Data recording method and system for temperature sensor

Abstract

The invention relates to the technical field of temperature sensors, and discloses a data recording method and system for a temperature sensor, and the system comprises an acquisition unit; a transfer unit; the judging unit is used for comparing the first difference value with a preset first difference value threshold value and judging the abnormal level of the temperature data according to a comparison result; the processing unit is used for adjusting the abnormal level of the temperature data according to the relation between the second difference value and a preset second difference value threshold value; and the storing and recording unit is used for storing and recording the adjusted temperature data according to the abnormal level. The data recording method and system for the temperature sensor provided by the invention have high flexibility and accuracy, and ensure the effectiveness and reliability of the temperature recording system through comprehensive analysis and refined processing of the temperature data.

Description

Technical Field

[0001] The present invention relates to the technical field of temperature sensors, and in particular to a data recording method and system for a temperature sensor. Background Art

[0002] With the advancement of science and technology and the improvement of industrial automation, temperature sensors are increasingly used in various fields, from temperature monitoring of industrial production lines to room temperature adjustment of smart homes, all of which rely on accurate temperature sensor measurements. However, in actual applications, due to environmental factors, equipment aging, or human error, the data of temperature sensors may be abnormal during recording, reducing the effectiveness and reliability of the entire data recording system.

[0003] Therefore, it is necessary to design a data recording method and system for a temperature sensor to solve the problems existing in the current technology. Summary of the invention

[0004] In view of this, the present invention proposes a data recording method and system for a temperature sensor, aiming to solve the problem in the current technology that due to various reasons such as environmental factors, equipment aging or human operating errors, the data of the temperature sensor will produce anomalies during recording, thereby reducing the effectiveness and reliability of the entire data recording system.

[0005] In one aspect, the present invention provides a data recording system for a temperature sensor, comprising:

[0006] A collection unit, used for collecting temperature data from the temperature sensor in real time and storing the temperature data in a storage repository;

[0007] a transfer unit, used to screen the temperature data in the storage repository and establish a normal temperature data set and an abnormal temperature data set according to the screening result, and the transfer unit is also used to send the normal temperature data set and the abnormal temperature data set to the judgment unit;

[0008] a judgment unit, configured to receive the normal temperature data set and the abnormal temperature data set, and calculate an average temperature value and a maximum temperature fluctuation value of the temperature data in the normal temperature data set, and further configured to calculate a first difference between the temperature data in the abnormal temperature data set and the average temperature value, compare the first difference with a preset first difference threshold, and judge the abnormal level of the temperature data according to the comparison result;

[0009] a processing unit, configured to calculate, after determining the abnormal level of the temperature data, a temperature fluctuation value between the temperature data in the abnormal temperature data set and the corresponding temperature data at a historical moment, and calculate a second difference between the temperature fluctuation value and the maximum temperature fluctuation value, and then adjust the abnormal level of the temperature data according to a relationship between the second difference and a preset second difference threshold;

[0010] The storage and recording unit stores and records the adjusted temperature data according to the abnormality level.

[0011] Furthermore, the transfer unit is used to screen the temperature data in the storage repository and establish a normal temperature data set and an abnormal temperature data set according to the screening result, including:

[0012] Dividing the temperature data in the storage repository according to time periods;

[0013] Calculate the variance of all temperature data within the same time period, compare the variance with a preset variance threshold, and make a judgment based on the comparison result;

[0014] When the variance is less than or equal to the variance threshold, all temperature data within the same time period are temporarily added to the normal temperature data set;

[0015] When the variance is greater than the variance threshold, all temperature data within the same time period are added to the abnormal temperature data set.

[0016] Further, when the variance is less than or equal to the variance threshold, all temperature data in the same time period are temporarily added to the normal temperature data set, and further comprising:

[0017] A temperature standard value is set in advance, and then all temperature data within the same time period are subtracted from the temperature standard value one by one to obtain a third difference value, and the third difference value is compared with a preset third difference threshold value, and based on the comparison result, it is determined whether the temperature data is transferred to the abnormal temperature data set.

[0018] Further, comparing the third difference with a preset third difference threshold, and judging whether to transfer the temperature data into the abnormal temperature data set according to the comparison result, includes:

[0019] When the third difference is less than or equal to the third difference threshold, retaining the temperature data to the normal temperature data set;

[0020] When the third difference is greater than the third difference threshold, the temperature data is transferred to the abnormal temperature data set.

[0021] Further, the judgment unit is further configured to calculate a first difference between the temperature data in the abnormal temperature data set and the average temperature value, compare the difference with a preset first difference threshold, and judge the abnormal level of the temperature data according to the comparison result, including:

[0022] The first difference threshold comprises a first minimum difference threshold and a first maximum difference threshold;

[0023] When the first difference is less than or equal to the first minimum difference threshold, determining that the abnormal level of the temperature data is the first level;

[0024] When the first difference is greater than the first lowest difference threshold and less than or equal to the first highest difference threshold, determining that the abnormal level of the temperature data is the second level;

[0025] When the first difference is greater than the first highest difference threshold, determining that the abnormal level of the temperature data is the third level;

[0026] The first level is smaller than the second level, and the second level is smaller than the third level.

[0027] Further, the processing unit is used to calculate the temperature fluctuation value of the temperature data in the abnormal temperature data set and the corresponding temperature data at the historical moment after determining the abnormal level of the temperature data, and calculate the second difference between the temperature fluctuation value and the maximum temperature fluctuation value, including:

[0028] The historical temperature data is the temperature data at the corresponding historical moment in the same time period, and the maximum temperature fluctuation value is the difference between the maximum temperature data and the minimum temperature data in the normal temperature data set.

[0029] Further, when adjusting the abnormal level of the temperature data according to the relationship between the second difference and a preset second difference threshold, the method includes:

[0030] The second difference threshold comprises a second lowest difference threshold and a second highest difference threshold;

[0031] When the second difference is less than or equal to the second lowest difference threshold, lowering the abnormal level of the temperature data;

[0032] When the second difference is greater than the second lowest difference threshold and less than or equal to the second highest difference threshold, maintaining the abnormal level of the current temperature data unchanged;

[0033] When the second difference is greater than the second highest difference threshold, the abnormal level of the temperature data is increased.

[0034] Further, when the processing unit determines to lower the abnormal level of the temperature data, it includes:

[0035] When the second difference is less than or equal to the second lowest difference threshold, subtract the second lowest difference threshold from the second difference to obtain a fourth difference;

[0036] comparing the fourth difference with a preset fourth difference threshold, and adjusting the abnormal level of the temperature data according to the comparison result;

[0037] When the fourth difference is less than or equal to the fourth difference threshold, it is determined that the abnormal level of the temperature data is lowered by two levels;

[0038] When the fourth difference is greater than the fourth difference threshold, it is determined that the abnormal level of the temperature data is lowered by one level;

[0039] The abnormal level of the temperature data is lowered to the first level.

[0040] Further, when the processing unit determines to increase the abnormal level of the temperature data, it includes:

[0041] When the second difference is greater than the second highest difference threshold, subtracting the second highest difference threshold from the second difference to obtain a fifth difference;

[0042] comparing the fifth difference with a preset fifth difference threshold, and adjusting the abnormal level of the temperature data according to the comparison result;

[0043] When the fifth difference is less than or equal to the fifth difference threshold, it is determined that the abnormal level of the temperature data is increased by one level;

[0044] When the fifth difference is greater than the fifth difference threshold, it is determined that the abnormal level of the temperature data is increased by two levels;

[0045] The highest abnormal level of the temperature data is adjusted to the third level.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows: in the data recording system for temperature sensors provided by the invention, the acquisition unit is used to acquire temperature data in real time, which can ensure that the system can quickly capture every subtle fluctuation of temperature changes, thereby providing a solid foundation for subsequent data analysis and processing; the transfer unit is a bridge for data processing, and by preliminarily screening the collected temperature data, the transfer unit can quickly distinguish between normal and abnormal temperature data, which not only reduces the workload of subsequent processing units, but also improves the response speed and accuracy of the entire system; the judgment unit is used to conduct in-depth analysis and judgment of temperature data according to preset rules and thresholds, and by calculating the average value and fluctuation range of the normal temperature data set, the judgment unit can establish a baseline for evaluating whether the subsequent temperature data is normal or not; for abnormal temperature data, the judgment unit calculates its difference from the baseline The difference is compared with the set threshold to determine its abnormal level. This quantitative analysis method makes the abnormal judgment of temperature data more objective and accurate; the processing unit is the key to fine-tuning the abnormal level of temperature data. After determining the preliminary abnormal level, the processing unit will further analyze the temperature fluctuation in the abnormal temperature data and compare it with the fluctuation range of normal temperature data. By calculating the difference between the two and combining with the preset threshold, the processing unit can divide the abnormal level more carefully and accurately. This adjustment mechanism enables the system to better adapt to the temperature change characteristics in different scenarios and improve the accuracy and reliability of data recording; the storage and recording unit classifies and stores the adjusted temperature data according to the abnormal level. This classified storage method is not only convenient for subsequent data query and analysis, but also can provide valuable data support for system optimization and improvement.

[0047] In another aspect, the present invention further provides a data recording method for a temperature sensor, comprising the following steps:

[0048] S100: collecting temperature data from a temperature sensor in real time and storing the temperature data in a storage repository;

[0049] S200: screening the temperature data in the storage repository, and establishing a normal temperature data set and an abnormal temperature data set according to the screening results;

[0050] S300: calculating an average temperature value and a maximum temperature fluctuation value of the temperature data in the normal temperature data set, calculating a first difference between the temperature data in the abnormal temperature data set and the average temperature value, comparing the first difference with a preset first difference threshold, and determining an abnormal level of the temperature data according to the comparison result;

[0051] S400: after determining the abnormal level of the temperature data, calculating the temperature fluctuation value of the temperature data in the abnormal temperature data set and the corresponding temperature data at the historical moment, and calculating the second difference between the temperature fluctuation value and the maximum temperature fluctuation value, and then adjusting the abnormal level of the temperature data according to the relationship between the second difference and a preset second difference threshold;

[0052] S500: storing and recording the adjusted temperature data according to the abnormality level.

[0053] It is understandable that the above-mentioned data recording method and system for temperature sensor have the same beneficial effects, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0055] Figure 1 A structural block diagram of a data recording system for a temperature sensor provided by an embodiment of the present invention;

[0056] Figure 2 The present invention provides a flow chart of a method for recording data of a temperature sensor according to an embodiment of the present invention. DETAILED DESCRIPTION

[0057] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0058] See also Figure 1 As shown, in some embodiments of the present application, this embodiment provides a data recording system for a temperature sensor, including:

[0059] A collection unit, used for collecting temperature data from the temperature sensor in real time and storing the temperature data in a storage repository;

[0060] a transfer unit, used to screen the temperature data in the storage repository and establish a normal temperature data set and an abnormal temperature data set according to the screening result, and the transfer unit is also used to send the normal temperature data set and the abnormal temperature data set to the judgment unit;

[0061] a judgment unit, configured to receive the normal temperature data set and the abnormal temperature data set, and calculate an average temperature value and a maximum temperature fluctuation value of the temperature data in the normal temperature data set, and further configured to calculate a first difference between the temperature data in the abnormal temperature data set and the average temperature value, compare the first difference with a preset first difference threshold, and judge the abnormal level of the temperature data according to the comparison result;

[0062] a processing unit, configured to calculate, after determining the abnormal level of the temperature data, a temperature fluctuation value between the temperature data in the abnormal temperature data set and the corresponding temperature data at a historical moment, and calculate a second difference between the temperature fluctuation value and the maximum temperature fluctuation value, and then adjust the abnormal level of the temperature data according to a relationship between the second difference and a preset second difference threshold;

[0063] The storage and recording unit stores and records the adjusted temperature data according to the abnormality level.

[0064] It can be seen that in the data recording system for the temperature sensor provided in this embodiment, the acquisition unit is used to collect temperature data in real time, which can ensure that the system can quickly capture every subtle fluctuation of temperature changes, thereby providing a solid foundation for subsequent data analysis and processing; the transfer unit is a bridge for data processing. By preliminarily screening the collected temperature data, the transfer unit can quickly distinguish between normal and abnormal temperature data, which not only reduces the workload of the subsequent processing unit, but also improves the response speed and accuracy of the entire system; the judgment unit is used to conduct in-depth analysis and judgment of the temperature data according to preset rules and thresholds. By calculating the average value and fluctuation range of the normal temperature data set, the judgment unit can establish a baseline for evaluating whether the subsequent temperature data is normal or not; for abnormal temperature data, the judgment unit calculates the difference between it and the baseline, and The abnormal level is determined by comparing it with the set threshold. This quantitative analysis method makes the abnormal judgment of temperature data more objective and accurate. The processing unit is the key to fine-tuning the abnormal level of temperature data. After determining the preliminary abnormal level, the processing unit will further analyze the temperature fluctuation in the abnormal temperature data and compare it with the fluctuation range of normal temperature data. By calculating the difference between the two and combining it with the preset threshold, the processing unit can make a more detailed and accurate division of the abnormal level. This adjustment mechanism enables the system to better adapt to the temperature change characteristics in different scenarios and improve the accuracy and reliability of data recording. The storage and recording unit classifies and stores the adjusted temperature data according to the abnormal level. This classified storage method not only facilitates subsequent data query and analysis, but also provides valuable data support for system optimization and improvement.

[0065] Specifically, the transfer unit is used to screen the temperature data in the storage repository and establish a normal temperature data set and an abnormal temperature data set according to the screening result, including:

[0066] Dividing the temperature data in the storage repository according to time periods;

[0067] Calculate the variance of all temperature data within the same time period, compare the variance with a preset variance threshold, and make a judgment based on the comparison result;

[0068] When the variance is less than or equal to the variance threshold, all temperature data within the same time period are temporarily added to the normal temperature data set;

[0069] When the variance is greater than the variance threshold, all temperature data within the same time period are added to the abnormal temperature data set.

[0070] Specifically, when the variance is less than or equal to the variance threshold, all temperature data in the same time period are temporarily added to the normal temperature data set, and the method further includes:

[0071] A temperature standard value is set in advance, and then all temperature data within the same time period are subtracted from the temperature standard value one by one to obtain a third difference value, and the third difference value is compared with a preset third difference threshold value, and based on the comparison result, it is determined whether the temperature data is transferred to the abnormal temperature data set.

[0072] Specifically, comparing the third difference with a preset third difference threshold, and judging whether to transfer the temperature data into the abnormal temperature data set according to the comparison result, includes:

[0073] When the third difference is less than or equal to the third difference threshold, retaining the temperature data to the normal temperature data set;

[0074] When the third difference is greater than the third difference threshold, the temperature data is transferred to the abnormal temperature data set.

[0075] It can be seen that in order to further enhance the flexibility and accuracy of the temperature sensor data recording system in this embodiment, the screening mechanism of the transfer unit is refined and optimized; in addition to the basic screening based on the variance of the temperature data within the time period, the temperature standard value is introduced to achieve more refined data classification; after all the temperature data within a certain time period are temporarily classified into the normal temperature data set, the system will not immediately stop further evaluation of the data; on the contrary, it will compare these data with the preset temperature standard value, which can be an average value, a median based on the statistical analysis of historical data, or a fixed value set according to a specific application scenario; by calculating the difference between each temperature data and the standard value (i.e., the third difference), the normality of these data can be more accurately evaluated; if the third difference between a certain temperature data and the standard value exceeds the preset third difference threshold, even if it was originally classified as normal temperature data, the system will re-evaluate its attribution and may transfer it from the normal temperature data set to the abnormal temperature data set; this enables the system to identify those situations where the overall fluctuation is not large but the individual data points deviate significantly from the normal state, thereby improving the sensitivity of anomaly detection.

[0076] Specifically, the judgment unit is further used to calculate a first difference between the temperature data in the abnormal temperature data set and the average temperature value, compare the difference with a preset first difference threshold, and judge the abnormal level of the temperature data according to the comparison result, including:

[0077] The first difference threshold comprises a first minimum difference threshold and a first maximum difference threshold;

[0078] When the first difference is less than or equal to the first minimum difference threshold, determining that the abnormal level of the temperature data is the first level;

[0079] When the first difference is greater than the first lowest difference threshold and less than or equal to the first highest difference threshold, determining that the abnormal level of the temperature data is the second level;

[0080] When the first difference is greater than the first highest difference threshold, determining that the abnormal level of the temperature data is the third level;

[0081] The first level is smaller than the second level, and the second level is smaller than the third level.

[0082] It can be seen that in the process of optimizing the abnormal level judgment of temperature data, the judgment unit adopts a more detailed grading strategy. By setting multiple difference thresholds (i.e., the first minimum difference threshold and the first maximum difference threshold), a more accurate quantitative evaluation of abnormal temperature data is achieved. This grading method not only improves the system's sensitivity to temperature anomalies, but also enables abnormal processing to take corresponding measures according to different levels, thereby improving the efficiency and accuracy of the overall system.

[0083] It can be understood that when the difference between a certain temperature data and the baseline (i.e., the average temperature value) falls within the first minimum difference threshold, the system determines that the data is a slight abnormality, i.e., a first-level abnormality. This type of abnormality may represent some temporary temperature changes that have little impact on the overall system, such as short-term fluctuations in environmental factors; when the difference exceeds the first minimum difference threshold but is still within the first maximum difference threshold, the system determines it to be a moderate abnormality, i.e., a second-level abnormality. This type of abnormality may indicate some temperature change trends that require attention, or may be an early signal that the system is about to face potential problems; and when the difference exceeds the first maximum difference threshold, the system determines it to be a serious abnormality, i.e., a third-level abnormality. This type of abnormality often represents that the system has experienced significant temperature changes, which may directly affect the normal operation or safety performance of the equipment. For this type of abnormality, the system should immediately trigger an alarm and automatically or manually start the corresponding emergency handling process to ensure the stability and safety of the system.

[0084] Specifically, the processing unit is used to calculate the temperature fluctuation value of the temperature data in the abnormal temperature data set and the corresponding temperature data at the historical moment after determining the abnormal level of the temperature data, and calculate the second difference between the temperature fluctuation value and the maximum temperature fluctuation value, including:

[0085] The historical temperature data is the temperature data at the corresponding historical moment in the same time period, and the maximum temperature fluctuation value is the difference between the maximum temperature data and the minimum temperature data in the normal temperature data set.

[0086] Specifically, when adjusting the abnormal level of the temperature data according to the relationship between the second difference and a preset second difference threshold, the method includes:

[0087] The second difference threshold comprises a second lowest difference threshold and a second highest difference threshold;

[0088] When the second difference is less than or equal to the second lowest difference threshold, lowering the abnormal level of the temperature data;

[0089] When the second difference is greater than the second lowest difference threshold and less than or equal to the second highest difference threshold, maintaining the abnormal level of the current temperature data unchanged;

[0090] When the second difference is greater than the second highest difference threshold, the abnormal level of the temperature data is increased.

[0091] Specifically, when the processing unit determines to lower the abnormal level of the temperature data, it includes:

[0092] When the second difference is less than or equal to the second lowest difference threshold, subtract the second lowest difference threshold from the second difference to obtain a fourth difference;

[0093] comparing the fourth difference with a preset fourth difference threshold, and adjusting the abnormal level of the temperature data according to the comparison result;

[0094] When the fourth difference is less than or equal to the fourth difference threshold, it is determined that the abnormal level of the temperature data is lowered by two levels;

[0095] When the fourth difference is greater than the fourth difference threshold, it is determined that the abnormal level of the temperature data is lowered by one level;

[0096] The abnormal level of the temperature data is lowered to the first level.

[0097] Specifically, when the processing unit determines to increase the abnormal level of the temperature data, it includes:

[0098] When the second difference is greater than the second highest difference threshold, subtracting the second highest difference threshold from the second difference to obtain a fifth difference;

[0099] comparing the fifth difference with a preset fifth difference threshold, and adjusting the abnormal level of the temperature data according to the comparison result;

[0100] When the fifth difference is less than or equal to the fifth difference threshold, it is determined that the abnormal level of the temperature data is increased by one level;

[0101] When the fifth difference is greater than the fifth difference threshold, it is determined that the abnormal level of the temperature data is increased by two levels;

[0102] The highest abnormal level of the temperature data is adjusted to the third level.

[0103] It can be seen that in the process of further refining the temperature data anomaly processing, the system not only determines the anomaly level through the difference threshold, but also introduces the consideration of temperature fluctuation value, thereby realizing the accurate capture of the dynamic changes of abnormal status. This multi-dimensional evaluation mechanism enables the system to respond more flexibly and accurately when facing complex and changeable temperature environments.

[0104] It can be understood that when the processing unit calculates the temperature fluctuation value of the temperature data and the temperature data at historical moments, and compares it with the maximum temperature fluctuation value, it is actually evaluating the degree of deviation of the current temperature state from the historical normal state; if this deviation is small (that is, the second difference is below the second lowest difference threshold), it may mean that the previous abnormal judgment was too sensitive, or the current temperature state is returning to normal, so the system will choose to lower the abnormal level of the temperature data. This adjustment not only helps to reduce false alarms, but also allows the system to adapt to environmental changes more flexibly; on the contrary, when the temperature fluctuation value increases significantly (that is, the second difference exceeds the second highest difference threshold), the system will regard this change as a signal of intensified abnormality, and then increase the abnormal level of the temperature data. This timely response can ensure that the system can quickly initiate higher-level emergency measures when faced with emergencies, thereby effectively preventing the expansion of potential problems.

[0105] It can be understood that when the processing unit adjusts the abnormality level, the fourth and fifth differences and the corresponding fourth and fifth difference thresholds are compared, which enables the system to finely control the adjustment amplitude of the abnormality level according to the specific size of the temperature fluctuation value; for example, when the temperature fluctuation value deviates extremely from the normal range (that is, the fourth or fifth difference is much larger than its corresponding threshold), the system may choose to increase or decrease two levels of abnormality level at one time to adapt to changes in temperature conditions more quickly. This hierarchical adjustment strategy not only improves the response speed of the system, but also makes the abnormality handling process more in line with the needs of actual conditions.

[0106] See also Figure 2As shown, in some embodiments of the present application, this embodiment provides a data recording method for a temperature sensor, comprising the following steps:

[0107] S100: collecting temperature data from a temperature sensor in real time and storing the temperature data in a storage repository;

[0108] S200: screening the temperature data in the storage repository, and establishing a normal temperature data set and an abnormal temperature data set according to the screening results;

[0109] S300: calculating an average temperature value and a maximum temperature fluctuation value of the temperature data in the normal temperature data set, calculating a first difference between the temperature data in the abnormal temperature data set and the average temperature value, comparing the first difference with a preset first difference threshold, and determining an abnormal level of the temperature data according to the comparison result;

[0110] S400: after determining the abnormal level of the temperature data, calculating the temperature fluctuation value of the temperature data in the abnormal temperature data set and the corresponding temperature data at the historical moment, and calculating the second difference between the temperature fluctuation value and the maximum temperature fluctuation value, and then adjusting the abnormal level of the temperature data according to the relationship between the second difference and a preset second difference threshold;

[0111] S500: storing and recording the adjusted temperature data according to the abnormality level.

[0112] It can be seen that the data recording method for the temperature sensor provided in this embodiment is highly flexible and accurate. It ensures the effectiveness and reliability of the temperature recording system through comprehensive analysis and refined processing of temperature data; through multi-dimensional evaluation and refined control, it realizes accurate capture and timely response to abnormal conditions of temperature data. This efficient and intelligent data processing mechanism not only improves the overall performance of the temperature recording system, but also provides strong technical support for a variety of application scenarios that require precise temperature control.

[0113] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0114] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0115] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0116] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0117] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A data recording system for a temperature sensor, characterized in that: include: A collection unit, used for collecting temperature data from the temperature sensor in real time and storing the temperature data in a storage repository; a transfer unit, used to screen the temperature data in the storage repository and establish a normal temperature data set and an abnormal temperature data set according to the screening result, and the transfer unit is also used to send the normal temperature data set and the abnormal temperature data set to the judgment unit; a judgment unit, configured to receive the normal temperature data set and the abnormal temperature data set, and calculate an average temperature value and a maximum temperature fluctuation value of the temperature data in the normal temperature data set, and further configured to calculate a first difference between the temperature data in the abnormal temperature data set and the average temperature value, compare the first difference with a preset first difference threshold, and judge the abnormal level of the temperature data according to the comparison result; a processing unit, configured to calculate, after determining the abnormal level of the temperature data, a temperature fluctuation value between the temperature data in the abnormal temperature data set and the corresponding temperature data at a historical moment, and calculate a second difference between the temperature fluctuation value and the maximum temperature fluctuation value, and then adjust the abnormal level of the temperature data according to a relationship between the second difference and a preset second difference threshold; The storage and recording unit stores and records the adjusted temperature data according to the abnormality level.

2. The data recording system for temperature sensor according to claim 1, characterized in that: The transfer unit is used to screen the temperature data in the storage repository and establish a normal temperature data set and an abnormal temperature data set according to the screening result, including: Dividing the temperature data in the storage repository according to time periods; Calculate the variance of all temperature data within the same time period, compare the variance with a preset variance threshold, and make a judgment based on the comparison result; When the variance is less than or equal to the variance threshold, all temperature data within the same time period are temporarily added to the normal temperature data set; When the variance is greater than the variance threshold, all temperature data within the same time period are added to the abnormal temperature data set.

3. The data recording system for temperature sensor according to claim 2, characterized in that: When the variance is less than or equal to the variance threshold, all temperature data in the same time period are temporarily added to the normal temperature data set, further comprising: A temperature standard value is set in advance, and then all temperature data within the same time period are subtracted from the temperature standard value one by one to obtain a third difference value, and the third difference value is compared with a preset third difference threshold value, and based on the comparison result, it is determined whether the temperature data is transferred to the abnormal temperature data set.

4. The data recording system for temperature sensor according to claim 3, characterized in that: The third difference is compared with a preset third difference threshold, and according to the comparison result, it is determined whether to transfer the temperature data into the abnormal temperature data set, including: When the third difference is less than or equal to the third difference threshold, retaining the temperature data to the normal temperature data set; When the third difference is greater than the third difference threshold, the temperature data is transferred to the abnormal temperature data set.

5. The data recording system for temperature sensor according to claim 4, characterized in that: The judgment unit is further configured to calculate a first difference between the temperature data in the abnormal temperature data set and the average temperature value, compare the difference with a preset first difference threshold, and judge the abnormal level of the temperature data according to the comparison result, including: The first difference threshold comprises a first minimum difference threshold and a first maximum difference threshold; When the first difference is less than or equal to the first minimum difference threshold, determining that the abnormal level of the temperature data is the first level; When the first difference is greater than the first lowest difference threshold and less than or equal to the first highest difference threshold, determining that the abnormal level of the temperature data is the second level; When the first difference is greater than the first highest difference threshold, determining that the abnormal level of the temperature data is the third level; The first level is smaller than the second level, and the second level is smaller than the third level.

6. The data recording system for temperature sensor according to claim 5, characterized in that: The processing unit is used to calculate the temperature fluctuation value of the temperature data in the abnormal temperature data set and the corresponding temperature data at a historical moment after determining the abnormal level of the temperature data, and calculate the second difference between the temperature fluctuation value and the maximum temperature fluctuation value, including: The historical temperature data is the temperature data at the corresponding historical moment in the same time period, and the maximum temperature fluctuation value is the difference between the maximum temperature data and the minimum temperature data in the normal temperature data set.

7. The data recording system for a temperature sensor according to claim 6, characterized in that: When adjusting the abnormal level of the temperature data according to the relationship between the second difference and a preset second difference threshold, the method includes: The second difference threshold comprises a second lowest difference threshold and a second highest difference threshold; When the second difference is less than or equal to the second lowest difference threshold, lowering the abnormal level of the temperature data; When the second difference is greater than the second lowest difference threshold and less than or equal to the second highest difference threshold, maintaining the abnormal level of the current temperature data unchanged; When the second difference is greater than the second highest difference threshold, the abnormal level of the temperature data is increased.

8. The data recording system for a temperature sensor according to claim 7, characterized in that: When the processing unit determines to lower the abnormal level of the temperature data, it includes: When the second difference is less than or equal to the second lowest difference threshold, subtract the second lowest difference threshold from the second difference to obtain a fourth difference; comparing the fourth difference with a preset fourth difference threshold, and adjusting the abnormal level of the temperature data according to the comparison result; When the fourth difference is less than or equal to the fourth difference threshold, it is determined that the abnormal level of the temperature data is lowered by two levels; When the fourth difference is greater than the fourth difference threshold, it is determined that the abnormal level of the temperature data is lowered by one level; The abnormal level of the temperature data is lowered to the first level.

9. The data recording system for a temperature sensor according to claim 8, characterized in that: When the processing unit determines to increase the abnormal level of the temperature data, it includes: When the second difference is greater than the second highest difference threshold, subtracting the second highest difference threshold from the second difference to obtain a fifth difference; comparing the fifth difference with a preset fifth difference threshold, and adjusting the abnormal level of the temperature data according to the comparison result; When the fifth difference is less than or equal to the fifth difference threshold, it is determined that the abnormal level of the temperature data is increased by one level; When the fifth difference is greater than the fifth difference threshold, it is determined that the abnormal level of the temperature data is increased by two levels; The highest abnormal level of the temperature data is adjusted to the third level.

10. A data recording method for a temperature sensor, applied to a data recording system for a temperature sensor as claimed in any one of claims 1 to 9, characterized in that: include: Collect temperature data from temperature sensors in real time and store the temperature data in a storage repository; Screening the temperature data in the storage repository, and establishing a normal temperature data set and an abnormal temperature data set according to the screening results; Calculating an average temperature value and a maximum temperature fluctuation value of the temperature data in the normal temperature data set, calculating a first difference between the temperature data in the abnormal temperature data set and the average temperature value, comparing the first difference with a preset first difference threshold, and determining an abnormal level of the temperature data according to the comparison result; After determining the abnormal level of the temperature data, calculating the temperature fluctuation value of the temperature data in the abnormal temperature data set and the corresponding temperature data at the historical moment, and calculating the second difference between the temperature fluctuation value and the maximum temperature fluctuation value, and then adjusting the abnormal level of the temperature data according to the relationship between the second difference and a preset second difference threshold; The adjusted temperature data is stored and recorded according to the abnormality level.

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