CN113566975B - Deep temperature measuring method and device based on thermal impulse method and earphone - Google Patents
Deep temperature measuring method and device based on thermal impulse method and earphone Download PDFInfo
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Abstract
The application provides a deep temperature measuring method, a device and an earphone based on a thermal impulse method, wherein the measuring method comprises the following steps: acquiring a thermal response characteristic parameter of at least one target temperature measuring point under a specific thermal shock condition; acquiring deep temperature data of a detection target according to the thermal response characteristic parameters; the method solves the problems of large measurement error and low measurement precision of the human body deep temperature in the prior art, calculates the deep temperature data of the detection target by utilizing the real-time thermal response characteristic parameters of at least one target temperature measuring point under the thermal shock condition, not only strips the influence of environmental factors on the deep temperature, but also eliminates the estimation error caused by individual difference, can more accurately measure the deep temperature data, and meets the requirements of different users.
Description
Technical Field
The invention relates to the technical field of temperature measurement, in particular to a deep temperature measurement method and device based on a thermal impulse method and an earphone.
Background
Along with the improvement of living standard of people, people pay more and more attention to their health, and body temperature is one of four vital sign parameters, and is particularly important for evaluating the health state of people. The body temperature data of people are collected for a long time, on one hand, the early warning of diseases such as fever and fever can be completed, and more importantly, the real-time collection of the body temperature is beneficial to the timely discovery of epidemic situations under the condition of epidemic disease normalization.
For the convenience of carrying, the ear temperature of a human body is usually measured by adopting an in-ear earphone at present, and a thermistor is arranged at a sound outlet of the earphone close to an ear cap and used for receiving heat radiation in an ear canal of the human body. However, the method is limited to measuring the temperature near the earcap, is easily affected by environmental factors, individual differences and the like, and is difficult to accurately distinguish the temperature change of the sensor caused by the change of the body temperature of the human body or the environmental factors and the like.
Therefore, the method for measuring the human body deep temperature in the prior art cannot eliminate the influence of environmental factors and individual differences, so that the measurement error is large, the measurement precision of the human body temperature is reduced, and the requirements of users are not met.
Disclosure of Invention
The application provides a deep temperature measuring method, a deep temperature measuring device and earphones based on a thermal impulse method, and solves the problems that in the prior art, the error of human body deep temperature measurement is large and the measurement precision is low.
In a first aspect, the present application provides a deep temperature measurement method based on a thermal impulse method, where the measurement method includes: acquiring a thermal response characteristic parameter of at least one target temperature measuring point under a specific thermal shock condition; and acquiring deep temperature data of the detection target according to the thermal response characteristic parameters.
Optionally, the thermal response characteristic parameter comprises one or more of a steady state temperature value, a specific temperature value, a rate of temperature change, and a maximum value of the rate of temperature change.
Optionally, the specific thermal shock conditions include: setting a first temperature sensor and a first heating module at a first target temperature measuring point; and controlling the heating curve of the first heating module to form a first thermal shock condition for the first target temperature measuring point.
Optionally, the specific thermal impulse condition further includes: setting a first temperature sensor at a first target temperature measuring point, and setting a second temperature sensor and a first heating module at a second target temperature measuring point; and controlling the heating curve of the first heating module, and forming a second thermal shock condition for the first target temperature measuring point and the second target temperature measuring point.
Optionally, acquiring a thermal response characteristic parameter of at least one target temperature measurement point under a specific thermal shock condition, including; under the unheated condition, acquiring an unheated temperature sequence of the at least one target temperature measuring point at the thermal equilibrium; starting the heating module to obtain a heating temperature matrix of the at least one target temperature measuring point under different heating powers; and calculating the thermal response characteristic parameter according to the unheated temperature sequence and the heating temperature matrix.
Optionally, a calculation formula for obtaining deep temperature data of the detection target according to the thermal response characteristic parameter is as follows:
wherein, T soff Showing the steady state temperature, T, of the first target temperature measurement point when unheated soni Denotes a heating power P i Specific temperature value of time first target temperature measuring point, T' soni (t) represents a heating power P i Temperature rate of change of time first target temperature measurement point, max (T' soni (t)) represents a heating power P i The maximum value of the rate of change of temperature at the first target temperature measurement point.
Optionally, a calculation formula for obtaining deep temperature data of the detection target according to the thermal response characteristic parameter is as follows:
wherein, T soff A first steady state temperature, T, representing a first target temperature measurement point when unheated eoff A second steady state temperature, T, representing a second target temperature measurement point when unheated soni Denotes a heating power P i Specific temperature value of time first target temperature measurement point, T eoni Denotes a heating power P i A specific temperature value, T ', of a second target temperature measuring point' soni (t) represents a heating power P i Temperature change rate of the first target temperature measurement point, max (T' soni (t)) represents a heating power P i The maximum value of the rate of change of temperature of the first target temperature measurement point.
Optionally, obtaining deep temperature data of the detection target according to the thermal response characteristic parameter, further comprising: acquiring training characteristic parameters and training temperature data of a training target; inputting the training characteristic parameters and the training temperature data into a learning model for training to obtain a target learning model; and inputting the thermal response characteristic parameters into the target learning model for calculation to obtain deep temperature data of the detection target.
In a second aspect, the present application provides a deep temperature measuring apparatus based on a thermal impulse method, the measuring apparatus including: the heating module is used for forming a specific thermal shock condition for at least one target temperature measuring point; the temperature sensor is used for acquiring temperature data of the target temperature measuring point under a specific thermal shock condition; and the temperature processor is connected with the at least one temperature sensor and used for acquiring thermal response characteristic parameters according to the temperature data and acquiring deep temperature data of the detection target according to the thermal response characteristic parameters.
Optionally, when the at least one temperature sensor includes a first temperature sensor, the first temperature sensor is disposed at a first target temperature measurement point, and is configured to collect an outer surface temperature of the detection target; the heating module is arranged on one side close to the first temperature sensor and used for forming a first thermal shock condition on a first target temperature measuring point.
Optionally, when the at least one temperature sensor includes a first temperature sensor and a second temperature sensor, the first temperature sensor is disposed at a first target temperature measurement point and is used to collect the outer surface temperature of the detection target, and the second temperature sensor is disposed at a second target temperature measurement point and is used to collect the ambient temperature far from the outer surface of the detection target; the heating module is arranged on one side close to the second temperature sensor and used for forming a second thermal shock condition for the first target temperature measuring point and the second target temperature measuring point.
In a third aspect, the present application provides an earphone including the above-described depth temperature measuring device based on the thermal impulse method.
Compared with the prior art, the method has the following beneficial effects:
according to the method and the device, the heating module is arranged at the at least one target temperature measuring point, so that the heating module generates heat impulse to the deep temperature area of the detection target and the at least one target temperature measuring point, and the deep temperature data of the detection target is calculated by utilizing the real-time thermal response characteristic parameters of the at least one target temperature measuring point under the heat impulse condition, so that the influence of environmental factors on the deep temperature is eliminated, the estimation error caused by individual difference is eliminated, the deep temperature data can be more accurately measured, and the requirements of different users are met.
Drawings
Fig. 1 is a schematic structural diagram of a deep temperature measuring device based on a thermal impulse method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of another deep temperature measuring device based on a thermal impulse method according to an embodiment of the present application;
fig. 3 is a schematic flowchart of a deep temperature measurement method based on a thermal impulse method according to an embodiment of the present application;
fig. 4 is a schematic flowchart illustrating a specific process of step S101 in fig. 3 according to an embodiment of the present application;
FIG. 5 is a deep temperature training diagram and an estimation diagram based on a learning model according to an embodiment of the present disclosure;
fig. 6 is a schematic flow chart illustrating an intermittent thermal impulse method according to an embodiment of the present application;
FIG. 7 is a schematic flow chart illustrating a continuous thermal shock method according to an embodiment of the present disclosure;
FIG. 8 is a schematic diagram of a pulse for adjusting the power of a heating module according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
In a first aspect, the present invention provides a deep temperature measuring apparatus based on a thermal impulse method, which specifically includes the following embodiments:
example one
Fig. 1 is a schematic structural diagram of a deep temperature measurement apparatus based on a thermal impulse method according to an embodiment of the present application, and as shown in fig. 1, the deep temperature measurement apparatus based on the thermal impulse method includes:
the heating module, the first temperature sensor and the temperature processor are arranged on the heating module;
the heating module is arranged on one side close to the first temperature sensor and used for forming a specific thermal shock condition on a first target temperature measuring point; the first temperature sensor is used for acquiring temperature data of the first target temperature measuring point under the specific thermal shock condition; the temperature processor is connected with the first temperature sensor and used for acquiring thermal response characteristic parameters according to the temperature data and acquiring deep temperature data of a detection target according to the thermal response characteristic parameters.
In this embodiment, a deep temperature measurement area of the detection target, that is, the temperature zone to be measured in fig. 1, is wrapped by the heat transfer medium, and cannot be directly measured by the sensor, and therefore, the temperature data acquired by the first target temperature measurement point close to the heat transfer medium needs to be estimated; the heat conduction medium is a medium between the temperature area to be measured and the first temperature sensor, so that the heat conduction medium comprises one or more of skin, air and a device shell of different parts of a human body.
In this embodiment, in order to remove the influence of environmental factors and eliminate the difference of skin thermal resistance values of different individuals, a heating module is disposed beside the first target temperature measuring point, i.e., the first temperature sensor, and the heating module can generate thermal impulse for a thermal system composed of the first target temperature measuring point, the heat conducting medium and the temperature zone to be measured. A time series of temperature changes over time caused by thermal shock can be observed through a first target temperature measurement point, wherein the first temperature sensor and the heating module form a deep temperature detection sensor for detecting a target.
The temperature T of the temperature zone to be measured is represented by Delta T C The temperature T of the first target temperature measuring point S The temperature difference between the two is as follows:
ΔT＝T c -T s (1)
after the heating module is started, a heat impulse is generated for the temperature of the target temperature measuring point, and the heating power and the heating duration of the heating module determine the size of the temperature difference change. When P represents the heating power of the heating module and T represents the duration of the thermal impulse, the relationship between P, T and Δ T can be expressed as follows:
ΔT＝f(P，t) (2)
when Δ T =0, T can be obtained C ＝T S I.e. the temperature T of the first target temperature measuring point S I.e. the deep temperature T C 。
From formula 1 and formula 2:
T c ＝T s +f(P,t) (3)
it should be noted that f (P, T) in formula 3 is the temperature T of the first target temperature measurement point S Performing temperature compensation to eliminate the influence of environmental factors and obtain the estimated deep temperature T C More precisely, f (P, t) can be obtained by collecting temperature data of the first target temperature measuring point under a specific thermal impulse condition.
Example two
Fig. 2 is a schematic structural diagram of another deep temperature measuring device based on a thermal impulse method according to an embodiment of the present application, and as shown in fig. 2, a target temperature measuring point (i.e., a second target temperature measuring point) and a path of temperature sensor (i.e., a second temperature sensor) are added on the basis of one embodiment, where the first temperature sensor is disposed at the first target temperature measuring point and is used to collect an outer surface temperature of the detection target, and the second temperature sensor is disposed at the second target temperature measuring point and is used to collect an ambient temperature far from an outer surface of the detection target; the heating module is arranged on one side close to the second temperature sensor and used for forming heat impulse conditions for the first target temperature measuring point and the second target temperature measuring point.
In addition, based on the deep temperature measuring device shown in fig. 2, the most basic scheme is the zero heat flow method, and the temperature T of the second target temperature measuring point on the environment side is controlled by controlling the heating power of the heating module e And the second side near the heat transfer mediumA target temperature measuring point temperature T S When the temperature difference is zero, heat balance is achieved (a typical heat balance judgment rule that the temperature change is not more than 0.05 in 10 minutes, and the specific judgment condition and time are related to the sensors and the measurement environment), and the temperatures of the two sensors are the deep temperature T C 。
Optionally, the present embodiment may also utilize different local thermal environments constructed by the heating modules to determine the coefficient to be determined y in the formula in real time, and the deep temperature calculation formula may be expressed as:
T C ＝T s +(T s -T e )*y (4)
the embodiment divides two environments of heating and non-heating, namely two thermal environment equations can be constructed:
solving the equation set (5) to obtain the ear temperature calculation formula as follows:
wherein, T in the above formula soff For not heating the first target temperature measuring point temperature, T eoff Temperature, T, of a second target temperature measuring point is not heated son Heating the first target temperature measuring point temperature, T eon And heating the second target temperature measurement point temperature.
By analogy, the deep temperature data acquisition method and the deep temperature data acquisition system can further provide three-way temperature sensors, four-way temperature sensors and other embodiments to further eliminate the influence of the environmental temperature and the individual difference on the deep temperature, and different embodiments adopt different calculation formulas to acquire the deep temperature data.
As can be seen from the first and second embodiments, the deep temperature measurement device based on the thermal impulse method provided in the present application includes: the heating module is used for forming a specific thermal shock condition for at least one target temperature measuring point; the temperature sensor is used for acquiring temperature data of the at least one target temperature measuring point under a specific thermal shock condition; and the temperature processor is connected with the at least one temperature sensor and used for acquiring the thermal response characteristic parameters according to the temperature data and acquiring deep part temperature data of the detection target according to the thermal response characteristic parameters.
Compared with the prior art, the method has the following beneficial effects:
according to the method and the device, the heating module is arranged at the at least one target temperature measuring point, so that the heating module generates heat impulse to the deep temperature area of the detection target and the at least one target temperature measuring point, and the deep temperature data of the detection target is calculated by utilizing the real-time thermal response characteristic parameters of the at least one target temperature measuring point under the heat impulse condition, so that the influence of environmental factors on the deep temperature is eliminated, the estimation error caused by individual difference is eliminated, the deep temperature data can be more accurately measured, and the requirements of different users are met.
In a second aspect, the present invention provides a deep temperature measurement method based on a thermal impulse method, which specifically includes the following embodiments:
EXAMPLE III
Fig. 3 is a schematic flow chart of a deep temperature measurement method based on a thermal impulse method according to an embodiment of the present application, and as shown in fig. 3, the measurement method adopted by the deep temperature measurement device based on the thermal impulse method specifically includes the following steps:
step S101, acquiring a thermal response characteristic parameter of at least one target temperature measuring point under a specific thermal shock condition;
in this embodiment, as shown in fig. 4, the obtaining of the thermal response characteristic parameter of at least one target temperature measurement point under a specific thermal shock condition specifically includes the following steps;
step S201, under the unheated condition, acquiring an unheated temperature sequence of the at least one target temperature measuring point in thermal equilibrium;
step S202, starting the heating module, and acquiring a heating temperature matrix of the at least one target temperature measuring point under different heating powers;
step S203, calculating the thermal response characteristic parameter according to the unheated temperature sequence and the heating temperature matrix.
It should be noted that, the sensor is installed on the surface of the detection target, when the heat conduction between the sensor and the detection target reaches balance, a plurality of temperature values of the sensor are recorded, and the plurality of temperature values form the unheated temperature sequence; then, the heating module is started, a plurality of heating temperatures under different heating powers are obtained, the heating temperatures under different heating powers form a heating temperature matrix, and finally, the thermal response characteristic parameters are calculated according to the unheated temperature sequence and the heating temperature matrix, wherein the thermal response characteristic parameters comprise but are not limited to one or more of steady-state temperature values, specific temperature values, temperature change rates and maximum values of the temperature change rates, and the different heating powers comprise heating powers P1, P2 \8230 \ 8230and Pi.
And S102, acquiring deep part temperature data of the detection target according to the thermal response characteristic parameters.
In this embodiment, acquiring deep temperature data of a detection target according to the thermal response characteristic parameter includes: acquiring training characteristic parameters and training temperature data of a training target; inputting the training characteristic parameters and the training temperature data into a learning model for training to obtain a target learning model; and inputting the thermal response characteristic parameters into the target learning model for calculation to obtain deep temperature data of the detection target.
It should be noted that, as shown in fig. 5a, when the depth temperature is known, the unheated temperature sequence and the heating temperature matrix obtained by the method of fig. 4 are used as training characteristic parameters, training is performed based on a machine learning model or a deep learning model to obtain a set of target model parameters, and the target model parameters are input into the machine learning model or the deep learning model to obtain a target learning model; as shown in fig. 5b, when the depth temperature is unknown, the obtained thermal response characteristic parameters are substituted into the target learning model for classification and identification, so as to obtain the depth temperature data of the detected target.
Compared with the prior art, the method has the following beneficial effects:
according to the method and the device, the heating module is arranged at the at least one target temperature measuring point, so that the heating module generates heat impulse to the deep temperature area of the detection target and the at least one target temperature measuring point, and the deep temperature data of the detection target is calculated by utilizing the real-time thermal response characteristic parameters of the at least one target temperature measuring point under the heat impulse condition, so that the influence of environmental factors on the deep temperature is eliminated, the estimation error caused by individual difference is eliminated, the deep temperature data can be more accurately measured, and the requirements of different users are met.
Example four
Fig. 6 is a schematic flow chart illustrating an intermittent thermal impulse method according to an embodiment of the present application; as shown in fig. 6, the specific workflow of the intermittent thermal impulse method is as follows:
(1) Mounting a sensor on the surface of an object to be measured;
(2) The heat conduction between the sensor and the object to be measured reaches approximate heat balance (dTs/dt)<0.05 Record the target temperature measurement point temperature { T) over time soff11 ,T soff12 ,…，T soff1n }(T soffij In, the corner mark off indicates off heating, i indicates the ith stage data, and j indicates the jth time point);
(3) Starting the heating module by the power Pi, and recording the temperature { T (temperature at target temperature measuring point) of the heating module during the period soni1 ,T soni2 ,…，T sonin }(T sonij In the middle, the corner mark on represents the starting heating, i represents the ith section of data, and j represents the jth time point);
(4) Closing the heating unit, and enabling the heat conduction between the sensor and the object to be measured to return to a heat equilibrium state before heating is not started (namely dTs/dt is less than 0.05);
(5) Repeating the steps 3-4 with different powers;
(6) And closing the heating module.
EXAMPLE five
FIG. 7 is a schematic flow chart illustrating a continuous thermal shock method according to an embodiment of the present disclosure; as shown in fig. 7, the specific workflow of the continuous thermal shock method is as follows:
(1) Mounting a sensor on the surface of an object to be measured;
(2) The heat conduction between the sensor and the object to be measured reaches an approximate thermal equilibrium (dTs/dt)<0.05 Record the target temperature measurement point temperature { T } for that period of time soff11 ,T soff12 ,…，T soff1n }(T soffij In, the corner mark off indicates off heating, i indicates the ith stage data, and j indicates the jth time point);
(3) Starting the heating module with the power Pi, and recording the temperature { T } of the target temperature measuring point in the period of time soni1 ,T soni2 ,…，T sonin }(T sonij In the middle, the corner mark on represents the starting heating, i represents the ith section of data, and j represents the jth time point);
(4) Repeating step 3 at different powers;
(5) And closing the heating module.
It should be noted that the discontinuous thermal excitation manner can obtain more thermal response characteristic parameters than the continuous thermal excitation manner, including the maximum difference of the temperature changes caused by heating with different powers, and the maximum of the derivative of the temperature changes caused by heating with different powers. However, the intermittent heat impulse method requires a long time, and the system to be measured needs to return to a heat balance state before heating is started every time.
Example six
With reference to the first embodiment, the fourth embodiment and the fifth embodiment, the specific thermal shock conditions in this embodiment include: setting a first temperature sensor and a first heating module at a first target temperature measuring point; controlling a heating curve of the first heating module, and forming a first thermal shock condition for the first target temperature measuring point; wherein the heating curve comprises heating power and heating time length.
In this embodiment, the calculation formula for obtaining the deep portion temperature data of the detection target according to the thermal response characteristic parameter is as follows:
wherein, T soff Showing the steady state temperature, T, of the first target temperature measurement point when unheated soni Denotes a heating power P i Specific temperature value of time first target temperature measuring point, T' soni (t) represents a heating power P i Temperature rate of change of time first target temperature measurement point, max (T' soni (t)) represents a heating power P i The maximum value of the rate of change of temperature of the first target temperature measurement point.
Note that, in this embodiment, the unheated temperature sequence { T ] before the heat impulse is extracted soff111 ,T soff112 ,…，T soff11n And heating temperature matrix after starting thermal impulse { T } sonik1 ,T sonik2 ,…，T sonikn Performing deep temperature estimation on the thermal response characteristic parameters of the electronic device; t in equation 7 soff The last temperature before the start of heating, T, can be taken approximately soni The actual temperature of the target measurement point when the heating module is heated to meet a specific condition generally refers to the maximum temperature value after heating is started; t' soni (T) is the derivative of the temperature change after activation of the heating modules, i.e. the rate of temperature change, max (T' soni (t)) is the maximum value of the derivative of the temperature change after activation of the heating module; k is a radical of formula 1 ，k 2 ，…，k 2M+1 And b is a pending parameter, and the pending parameter can be determined by acquiring a large amount of data and utilizing an optimization algorithm (including a Newton steepest descent method, a particle swarm algorithm and the like).
Further, let k in equation 7 1 ·T soff In the first place, the first item is,
in the second term, the first term is,
the third term is the surface temperature of the object before the heating is turned on, and reflects the temperature under the combined action of the deep temperature and the ambient temperature, and when the external environment is stable, the temperature change changes with the change of the deep temperature, and the deep temperature can be reflected to a certain extent. But need to eliminate the ringThe ambient temperature influence, and the obtained deep temperature still needs to observe more data for calculation; the second term reflects the temperature influence of heating on the measuring point, the heating power is adjusted at certain intervals, when the temperature difference between the deep temperature and the surface temperature is different, the temperature rise value (including the maximum value which can be reached after heating and the temperature difference value which can be caused for a period of time) caused by the heating power is different, and the first term is added and compensated by fitting the relationship between the temperature rise value and the temperature difference value, so that the temperature estimation value which is closer to the deep temperature can be obtained; the third term is closer to the third term in physical significance, but the third term can be relatively calculated according to temperature data observed in a short time, when the temperature difference between the deep temperature and the surface temperature is different, the maximum rates of temperature change caused by different heating powers are different, and obviously, the temperature change rate becomes slower and slower with time after a period of time.
EXAMPLE seven
With reference to the second embodiment, the fourth embodiment and the fifth embodiment, the specific thermal shock conditions further include: setting a first temperature sensor at a first target temperature measuring point, and setting a second temperature sensor and a first heating module at a second target temperature measuring point; and controlling the heating curve of the first heating module, and forming a second thermal shock condition for the first target temperature measuring point and the second target temperature measuring point.
In this embodiment, the calculation formula for obtaining the deep portion temperature data of the detection target according to the thermal response characteristic parameter is as follows:
wherein, T soff A first steady state temperature, T, representing a first target temperature measurement point when unheated eoff A second steady state temperature, T, representing a second target temperature measurement point when unheated soni Denotes a heating power P i Specific temperature value of time first target temperature measuring point, T eoni Denotes a heating power P i A specific temperature value, T ', of a second target temperature measuring point' soni (t) represents a heating power P i Temperature change rate of the first target temperature measurement point, max (T' soni (t)) represents a heating power P i The maximum value of the rate of change of temperature at the first target temperature measurement point.
Note that T is soff Under the condition of not starting heating, the first steady-state temperature of the first target temperature measuring point can be approximately the last temperature before starting heating; t is a unit of eoff Under the condition of not starting heating, the second steady-state temperature of the second target temperature measuring point can be approximately the last temperature before starting heating; t is soni 、T eoni Respectively, the actual temperature of the first target temperature measuring point and the actual temperature of the second target temperature measuring point when a specific condition (generally, the maximum temperature after heating starting) is met after the heating unit is started by the power Pi; max (T' soni (t)) the maximum value of the rate of change of temperature at the first target temperature measurement point after the heating unit has been started at power Pi; k is a radical of 1 ，k 2 ，…，k 2M+2 And b is a pending parameter, and the pending parameter can be determined by acquiring a large amount of data and utilizing an optimization algorithm (including a Newton steepest descent method, a particle swarm algorithm and the like).
To explain further, let k in equation 8 1 ·T soff Is the first term, k 2 ·(T soff -T eoff ) In the second term, the first term is,
in the third item, the first item is,
the fourth term is the surface temperature of the object before the heating is turned on, and reflects the temperature under the combined action of the deep temperature and the ambient temperature, and when the external environment is stable, the temperature change changes with the change of the deep temperature, and the deep temperature can be reflected to a certain extent. However, the influence of the environmental temperature needs to be eliminated, and more data still need to be observed for calculation when the deep temperature is obtained; the second term reflects the temperature drop between two temperature sensors in the direction of the two temperature sensors, the deep part temperature and the surface temperature in the direction before starting heatingThere is a linear relationship for the temperature drop above; the third term is the temperature drop value of the two paths of temperature sensors along the gradient described by the second term after the heating is started by different heating powers, and the temperature drop value has a linear relation with the deep part temperature and the surface temperature in the direction; the fourth term reflects more the magnitude of the temperature difference between the deep temperature and the surface temperature, and the larger the temperature difference is, the larger the temperature rise transient value can be caused; the fifth term is offset compensation, including compensation that compensates for temperature loss caused in a direction perpendicular to the described gradient of the second term. The second term to the fifth term compensate the temperature difference between the core temperature and the surface temperature.
Example eight
The heating module in fig. 1 and 2 may be a resistor device, one end of the resistor device is grounded, and the other end of the resistor device is connected with the temperature processor, and the resistor is powered by a PIN of the temperature processor to realize heating; in this embodiment, the temperature processor controls the power of the heating module by adjusting the pulse signal input to the heating module, and as shown in FIG. 8, the heating power is controlled by controlling the duty ratio (t 1: t2, t1 represents the duration of high level), i.e. by controlling the duration of PIN to high and low levels to achieve different heating powers. Different heating powers can also be realized by directly reducing the voltage of the PIN PIN.
In the embodiment, a manner of controlling the duty ratio is taken as an example to describe the heating power, where expression 9 shows one regulation period, expression 10 describes the duty ratio, and expression 11 describes the relationship between the power P and the duty ratio; generally, T is preferably 1-2s to ensure the stability of the heating process.
T＝t 1 +t 2 (9)
x＝t 1 /t 2 (10)
P＝g(x)＝k·x (11)
Where k is a constant, related to circuit design.
In another embodiment of the present application, the plurality of sensors also perform temperature data acquisition of a plurality of target temperature measurement points according to the thermal shock flow described in fig. 6 or fig. 7. Or the deep temperature detection can be carried out by adopting a thermal impulse method,
by T d The temperature difference between the two temperature observation points is shown in equation 12, and T can be used doffijk Denotes the temperature difference between the j-th person at the two temperature observation points at the time k under the condition that the heating unit is switched off, T doffijk The temperature difference at the time k at the heating power Pi of the jth person is represented by equation 13, where equation 13 is a specific development of equation 12.
T d ＝T s -T e (12)
T doffijk ＝T soffijk -T eoffijk (13)
As shown in fig. 5a, when the depth temperature is known, training is performed based on the machine learning/deep learning model according to the training temperature data of the training temperature measurement points recorded in fig. 6 or fig. 7, and a set of model parameters is obtained.
As shown in fig. 5b, when the depth temperature is unknown, the deep temperature of the inspection target can be obtained by recording the temperature data of the target temperature measurement point according to fig. 6 or fig. 7, and substituting the model parameters into the machine learning/deep learning model.
The method and the device utilize the sensor array to estimate the body temperature of the human body, carry out heat impulse by introducing the heater, estimate the temperature of the cochlea by utilizing the thermal response characteristic parameters of the specific temperature measuring point, fully consider the difference of different people from a model, and can more accurately measure the ear temperature of the human body.
In a third aspect, the present application provides an earphone including the thermal impulse method-based core temperature measuring device according to the first and second embodiments.
It should be noted that, the deep temperature measuring device based on the thermal impulse method in the present application can also monitor the internal copper core temperature of the high-voltage wire, and the deep temperature of a microwave oven, an electric oven, and the like.
Finally, it is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation 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 but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising one of 8230; \8230;" 8230; "does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A deep temperature measurement method based on a thermal impulse method is characterized by comprising the following steps:
acquiring a thermal response characteristic parameter of at least one target temperature measuring point under a specific thermal shock condition;
the power curve of the heating module is changed to form the specific thermal shock condition for the target temperature measuring point;
the thermal response characteristic parameter is obtained based on the temperature response of the target temperature measuring point under the change of the power curve of the heating module;
acquiring deep temperature data of a detection target according to the thermal response characteristic parameters;
acquiring thermal response characteristic parameters of at least one target temperature measuring point under a specific thermal shock condition, wherein the thermal response characteristic parameters comprise; under the unheated condition, acquiring an unheated temperature sequence of the at least one target temperature measuring point at the thermal equilibrium; starting the heating module to obtain a heating temperature matrix of the at least one target temperature measuring point under different heating powers; calculating the thermal response characteristic parameter according to the unheated temperature sequence and the heating temperature matrix;
the thermal response characteristic parameter includes a steady state temperature value, a specific temperature value, a temperature change rate, and a maximum value of the temperature change rate.
2. The thermal impulse method-based deep temperature measurement method of claim 1, wherein the specific thermal impulse conditions include:
setting a first temperature sensor and a first heating module at a first target temperature measuring point;
and controlling a power curve of the first heating module to form a first thermal shock condition for the first target temperature measuring point.
3. The thermal impulse method-based deep temperature measurement method of claim 1, wherein the specific thermal impulse conditions further include:
setting a first temperature sensor at a first target temperature measuring point, and setting a second temperature sensor and a first heating module at a second target temperature measuring point;
and controlling a power curve of the first heating module, and forming a second thermal shock condition for the first target temperature measurement point and the second target temperature measurement point.
4. The deep temperature measurement method based on the thermal impulse method according to claim 2, wherein a calculation formula for obtaining deep temperature data of a detection target from the thermal response characteristic parameter is:
wherein, T soff Showing the steady state temperature, T, of the first target temperature measurement point when unheated soni Denotes a heating power P i Specific temperature value of time first target temperature measuring point, T' soni (t) represents a heating power P i Temperature variation of time first target temperature measuring pointRate of conversion, max (T' soni (t)) represents a heating power P i Maximum value of the rate of change of temperature, k, of the time first target temperature measurement point 1 ，k 2 ，…，k 2M+1 And b is a undetermined parameter, and the undetermined parameter is determined by utilizing an optimization algorithm.
5. The deep temperature measurement method based on the thermal impulse method according to claim 3, wherein a calculation formula for obtaining deep temperature data of a detection target from the thermal response characteristic parameter is:
wherein, T soff A first steady state temperature, T, representing a first target temperature measurement point when unheated eoff A second steady state temperature, T, representing a second target temperature measurement point when unheated soni Denotes a heating power P i Specific temperature value of time first target temperature measuring point, T eoni Denotes a heating power P i A specific temperature value, T ', of a second target temperature measuring point' soni (t) represents a heating power P i Temperature rate of change of time first target temperature measurement point, max (T' soni (t)) represents a heating power P i Maximum value of temperature change rate of time first target temperature measurement point, k 1 ，k 2 ，…，k 2M+1 And b is a undetermined parameter, and the undetermined parameter is determined by utilizing an optimization algorithm.
6. The deep temperature measurement method based on a thermal impulse method according to claim 1, wherein deep temperature data of a detection target is acquired from the thermal response characteristic parameter, and the method further includes:
acquiring training characteristic parameters and training temperature data of a training target;
inputting the training characteristic parameters and the training temperature data into a learning model for training to obtain a target learning model;
and inputting the thermal response characteristic parameters into the target learning model for calculation to obtain deep temperature data of the detection target.
7. A deep temperature measuring apparatus based on a thermal impulse method according to the measuring method of claim 1, the measuring apparatus comprising:
the heating module is used for forming a specific thermal shock condition for at least one target temperature measuring point through the change of a power curve of the heating module;
the temperature sensor is used for acquiring temperature data of the at least one target temperature measuring point under a specific thermal shock condition;
and the temperature processor is connected with the at least one temperature sensor and used for acquiring the thermal response characteristic parameters according to the temperature data and acquiring deep part temperature data of the detection target according to the thermal response characteristic parameters.
8. The deep temperature measuring apparatus according to claim 7, characterized in that,
when the at least one temperature sensor comprises a first temperature sensor, the first temperature sensor is arranged at a first target temperature measuring point and is used for collecting the outer surface temperature of the detection target;
the heating module is arranged on one side close to the first temperature sensor and used for forming a first thermal shock condition on a first target temperature measuring point.
9. The deep temperature measurement apparatus based on thermal impulse method according to claim 7,
when the at least one temperature sensor comprises a first temperature sensor and a second temperature sensor, the first temperature sensor is arranged at a first target temperature measuring point and used for collecting the outer surface temperature of the detection target, and the second temperature sensor is arranged at a second target temperature measuring point and used for collecting the environment temperature far away from the outer surface of the detection target;
the heating module is arranged on one side close to the second temperature sensor and used for forming a second thermal shock condition for the first target temperature measuring point and the second target temperature measuring point.
10. A headset characterized in that it comprises a thermal impulse method based core temperature measuring device according to any of claims 7-9.
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