CN117725344B - Error-based oxygen partial pressure optimization fitting method, electronic equipment and storage medium - Google Patents
Error-based oxygen partial pressure optimization fitting method, electronic equipment and storage medium Download PDFInfo
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- 239000001301 oxygen Substances 0.000 title claims abstract description 113
- 229910052760 oxygen Inorganic materials 0.000 title claims abstract description 113
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 title claims abstract description 108
- 238000000034 method Methods 0.000 title claims abstract description 70
- 238000005457 optimization Methods 0.000 title claims abstract description 24
- 238000003860 storage Methods 0.000 title claims abstract description 22
- 230000008569 process Effects 0.000 claims abstract description 14
- 238000004590 computer program Methods 0.000 claims description 10
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- 238000012545 processing Methods 0.000 description 8
- 238000006243 chemical reaction Methods 0.000 description 6
- 239000007789 gas Substances 0.000 description 4
- 239000000126 substance Substances 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 3
- 238000010791 quenching Methods 0.000 description 3
- 230000000171 quenching effect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 150000002926 oxygen Chemical class 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 238000009530 blood pressure measurement Methods 0.000 description 1
- 210000001124 body fluid Anatomy 0.000 description 1
- 239000010839 body fluid Substances 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
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- 230000031700 light absorption Effects 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
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- 239000000203 mixture Substances 0.000 description 1
- 230000001172 regenerating effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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Abstract
The application relates to an error-based oxygen partial pressure optimization fitting method, electronic equipment and a storage medium, wherein temperature, phase and first oxygen partial pressure data in the working process of an oxygen partial pressure sensor are obtained; obtaining a function to be fitted, wherein the function to be fitted is used for obtaining second oxygen partial pressure data according to the temperature and the phase; obtaining an error function according to the weight function and the function to be fitted, wherein the error function is used for describing the error between the first oxygen partial pressure data and the second oxygen partial pressure data; solving an error function to obtain an error array; if the error array does not meet the preset condition, updating the error function according to the error array, and then solving again until the obtained error array meets the preset condition. According to the technical scheme, the problem that local errors of the oxygen partial pressure data obtained by fitting are overlarge can be avoided through the optimized relative errors between the first oxygen partial pressure data and the second oxygen partial pressure data.
Description
Technical Field
The application relates to the technical field of oxygen sensors, in particular to an oxygen partial pressure optimization fitting method based on errors, electronic equipment and a storage medium.
Background
An oxygen partial pressure sensor is a device for measuring the partial pressure of oxygen by which the oxygen concentration is reflected. The fluorescence quenching method oxygen partial pressure gas sensor is an advanced technology for high-precision nondestructive monitoring of oxygen concentration. The method realizes accurate measurement of the oxygen concentration (oxygen partial pressure) through fluorescence quenching reaction, and has the advantages of high precision, no damage, quick response, good stability and the like. The working principle of the fluorescence quenching method oxygen partial pressure gas sensor is to detect the oxygen partial pressure by utilizing the light absorption or fluorescence phenomenon. As the light passes through the oxygen-containing gas, the light is absorbed or scattered, resulting in an attenuation of the light intensity. By measuring the degree of attenuation of the light intensity, the oxygen partial pressure can be estimated. Therefore, the calibration fitting algorithm of the oxygen partial pressure with respect to the phase and the temperature has an important influence on the oxygen partial pressure measurement accuracy.
In the course of conception and implementation of the present application, the applicant has found at least the following problems: the conventional oxygen partial pressure calibration fitting algorithm generally adopts a least square method, and the idea of the least square method is to find a curve nearest to all data. The best function match for the data is found by minimizing the sum of squares of the errors. The basic principle of the least squares method is to choose the unknown parameters such that the sum of squares of the differences between the theoretical and observed values of the assumed fitting function is minimized, i.e. the best function match for the data is found by minimizing the sum of squares of the errors. The overall error sum of the fitting method is minimal, but there may be a problem of excessive local errors.
Disclosure of Invention
Aiming at the technical problems, the application provides an oxygen partial pressure optimization fitting method based on errors, electronic equipment and a storage medium.
In order to solve the technical problems, the application provides an oxygen partial pressure optimization fitting method based on errors, which comprises the following steps:
Acquiring temperature, phase and first oxygen partial pressure data in the working process of an oxygen partial pressure sensor;
obtaining a function to be fitted, wherein the function to be fitted is used for obtaining second oxygen partial pressure data according to the temperature and the phase;
Obtaining an error function according to the weight function and the function to be fitted, wherein the error function is used for describing the error between the first oxygen partial pressure data and the second oxygen partial pressure data;
Solving the error function to obtain an error array;
if the error array does not meet the preset condition, updating the error function according to the error array, and then solving again until the obtained error array meets the preset condition.
Optionally, the expression of the function to be fitted is any one of the following:
(1)
(2)
(3)
Where P O2 is the partial pressure of oxygen, θ is the phase under aerobic conditions, A, B, C, D is a second order expression for temperature T, i.e Wherein a11、a12、a13、a21、a22、a23、a31、a32、a33、a41、a42、a43 is the calibration coefficient.
Optionally, before the obtaining an error function according to the weight function and the function to be fitted, the method further includes:
defining a precision requirement function;
defining a weight region function;
and obtaining a weight function according to the precision requirement function and the weight region function.
Optionally, the solving the error function further includes:
The error function is solved by the fastest descent method.
Optionally, the method comprises:
solving the error function to obtain a first error array;
If the maximum value in the first error array is greater than or equal to a preset value, updating the error function according to the first error array;
solving the updated error function to obtain a second error array;
And if the maximum value in the second error array is greater than or equal to a preset value, updating the error function again according to the second error array until the maximum value of the error array obtained by solving is smaller than the preset value.
Optionally, the updating the error function according to the error array includes:
determining partial second oxygen partial pressure data according to the distribution rule of the error array;
adjusting the weight value of the partial second oxygen partial pressure data in the weight function to update the weight function;
and updating the error function according to the weight function.
Optionally, the solving the error function to obtain an error array further includes:
And solving the error function to obtain an error array and a calibration coefficient of the function to be fitted, wherein the error array corresponds to the calibration coefficient.
Optionally, after updating the error function according to the error array, solving again until the obtained error array meets a preset condition, the method further includes:
Outputting a calibration coefficient corresponding to the error array;
and updating the function to be fitted according to the calibration coefficient.
The application also provides electronic equipment, which comprises a storage medium and a controller, wherein the storage medium is stored with a computer program, and the computer program realizes the steps of the error-based oxygen partial pressure optimization fitting method when being executed by the controller.
The present application also provides a storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the error-based oxygen partial pressure optimization fitting method described above.
As described above, the error-based oxygen partial pressure optimization fitting method, the intelligent terminal and the storage medium provided by the application are characterized in that the temperature, the phase and the first oxygen partial pressure data in the working process of the oxygen partial pressure sensor are obtained; obtaining a function to be fitted, wherein the function to be fitted is used for obtaining second oxygen partial pressure data according to the temperature and the phase; obtaining an error function according to the weight function and the function to be fitted, wherein the error function is used for describing the error between the first oxygen partial pressure data and the second oxygen partial pressure data; solving an error function to obtain an error array; if the error array does not meet the preset condition, updating the error function according to the error array, and then solving again until the obtained error array meets the preset condition. According to the technical scheme, the problem that local errors of the oxygen partial pressure data obtained by fitting are overlarge can be avoided through the optimized relative errors between the first oxygen partial pressure data and the second oxygen partial pressure data.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application. In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
Fig. 1 is a schematic diagram of the structure of an oxygen partial pressure sensor.
FIG. 2 is one of the flow charts of the error-based oxygen partial pressure optimization fitting method according to embodiments of the present application.
FIG. 3 is a second flow chart of an error-based partial pressure optimization fitting method according to an embodiment of the application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments. Specific embodiments of the present application have been shown by way of the above drawings and will be described in more detail below. The drawings and the written description are not intended to limit the scope of the inventive concepts in any way, but rather to illustrate the inventive concepts to those skilled in the art by reference to the specific embodiments.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the accompanying claims.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or 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, the element defined by the phrase "comprising one … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element, and furthermore, elements having the same name in different embodiments of the application may have the same meaning or may have different meanings, the particular meaning of which is to be determined by its interpretation in this particular embodiment or by further combining the context of this particular embodiment.
It should be noted that, in this document, step numbers such as S401 and S402 are adopted, and the purpose of the present application is to more clearly and briefly describe the corresponding content, and not to constitute a substantial limitation on the sequence, and those skilled in the art may execute S402 first and then S401 when implementing the present application, which is within the scope of protection of the present application.
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
An oxygen partial pressure sensor is a device for measuring the partial pressure of oxygen in a gas mixture or body fluid. The oxygen partial pressure monitoring system can convert the partial pressure of oxygen into an electric signal or a digital signal, so that the real-time monitoring and recording of the oxygen partial pressure are realized. Fig. 1 is a schematic diagram of the structure of an oxygen partial pressure sensor. As shown in fig. 1, the oxygen partial pressure sensor includes an optical signal supply device 1, a photoelectric conversion device 2, and an electrical signal processing device 3. The optical signal providing apparatus 1 includes an excitation lamp 11, a reference lamp 12, a spectroscope 13, and an optical filter 14. The reference lamp 12 and the excitation lamp 11 are disposed on the same straight line, and the light directions are respectively directed toward each other when light is emitted. The spectroscope 13 is disposed at the midpoint of the straight line where the reference lamp 12 and the excitation lamp 11 are located, and the filter 14 is disposed on the optical path where the fluorescent substance 4 emits fluorescence. An optical filter 15 is arranged between the excitation lamp 11 and the spectroscope 13, and an attenuation sheet 16 is arranged between the reference lamp 12 and the spectroscope 13.
In the oxygen partial pressure detection, the fluorescent substance 4, the spectroscope 13 and the optical filter 14 are arranged on one straight line, and the reference lamp 12, the spectroscope 13 and the excitation lamp 11 are arranged on the other straight line, and the two straight lines are perpendicular to each other. The electric signal processing device 3 is electrically connected to the reference lamp 12 and the excitation lamp 11, and is configured to send a light emission command to the reference lamp 12 and the excitation lamp 11, so that the reference lamp 12 and the excitation lamp 11 emit light.
The electric signal processing device 3 sends out a luminous instruction to the excitation lamp 11, so that the excitation lamp 11 sends out excitation light, the excitation light 11 is reflected to the fluorescent substance 4 through the spectroscope 13 arranged in the light path direction, the fluorescent substance 4 sends out fluorescence and passes through the spectroscope 13 and then passes through the optical filter 14, the fluorescence reaches the photoelectric conversion device 2 to be converted into a fluorescence electric signal, and the fluorescence electric signal is processed by the electric signal processing device 3. The electric signal processing device 3 sends out a luminous instruction to the reference lamp 12, so that the reference lamp 12 emits reference light, the reference light is reflected by the spectroscope 13 arranged in the light path direction and then directly passes through the optical filter 14, the reference light reaches the photoelectric conversion device 2 to be converted into a reference photoelectric signal, and the reference photoelectric signal is processed by the electric signal processing device 3.
The photoelectric conversion device 2 includes a photodetector, an amplifying circuit, and a filter circuit electrically connected in this order. The photodetector is used for converting the optical signal passing through the optical filter into an electrical signal. Since the fluorescence intensity is weak, the fluorescence electric signal is amplified by the amplifying circuit. After the fluorescent electric signal is amplified, noise is amplified, and the amplified fluorescent electric signal is filtered by a filter circuit. The photoelectric conversion device 2 is electrically connected to the electric signal processing device 3, and is configured to transmit the converted electric signal to the electric signal processing device 3.
In order to solve the problem that the error of oxygen partial pressure data obtained by fitting in the prior art is overlarge, the embodiment of the application provides an oxygen partial pressure optimization fitting method based on the error. FIG. 2 is one of the flow charts of the error-based oxygen partial pressure optimization fitting method according to embodiments of the present application. FIG. 3 is a second flow chart of an error-based partial pressure optimization fitting method according to an embodiment of the application. As shown in fig. 2 and 3, the error-based oxygen partial pressure optimization fitting method of the present application includes:
step S401, temperature, phase and first oxygen partial pressure data in the working process of the oxygen partial pressure sensor are obtained.
Here, actual temperature, phase and first oxygen partial pressure data during operation of the plurality of sets of oxygen partial pressure sensors are collected. The temperature and the phase are used for calibrating and calculating second oxygen partial pressure data, the first oxygen partial pressure data is used as reference data, and the error value of the calculated second oxygen partial pressure data is used for evaluating.
Step S402, obtaining a function to be fitted, wherein the function to be fitted is used for obtaining second oxygen partial pressure data according to the temperature and the phase.
Here, a function to be fitted for fitting the second oxygen partial pressure data is defined, and the independent variables in the function to be fitted are the temperature and the phase actually acquired in step S401.
In an embodiment, the expression of the function to be fitted may be any one of the following second order polynomial or third order polynomial, wherein equation (1) is a second order polynomial, equation (2) is a scheme 1 of a third order polynomial, and equation (3) is a scheme 2 of a third order polynomial:
(1)
(2)
(3)
Where P O2 is the partial pressure of oxygen, θ is the phase under aerobic conditions, A, B, C, D is a second order expression for temperature T, i.e Wherein a11、a12、a13、a21、a22、a23、a31、a32、a33、a41、a42、a43 is the calibration coefficient.
The calibration coefficient can be realized by a pre-calibration mode. The pre-calibration method comprises the steps of selecting a plurality of temperature values of-40 ℃,10 ℃, 35 ℃, 50 ℃,70 ℃ and the like, wherein the number of the temperature values is not less than 4, each temperature value corresponds to 7-8 oxygen partial pressure values, and the method at least comprises a high-temperature high-oxygen environment and a low-temperature low-oxygen environment. And measuring corresponding phase values under different temperature and oxygen partial pressure conditions. Based on the plurality of sets (at least 28 sets) of known temperature values, oxygen partial pressure values, and phase values, a plurality of sets of polynomials including the above calibration coefficients are obtained, and these polynomials are solved to obtain the starting values of the above calibration coefficients.
Error data of the fitting results of the above three functions to be fitted are shown in table 1 below. As can be seen from the data in table 1, the error of the third order expression is lower than that of the second order expression, and the error of the scheme 2 of the third order polynomial (i.e., formula (3)) is lower than that of the scheme 1 of the third order polynomial (i.e., formula (2)). Therefore, the application prefers the formula (3) as a function to be fitted for calibrating the second oxygen partial pressure data, wherein A, B, C and D are second-order polynomials related to temperature, so that the accuracy of the oxygen partial pressure sensor in a high-temperature and high-oxygen environment can be obviously improved.
TABLE 1 error data for the function to be fitted
Step S403, obtaining an error function according to the weight function and the function to be fitted, wherein the error function is used for describing the error between the first oxygen partial pressure data and the second oxygen partial pressure data.
In one embodiment, before the error function is obtained according to the weight function and the function to be fitted, the oxygen partial pressure optimization fitting method based on the error further comprises:
defining a precision requirement function;
defining a weight region function;
and obtaining a weight function according to the precision requirement function and the weight region function.
Here, the independent variables of the precision requirement function δ and the weight region function q are both temperature and oxygen partial pressure. The weight function G is the ratio of the weight region function q and the precision requirement function δ, i.e., g=q/δ.
Specifically, first, a precision requirement function is defined as:
(4)
The weight region function is then defined as:
(5)
the weighting functions available from equation (4) and equation (5) are:
(6)
The error function is obtained according to the weight function and the function to be fitted:
(7)
Wherein G (T, ) Representing a weight function, P o2 (T, θ) representing second oxygen partial pressure data derived from the function to be fitted,/>The first oxygen partial pressure data representing the nth group.
Step S404, solving the error function to obtain an error array.
Here, the error function can be solved by the fastest descent method. The basic idea of the fastest descent method is to consider not only the direction of the gradient vector but also the modulo length of the gradient vector (i.e. the eigenvalues of the hessian matrix) in each iteration. By combining these two information, the fastest descent method can better determine the search direction and step size to achieve faster convergence speed.
The process of solving the error function by adopting the fastest descent method, namely the process of minimizing the obtained error by continuously adjusting the calibration coefficient. Specifically, a plurality of sets of original data (T, θ, P O2)N) are led into an error function, the calibration coefficient in P o2 (T, θ) (i.e. the expression of the function to be fitted) is used as a variable, the initial value of the calibration coefficient is used as a starting point x 0, the iteration number k=0, when the calibration coefficient is changed, the error function is solved to obtain the error value to be changed along with the change, the gradient of the current point x k is calculated. Where f (x) is the error function. The search is performed along the negative gradient direction, i.e. the search direction p k=-gk is calculated. The appropriate step size a k is chosen such that the objective function value decreases after a certain distance along the search direction p k. The current point x k+1=xk+αkpk is updated and the number of iterations is increased by 1, i.e. k=k+1. The above process is repeated until the error value is minimal. Therefore, the calibration coefficient is adjusted by adopting the fastest descent method, so that the calibration coefficient corresponding to the weighted error function when the error value is minimum is solved. Outputting the optimized error array and the calibration coefficient of the corresponding function to be fitted.
Step S405, if the error array does not meet the preset condition, updating the error function according to the error array and then solving again until the obtained error array meets the preset condition.
Here, it is determined whether the solved error array satisfies a preset condition. Specifically, if the maximum value in the first error array is greater than or equal to a preset value, updating the error function according to the first error array;
Solving the updated error function to obtain a second error array;
if the maximum value in the second error array is larger than or equal to the preset value, updating the error function again according to the second error array until the maximum value of the error array obtained by solving is smaller than the preset value.
If the maximum value in the error array is greater than the preset value, the preset value may take 0.2-0.35, and the error of the second oxygen partial pressure data obtained by fitting is considered to be too large, and the error function needs to be solved again after adjustment, so as to output a new calibration coefficient to update the function to be fitted. And until the maximum error value of the second oxygen partial pressure data obtained by fitting is smaller than a preset value. The optimization is iterated until the maximum error reaches 0.35. The test data show that the error value without optimization can reach 0.6-0.7, the average error value after optimization can reach 0.3, and the optimal error value can reach 0.2.
In other embodiments, if the maximum value of the error array is always greater than 0.35, when the iteration number reaches 1000, the error array is considered to satisfy the preset condition, and the iteration can be stopped, so that the dead loop can be avoided.
In one embodiment, updating the error function according to the error array includes:
Determining a portion of the second oxygen partial pressure data based on the error array;
adjusting the weight value of part of the second oxygen partial pressure data in the weight function to update the weight function;
And updating the error function according to the weight function.
Here, partial data with larger errors in the error array is extracted, for example, the error value of the first 5% -10% is selected according to the order of the error values in the error array. And then adjusting the weight ratio of the second oxygen partial pressure data corresponding to the error value in the weight function, for example, increasing the weight function of the data by 1.05 times to 1.2 times. And regenerating an updated error function based on the updated weight function and the function to be fitted, and then solving the updated error function to output a new error array and a corresponding calibration coefficient.
Since the error array corresponds to the calibration factor. And solving again after updating the error function according to the error array until the obtained error array meets the preset condition, and further comprising:
outputting a calibration coefficient corresponding to the error array;
And updating the function to be fitted according to the calibration coefficient.
And when the maximum value in the error array is smaller than or equal to a preset value, the output error array is considered to meet the optimization requirement, and the function to be fitted can be updated according to a new calibration coefficient obtained after the error function is solved, so that second oxygen partial pressure data meeting the error requirement is calculated through calibration of the function to be fitted, and the calibration precision of the oxygen partial pressure is improved.
The application relates to an error-based oxygen partial pressure optimization fitting method, which comprises the following steps: acquiring temperature, phase and first oxygen partial pressure data in the working process of an oxygen partial pressure sensor; obtaining a function to be fitted, wherein the function to be fitted is used for obtaining second oxygen partial pressure data according to the temperature and the phase; obtaining an error function according to the weight function and the function to be fitted, wherein the error function is used for describing the error between the first oxygen partial pressure data and the second oxygen partial pressure data; solving an error function to obtain an error array; if the error array does not meet the preset condition, updating the error function according to the error array, and then solving again until the obtained error array meets the preset condition. According to the technical scheme, the problem that local errors of the oxygen partial pressure data obtained by fitting are overlarge can be avoided through the optimized relative errors between the first oxygen partial pressure data and the second oxygen partial pressure data.
The application also provides an electronic device comprising a storage medium and a controller, the storage medium having stored thereon a computer program which, when executed by the controller, implements the steps of the method as described in the above embodiments.
The application also provides a storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method as described in the above embodiments. .
It can be understood that the above scenario is merely an example, and does not constitute a limitation on the application scenario of the technical solution provided by the embodiment of the present application, and the technical solution of the present application may also be applied to other scenarios. For example, as one of ordinary skill in the art can know, with the evolution of the system architecture and the appearance of new service scenarios, the technical solution provided by the embodiment of the present application is also applicable to similar technical problems.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
The steps in the method of the embodiment of the application can be sequentially adjusted, combined and deleted according to actual needs.
The units in the device of the embodiment of the application can be combined, divided and deleted according to actual needs.
In the present application, the same or similar term concept, technical solution and/or application scenario description will be generally described in detail only when first appearing and then repeatedly appearing, and for brevity, the description will not be repeated generally, and in understanding the present application technical solution and the like, reference may be made to the previous related detailed description thereof for the same or similar term concept, technical solution and/or application scenario description and the like which are not described in detail later.
In the present application, the descriptions of the embodiments are emphasized, and the details or descriptions of the other embodiments may be referred to.
The technical features of the technical scheme of the application can be arbitrarily combined, and all possible combinations of the technical features in the above embodiment are not described for the sake of brevity, however, as long as there is no contradiction between the combinations of the technical features, the application shall be considered as the scope of the description of the application.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, a controlled terminal, or a network device, etc.) to perform the method of each embodiment of the present application.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable devices. The computer instructions may be stored in a storage medium or transmitted from one storage medium to another storage medium, for example, from one website, computer, server, or data center to another website, computer, server, or data center by a wired (e.g., coaxial cable, fiber optic, digital subscriber line), or wireless (e.g., infrared, wireless, microwave, etc.) means. The storage media may be any available media that can be accessed by a computer or a data storage device such as a server, data center, or the like that contains an integration of one or more available media. Usable media may be magnetic media (e.g., floppy disks, storage disks, magnetic tape), optical media (e.g., DVD), or semiconductor media (e.g., solid state storage disk Solid STATE DISK (SSD)), etc.
The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the application, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (8)
1. An error-based oxygen partial pressure optimization fitting method is characterized by comprising the following steps:
Acquiring temperature, phase and first oxygen partial pressure data in the working process of an oxygen partial pressure sensor;
obtaining a function to be fitted, wherein the function to be fitted is used for obtaining second oxygen partial pressure data according to the temperature and the phase;
Obtaining an error function according to the weight function and the function to be fitted, wherein the error function is used for describing the error between the first oxygen partial pressure data and the second oxygen partial pressure data;
Solving the error function to obtain an error array;
If the error array does not meet the preset condition, updating the error function according to the error array, and then solving again until the obtained error array meets the preset condition;
the solving the error function to obtain an error array further comprises:
solving the error function to obtain an error array and a calibration coefficient of the function to be fitted, wherein the error array corresponds to the calibration coefficient;
and after updating the error function according to the error array, solving again until the obtained error array meets the preset condition, wherein the method further comprises the following steps:
Outputting a calibration coefficient corresponding to the error array;
and updating the function to be fitted according to the calibration coefficient.
2. The method according to claim 1, wherein the expression of the function to be fitted is any one of the following:
(1)
(2)
(3)
Where P O2 is the partial pressure of oxygen, θ is the phase under aerobic conditions, A, B, C, D is a second order expression for temperature T, i.e Wherein a11、a12、a13、a21、a22、a23、a31、a32、a33、a41、a42、a43 is the calibration coefficient.
3. The method of claim 1, wherein before the deriving the error function from the weight function and the function to be fitted, the method further comprises:
defining a precision requirement function;
defining a weight region function;
and obtaining a weight function according to the precision requirement function and the weight region function.
4. The method of claim 1, wherein said solving the error function further comprises:
The error function is solved by the fastest descent method.
5. The method according to claim 1, characterized in that the method comprises:
solving the error function to obtain a first error array;
If the maximum value in the first error array is greater than or equal to a preset value, updating the error function according to the first error array;
solving the updated error function to obtain a second error array;
And if the maximum value in the second error array is greater than or equal to a preset value, updating the error function again according to the second error array until the maximum value of the error array obtained by solving is smaller than the preset value.
6. The method of claim 1, wherein the updating the error function from the error array comprises:
determining partial second oxygen partial pressure data according to the distribution rule of the error array;
adjusting the weight value of the partial second oxygen partial pressure data in the weight function to update the weight function;
and obtaining an updated error function according to the updated weight function and the function to be fitted.
7. An electronic device comprising a storage medium and a controller, characterized in that the storage medium has stored thereon a computer program which, when executed by the controller, implements the steps of the error-based oxygen partial pressure optimization fitting method according to any one of claims 1 to 6.
8. A storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the error-based oxygen partial pressure optimization fitting method of any one of claims 1 to 6.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103034988A (en) * | 2012-12-18 | 2013-04-10 | 武汉大学 | Space-time quantitative remote sensing fusion method of arbitrary number of sensors |
| CN109639329A (en) * | 2018-11-16 | 2019-04-16 | 上海无线电设备研究所 | The only quick shaping method of phase weighting wave beam |
| CN111397755A (en) * | 2020-04-08 | 2020-07-10 | 上海电机***节能工程技术研究中心有限公司 | Correction method for absolute error of temperature measuring instrument |
| CN111537487A (en) * | 2020-05-25 | 2020-08-14 | 清华大学 | Temperature compensation method and device of optical oxygen sensor |
| WO2021196360A1 (en) * | 2020-03-31 | 2021-10-07 | 深圳奥比中光科技有限公司 | Temperature measurement method and system |
| CN113916849A (en) * | 2021-09-10 | 2022-01-11 | 山东省科学院海洋仪器仪表研究所 | Calibration method and calibration device for optical dissolved oxygen sensor |
| CN116224070A (en) * | 2022-12-01 | 2023-06-06 | 国网山东省电力公司潍坊供电公司 | OCV (open circuit voltage) -SOC (system on a chip) model-based full-temperature lithium ion battery OCV (open circuit voltage) evaluation method and system |
| CN116721736A (en) * | 2023-05-29 | 2023-09-08 | 西安交通大学 | Exercise effect monitoring method, system, equipment and readable storage medium |
| CN117168684A (en) * | 2023-08-31 | 2023-12-05 | 航宇救生装备有限公司 | Oxygen partial pressure test method for pressurized oxygen supply mask |
-
2024
- 2024-02-07 CN CN202410173795.XA patent/CN117725344B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103034988A (en) * | 2012-12-18 | 2013-04-10 | 武汉大学 | Space-time quantitative remote sensing fusion method of arbitrary number of sensors |
| CN109639329A (en) * | 2018-11-16 | 2019-04-16 | 上海无线电设备研究所 | The only quick shaping method of phase weighting wave beam |
| WO2021196360A1 (en) * | 2020-03-31 | 2021-10-07 | 深圳奥比中光科技有限公司 | Temperature measurement method and system |
| CN111397755A (en) * | 2020-04-08 | 2020-07-10 | 上海电机***节能工程技术研究中心有限公司 | Correction method for absolute error of temperature measuring instrument |
| CN111537487A (en) * | 2020-05-25 | 2020-08-14 | 清华大学 | Temperature compensation method and device of optical oxygen sensor |
| CN113916849A (en) * | 2021-09-10 | 2022-01-11 | 山东省科学院海洋仪器仪表研究所 | Calibration method and calibration device for optical dissolved oxygen sensor |
| WO2023035386A1 (en) * | 2021-09-10 | 2023-03-16 | 山东省科学院海洋仪器仪表研究所 | Method and apparatus for calibrating optical dissolved oxygen sensor |
| CN116224070A (en) * | 2022-12-01 | 2023-06-06 | 国网山东省电力公司潍坊供电公司 | OCV (open circuit voltage) -SOC (system on a chip) model-based full-temperature lithium ion battery OCV (open circuit voltage) evaluation method and system |
| CN116721736A (en) * | 2023-05-29 | 2023-09-08 | 西安交通大学 | Exercise effect monitoring method, system, equipment and readable storage medium |
| CN117168684A (en) * | 2023-08-31 | 2023-12-05 | 航宇救生装备有限公司 | Oxygen partial pressure test method for pressurized oxygen supply mask |
Non-Patent Citations (3)
| Title |
|---|
| 基于新的改进粒子群算法的BP神经网络在拟合非线性函数中的应用;林宇锋;邓洪敏;史兴宇;;计算机科学;20171115(S2);第61-64页 * |
| 基于无线传感器网络的水产养殖水质监测***开发与试验;黄建清;王卫星;姜晟;孙道宗;欧国成;卢康榉;;农业工程学报;20130215(04);第191-198页 * |
| 海洋水文气象观测设备误差校准算法研究;杨俊贤;万婧;刘忠民;赵杰;杨立;朱洪海;惠力;杨英;;山东科学;20170615(03);第5-11页 * |
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