the effectiveness and efficiency of the cooling channel, and detecting the environmental conditions based on the effectiveness and efficiency of the cooling channel; when a limited cooling environment is detected, adjust the cooling strategy to strengthen internal heat dispersion and processor power consumption control; when a favorable cooling environment is detected, reduce the fan speed to reduce noise and energy consumption.

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