CN112286469B - Solid state disk temperature rise control method and solid state disk - Google Patents
Solid state disk temperature rise control method and solid state disk Download PDFInfo
- Publication number
- CN112286469B CN112286469B CN202011576970.8A CN202011576970A CN112286469B CN 112286469 B CN112286469 B CN 112286469B CN 202011576970 A CN202011576970 A CN 202011576970A CN 112286469 B CN112286469 B CN 112286469B
- Authority
- CN
- China
- Prior art keywords
- solid state
- state disk
- prediction model
- temperature rise
- historical
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 239000007787 solid Substances 0.000 title claims abstract description 172
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000001816 cooling Methods 0.000 claims abstract description 51
- 238000012549 training Methods 0.000 claims abstract description 31
- 230000009467 reduction Effects 0.000 claims abstract description 4
- 230000007613 environmental effect Effects 0.000 claims description 12
- 238000013507 mapping Methods 0.000 claims description 5
- 230000009286 beneficial effect Effects 0.000 abstract description 3
- 230000002265 prevention Effects 0.000 abstract description 3
- 238000010801 machine learning Methods 0.000 description 8
- 230000008569 process Effects 0.000 description 7
- 238000012937 correction Methods 0.000 description 5
- 238000012795 verification Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000017525 heat dissipation Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0602—Interfaces specially adapted for storage systems specifically adapted to achieve a particular effect
- G06F3/0614—Improving the reliability of storage systems
- G06F3/0616—Improving the reliability of storage systems in relation to life time, e.g. increasing Mean Time Between Failures [MTBF]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0602—Interfaces specially adapted for storage systems specifically adapted to achieve a particular effect
- G06F3/0614—Improving the reliability of storage systems
- G06F3/0619—Improving the reliability of storage systems in relation to data integrity, e.g. data losses, bit errors
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/06—Digital input from, or digital output to, record carriers, e.g. RAID, emulated record carriers or networked record carriers
- G06F3/0601—Interfaces specially adapted for storage systems
- G06F3/0668—Interfaces specially adapted for storage systems adopting a particular infrastructure
- G06F3/0671—In-line storage system
- G06F3/0673—Single storage device
- G06F3/0679—Non-volatile semiconductor memory device, e.g. flash memory, one time programmable memory [OTP]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G11—INFORMATION STORAGE
- G11B—INFORMATION STORAGE BASED ON RELATIVE MOVEMENT BETWEEN RECORD CARRIER AND TRANSDUCER
- G11B33/00—Constructional parts, details or accessories not provided for in the other groups of this subclass
- G11B33/14—Reducing influence of physical parameters, e.g. temperature change, moisture, dust
- G11B33/1406—Reducing the influence of the temperature
- G11B33/144—Reducing the influence of the temperature by detection, control, regulation of the temperature
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Human Computer Interaction (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Computer Security & Cryptography (AREA)
- Computing Systems (AREA)
- Mathematical Physics (AREA)
- Control Of Temperature (AREA)
Abstract
The invention discloses a solid state disk temperature rise control method and a solid state disk, which comprise the following steps: establishing a first prediction model for predicting the temperature rise of the solid state disk, and performing model training on the first prediction model; establishing a second prediction model for obtaining the optimal cooling measure of the solid state disk, and training the second prediction model; and obtaining the operating condition and the estimated operating time of the controlled solid state disk, and determining the optimal predicted cooling measure of the solid state disk according to the operating condition, the estimated operating time, the first prediction model and the second prediction model. The technical scheme of the invention aims to solve the problem that the solid state disk lacks a temperature rise prevention measure, and a user can predict the future temperature rise condition of the solid state disk so as to take an optimal temperature reduction measure in advance to avoid the exceeding of the temperature of the solid state disk, thereby being beneficial to ensuring the performance of the solid state disk, prolonging the service life of the solid state disk and preventing data loss.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a solid state disk temperature rise control method and a solid state disk.
Background
The solid state disk often has the condition of overhigh temperature in the use process, and the overhigh temperature can influence the service life of the solid state disk and can also cause data loss. In the prior art, after the temperature of the solid state disk actually rises, common cooling measures are performed on the solid state disk, and an effective temperature rise prevention method is lacked.
Disclosure of Invention
The invention mainly aims to provide a solid state disk temperature rise control method, and aims to solve the problem that a solid state disk lacks a temperature rise prevention measure.
In order to achieve the above object, the solid state disk temperature rise control method provided by the present invention comprises the following steps:
establishing a first prediction model for predicting the temperature rise of the solid state disk, and performing model training on the first prediction model;
establishing a second prediction model for obtaining the optimal cooling measure of the solid state disk, and training the second prediction model;
and obtaining the operating condition and the estimated operating time of the controlled solid state disk, and determining the optimal predicted cooling measure of the solid state disk according to the operating condition, the estimated operating time, the first prediction model and the second prediction model.
Preferably, the step of establishing a first prediction model for predicting the temperature rise of the solid state disk and performing model training on the first prediction model includes:
establishing a first prediction model for predicting the temperature rise of the solid state disk;
acquiring a plurality of groups of first training parameters, wherein the first training parameters comprise solid state disk operating conditions and temperature rise data of the solid state disk after the solid state disk continuously operates for a preset time under different operating conditions;
and inputting a plurality of groups of first training parameters into a first prediction model for predicting the temperature rise data of the solid state disk so as to train the first prediction model.
Preferably, the step of establishing a second prediction model for obtaining the optimal cooling measure of the solid state disk, and training the second prediction model, includes:
establishing a second prediction model for predicting the optimal cooling measure of the solid state disk;
acquiring a plurality of groups of second training data, wherein the second training data comprise optimal cooling measures of the solid state disk under different operation modes and different temperature values;
and inputting a plurality of groups of second training parameters into a second prediction model for predicting the optimal cooling measure of the solid state disk so as to train the second prediction model.
Preferably, the step of obtaining the operating condition and the estimated operating time of the controlled solid state disk and determining the predicted optimal cooling measure of the solid state disk according to the operating condition, the estimated operating time, the first prediction model and the second prediction model includes:
acquiring the operating condition and the estimated operating time of the controlled solid state disk, inputting the operating condition and the estimated operating time into the first prediction model to obtain first output data, and determining predicted temperature rise data of the solid state disk when the estimated operating time is reached according to the first output data;
and acquiring a current working mode of the controlled solid state disk, inputting the predicted temperature rise data and the current working mode into the second prediction model to obtain second output data, and determining the predicted optimal cooling measure of the solid state disk according to the second output data.
Preferably, the method for controlling temperature rise of the solid state disk further includes:
and executing temperature rise control on the controlled solid state disk according to the predicted optimal temperature reduction measure so as to control the temperature rise of the solid state disk in advance.
Preferably, the operating conditions include operating conditions respectively corresponding to the solid state disk at different historical time points.
Preferably, the first prediction model is H ═ Φ (F);
f is input data of the first prediction model, and H is predicted temperature rise data output by the first prediction model; and F represents various factors influencing the temperature rise of the solid state disk, including historical environmental temperature data, historical temperature data of the solid state disk, historical humidity data, historical wind speed data, historical operation modes and predicted operation time.
Preferably, the predicted temperature H output by the first prediction model is calculated by the following formula:
wherein, F1Is the historical temperature data of the environment,Is the ambient historical temperature coefficient, F2History temperature of the solid state disk,Is the historical temperature coefficient, F, of the hard disk3As historical humidity data, Fb1Is standard humidity, F4Is historical wind speed, Fb2Is the standard wind speed, T is the standard temperature,Are the operating mode coefficients determined by the historical operating mode and the expected operating time.
Preferably, the first and second electrodes are formed of a metal,
wherein,is the environmental historical temperature data of the ith time point in the historical time,the solid state disk historical temperature data at the ith time point in the historical time point,is historical humidity data at the ith time point in the historical time,is historical wind speed data of the ith time point in the historical time,the operation mode coefficient at the ith time point in the historical time point,by historical operating modes and operating modesAnd (4) obtaining the mapping table corresponding to the formula coefficient by query, wherein n represents the number of historical time points.
In addition, in order to achieve the above object, the present invention further provides a solid state disk, wherein the temperature control is performed by using any one of the above temperature rise control methods for solid state disks.
The application field of machine learning is more and more extensive, but in the field of solid-state storage, the application of machine learning is still less. Temperature control is an important guarantee for the performance and the service life of the solid state disk. In the technical scheme of the invention, by utilizing the principle of machine learning, the prediction model can predict the temperature rise data of the solid state disk after the continuous operation for the preset time according to different operation conditions and predicted operation time, and can predict the optimal temperature control scheme according to different temperature rise data, so that the temperature rise control of the solid state disk can be executed according to the optimal temperature control scheme at present, and the effective temperature control of the solid state disk is realized. Therefore, when the operating conditions of the controlled solid state disk are known (for example, the ambient temperature can be measured, and the operating program can be known), the user can predict the temperature rise of the solid state disk in the future so as to take an optimal cooling measure in advance to avoid the temperature of the solid state disk from exceeding the standard, which is beneficial to ensuring the performance of the solid state disk, prolonging the service life of the solid state disk and preventing data loss. The invention adopts a machine learning prediction model, so that the prediction data is accurate and effective.
Drawings
Fig. 1 is a schematic flow chart of a solid state disk temperature rise control method according to a first embodiment of the present invention.
The objects, features and advantages of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the following description, suffixes such as "unit", "means", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in themselves. Thus, "unit", "means" or "unit" may be used mixedly.
Referring to fig. 1, in order to achieve the above object, a method for controlling temperature rise of a solid state disk according to a first embodiment of the present invention includes the following steps:
step S10, establishing a first prediction model for predicting the temperature rise of the solid state disk, and carrying out model training on the first prediction model;
step S20, establishing a second prediction model for obtaining the optimal cooling measure of the solid state disk, and training the second prediction model;
and step S30, acquiring the operating condition and the estimated operating time of the controlled solid state disk, and determining the predicted optimal cooling measure of the solid state disk according to the operating condition, the estimated operating time, the first prediction model and the second prediction model.
The application field of machine learning is more and more extensive, but in the field of solid-state storage, the application of machine learning is still less. Temperature control is an important guarantee for the performance and the service life of the solid state disk. In the technical scheme of the invention, by utilizing the principle of machine learning, the prediction model can predict the temperature rise data of the solid state disk after the continuous operation for the preset time according to different operation conditions and predicted operation time, and can predict the optimal temperature control scheme according to different temperature rise data, so that the temperature rise control of the solid state disk can be executed according to the optimal temperature control scheme at present, and the effective temperature control of the solid state disk is realized. Therefore, when the operating conditions of the controlled solid state disk are known (for example, the ambient temperature can be measured, and the operating program can be known), the user can predict the temperature rise of the solid state disk in the future so as to take an optimal cooling measure in advance to avoid the temperature of the solid state disk from exceeding the standard, which is beneficial to ensuring the performance of the solid state disk, prolonging the service life of the solid state disk and preventing data loss. The invention adopts a machine learning prediction model, so that the prediction data is accurate and effective.
In one embodiment, the operation condition may be various conditions at the starting time point, including an ambient temperature, a solid state disk temperature, a humidity, a wind speed, and an operation mode at the starting time point. The operation mode includes a plurality of operation program parameters, for example, the number of currently operated programs, program names, and the amount of memory occupied by each operation program.
In another embodiment, the operating conditions may also include operating conditions corresponding to the solid state disk at different historical time points (including the starting time point and a time point before the starting time point), for example, an ambient temperature at each historical time point, a temperature of the solid state disk at each historical time point, a humidity at each historical time point, a wind speed at each historical time point, and an operating mode at each historical time point in a historical period starting from the starting time point and counting back several time points. The operation conditions are determined through the operation conditions respectively corresponding to the solid state disk at different historical time points, and the cumulative effect of temperature rise in each historical time point cannot be ignored, so that the prediction data of the temperature of the solid state disk in the future is more accurate, and more accurate temperature rise control is realized.
Based on the first embodiment of the method for controlling temperature rise of solid state disk of the present invention, in the second embodiment of the method for controlling temperature rise of solid state disk of the present invention, the step S10 includes:
step S11, establishing a first prediction model for predicting the temperature rise of the solid state disk;
step S12, acquiring a plurality of groups of first training parameters, wherein the first training parameters comprise solid state disk operating conditions and temperature rise data of the solid state disk after the solid state disk continuously operates for a preset time under different operating conditions;
and step S13, inputting a plurality of groups of first training parameters into a first prediction model for predicting the temperature rise data of the solid state disk, so as to train the first prediction model.
Specifically, in this embodiment, two prediction models are used, the first prediction model is used to predict solid state disk temperature rise data, the second prediction model is used to predict an optimal cooling measure, the prediction processes of the two models can be calculated by using the same terminal, the first terminal can also be used to perform the prediction calculation of the first prediction model, and the second terminal can be used to perform the prediction calculation of the second prediction model, so that the computation workload of a single terminal can be reduced, and when the computation capability of the first terminal is insufficient, only the prediction process of the first prediction model can be performed to obtain predicted temperature rise data, and the temperature rise data is fed back to a user.
Specifically, the predicted temperature rise data of the solid state disk of the first prediction model and the predicted optimal cooling measure of the second prediction model are fed back to the user respectively, and the feedback mode can be displayed through characters or pictures or prompted through prompt tones.
Based on the first embodiment or the second embodiment of the method for controlling temperature rise of solid state disk of the present invention, in a third embodiment of the method for controlling temperature rise of solid state disk of the present invention, the step S20 includes:
step S21, establishing a second prediction model for predicting the optimal cooling measure of the solid state disk;
step S22, acquiring a plurality of groups of second training data, wherein the second training data comprise optimal cooling measures of the solid state disk under different operation modes and different temperature values;
and step S23, inputting a plurality of groups of second training parameters into a second prediction model for predicting the optimal cooling measures of the solid state disk, so as to train the second prediction model.
Specifically, a plurality of cooling measures are preset in the invention, the output result of each second prediction model corresponds to an optimal cooling measure, the predicted optimal cooling measure is sent to the control system of the solid state disk, the control system of the solid state disk is connected with a cooling component, and the cooling component can be a fan, an external cooling device and the like. After receiving the predicted optimal cooling measure, the control system executes the optimal cooling measure, for example, when the optimal cooling measure is to control the rotating speed of the fan to the set rotating speed, the control system controls the wind speed to operate so as to keep the set rotating speed; when the optimal cooling measure is to close the idle task, detecting the current idle task and executing the closing of the current idle task; and when the optimal cooling measure is to close the tasks occupying excessive memory, detecting the task items occupying excessive memory, and closing the task items occupying excessive memory.
The optimum cooling measure may be a single cooling measure or a combination of at least two cooling measures.
Based on the first to third embodiments of the method for controlling temperature rise of solid state disk of the present invention, in a fourth embodiment of the method for controlling temperature rise of solid state disk of the present invention, the step S30 includes:
step S31, acquiring the operating condition and the estimated operating time of the controlled solid state disk, inputting the operating condition and the estimated operating time into the first prediction model to obtain first output data, and determining the predicted temperature rise data of the solid state disk when the estimated operating time is reached according to the first output data;
and step S32, acquiring the current working mode of the controlled solid state disk, inputting the predicted temperature rise data and the current working mode into the second prediction model to obtain second output data, and determining the predicted optimal cooling measure of the solid state disk according to the second output data.
In the embodiment, the temperature rise result of the solid state disk is related to the operation condition of the solid state disk and the predicted operation time. For example, the temperatures of the solid state disk are definitely different when the solid state disk is operated for 30 minutes, 1 hour and 2 hours under the same operation condition. Therefore, the invention adopts the running condition and the predicted running time as input quantities to predict the temperature rise of the solid state disk.
The expected runtime may be one point in time, or multiple points in time. For example, when the user sets the expected operation time to be 1 hour, the predicted result is temperature rise data corresponding to 1 hour of operation. When the user sets the predicted operation time to be 1 hour, 2 hours and 3 hours, the prediction result is temperature rise data corresponding to the operation time of 1 hour, 2 hours and 3 hours respectively, and the prediction result is displayed by a prediction temperature rise matrix formed by each predicted operation time point. When the predicted operation time is a plurality of time points, a plurality of predicted optimal cooling measures can be obtained in sequence.
Based on the first embodiment to the fourth embodiment of the method for controlling temperature rise of a solid state disk of the present invention, in a fifth embodiment of the method for controlling temperature rise of a solid state disk of the present invention, the method for controlling temperature rise of a solid state disk further includes:
and step S40, executing temperature rise control on the controlled solid state disk according to the predicted optimal temperature reduction measure so as to control the temperature rise of the solid state disk in advance.
When the predicted operation time is a plurality of time points, a plurality of predicted optimal cooling measures are obtained in sequence, wherein each predicted optimal cooling measure is executed in a time interval at each predicted time point.
For example, when the predicted operation time is the first operation time, the second operation time, and the third operation time, the first predicted optimal cooling measure, the second predicted optimal cooling measure, and the third predicted optimal cooling measure are obtained. The time interval of the first optimal cooling measure is from the current time point to the time interval corresponding to the first running time, the time interval of the second optimal cooling measure is from the first running time to the second running time, and the time interval of the third optimal cooling measure is from the second running time to the third running time.
Based on the first to fifth embodiments of the method for controlling temperature rise of a solid state disk of the present invention, in a sixth embodiment of the method for controlling temperature rise of a solid state disk of the present invention, the first prediction model is H ═ Φ (F);
f is input data of the first prediction model, and H is predicted temperature rise data output by the first prediction model; and F represents various factors influencing the temperature rise of the solid state disk, including historical environmental temperature data, historical temperature data of the solid state disk, historical humidity data, historical wind speed data, historical operation modes and predicted operation time.
The solid state disk temperature rise is influenced by various factors, and in the invention, the environmental temperature, the initial temperature of the solid state disk and the running mode are mainly adopted. Because the humidity and the wind speed have certain influence on the temperature change, the humidity and the wind speed are introduced to carry out prediction temperature correction so as to enable the prediction result to be more accurate.
The operation mode includes a plurality of operation program parameters, for example, the number of currently operated programs, program names, and the amount of memory occupied by each operation program. The operation mode is used for representing the current task condition, the temperature rise is slow under the condition that the memory occupied by the current task is not high, and otherwise, the temperature rise is rapid, so that the operation mode is introduced as one of important parameters for temperature rise prediction.
Based on the sixth embodiment of the method for controlling temperature rise of the solid state disk, in the seventh embodiment of the method for controlling temperature rise of the solid state disk, the predicted temperature H output by the first prediction model is calculated by the following formula:
wherein, F1Is the historical temperature data of the environment,Is the ambient historical temperature coefficient, F2History temperature of the solid state disk,Is the historical temperature coefficient, F, of the hard disk3As historical humidity data, Fb1Is standard humidity, F4Is historical wind speed, Fb2Is the standard wind speed, T is the standard temperature,Are the operating mode coefficients determined by the historical operating mode and the expected operating time.
In the present embodiment, the environmental history temperature coefficient is introducedHistory temperature coefficient of hard diskCoefficient of operation modeStandard humidity Fb1Standard wind speed Fb2And the standard temperature T as correction data to correct the temperature rise prediction data.
Before model training of the first prediction model, different initial values can be given to each correction data, historical data of factors influencing the temperature rise of the solid state disk and the initial values of the correction data are brought into the first prediction model to carry out prediction effect verification, and each correction data is assigned with a value according to the initial value with the minimum error after verification.
According to the verification result of the present invention, the ambient historical temperature coefficientHas a value range of [0.1,0.2 ]]History temperature coefficient of hard diskHas a value range of [0.8,0.9 ]]Coefficient of operation modeHas a value range of [0.9,1.2 ]]Standard humidity Fb1The value is [50%,60%]Standard wind speed Fb2The value is [0.3,0.6 ]]M/s, standard temperature T of [25,30 ]]℃。
Wherein, when the environmental historical temperature is above 25 ℃, the environmental historical temperature coefficientIs preferably [0.15,0.2 ]]At this time, the influence of the ambient temperature on the temperature rise of the solid state disk is larger; when the environmental historical temperature is below 25 ℃, the environmental historical temperature coefficientThe value of (1) is preferably [0.1,0.15), and at the moment, the influence of the ambient temperature on the temperature rise of the solid state disk is smaller.
Specifically, the solid state disk generates heat during operation, and the higher the humidity is, the more unfavorable the heat dissipation is, therefore,the positive influence of humidity on the current temperature rise is reflected.
Further, the wind speed has negative influence on the current temperature rise, the larger the wind speed is, the faster the heat dissipation is, and the smaller the temperature rise effect is, therefore,the negative influence of the wind speed on the current temperature rise is reflected.
Based on the seventh embodiment of the method for controlling temperature rise of the solid state disk, in the eighth embodiment of the method for controlling temperature rise of the solid state disk, provided by the invention:
wherein,is the environmental historical temperature data of the ith time point in the historical time,the solid state disk historical temperature data at the ith time point in the historical time point,is historical humidity data at the ith time point in the historical time,is historical wind speed data of the ith time point in the historical time,the operation mode coefficient at the ith time point in the historical time point,by historical operating modes and operating modesAnd (4) obtaining the mapping table corresponding to the formula coefficient by query, wherein n represents the number of historical time points.
The historical time point determines how many groups of data are of various factors influencing the temperature rise of the solid state disk. For example, if the historical time point is 3, there are three sets of data for each factor that affects the temperature rise of the solid state disk.
In the invention, a mapping relation table of the operation mode and the operation mode coefficient is established, and after the operation mode is determined, the corresponding operation mode coefficient can be determined according to the table look-up.
For example,referring to the operation mode coefficient of the ith historical time point, after the operation mode of the ith historical time point is detected, the mapping table is inquired through the operation mode, and then the corresponding operation mode coefficient can be obtained.
The data acquisition terminal for acquiring the operating conditions is arranged and comprises a first acquisition unit for acquiring the ambient temperature, a second acquisition unit for acquiring the temperature of the solid state disk, a third acquisition unit for acquiring the humidity and a fourth acquisition unit for acquiring the wind speed. Each acquisition unit is a different sensor.
Further, the operation mode data can be obtained through data fed back by the host side.
In addition, in order to achieve the above object, the present invention further provides a solid state disk, wherein the temperature control is performed by using any one of the above temperature rise control methods for solid state disks.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by a program plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation method. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a program product, which is stored in a computer-readable storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above, and includes several instructions for enabling a terminal device to enter the method according to the embodiments of the present invention.
In the description herein, references to the description of the term "an embodiment," "another embodiment," "other embodiments," or "first through Xth embodiments," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, method steps, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (8)
1. A temperature rise control method for a solid state disk is characterized by comprising the following steps:
establishing a first prediction model for predicting the temperature rise of the solid state disk, and performing model training on the first prediction model;
establishing a second prediction model for obtaining the optimal cooling measure of the solid state disk, and training the second prediction model;
obtaining the operating condition and the estimated operating time of the controlled solid state disk, and determining the optimal predicted cooling measure of the solid state disk according to the operating condition, the estimated operating time, the first prediction model and the second prediction model;
the first prediction model is H ═ Φ (F);
f is input data of the first prediction model, and H is predicted temperature rise data output by the first prediction model; f represents various factors influencing the temperature rise of the solid state disk, including historical environmental temperature data, historical temperature data of the solid state disk, historical humidity data, historical wind speed data, historical operation modes and estimated operation time;
the predicted temperature H output by the first prediction model is calculated by the following formula:
wherein, F1Is the historical temperature data of the environment,Is the ambient historical temperature coefficient, F2History temperature of the solid state disk,Is the historical temperature coefficient, F, of the hard disk3As historical humidity data, Fb1Is standard humidity, F4Is historical wind speed, Fb2Is the standard wind speed, T is the standard temperature,Are the operating mode coefficients determined by the historical operating mode and the expected operating time.
2. The method for controlling the temperature rise of the solid state disk according to claim 1, wherein the step of establishing a first prediction model for predicting the temperature rise of the solid state disk and performing model training on the first prediction model comprises the following steps:
establishing a first prediction model for predicting the temperature rise of the solid state disk;
acquiring a plurality of groups of first training parameters, wherein the first training parameters comprise solid state disk operating conditions and temperature rise data of the solid state disk after the solid state disk continuously operates for a preset time under different operating conditions;
and inputting a plurality of groups of first training parameters into a first prediction model for predicting the temperature rise data of the solid state disk so as to train the first prediction model.
3. The method for controlling the temperature rise of the solid state disk according to claim 1, wherein the step of establishing a second prediction model for obtaining an optimal cooling measure of the solid state disk and training the second prediction model comprises the following steps:
establishing a second prediction model for predicting the optimal cooling measure of the solid state disk;
acquiring a plurality of groups of second training data, wherein the second training data comprise optimal cooling measures of the solid state disk under different operation modes and different temperature values;
and inputting a plurality of groups of second training parameters into a second prediction model for predicting the optimal cooling measure of the solid state disk so as to train the second prediction model.
4. The method for controlling the temperature rise of the solid state disk according to any one of claims 1 to 3, wherein the step of obtaining the operating condition and the predicted operating time of the controlled solid state disk and determining the predicted optimal temperature-reducing measure of the solid state disk according to the operating condition, the predicted operating time, the first prediction model and the second prediction model comprises:
acquiring the operating condition and the estimated operating time of the controlled solid state disk, inputting the operating condition and the estimated operating time into the first prediction model to obtain first output data, and determining predicted temperature rise data of the solid state disk when the estimated operating time is reached according to the first output data;
and acquiring a current working mode of the controlled solid state disk, inputting the predicted temperature rise data and the current working mode into the second prediction model to obtain second output data, and determining the predicted optimal cooling measure of the solid state disk according to the second output data.
5. The method for controlling the temperature rise of the solid state disk according to any one of claims 1 to 3, further comprising:
and executing temperature rise control on the controlled solid state disk according to the predicted optimal temperature reduction measure so as to control the temperature rise of the solid state disk in advance.
6. The method for controlling the temperature rise of the solid state disk according to any one of claims 1 to 3, wherein the operating conditions comprise operating conditions respectively corresponding to the solid state disk at different historical time points.
7. The method for controlling temperature rise of the solid state disk according to any one of claims 1 to 3, wherein:
wherein,is the environmental historical temperature data of the ith time point in the historical time,the solid state disk historical temperature data at the ith time point in the historical time point,is historical humidity data at the ith time point in the historical time,is historical wind speed data of the ith time point in the historical time,the operation mode coefficient at the ith time point in the historical time point,and (4) obtaining the number of historical time points by querying a mapping table corresponding to the historical operation mode and the operation mode coefficient, wherein n represents the number of the historical time points.
8. A solid state disk, characterized in that the temperature control is carried out by the solid state disk temperature rise control method according to any one of claims 1 to 7.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202011576970.8A CN112286469B (en) | 2020-12-28 | 2020-12-28 | Solid state disk temperature rise control method and solid state disk |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202011576970.8A CN112286469B (en) | 2020-12-28 | 2020-12-28 | Solid state disk temperature rise control method and solid state disk |
Publications (2)
Publication Number | Publication Date |
---|---|
CN112286469A CN112286469A (en) | 2021-01-29 |
CN112286469B true CN112286469B (en) | 2021-03-23 |
Family
ID=74426429
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202011576970.8A Active CN112286469B (en) | 2020-12-28 | 2020-12-28 | Solid state disk temperature rise control method and solid state disk |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN112286469B (en) |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9081676B2 (en) * | 2009-06-02 | 2015-07-14 | Lenovo Enterprise Solutions (Singapore) Pte. Ltd. | Operating computer memory |
CN108194398A (en) * | 2017-12-29 | 2018-06-22 | 青岛海信医疗设备股份有限公司 | Control method for fan and device |
CN110389866A (en) * | 2018-04-20 | 2019-10-29 | 武汉安天信息技术有限责任公司 | Disk failure prediction technique, device, computer equipment and computer storage medium |
CN110489303A (en) * | 2019-08-22 | 2019-11-22 | 江苏华存电子科技有限公司 | A kind of temperature prediction control management method and device based on NVMe SSD hard disk |
-
2020
- 2020-12-28 CN CN202011576970.8A patent/CN112286469B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US9081676B2 (en) * | 2009-06-02 | 2015-07-14 | Lenovo Enterprise Solutions (Singapore) Pte. Ltd. | Operating computer memory |
CN108194398A (en) * | 2017-12-29 | 2018-06-22 | 青岛海信医疗设备股份有限公司 | Control method for fan and device |
CN110389866A (en) * | 2018-04-20 | 2019-10-29 | 武汉安天信息技术有限责任公司 | Disk failure prediction technique, device, computer equipment and computer storage medium |
CN110489303A (en) * | 2019-08-22 | 2019-11-22 | 江苏华存电子科技有限公司 | A kind of temperature prediction control management method and device based on NVMe SSD hard disk |
Also Published As
Publication number | Publication date |
---|---|
CN112286469A (en) | 2021-01-29 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN111430844A (en) | Heat management method and device during battery pack charging and automobile | |
CN111430845A (en) | Battery pack thermal management method and device, storage medium and electronic equipment | |
CN110928341B (en) | Temperature control method, device, equipment and storage medium | |
CN113708389A (en) | Wind power plant primary frequency modulation model parameter identification method and system based on actual power response | |
CN115288871B (en) | Engine real-time torque calculation method, device, equipment and readable storage medium | |
CN112286469B (en) | Solid state disk temperature rise control method and solid state disk | |
CN110979037A (en) | Air compressor control method and system of hybrid power vehicle and storage medium | |
KR101454483B1 (en) | Resonant frequency identification | |
JPH0695707A (en) | Model forecast controller | |
Amirijoo et al. | Error-driven QoS management in imprecise real-time databases | |
JP2011165152A (en) | Energy-demand predicting device and energy demand prediction method | |
CN117404863A (en) | Variable frequency regulation and control method and device, storage medium and refrigeration equipment | |
JP2010218007A (en) | Disturbance estimation device, control object model estimation device, feedforward amount estimation device, and controller | |
CN116387555A (en) | Heat dissipation regulation and control method and device for fuel cell cooling loop | |
CN112682392B (en) | Hydraulic control method and device | |
CN115459299A (en) | Low-voltage distribution reactive power regulation method and device, computer equipment and storage medium | |
CN104376367A (en) | Short-term load forecast method based on air temperature and non-linear auto-regression timing sequence model | |
CN114167963A (en) | Fan control management method, device, equipment and machine readable storage medium | |
CN112943557B (en) | Wind power plant, wind generating set and method and equipment for predicting operation state of wind generating set | |
CN114895724A (en) | Intelligent household equipment, temperature compensation method and readable storage medium | |
CN109099002B (en) | Fan speed regulation method and device | |
CN118466627B (en) | Temperature self-adaptive regulation and control method, device and system for computer host | |
CN118466375B (en) | Environment control method, device and system applied to GIS control cabinet | |
CN112467243B (en) | Battery pack cooling control method and device | |
CN115085614A (en) | Permanent magnet synchronous motor model prediction control system and control method based on Gaussian process and permanent magnet synchronous motor |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |