Data collector calibration method based on big data

Abstract

The invention relates to the technical field of data collector calibration, in particular to a data collector calibration method based on big data. Operation parameters and environment parameters corresponding to the data acquisition unit and standard operation parameters and standard environment parameters during verification are obtained from a database; analyzing the acquired operation parameters and environment parameters corresponding to different time points of the data acquisition unit to obtain state values, and sending the state values to a server for storage; the to-be-calibrated data collector is calibrated and checked, and a calibration result is sent to the server to be stored; through comprehensive evaluation of a plurality of parameters, the operation state evaluation accuracy and calibration efficiency of the data collector are improved, and misjudgment possibly caused by a single parameter is avoided; the parameter value is updated in real time, the calibration time is flexibly controlled, the operation state of the equipment is continuously monitored, the abnormality of the data collector can be found in time, and the risk of data inaccuracy or loss caused by the fault of the data collector is reduced.

Description

Technical Field

[0001] The present invention relates to the field of data analysis, and in particular to a data collector calibration method based on big data. Background Art

[0002] A data collector is a device or tool used to collect, record and process various types of data. It plays an important role in many fields, including scientific research, engineering, business and social surveys. In applications such as the Internet of Things and smart cities, the effectiveness of big data analysis depends on real-time and accurate data collection. Real-time data collection and transmission enable enterprises to respond quickly to changing environmental and market conditions, thereby making faster and more informed decisions. The accuracy of the data collector directly affects the reliability of the decision. Data collectors play a vital role in modern society. They are not only the core link of data analysis and decision support, but also play an indispensable role in resource optimization and security management. With the development of big data and Internet of Things technologies, the application scope of data collectors will continue to expand, and their importance will become more and more prominent.

[0003] At present, although data loggers are widely important in modern applications, the measured values ​​of data loggers may drift over time. Even after the initial calibration, long-term use may lead to a decrease in measurement accuracy. The aging of electronic components and changes in environmental conditions are the main causes of drift. In order to maintain high accuracy, the meter needs to be calibrated regularly, but frequent calibration increases operation and maintenance costs and may also lead to increased equipment downtime, so the right time for calibration is needed. Summary of the invention

[0004] To this end, the present invention provides a data collector calibration method based on big data to overcome the problems mentioned in the above background technology.

[0005] To achieve the above object, the present invention provides a data collector calibration method based on big data, comprising the following steps:

[0006] S1: Obtain the operating parameters and environmental parameters corresponding to the data collector from the database, as well as the standard operating parameters and standard environmental parameters during verification;

[0007] S2: Analyze the operating parameters and environmental parameters corresponding to different time points of the acquired data collector to obtain a state value, and send the state value to the server for storage; wherein the specific analysis steps of the state value are as follows:

[0008] Substitute the values ​​of voltage and current evaluation value Hi, temperature evaluation value Gi, humidity evaluation value Ki and electromagnetic intensity evaluation value Ui into the formula Pi=b1×Hi+b2×Gi+b3×Ki+b4×Ui to calculate the state value of the data collector, where b1, b2, b3 and b4 are the set weight factors respectively, and send the state value of the data collector to the database for storage;

[0009] A state threshold interval is set, and the state value of the data collector is compared and analyzed with the set state threshold interval. When the state value is greater than the maximum value of the set state threshold interval, it is recorded as a data collector in normal use; when the state value is within the set state threshold interval, it is recorded as a data collector that is given priority for calibration; when the state value is less than the minimum value of the set state threshold interval, it is recorded as a data collector that is given emergency treatment for calibration; and both the data collector that is given priority for calibration and the data collector that is given emergency treatment for calibration are marked as data collectors to be calibrated;

[0010] S3: Perform a calibration check on the data collector to be calibrated and send the calibration result to the server for storage.

[0011] As a preferred embodiment of the present invention, the operating parameters and environmental parameters corresponding to the data collector include: voltage value, current value, temperature value, humidity value and electromagnetic intensity value of the data collector; the standard operating parameters and standard environmental parameters during verification include: standard voltage value, standard current value, standard temperature range, standard humidity range and standard electromagnetic intensity range.

[0012] As a preferred embodiment of the present invention, the specific analysis steps of the voltage and current evaluation values ​​are as follows:

[0013] Obtain the voltage and current values ​​corresponding to different moments from the database, and record the above values ​​as Yi and Li respectively; where i = 1, 2, 3 ... I, where i = 1, 2, 3 ... I, I is a positive integer, I represents the total number of acquisition moments, and i represents the sequence number of any acquisition moment; and obtain the standard voltage and standard current values ​​in the standard operating parameters, and record the standard voltage and standard current values ​​in the standard operating parameters as BYi and BLi respectively; enter the values ​​of the voltage value Yi, the current value Li, the standard voltage value BYi and the standard current value BLi into the formula The voltage and current evaluation value Hi corresponding to the data collector is calculated, where a1 and a2 are the set weight factors respectively.

[0014] As a preferred embodiment of the present invention, the specific analysis steps of the temperature evaluation value are:

[0015] The temperature values ​​of the data collector at different times are obtained from the database, and the temperature values ​​of the data collector corresponding to different collection times are compared with the standard temperature ranges stored in the database. When the temperature of the data collector at a certain collection time is within the standard temperature range stored in the database, the collection time is recorded as the normal temperature collection time; when the temperature of the data collector at a certain collection time is not within the standard temperature range stored in the database, the collection time is recorded as the abnormal temperature collection time; the normal temperature period of the data collector is composed of adjacent normal temperature collection times, and the abnormal temperature period of the data collector is composed of adjacent abnormal temperature collection times. The total duration of the normal temperature period and the total duration of the abnormal temperature period corresponding to each collection time of the data collector are calculated; the values ​​of the total duration of the normal temperature period and the total duration of the abnormal temperature period are substituted into the formula The temperature evaluation value Gi corresponding to the data collector is calculated, where a3 and a4 are the set weight factors respectively.

[0016] As a preferred embodiment of the present invention, the specific analysis steps of the humidity evaluation value are:

[0017] The humidity values ​​of the data collector at different times are obtained from the database, and the humidity values ​​of the data collector corresponding to different collection times are compared with the standard humidity intervals stored in the database. When the humidity of the data collector at a certain collection time is within the standard humidity interval stored in the database, the collection time is recorded as the normal humidity collection time; when the temperature of the data collector at a certain collection time is not within the standard humidity interval stored in the database, the collection time is recorded as the abnormal humidity collection time; the normal temperature collection times constitute the normal humidity time point set of the data collector, and the abnormal humidity collection times constitute the abnormal humidity time point set of the data collector. The total number of time points in the normal humidity period and the total number of time points in the abnormal humidity period corresponding to each collection time of the data collector are calculated, and they are recorded as BDi and YDi respectively; the values ​​of the total number of time points in the normal temperature period BDi and the total number of time points in the abnormal temperature period YDi are substituted into the formula The humidity assessment value Ki corresponding to the data collector is calculated, where a5 and a6 are the set weight factors respectively.

[0018] As a preferred embodiment of the present invention, the specific analysis steps of the electromagnetic intensity evaluation value are as follows:

[0019] The electromagnetic intensity values ​​of the data collector at different times are obtained from the database, and the electromagnetic intensity values ​​of the data collector corresponding to different collection times are compared with the standard electromagnetic intensity intervals stored in the database. When the electromagnetic intensity value of the data collector at a certain collection time is within the standard electromagnetic intensity interval stored in the database, the collection time is recorded as a normal electromagnetic intensity moment; when the electromagnetic intensity value of the data collector at a certain collection time is not within the standard electromagnetic intensity interval stored in the database, the collection time is recorded as an abnormal electromagnetic intensity moment; the total number of normal electromagnetic intensity moments and the total number of abnormal electromagnetic intensity moments corresponding to each collection time of the statistical data collector are calculated, and they are recorded as BQi and YQi respectively; the values ​​of the total number of normal electromagnetic intensity time periods BQi and the total number of abnormal electromagnetic intensity time periods YQi are substituted into the formula The electromagnetic intensity evaluation value Ui corresponding to the data collector is calculated, where a7 and a8 are the set weight factors respectively.

[0020] As a preferred embodiment of the present invention, the data collector to be calibrated is calibrated and the result is sent to the server for storage; the specific calibration steps are as follows:

[0021] Step 1: Place the data collector to be calibrated and the calibration equipment in a standard environment and run them for more than half an hour to ensure that the data collector to be calibrated is in normal working condition;

[0022] Step 2: Check whether the appearance of the data collector to be calibrated is intact and the connection is firm, and make sure there is no physical damage or loose connection; start the data collector to be calibrated and check whether its basic functions are normal and whether it can collect and transmit data normally;

[0023] Step 3: Run the data collector to be calibrated in a specified environment to collect current operating parameter data; send the collected current data to a database for storage and compare it with the standard operating parameter value;

[0024] Step 4: Compare and analyze the collected data with the standard parameter values; compare the state value of the data collector to be calibrated at the current time point with the set state threshold range, and continue to calibrate and adjust the data collector whose value is not within the normal range; collect data again after adjustment and analyze it, and repeat this process until the error is within the standard range;

[0025] Step 5: Perform verification tests on the data logger after multiple calibrations to ensure that the logger performs consistently and accurately under different conditions; record the test results after calibration and form a complete calibration report; make a final assessment of the status of the data logger based on the verification test results. If the data logger meets the calibration requirements, it is considered qualified; otherwise, further maintenance or replacement is required; archive all data, analysis results, adjustment records and final judgment results during the calibration process, and update the calibrated parameter values ​​and status to the database;

[0026] Step 6: Summarize the calibration process and generate a formal calibration report; the calibration report includes: equipment information, calibration information, calibration steps, error analysis, adjustment records and final judgment results, and send the formal calibration report to the database for storage; after the data collector is put into use, continuously monitor its operating status to promptly detect whether the parameters of the data collector are normal and take corresponding measures.

[0027] Beneficial effects of the present invention:

[0028] 1. Through comprehensive evaluation and adaptive calibration of multiple parameters, the accuracy of data collector operation status evaluation and calibration efficiency are significantly improved, which can more comprehensively reflect the operation status of the data collector and avoid misjudgment caused by a single parameter. By analyzing the operation parameters at different times and comparing them with the standard values, this method can monitor the status of the data collector in real time. Real-time monitoring and evaluation help to discover potential problems in a timely manner and avoid inaccurate data caused by equipment failure. According to the status value of the data collector, it is divided into three categories: normal use, priority attention and emergency processing. It can effectively give priority to equipment in abnormal status and avoid further problems caused by delayed calibration. In particular, for data collectors with priority calibration and emergency calibration, calibration measures can be taken immediately to ensure the accuracy of the data and the stability of the data collector.

[0029] 2. By calibrating the data collector in a standard environment and testing it after stable operation, we ensure that the calibration process and results are highly consistent and reliable, reducing the impact of environmental factors on calibration accuracy; by comparing and analyzing the collected data with the standard parameter values ​​in detail, we can promptly discover deviations in the data collector, ensure that the equipment always operates within the standard range, improve calibration efficiency, and enable the equipment to meet standard requirements in the shortest time; by updating parameter values ​​in real time, flexibly controlling calibration time, and continuously monitoring the equipment operation status, we can promptly discover data collector anomalies and reduce the risk of inaccurate or lost data due to data collector failure. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic flow chart of the method of the present invention. DETAILED DESCRIPTION

[0031] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0032] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0033] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0034] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0035] See also Figure 1 As shown, the present invention is a data collector calibration method based on big data, comprising the following steps:

[0036] S1: Obtaining the operating parameters and environmental parameters corresponding to the data collector, as well as the standard operating parameters and standard environmental parameters during verification from the database; wherein the operating parameters and environmental parameters corresponding to the data collector include: the voltage value, current value, temperature value, humidity value and electromagnetic intensity value of the data collector; the standard operating parameters and standard environmental parameters during verification include: standard voltage value, standard current value, standard temperature range, standard humidity range and standard electromagnetic intensity range; it should be noted that the standard operating parameters and standard environmental parameters refer to the optimal operating parameters and optimal operating range set when the data collector leaves the factory;

[0037] S2: Analyze the operating parameters and environmental parameters corresponding to different time points of the acquired data collector to obtain the status value, and send the status value to the server for storage; the specific steps are as follows:

[0038] Obtain the voltage and current values ​​corresponding to different moments from the database, and record the above values ​​as Yi and Li respectively; where i = 1, 2, 3 ... I, where i = 1, 2, 3 ... I, I is a positive integer, I represents the total number of acquisition moments, and i represents the sequence number of any acquisition moment; and record the standard voltage value and standard current value in the standard operating parameters as BYi and BLi respectively; substitute the values ​​of the voltage value Yi, the current value Li, the standard voltage value BYi and the standard current value BLi into the set formula The voltage and current evaluation value Hi corresponding to the data logger is calculated, where a1 and a2 are the set weight factors respectively;

[0039] The temperature values ​​of the data collector at different times are obtained from the database, and the temperature values ​​of the data collector corresponding to different collection times are compared with the standard temperature ranges stored in the database. When the temperature of the data collector at a certain collection time is within the standard temperature range stored in the database, the collection time is recorded as the normal temperature collection time; when the temperature of the data collector at a certain collection time is not within the standard temperature range stored in the database, the collection time is recorded as the abnormal temperature collection time; the normal temperature period of the data collector is composed of adjacent normal temperature collection times, and the abnormal temperature period of the data collector is composed of adjacent abnormal temperature collection times. The total duration of the normal temperature period and the total duration of the abnormal temperature period corresponding to each collection time of the data collector are calculated, and they are recorded as BWi and YWi respectively; the total duration of the normal temperature period BWi and the total duration of the abnormal temperature period YWi are substituted into the set formula The temperature evaluation value Gi corresponding to the data collector is calculated, where a3 and a4 are the set weight factors respectively;

[0040] The humidity values ​​of the data collector at different times are obtained from the database, and the humidity values ​​of the data collector corresponding to different collection times are compared with the standard humidity intervals stored in the database. When the humidity of the data collector at a certain collection time is within the standard humidity interval stored in the database, the collection time is recorded as the normal humidity collection time; when the temperature of the data collector at a certain collection time is not within the standard humidity interval stored in the database, the collection time is recorded as the abnormal humidity collection time; the normal humidity collection time constitutes a set of normal humidity time points of the data collector, and the abnormal humidity collection time constitutes a set of abnormal humidity time points of the data collector. The total number of time points in the normal humidity period and the total number of time points in the abnormal humidity period corresponding to each collection time of the data collector are calculated, and they are recorded as BDi and YDi respectively; the values ​​of the total number of time points in the normal humidity period BDi and the total number of time points in the abnormal humidity period YDi are substituted into the set formula The humidity assessment value Ki corresponding to the data collector is calculated, where a5 and a6 are the set weight factors respectively;

[0041] The electromagnetic intensity values ​​of the data collector at different times are obtained from the database, and the electromagnetic intensity values ​​of the data collector corresponding to different collection times are compared with the standard electromagnetic intensity intervals stored in the database. When the electromagnetic intensity value of the data collector at a certain collection time is within the standard electromagnetic intensity interval stored in the database, it means that the signal transmission of the data collector is normal, and the collection time is recorded as the normal electromagnetic intensity moment; when the electromagnetic intensity value of the data collector at a certain collection time is not within the standard electromagnetic intensity interval stored in the database, it means that electromagnetic interference will cause the data transmission of the data collector to be unstable or lost, and the collection time is recorded as the abnormal electromagnetic intensity moment; the total number of normal electromagnetic intensity moments and the total number of abnormal electromagnetic intensity moments corresponding to each collection time of the statistical data collector are calculated, and they are recorded as BQi and YQi respectively; the values ​​of the total number of normal electromagnetic intensity time periods BQi and the total number of abnormal electromagnetic intensity time periods YQi are substituted into the set formula The electromagnetic intensity evaluation value Ui corresponding to the data collector is calculated, where a7 and a8 are the set weight factors respectively;

[0042] Substitute the values ​​of voltage and current evaluation value Hi, temperature evaluation value Gi, humidity evaluation value Ki and electromagnetic intensity evaluation value Ui into the set formula Pi = b1 × Hi + b2 × Gi + b3 × Ki + b4 × Ui to calculate the state value Ui of the data collector, where b1, b2, b3 and b4 are the set weight factors respectively, and send the state value of the data collector to the database for storage; set a state threshold interval, compare and analyze the state value of the data collector with the set state threshold interval, and when the state value is greater than the maximum value of the set state threshold interval, it means that the current data collector is The status is normal, which is recorded as a data collector in normal use; when the status value is within the set status threshold range, it is recorded as a data collector with priority attention and calibration; when the status value is less than the minimum value of the set status threshold range, it is recorded as a data collector with emergency treatment and calibration; and both the data collector with priority attention and the data collector with emergency treatment and calibration are marked as data collectors to be calibrated; it should be noted that the data collector is calibrated once for a fixed period of time, the data collector in normal use is calibrated according to the fixed period of time, and both the data collector with priority attention and the data collector with emergency treatment and calibration need to be calibrated in advance;

[0043] Through comprehensive evaluation and adaptive calibration of multiple parameters, the accuracy of data collector operation status evaluation and calibration efficiency are significantly improved, which can more comprehensively reflect the operation status of the data collector and avoid misjudgment caused by a single parameter. By analyzing the operation parameters at different times and comparing them with the standard values, the method can monitor the status of the data collector in real time. Real-time monitoring and evaluation help to discover potential problems in time and avoid inaccurate data caused by equipment failure. According to the status value of the data collector, it is divided into three categories: normal use, priority attention and emergency treatment. It can effectively give priority to equipment in abnormal status and avoid further problems caused by delayed calibration. In particular, for data collectors with priority calibration and emergency calibration, calibration measures can be taken immediately to ensure the accuracy of the data and the stability of the data collector.

[0044] S3: Perform a calibration check on the data collector to be calibrated and send the calibration result to the server for storage; the specific steps are as follows:

[0045] Step 1: Place the data collector to be calibrated and the calibration equipment in a standard environment and run them for more than half an hour to ensure that the data collector to be calibrated is in normal working condition; it should be noted that the data collector to be calibrated includes a data collector of priority concern and a data collector of emergency processing calibration, and the calibration is performed in the order of status value from small to large, and the data collector of priority concern has a status value greater than the emergency processing calibration data;

[0046] Step 2: Check whether the appearance of the data collector to be calibrated is intact and the connection is firm, and make sure there is no physical damage or loose connection; start the data collector to be calibrated and check whether its basic functions are normal and whether it can collect and transmit data normally;

[0047] Step 3: Run the data collector to be calibrated in a specified environment to collect current operating parameter data; send the collected current data to a database for storage and compare it with the standard operating parameter value;

[0048] Step 4: Compare and analyze the collected data with the standard parameter values; compare the state value of the data collector to be calibrated at the current time point with the set state threshold range, and continue to calibrate and adjust the data collector whose value is not within the normal range; collect data again after adjustment and analyze it, and repeat this process until the error is within the standard range;

[0049] Step 5: Perform verification tests on the data logger after multiple calibrations to ensure that the logger performs consistently and accurately under different conditions; record the test results after calibration and form a complete calibration report; make a final assessment of the status of the data logger based on the verification test results. If the data logger meets the calibration requirements, it is considered qualified; otherwise, further maintenance or replacement is required; archive all data, analysis results, adjustment records and final judgment results during the calibration process, and update the calibrated parameter values ​​and status to the database;

[0050] Step 6: Summarize the calibration process and generate a formal calibration report; the calibration report includes: equipment information, calibration information, calibration steps, error analysis, adjustment records and final judgment results, and send the formal calibration report to the database for storage; after the data collector is put into use, continuously monitor its operating status to promptly find out whether the parameters of the data collector are normal and take corresponding measures;

[0051] By calibrating the data collector in a standard environment and testing it after stable operation, we ensure that the calibration process and results are highly consistent and reliable, reducing the impact of environmental factors on calibration accuracy; by comparing and analyzing the collected data with the standard parameter values ​​in detail, we can promptly discover deviations in the data collector, ensure that the equipment always operates within the standard range, improve calibration efficiency, and enable the equipment to meet standard requirements in the shortest time; by updating parameter values ​​in real time, flexibly controlling calibration time, and continuously monitoring the equipment operation status, we can promptly discover data collector anomalies and reduce the risk of inaccurate data or loss due to data collector failure.

[0052] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0053] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data collector calibration method based on big data, characterized in that: The following steps are involved: S1: Obtain the operating parameters and environmental parameters corresponding to the data collector from the database, as well as the standard operating parameters and standard environmental parameters during verification; S2: Analyze the operating parameters and environmental parameters corresponding to different time points of the data collector to obtain the status value, and send the status value to the server for storage; the specific analysis steps of the status value are as follows: Normalizing the values ​​of the voltage and current evaluation values, the temperature evaluation value, the humidity evaluation value, and the electromagnetic intensity evaluation value to obtain the state value of the data collector; A state threshold interval is set, and the state value of the data collector is compared and analyzed with the set state threshold interval. When the state value is greater than the maximum value of the set state threshold interval, it is recorded as a data collector in normal use; when the state value is within the set state threshold interval, it is recorded as a data collector that is given priority for calibration; when the state value is less than the minimum value of the set state threshold interval, it is recorded as a data collector that is given emergency treatment for calibration; and both the data collector that is given priority for calibration and the data collector that is given emergency treatment for calibration are marked as data collectors to be calibrated; S3: Perform a calibration check on the data collector to be calibrated and send the calibration result to the server for storage.

2. The data collector calibration method based on big data according to claim 1, characterized in that: The operating parameters and environmental parameters corresponding to the data logger include: voltage value, current value, temperature value, humidity value and electromagnetic intensity value of the data logger; the standard operating parameters and standard environmental parameters during calibration include: standard voltage value, standard current value, standard temperature range, standard humidity range and standard electromagnetic intensity range.

3. The data collector calibration method based on big data according to claim 1, characterized in that: The specific analysis steps of the voltage and current evaluation values ​​are as follows: The voltage and current values ​​corresponding to different times are obtained from the database; and the standard voltage and standard current values ​​in the standard operating parameters are obtained; the voltage, current, standard voltage and standard current values ​​are normalized to obtain the voltage and current evaluation values ​​corresponding to the data collector.

4. The data collector calibration method based on big data according to claim 1, characterized in that: The specific analysis steps of the temperature evaluation value are: Obtain the temperature values ​​of the data collector at different times from the database, compare the temperature values ​​of the data collector corresponding to different collection times with the standard temperature intervals stored in the database, and when the temperature of the data collector at a certain collection time is within the standard temperature interval stored in the database, record the collection time as a normal temperature collection time; when the temperature of the data collector at a certain collection time is not within the standard temperature interval stored in the database, record the collection time as an abnormal temperature collection time; the normal temperature period of the data collector is composed of adjacent normal temperature collection times, and the abnormal temperature period of the data collector is composed of adjacent abnormal temperature collection times, and the total duration of the normal temperature period and the total duration of the abnormal temperature period corresponding to each collection time of the data collector are calculated; The total duration of the normal temperature period and the total duration of the abnormal temperature period are normalized to obtain the temperature evaluation value corresponding to the data collector.

5. The data collector calibration method based on big data according to claim 1, characterized in that: The specific analysis steps for humidity assessment value are: The humidity values ​​of the data collector at different times are obtained from the database, and the humidity values ​​of the data collector corresponding to different collection times are compared with the standard humidity intervals stored in the database. When the humidity of the data collector at a certain collection time is within the standard humidity interval stored in the database, the collection time is recorded as the normal humidity collection time; when the temperature of the data collector at a certain collection time is not within the standard humidity interval stored in the database, the collection time is recorded as the abnormal humidity collection time; the normal humidity collection times constitute a set of normal humidity time points of the data collector, and the abnormal humidity collection times constitute a set of abnormal humidity time points of the data collector, and the total number of time points of the normal humidity time period and the total number of time points of the abnormal humidity time period corresponding to each collection time of the data collector are calculated; The total number of time points in the normal humidity period and the total number of time points in the abnormal humidity period are normalized to obtain the humidity assessment value corresponding to the data collector.

6. The data collector calibration method based on big data according to claim 1, characterized in that: The specific analysis steps of the electromagnetic intensity assessment value are as follows: The electromagnetic intensity values ​​of the data collector at different times are obtained from the database, and the electromagnetic intensity values ​​of the data collector corresponding to different collection times are compared with the standard electromagnetic intensity intervals stored in the database. When the electromagnetic intensity value of the data collector at a certain collection time is within the standard electromagnetic intensity interval stored in the database, the collection time is recorded as a normal electromagnetic intensity moment; when the electromagnetic intensity value of the data collector at a certain collection time is not within the standard electromagnetic intensity interval stored in the database, the collection time is recorded as an abnormal electromagnetic intensity moment; the total number of normal electromagnetic intensity moments and the total number of abnormal electromagnetic intensity moments corresponding to each collection time of the data collector are counted; the total number of normal electromagnetic intensity time periods and the total number of abnormal electromagnetic intensity time periods are normalized to obtain the electromagnetic intensity evaluation value corresponding to the data collector.

7. The data collector calibration method based on big data according to claim 1, characterized in that: Perform calibration check on the data collector to be calibrated and send the results to the server for storage; the specific calibration steps are as follows: Step 1: Place the data collector to be calibrated and the calibration equipment in a standard environment and run them for more than half an hour to ensure that the data collector to be calibrated is in normal working condition; Step 2: Check the appearance of the data logger to be calibrated to see if it is intact and the connection is secure, ensuring there is no physical damage or loose connection; Start the data collector to be calibrated and check whether its basic functions are normal and whether it can collect and transmit data normally; Step 3: Run the data collector to be calibrated in a specified environment to collect current operating parameter data; send the collected current data to a database for storage and compare it with the standard operating parameter value; Step 4: Compare and analyze the collected data with the standard parameter values; compare the state value of the data collector to be calibrated at the current time point with the set state threshold range, and continue to calibrate and adjust the data collector whose value is not within the normal range; collect data again after adjustment and analyze it, and repeat this process until the error is within the standard range; Step 5: Perform verification tests on the data logger after multiple calibrations to ensure that the logger performs consistently and accurately under different conditions; record the test results after calibration and form a complete calibration report; make a final assessment of the status of the data logger based on the verification test results. If the data logger meets the calibration requirements, it is considered qualified; otherwise, further maintenance or replacement is required; archive all data, analysis results, adjustment records and final judgment results during the calibration process, and update the calibrated parameter values ​​and status to the database; Step 6: Summarize the calibration process and generate a formal calibration report; The calibration report includes: equipment information, calibration information, calibration steps, error analysis, adjustment records and final judgment results, and the formal calibration report is sent to the database for storage; After the data logger is put into use, its operating status is continuously monitored.

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