CN110672143A - Sensor calibration method - Google Patents
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- CN110672143A CN110672143A CN201911079392.4A CN201911079392A CN110672143A CN 110672143 A CN110672143 A CN 110672143A CN 201911079392 A CN201911079392 A CN 201911079392A CN 110672143 A CN110672143 A CN 110672143A
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Abstract
The invention provides a sensor calibration method, and relates to the technical field of sensors. The sensor calibration method comprises the following steps: s1, establishing a connecting channel between a sensor and a parameter acquisition system, and acquiring working parameters of the sensor; s2, the central processing unit analyzes the working parameters of the sensor, matches the error characteristic values and establishes error-related data reports; s3, generating a central processing unit error calibration system, establishing an error calibration system and a sensor transmission channel, and correcting working parameters of the sensor in real time; s4, generating a calibration data reference table, uploading the calibration data reference table to a cloud server, and establishing a bidirectional transmission channel between the cloud server and a central processing unit; and S5, generating a parameter calibration model, downloading a cloud data import model, and training a sensor calibration intelligent algorithm. The calibration method of the sensor is simple, a large amount of time and labor are not needed, the calibration efficiency of the sensor is improved, and meanwhile the calibration cost of the sensor is reduced.
Description
Technical Field
The invention relates to the technical field of sensors, in particular to a sensor calibration method.
Background
The sensor is a detection device which can sense the measured information and convert the sensed information into electric signals or other information in required forms to be output according to a certain rule so as to meet the requirements of transmission, processing, storage, display, recording, control and the like of the information.
The sensor is widely applied to various fields of social development and human life, such as industrial automation, agricultural modernization, aerospace technology, military engineering, robotics, resource development, ocean exploration, environment monitoring, security, medical diagnosis, transportation, household appliances and the like, and the accuracy of data input by the sensor in a working state is very important, so that the sensor needs to be calibrated after production and manufacture and in a using process.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a sensor calibration method, which solves the problems that the existing sensor calibration mode is troublesome, a large amount of time and labor are needed, the calibration efficiency of the sensor is reduced, and the calibration cost of the sensor is also improved.
(II) technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme: a sensor calibration method, comprising the steps of:
s1, establishing a connecting channel between a sensor and a parameter acquisition system, and acquiring working parameters of the sensor;
s2, the central processing unit analyzes the working parameters of the sensor, matches the error characteristic values and establishes error-related data reports;
s3, generating a central processing unit error calibration system, establishing an error calibration system and a sensor transmission channel, and correcting working parameters of the sensor in real time;
s4, generating a calibration data reference table, uploading the calibration data reference table to a cloud server, and establishing a bidirectional transmission channel between the cloud server and a central processing unit;
and S5, generating a parameter calibration model, downloading a cloud data import model, and training a sensor calibration intelligent algorithm.
Preferably, a connecting channel between the sensor and the parameter acquisition system is established in the step 1, and working parameters of the sensor are acquired, which specifically comprises the following steps:
1) electrically connecting the sensor with the parameter acquisition system through a wire, enabling the sensor to be in a working state, and checking whether the working state of the sensor is stable;
2) the parameter acquisition system acquires various performance parameters of the sensor in a stable working state, optimizes and integrates all acquired data, and then sends the data to the central processing unit.
Preferably, the cpu in step 2 analyzes the sensor operating parameters, matches the error characteristic values, and establishes an error-related data report, specifically as follows:
1) after receiving the performance parameters of the sensors, the central processing unit immediately matches the parameters of the sensors with the same type under the normal working state, and then analyzes the normal parameter range and the acquired parameter range to find out the abnormal characteristic parameters;
2) listing a comparison report between the normal characteristic parameters and the abnormal characteristic parameters, calculating the calibration range of the sensor, and obtaining the relative error value W of the parameters1According to the formula △ W ═ W1-W2To obtain an absolute error value △ W, where W2To allow for error values.
Preferably, the step 3 generates a central processing unit error calibration system, establishes an error calibration system and a sensor transmission channel, and corrects the sensor working parameters in real time, specifically as follows:
1) an error calibration system is additionally arranged in a central processing unit, and the central processing unit sends the calculated sensor calibration range to the error calibration system;
2) and establishing an error calibration system through a lead to be electrically connected with the sensor, adjusting the existing abnormal characteristic parameters by the error calibration system according to the calibration range value, and calibrating the absolute error value △ W of the sensor.
Preferably, the calibration data reference table generated in step 4 is uploaded to a cloud server, and a bidirectional transmission channel between the cloud server and a central processing unit is established, specifically as follows:
1) establishing a calibration data reference table according to an absolute error value △ W calibrated by an error calibration system, and then uploading the reference table to a cloud server;
2) a bidirectional transmission channel between the cloud server and the central processing unit is established in a signal transmission mode, and data uploading and downloading are achieved between the cloud server and the central processing unit.
Preferably, the parameter calibration model is generated in the step 5, the cloud data import model is downloaded, and the sensor calibration intelligent algorithm is trained as follows:
1) generating a parameter calibration model according to a sensor calibration process, wherein the parameter calibration model can automatically download a calibration data reference table and import the calibration data reference table into the model;
2) the parameter calibration model carries out deep learning on the data reference table, summarizes the calibration process of the abnormal characteristic parameters, thereby generating a sensor calibration intelligent algorithm and testing the intelligent algorithm.
(III) advantageous effects
The invention provides a sensor calibration method. The method has the following beneficial effects:
according to the sensor calibration method, the working parameters of the sensor are analyzed through the central processing unit, the error characteristic values are matched, then the central processing unit error calibration system is generated, the working parameters of the sensor are corrected in real time, the parameter calibration model is generated at the same time, the intelligent algorithm for calibrating the sensor is trained, so that the sensor can be calibrated only by leading the working parameters of the sensor into the intelligent algorithm when the sensor is calibrated in the future, the sensor calibration mode is simple, a large amount of time and manpower are not needed, the calibration efficiency of the sensor is improved, and meanwhile, the calibration cost of the sensor is also reduced.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
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 only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
as shown in fig. 1, an embodiment of the present invention provides a sensor calibration method, including the following steps:
s1, establishing a connecting channel between a sensor and a parameter acquisition system, and acquiring working parameters of the sensor;
s2, the central processing unit analyzes the working parameters of the sensor, matches the error characteristic values and establishes error-related data reports;
s3, generating a central processing unit error calibration system, establishing an error calibration system and a sensor transmission channel, and correcting working parameters of the sensor in real time;
s4, generating a calibration data reference table, uploading the calibration data reference table to a cloud server, and establishing a bidirectional transmission channel between the cloud server and a central processing unit;
and S5, generating a parameter calibration model, downloading a cloud data import model, and training a sensor calibration intelligent algorithm.
The sensor working parameters are analyzed through the central processing unit, error characteristic values are matched, then a central processing unit error calibration system is generated, the sensor working parameters are corrected in real time, a parameter calibration model is generated simultaneously, an intelligent algorithm for sensor calibration is trained, the sensor can be calibrated only by leading the sensor working parameters into the intelligent algorithm when the sensor is calibrated in the future, the sensor calibration mode is simple, a large amount of time and manpower are not needed, the calibration efficiency of the sensor is improved, and meanwhile, the sensor calibration cost is also reduced.
Wherein, a connecting channel between the sensor and the parameter acquisition system is established in the step 1, and the working parameters of the sensor are acquired, which comprises the following steps:
1) electrically connecting the sensor with the parameter acquisition system through a wire, enabling the sensor to be in a working state, and checking whether the working state of the sensor is stable;
2) the parameter acquisition system acquires various performance parameters of the sensor in a stable working state, optimizes and integrates all acquired data, and then sends the data to the central processing unit.
The central processing unit in step 2 analyzes the working parameters of the sensor, matches the error characteristic values, and establishes an error-related data report, which specifically comprises the following steps:
1) after receiving the performance parameters of the sensors, the central processing unit immediately matches the parameters of the sensors with the same type under the normal working state, and then analyzes the normal parameter range and the acquired parameter range to find out the abnormal characteristic parameters;
2) listing a comparison report between the normal characteristic parameters and the abnormal characteristic parameters, calculating the calibration range of the sensor, and obtaining the relative error value W of the parameters1According to the formula △ W ═ W1-W2To obtain an absolute error value △ W, where W2To allow for error values.
Generating a central processing unit error calibration system in the step 3, establishing an error calibration system and a sensor transmission channel, and correcting working parameters of the sensor in real time, wherein the method specifically comprises the following steps:
1) an error calibration system is additionally arranged in a central processing unit, and the central processing unit sends the calculated sensor calibration range to the error calibration system;
2) and establishing an error calibration system through a lead to be electrically connected with the sensor, adjusting the existing abnormal characteristic parameters by the error calibration system according to the calibration range value, and calibrating the absolute error value △ W of the sensor.
Wherein, the calibration data reference table is generated in the step 4, the calibration data reference table is uploaded to a cloud server, and a bidirectional transmission channel between the cloud server and a central processing unit is established, which specifically comprises the following steps:
1) establishing a calibration data reference table according to an absolute error value △ W calibrated by an error calibration system, and then uploading the reference table to a cloud server;
2) a bidirectional transmission channel between the cloud server and the central processing unit is established in a signal transmission mode, and data uploading and downloading are achieved between the cloud server and the central processing unit.
Wherein generate parameter calibration model in step 5, download the leading-in model of high in the clouds data, train sensor calibration intelligent algorithm, specifically as follows:
1) generating a parameter calibration model according to a sensor calibration process, wherein the parameter calibration model can automatically download a calibration data reference table and import the calibration data reference table into the model;
2) the parameter calibration model carries out deep learning on the data reference table, summarizes the calibration process of the abnormal characteristic parameters, thereby generating a sensor calibration intelligent algorithm and testing the intelligent algorithm.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. A method of calibrating a sensor, comprising: the method comprises the following steps:
s1, establishing a connecting channel between a sensor and a parameter acquisition system, and acquiring working parameters of the sensor;
s2, the central processing unit analyzes the working parameters of the sensor, matches the error characteristic values and establishes error-related data reports;
s3, generating a central processing unit error calibration system, establishing an error calibration system and a sensor transmission channel, and correcting working parameters of the sensor in real time;
s4, generating a calibration data reference table, uploading the calibration data reference table to a cloud server, and establishing a bidirectional transmission channel between the cloud server and a central processing unit;
and S5, generating a parameter calibration model, downloading a cloud data import model, and training a sensor calibration intelligent algorithm.
2. A method of calibrating a sensor according to claim 1, wherein: in the step 1, a connecting channel between the sensor and the parameter acquisition system is established to acquire working parameters of the sensor, and the method specifically comprises the following steps:
1) electrically connecting the sensor with the parameter acquisition system through a wire, enabling the sensor to be in a working state, and checking whether the working state of the sensor is stable;
2) the parameter acquisition system acquires various performance parameters of the sensor in a stable working state, optimizes and integrates all acquired data, and then sends the data to the central processing unit.
3. A method of calibrating a sensor according to claim 1, wherein: the central processing unit in the step 2 analyzes the working parameters of the sensor, matches the error characteristic value, and establishes an error-related data report, which specifically comprises the following steps:
1) after receiving the performance parameters of the sensors, the central processing unit immediately matches the parameters of the sensors with the same type under the normal working state, and then analyzes the normal parameter range and the acquired parameter range to find out the abnormal characteristic parameters;
2) listing a comparison report between the normal characteristic parameters and the abnormal characteristic parameters, calculating the calibration range of the sensor, and obtaining the relative error value W of the parameters1According to the formula △ W ═ W1-W2To obtain an absolute error value △ W, where W2To allow for error values.
4. A method of calibrating a sensor according to claim 1, wherein: generating a central processing unit error calibration system in the step 3, establishing an error calibration system and a sensor transmission channel, and correcting working parameters of the sensor in real time, wherein the method specifically comprises the following steps:
1) an error calibration system is additionally arranged in a central processing unit, and the central processing unit sends the calculated sensor calibration range to the error calibration system;
2) and establishing an error calibration system through a lead to be electrically connected with the sensor, adjusting the existing abnormal characteristic parameters by the error calibration system according to the calibration range value, and calibrating the absolute error value △ W of the sensor.
5. A method of calibrating a sensor according to claim 1, wherein: generating a calibration data reference table in the step 4, uploading the calibration data reference table to a cloud server, and establishing a bidirectional transmission channel between the cloud server and a central processing unit, wherein the method specifically comprises the following steps:
1) establishing a calibration data reference table according to an absolute error value △ W calibrated by an error calibration system, and then uploading the reference table to a cloud server;
2) a bidirectional transmission channel between the cloud server and the central processing unit is established in a signal transmission mode, and data uploading and downloading are achieved between the cloud server and the central processing unit.
6. A method of calibrating a sensor according to claim 1, wherein: generating a parameter calibration model in the step 5, downloading a cloud data import model, and training a sensor calibration intelligent algorithm, wherein the method specifically comprises the following steps:
1) generating a parameter calibration model according to a sensor calibration process, wherein the parameter calibration model can automatically download a calibration data reference table and import the calibration data reference table into the model;
2) the parameter calibration model carries out deep learning on the data reference table, summarizes the calibration process of the abnormal characteristic parameters, thereby generating a sensor calibration intelligent algorithm and testing the intelligent algorithm.
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| US11205234B1 (en) | 2020-06-30 | 2021-12-21 | Quanta Computer Inc. | Farm-sensing system and calibration method of sensor data thereof |
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Application publication date: 20200110 |