CN113566975A - 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 human deep temperature measuring errors are large and measuring precision is low in the prior art.
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 measurement point and the second target temperature measurement 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, TsoffShowing the steady state temperature, T, of the first target temperature measurement point when unheatedsoniDenotes a heating power PiSpecific temperature value of time first target temperature measuring point, T'soni(t) represents a heating power PiTemperature rate of change of time first target temperature measurement point, max (T'soni(t)) represents a heating power PiThe 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, TsoffA first steady state temperature, T, representing a first target temperature measurement point when unheatedeoffIndicating no heatingSecond steady state temperature, T, of the second target temperature measurement pointsoniDenotes a heating power PiSpecific temperature value of time first target temperature measuring point, TeoniDenotes a heating power PiSpecific temperature value of time second target temperature measuring point, T'soni(t) represents a heating power PiTemperature rate of change of time first target temperature measurement point, max (T'soni(t)) represents a heating power PiThe maximum value of the rate of change of temperature at 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 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 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 for collecting 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 for collecting the ambient 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.
In a third aspect, the present application provides a headset comprising the above-mentioned thermal impulse method-based deep temperature measuring apparatus.
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 flow chart 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 any inventive step based on the embodiments of the present invention, are within the 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 measuring apparatus based on a thermal impulse method according to an embodiment of the present application, and as shown in fig. 1, the deep temperature measuring apparatus based on the thermal impulse method includes:
the device comprises a heating module, a first temperature sensor and a temperature processor;
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, a 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 zone to be measured and the first temperature sensor, so that the heat conduction medium comprises one or more of skin, air and device shells 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 measuring 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 TCThe temperature T of the first target temperature measuring pointSThe temperature difference between the two is as follows:
ΔT＝Tc-Ts (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. Where P denotes the heating power of the heating module and T denotes the duration of the thermal impulse, P, T can be related to Δ T as follows:
ΔT＝f(P，t) (2)
when Δ T is 0, T is obtainedC＝TSI.e. the temperature T of the first target temperature measuring pointSI.e. the deep temperature TC。
From formula 1 and formula 2:
Tc＝Ts+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 pointSPerforming temperature compensation to eliminate the influence of environmental factors and obtain the estimated deep temperature TCMore 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 a heat impulse condition 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 moduleeAnd a first target temperature measuring point temperature T close to the heat transfer medium sideSWhen 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 TC。
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:
TC＝Ts+(Ts-Te)*y (4)
the present embodiment is divided into two environments of heating and non-heating, i.e. 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 formulasoffFor not heating the first target temperature measuring point temperature, TeoffFor not heating the second target temperature measuring point temperature, TsonHeating the first target temperature measurement point temperature, TeonAnd heating the second target temperature measurement point temperature.
By analogy, the application can also 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 the difference between different embodiments is to adopt different calculation formulas to obtain deep temperature data.
As can be seen from the first and second embodiments, the deep temperature measurement device based on the thermal impulse method according to 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 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.
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 thermal response characteristic parameters 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 starting the heating module, obtaining a plurality of heating temperatures under different heating powers, forming the plurality of heating temperatures under different heating powers into a heating temperature matrix, and finally calculating the thermal response characteristic parameters 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 and P2 … … Pi.
And S102, acquiring deep 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 depth learning model to obtain a set of target model parameters, and the target model parameters are input into the machine learning model or the depth 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 (namely dTs/dt <0.05), and the target temperature measuring point temperature { Toff 11, Toff 12, … and Toff 1n } of the time is recorded (in Toff fij, an angle mark off represents the off heating, i represents the ith section of data, and j represents the jth time point);
(3) starting the heating module by using the power Pi, and recording the target temperature measuring point temperature { Tsoni1, Tsoni2, … and Tsonin } of the time (in Tsonij, a corner mark on represents the starting heating, i represents the ith 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 approximate heat balance (namely dTs/dt <0.05), and the target temperature measuring point temperature { Toff 11, Toff 12, … and Toff 1n } of the time is recorded (in Toff fij, an angle mark off represents the off heating, i represents the ith section of data, and j represents the jth time point);
(3) starting the heating module by using the power Pi, and recording the target temperature measuring point temperature { Tsoni1, Tsoni2, … and Tsonin } of the time (in Tsonij, a corner mark on represents the starting heating, i represents the ith data, and j represents the jth time point);
(4) repeating step 3 with 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 to form 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 temperature data of the detection target according to the thermal response characteristic parameter is as follows:
wherein, TsoffShowing the steady state temperature, T, of the first target temperature measurement point when unheatedsoniDenotes a heating power PiSpecific temperature value of time first target temperature measuring point, T'soni(t) represents a heating power PiTemperature rate of change of time first target temperature measurement point, max (T'soni(t)) represents a heating power PiThe maximum value of the rate of change of temperature at the first target temperature measurement point.
In the present embodiment, the thermal response characteristic parameters of the non-heated temperature sequence { Tsoff111, Tsoff112, …, Tsoff11n } before the hot impact and the heated temperature matrix { Tsonik1, Tsonik2, …, Tsonikn } after the hot impact is turned on are extracted to perform deep temperature estimation; t in equation 7soffThe last temperature before the start of heating, T, can be taken approximatelysoniThe 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 of1，k2，…，k2M+1B is a parameter to be determined, and an optimization algorithm (including Newton's steepest) can be used by collecting a large amount of dataDescent method, particle swarm algorithm, etc.) to determine the parameters to be determined.
Further, let k in equation 71·TsoffIn the first item, 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. 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 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 measurement point and the second target temperature measurement point.
In this embodiment, the calculation formula for obtaining the deep temperature data of the detection target according to the thermal response characteristic parameter is as follows:
wherein, TsoffA first steady state temperature, T, representing a first target temperature measurement point when unheatedeoffA second steady state temperature, T, representing a second target temperature measurement point when unheatedsoniDenotes a heating power PiSpecific temperature value of time first target temperature measuring point, TeoniDenotes a heating power PiSpecific temperature value of time second target temperature measuring point, T'soni(t) represents a heating power PiTemperature rate of change of time first target temperature measurement point, max (T'soni(t)) represents a heating power PiThe maximum value of the rate of change of temperature at the first target temperature measurement point.
Note that T issoffUnder 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 iseoffUnder 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 issoni、TeoniRespectively, 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)) is the maximum value of the rate of change of temperature at the first target temperature measurement point after the heating unit has been started with power Pi; k is a radical of1，k2，…，k2M+2And 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 81·TsoffIs the first term, k2·(Tsoff-Teoff) In the second term, the first term is,
in the third item, the first and second items,
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 the two temperature sensors in the direction of the two temperature sensors at the deep part temperature of the heating front edge, and the temperature drop has a linear relation with the deep part temperature and the surface temperature in the direction; 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 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 to compensate for temperature loss caused in the direction perpendicular to the gradient described by 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 the present embodiment, the temperature processor achieves the purpose of controlling the power of the heater modules by adjusting the pulse signals input to the heater modules, and as shown in FIG. 8, the heating power is controlled by controlling the duty ratio (t1: t2, t1 represents the high level duration), that is, by controlling the duration of the PIN 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, the heating power is described by taking a mode of controlling the duty ratio as an example, 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＝t1+t2 (9)
x＝t1/t2 (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 TdThe temperature difference between the two temperature observation points is shown in formula 12, and T can be useddoffiijkDenotes the temperature difference between the i-th person at time k and the two temperature observation points, T, with the heating unit turned offdoffiijkThe temperature difference at the moment k at the heating power Pi for the ith individual is shown by equation 13, where equation 13 is a specific development of equation 12.
Td＝Ts-Te (12)
Tdoffijk＝Tsoffijk-Teoffijk (13)
As shown in fig. 5a, when the depth temperature is known, training is performed based on the machine learning/depth 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 temperature data of the target temperature measurement point is recorded according to fig. 6 or fig. 7, and the deep temperature of the inspection target can be obtained by substituting model parameters into the machine learning/depth 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 a headset including the thermal impulse method-based core temperature measuring apparatus 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 phrase "comprising an … …" does not exclude the presence of other identical 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 (12)
1. A deep temperature measuring 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;
and acquiring deep temperature data of the detection target according to the thermal response characteristic parameters.
2. The thermal impulse method-based deep temperature measurement method of claim 1, wherein the thermal response characteristic parameters include one or more of a steady-state temperature value, a specific temperature value, a temperature change rate, and a maximum value of the temperature change rate.
3. The thermal impulse method-based deep temperature measurement method according to claim 2, 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.
4. The thermal impulse method-based deep temperature measurement method of claim 2, 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.
5. The deep temperature measurement method based on the thermal impulse method according to claim 1, wherein the thermal response characteristic parameters of at least one target temperature measurement point under a specific thermal impulse condition are obtained, 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.
6. 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, TsoffShowing the steady state temperature, T, of the first target temperature measurement point when unheatedsoniDenotes a heating power PiSpecific temperature value of time first target temperature measuring point, T'soni(t) represents a heating power PiTemperature rate of change of time first target temperature measurement point, max (T'soni(t)) represents a heating power PiThe maximum value of the rate of change of temperature at the first target temperature measurement point.
7. The deep temperature measurement method based on the thermal impulse method according to claim 4, wherein a calculation formula for obtaining deep temperature data of a detection target from the thermal response characteristic parameter is:
wherein, TsoffA first steady state temperature, T, representing a first target temperature measurement point when unheatedeoffA second steady state temperature, T, representing a second target temperature measurement point when unheatedsoniDenotes a heating power PiSpecific temperature value of time first target temperature measuring point, TeoniDenotes a heating power PiSpecific temperature value of time second target temperature measuring point, T'soni(t) represents a heating power PiIs first ofA rate of change of temperature at the target temperature measurement point, max (T'soni(t)) represents a heating power PiThe maximum value of the rate of change of temperature at the first target temperature measurement point.
8. The method for deep temperature measurement based on thermal impulse method according to claim 1, wherein deep temperature data of a detection target is acquired based on 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.
9. A deep temperature measuring apparatus based on a thermal impulse method, the measuring apparatus comprising:
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 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.
10. The deep temperature measurement apparatus based on thermal impulse method according to claim 9,
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.
11. The deep temperature measurement apparatus based on thermal impulse method according to claim 9,
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.
12. A headset, characterized in that the headset comprises a thermal impulse method based core temperature measuring device according to any of claims 9-11.
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| JP2002202205A (en) * | 2000-10-24 | 2002-07-19 | Terumo Corp | Deep part temperature measuring device |
| CN102706470A (en) * | 2010-10-29 | 2012-10-03 | 精工爱普生株式会社 | Temperature measurement device and temperature measuring method |
| US20190049317A1 (en) * | 2016-04-22 | 2019-02-14 | Murata Manufacturing Co., Ltd. | Deep body thermometer |
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| JP2002202205A (en) * | 2000-10-24 | 2002-07-19 | Terumo Corp | Deep part temperature measuring device |
| CN102706470A (en) * | 2010-10-29 | 2012-10-03 | 精工爱普生株式会社 | Temperature measurement device and temperature measuring method |
| US20190049317A1 (en) * | 2016-04-22 | 2019-02-14 | Murata Manufacturing Co., Ltd. | Deep body thermometer |
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