CN115031853A - Infrared temperature measurement data processing method and device - Google Patents
Infrared temperature measurement data processing method and device Download PDFInfo
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- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
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Abstract
The application discloses an infrared temperature measurement data processing method and device, wherein infrared temperature measurement data are obtained and detected to obtain a detection result, when the detection result meets a preset condition, the infrared temperature measurement data are used for carrying out data updating on original data, and an updating log is generated according to the infrared temperature measurement data; the detection result represents the accuracy of the infrared temperature measurement data, and the original data represents the historical temperature data of the target equipment and the corresponding historical environmental temperature data; the acquired infrared temperature measurement data are detected, historical temperature data are updated only when the detection result meets the preset condition, accuracy of the infrared temperature measurement data is guaranteed, and the data are recorded for follow-up consultation and continuous monitoring.
Description
Technical Field
The application relates to the technical field of infrared thermal imaging, in particular to an infrared temperature measurement data processing method and device.
Background
Any object can continuously radiate infrared heat energy outwards due to the movement of molecules of the object, so that a certain temperature field, commonly called thermal image, is formed on the surface of the object. The infrared thermal imager measures the surface temperature and the temperature field distribution of the equipment by absorbing the infrared radiation energy emitted by an object, displays the thermal image on a liquid crystal screen by utilizing an infrared optical technology, and converts the invisible thermal image into a visible light image. Use thermal imaging system check out test set temperature, the testing process is safe high-efficient, monitoring data is directly perceived reliable, can accurately reflect the equipment inside and outside condition of generating heat, play huge effect in the aspect of discovery equipment potential safety hazard, reduction operation and maintenance cost, promotion electric wire netting safety level.
However, when the conventional thermal imager performs infrared temperature measurement on the electrical equipment, the following disadvantages exist: the conventional thermal imager needs to record measurement data in a manual screen capturing, video recording or paper recording mode, in the measurement process, data recording is troublesome and labor-consuming, workers basically only record the heating condition of equipment exceeding an allowable temperature limit value, equipment with the heating temperature within the limit value is not concerned, a large amount of infrared monitoring data is lost, and then storage modes such as pictures, audios, videos and paper records are superposed, so that the problems of being not visual after the fact and inconvenient in data extraction exist, an infrared monitoring database of electrical equipment cannot be constructed, the data enabling work such as large data analysis application and data value deep mining cannot be mentioned at all, the infrared temperature measurement work that the workers consume a large amount of time and enterprises pay high cost is directly caused, and the maximum efficiency is not exerted.
Disclosure of Invention
The present application is proposed to solve the above-mentioned technical problems. The embodiment of the application provides an infrared temperature measurement data processing method and device, and the technical problem is solved.
According to one aspect of the application, an infrared temperature measurement data processing method is provided, and comprises the following steps: acquiring infrared temperature measurement data; the infrared temperature measurement data comprise target equipment temperature data and environment temperature data; detecting the infrared temperature measurement data to obtain a detection result; the detection result represents the accuracy of the infrared temperature measurement data; when the detection result meets a preset condition, updating original data by the infrared temperature measurement data; the original data represents initial temperature data of the target equipment obtained through measurement and corresponding initial environment temperature data; and generating an update log according to the infrared temperature measurement data.
In an embodiment, the infrared thermometry data processing method further includes: when the detection result does not meet the preset condition, performing data cleaning on the infrared temperature measurement data; detecting the cleaned infrared temperature measurement data to obtain a secondary detection result; when the secondary detection result meets the preset condition, updating original data by using the cleaned infrared temperature measurement data; and generating a cleaning log according to the cleaned infrared temperature measurement data.
In an embodiment, the performing data cleaning on the infrared temperature measurement data includes: and carrying out any one or more of the following operations on the infrared temperature measurement data: setting missing value and modifying error value.
In an embodiment, before the detecting the infrared thermometry data, the infrared thermometry data processing method further includes: preprocessing the infrared temperature measurement data to obtain preprocessed infrared temperature measurement data; the detecting the infrared temperature measurement data comprises: and detecting the preprocessed infrared temperature measurement data.
In an embodiment, the preprocessing the infrared thermometry data includes: and modifying the format of the infrared temperature measurement data into a standard data format.
In an embodiment, before the updating the original data with the infrared temperature measurement data, the infrared temperature measurement data processing method further includes: and carrying out duplicate removal cleaning on the infrared temperature measurement data.
In an embodiment, the performing the deduplication cleaning on the infrared thermometry data includes: and inputting the infrared temperature measurement data into a convolutional neural network model to remove repeated data or similar data in the infrared temperature measurement data.
In an embodiment, the detecting the infrared temperature measurement data to obtain a detection result includes: selecting at least one evaluation mode; the evaluation mode comprises accuracy evaluation, precision evaluation, recall evaluation and an F1 value; acquiring real data; wherein the real data characterizes real temperature data of the target device and real temperature data of the corresponding environment; and calculating to obtain the detection result according to the infrared temperature measurement data and the real data based on the evaluation mode.
In an embodiment, after the updating the original data with the infrared temperature measurement data, the infrared temperature measurement data processing method further includes: and uploading the infrared temperature measurement data to a database and generating a return log.
According to another aspect of the present application, there is provided an infrared thermometry data processing apparatus, comprising: the data acquisition module is used for acquiring infrared temperature measurement data; the infrared temperature measurement data comprise target equipment temperature data and environment temperature data; the data detection module is used for detecting the infrared temperature measurement data to obtain a detection result; the detection result represents the accuracy of the infrared temperature measurement data; the data updating module is used for updating original data by the infrared temperature measurement data when the detection result meets a preset condition; the original data represents initial temperature data of the target equipment obtained through measurement and corresponding initial environment temperature data; and the first log module is used for generating an update log according to the infrared temperature measurement data.
According to the method and the device for processing the infrared temperature measurement data, the infrared temperature measurement data are obtained and detected to obtain a detection result, when the detection result meets the preset condition, the original data are updated by the infrared temperature measurement data, and an update log is generated according to the infrared temperature measurement data; the detection result represents the accuracy of the infrared temperature measurement data, and the original data represents the historical temperature data of the target equipment and the corresponding historical environmental temperature data; the acquired infrared temperature measurement data are detected, historical temperature data are updated only when the detection result meets the preset condition, accuracy of the infrared temperature measurement data is guaranteed, and the data are recorded for follow-up consultation and continuous monitoring.
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The above and other objects, features and advantages of the present application will become more apparent by describing in more detail embodiments of the present application with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of the embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings, like reference numbers generally represent like parts or steps.
Fig. 1 is a schematic flowchart of an infrared temperature measurement data processing method according to an exemplary embodiment of the present application.
Fig. 2 is a schematic flowchart of a method for processing infrared temperature measurement data according to another exemplary embodiment of the present application.
Fig. 3 is a schematic flowchart of a method for processing infrared temperature measurement data according to another exemplary embodiment of the present application.
Fig. 4 is a schematic flowchart of a method for processing infrared temperature measurement data according to another exemplary embodiment of the present application.
Fig. 5 is a schematic flowchart of a method for processing infrared temperature measurement data according to another exemplary embodiment of the present application.
Fig. 6 is a schematic flowchart of a method for detecting infrared thermometry data according to an exemplary embodiment of the present application.
Fig. 7 is a schematic flowchart of a method for processing infrared temperature measurement data according to another exemplary embodiment of the present application.
Fig. 8 is a schematic structural diagram of an infrared temperature measurement data processing apparatus according to an exemplary embodiment of the present application.
Fig. 9 is a schematic structural diagram of an infrared temperature measurement data processing apparatus according to another exemplary embodiment of the present application.
Fig. 10 is a block diagram of an electronic device provided in an exemplary embodiment of the present application.
Detailed Description
Fig. 1 is a schematic flowchart of an infrared temperature measurement data processing method according to an exemplary embodiment of the present application. As shown in fig. 1, the infrared temperature measurement data processing method includes the following steps:
step 110: and acquiring infrared temperature measurement data.
The infrared temperature measurement data comprise target equipment temperature data and environment temperature data. And carrying out temperature measurement work by an infrared thermal imager. In the testing process, a worker operates the system by one key, and the system can automatically record the data of the current equipment, such as the infrared temperature measurement time, the highest temperature of the equipment and the like. The instrument is integrated with an environmental temperature monitoring sensing device, and can synchronously record the environmental temperature in real time.
Step 120: and detecting the infrared temperature measurement data to obtain a detection result.
Wherein, the detection result represents the accuracy of the infrared temperature measurement data. Similar repeated records and a small amount of dirty data such as null values and error values exist in thermal imaging historical data of the power industry. After the infrared temperature measurement data are obtained, the infrared temperature measurement data are detected to obtain dirty data in the infrared temperature measurement data, so that the dirty data are modified or adjusted in a targeted manner, and the accuracy of the infrared temperature measurement data is guaranteed.
Step 130: and when the detection result meets the preset condition, updating the original data by using the infrared temperature measurement data.
The original data represents measured initial temperature data of the target device and corresponding initial environment temperature data. The specific preset condition may be any one or combination of more of accuracy, precision, recall, and F1 values (e.g., a weighted average of a plurality). When the infrared temperature measurement data meet the preset conditions (namely the accuracy of the infrared temperature measurement data is higher, the temperature data of the measured target equipment can be better reflected), the original data is updated by the current infrared temperature measurement data, wherein the original data is the initial data obtained by the measurement of the thermal imager. Namely, the infrared temperature measurement data meeting the preset conditions are taken as final data.
Step 140: and generating an update log according to the infrared temperature measurement data.
And after the final infrared temperature measurement data is obtained, generating an update log according to the infrared temperature measurement data, namely recording the data update time, update data and other information for subsequent consultation and inspection.
According to the infrared temperature measurement data processing method, infrared temperature measurement data are obtained and detected to obtain a detection result, when the detection result meets a preset condition, data updating is carried out on the original data through the infrared temperature measurement data, and an updating log is generated according to the infrared temperature measurement data; the detection result represents the accuracy of the infrared temperature measurement data, and the original data represents the historical temperature data of the target equipment and the corresponding historical environmental temperature data; the acquired infrared temperature measurement data are detected, historical temperature data are updated only when the detection result meets the preset condition, accuracy of the infrared temperature measurement data is guaranteed, and the data are recorded for follow-up consultation and continuous monitoring.
Fig. 2 is a schematic flowchart of a method for processing infrared temperature measurement data according to another exemplary embodiment of the present application. As shown in fig. 2, the infrared temperature measurement data processing method may further include:
step 150: and when the detection result does not meet the preset condition, performing data cleaning on the infrared temperature measurement data.
Specifically, when the infrared temperature measurement data do not satisfy the preset condition, that is, the accuracy of the infrared temperature measurement data is not high, it is indicated that more missing values, error values and the like exist in the infrared temperature measurement data, and the infrared temperature measurement data need to be cleaned at this time. In an embodiment, the specific implementation manner of step 150 may be: and carrying out any one or more of the following operations on the infrared temperature measurement data: setting missing values and modifying error values. Specifically, missing value cleaning, error value cleaning and the like can be included to obtain accurate infrared temperature measurement data. The specific cleaning mode can comprise an edit distance algorithm, a BP algorithm, a WE-CNN, a SIM-CNN, a priority queue algorithm, an SNM algorithm, an MPN algorithm, an I-MPN algorithm and the like.
Step 160: and detecting the cleaned infrared temperature measurement data to obtain a secondary detection result.
And after the cleaning is finished, detecting the cleaned infrared temperature measurement data to obtain a secondary detection result.
Step 170: and when the secondary detection result meets the preset condition, updating the original data by using the cleaned infrared temperature measurement data.
And if the detection result of the cleaned infrared temperature measurement data meets the preset condition, updating the original data by the cleaned infrared temperature measurement data, namely, taking the cleaned infrared temperature measurement data as final infrared temperature measurement data.
Step 180: and generating a cleaning log according to the cleaned infrared temperature measurement data.
And after the final infrared temperature measurement data is obtained, generating an update log according to the infrared temperature measurement data, namely recording the data update time, update data and other information for subsequent consultation and inspection.
Fig. 3 is a schematic flowchart of a method for processing infrared temperature measurement data according to another exemplary embodiment of the present application. As shown in fig. 3, before step 120, the infrared thermometry data processing method may further include:
step 190: and preprocessing the infrared temperature measurement data to obtain preprocessed infrared temperature measurement data.
Correspondingly, step 120 may be adjusted to: and detecting the preprocessed infrared temperature measurement data. The infrared thermometry data is preprocessed to convert each Word in each record into a Word vector (Word Embedding) that the model can recognize. According to the problems and the characteristics of the infrared thermal imaging historical data in the power industry, the main steps of data preprocessing are divided into three parts, namely simple cleaning of historical data missing values, simple cleaning of error values, word segmentation and word vector generation.
Fig. 4 is a schematic flowchart of a method for processing infrared temperature measurement data according to another exemplary embodiment of the present application. As shown in fig. 4, step 190 may include:
step 191: and modifying the format of the infrared temperature measurement data into a standard data format.
The format modification mainly comprises a standard data format, a unified data expression mode, a unified contraction and the like, for example, a date field adopts an ISO8601 international standard, a YYYY-MM-DD format is used, a monitoring point adopts an 11-bit fixed format and the like, and the format standards are stored in a rule base.
Fig. 5 is a schematic flowchart of a method for processing infrared temperature measurement data according to another exemplary embodiment of the present application. As shown in fig. 5, before step 130, the infrared thermometry data processing method may further include:
step 1100: and carrying out duplicate removal cleaning on the infrared temperature measurement data.
In an embodiment, the specific implementation manner of step 1100 may be: and inputting the infrared temperature measurement data into a convolutional neural network model to remove repeated data or similar data in the infrared temperature measurement data. Cleansing of similar duplicate records can be significant changes to the entire data set, which can affect the overall number of records. But if the cleaning of similar duplicate records is performed first, the result of cleaning of similar duplicate records is not ideal and even the cleaning fails. Cleaning of similar duplicate records cannot be done directly, before which most missing and erroneous values need to be cleared. Because the research focus is on cleaning similar repeated records in infrared thermal imaging historical data in the power industry, dirty data such as missing values, data violating constraint rules and error data are obtained.
Fig. 6 is a schematic flowchart of a method for detecting infrared thermometry data according to an exemplary embodiment of the present application. As shown in fig. 6, the step 120 may include:
step 121: and selecting at least one evaluation mode.
The evaluation mode comprises accuracy evaluation, precision evaluation, recall evaluation and F1 value.
Step 122: and acquiring real data.
Wherein the real data characterizes real temperature data of the target device and real temperature data of the corresponding environment.
Step 123: and calculating to obtain a detection result according to the infrared temperature measurement data and the real data based on the evaluation mode.
Fig. 7 is a schematic flowchart of a method for processing infrared temperature measurement data according to another exemplary embodiment of the present application. As shown in fig. 7, after step 130, the infrared thermometry data processing method may further include:
step 1110: and uploading the infrared temperature measurement data to a database and generating a return log.
The main function of the data returning module is to upload the cleaned result to the original database, and meanwhile, a temporary database display interface is also arranged, so that the cleaned data can be displayed to a user, and related operations can be performed again according to the functions or modules such as a return rule modification module, a data cleaning module or a data evaluation module and the like selected by the user. The specific operation mode can be as follows: the data in the current temporary library is firstly displayed to a user, and the user can select three operations of re-cleaning, data uploading and data non-uploading according to the data condition. And selecting to re-clean the module number needing to be appointed, and generating a return log. After selecting the uploaded data, the name of the uploaded table needs to be specified, if the name of the uploaded table is the same as the name of the original data table, the original data table is covered, otherwise, a table is newly built, a data return log is generated after uploading, then the temporary library data is deleted, and the operation is finished. If the data is not uploaded, the temporary library data is deleted and the operation is finished after the data return log is generated.
Fig. 8 is a schematic structural diagram of an infrared temperature measurement data processing apparatus according to an exemplary embodiment of the present application. As shown in fig. 8, the infrared thermometry data processing apparatus 80 includes: the data acquisition module 81 is used for acquiring infrared temperature measurement data; the infrared temperature measurement data comprise target equipment temperature data and environment temperature data; the data detection module 82 is used for detecting the infrared temperature measurement data to obtain a detection result; wherein the detection result represents the accuracy of the infrared temperature measurement data; the data updating module 83 is used for updating the original data by using the infrared temperature measurement data when the detection result meets the preset condition; the original data represents initial temperature data of the target equipment obtained by measurement and corresponding initial environment temperature data; and a first log module 84 for generating an update log according to the infrared temperature measurement data.
According to the infrared temperature measurement data processing device, infrared temperature measurement data are obtained through the data obtaining module 81, the data detection module 82 detects the infrared temperature measurement data to obtain a detection result, when the detection result meets a preset condition, the data updating module 83 performs data updating on original data through the infrared temperature measurement data, and the first log module 84 generates an updating log according to the infrared temperature measurement data; the detection result represents the accuracy of the infrared temperature measurement data, and the original data represents the historical temperature data of the target equipment and the corresponding historical environmental temperature data; the acquired infrared temperature measurement data are detected, historical temperature data are updated only when the detection result meets the preset condition, accuracy of the infrared temperature measurement data is guaranteed, and the data are recorded for follow-up consultation and continuous monitoring.
Fig. 9 is a schematic structural diagram of an infrared temperature measurement data processing apparatus according to another exemplary embodiment of the present application. As shown in fig. 9, the infrared thermometry data processing apparatus 80 may further include: and the cleaning module 85 is used for cleaning the data of the infrared temperature measurement data when the detection result does not meet the preset condition. Correspondingly, the data detection module 82 may be configured to: detecting the cleaned infrared temperature measurement data to obtain a secondary detection result; the data update module 83 may be configured to: when the secondary detection result meets the preset condition, updating the original data by using the cleaned infrared temperature measurement data; the first log module 84 may be configured to: and generating a cleaning log according to the cleaned infrared temperature measurement data.
In an embodiment, the purge module 85 may be further configured to: and carrying out any one or more of the following operations on the infrared thermometry data: setting missing value and modifying error value.
In an embodiment, as shown in fig. 9, the infrared thermometry data processing apparatus 80 may further include: and the preprocessing module 86 is used for preprocessing the infrared temperature measurement data to obtain preprocessed infrared temperature measurement data. Correspondingly, the data detection module 82 may be configured to: and detecting the preprocessed infrared temperature measurement data.
In an embodiment, the pre-processing module 86 may be configured to: and modifying the format of the infrared temperature measurement data into a standard data format.
In an embodiment, as shown in fig. 9, the infrared thermometry data processing apparatus 80 may further include: and the de-weight module 87 is used for performing de-weight cleaning on the infrared temperature measurement data.
In an embodiment, the deduplication module 87 may be configured to: and inputting the infrared temperature measurement data into a convolutional neural network model to remove repeated data or similar data in the infrared temperature measurement data.
In an embodiment, the data detection module 82 may be configured to: selecting at least one evaluation mode; acquiring real data; and calculating to obtain a detection result according to the infrared temperature measurement data and the real data based on the evaluation mode.
In an embodiment, as shown in fig. 9, the infrared thermometry data processing apparatus 80 may further include: and the return module 88 is used for uploading the infrared temperature measurement data to a database and generating a return log.
Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be understood that the described embodiments are only some embodiments of the present application and not all embodiments of the present application, and that the present application is not limited by the example embodiments described herein.
Next, an electronic apparatus according to an embodiment of the present application is described with reference to fig. 10. The electronic device may be either or both of the first device and the second device, or a stand-alone device separate from them, which stand-alone device may communicate with the first device and the second device to receive the acquired input signals therefrom.
FIG. 10 illustrates a block diagram of an electronic device in accordance with an embodiment of the present application.
As shown in fig. 10, the electronic device 10 includes one or more processors 11 and memory 12.
The processor 11 may be a Central Processing Unit (CPU) or other form of processing unit having data processing capabilities and/or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.
Memory 12 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, Random Access Memory (RAM), cache memory (cache), and/or the like. The non-volatile memory may include, for example, Read Only Memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer readable storage medium and executed by the processor 11 to implement the above-described infrared thermometry data processing methods of the various embodiments of the present application and/or other desired functions. Various content such as an input signal, signal components, noise components, etc. may also be stored in the computer readable storage medium.
In one example, the electronic device 10 may further include: an input device 13 and an output device 14, which are interconnected by a bus system and/or other form of connection mechanism (not shown).
When the electronic device is a stand-alone device, the input means 13 may be a communication network connector for receiving the acquired input signals from the first device and the second device.
The input device 13 may also include, for example, a keyboard, a mouse, and the like.
The output device 14 may output various information including the determined distance information, direction information, and the like to the outside. The output devices 14 may include, for example, a display, speakers, printer, and a communication network and its connected remote output devices, among others.
Of course, for simplicity, only some of the components of the electronic device 10 relevant to the present application are shown in fig. 10, and components such as buses, input/output interfaces, and the like are omitted. In addition, the electronic device 10 may include any other suitable components depending on the particular application.
In addition to the above-described methods and apparatus, embodiments of the present application may also be a computer program product comprising computer program instructions that, when executed by a processor, cause the processor to perform the steps in the infrared thermometry data processing method according to various embodiments of the present application described in the "exemplary methods" section of this specification, supra.
The computer program product may be written with program code for performing the operations of embodiments of the present application in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present application may also be a computer readable storage medium having stored thereon computer program instructions, which, when executed by a processor, cause the processor to perform the steps in the infrared thermometry data processing method according to various embodiments of the present application described in the "exemplary methods" section above in this specification.
The computer-readable storage medium may take any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The foregoing describes the general principles of the present application in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present application are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present application. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the foregoing disclosure is not intended to be exhaustive or to limit the disclosure to the precise details disclosed.
The block diagrams of devices, apparatuses, devices, systems referred to in this application are only used as illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art. Words such as "including," "comprising," "having," and the like are open-ended words that mean "including, but not limited to," and are used interchangeably therewith. The words "or" and "as used herein mean, and are used interchangeably with, the word" and/or, "unless the context clearly dictates otherwise. The word "such as" is used herein to mean, and is used interchangeably with, the phrase "such as but not limited to".
It should also be noted that in the devices, apparatuses, and methods of the present application, each component or step can be decomposed and/or re-combined. These decompositions and/or recombinations are to be considered as equivalents of the present application.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the application. Thus, the present application is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, the description is not intended to limit embodiments of the application to the form disclosed herein. While a number of example aspects and embodiments have been discussed above, those of skill in the art will recognize certain variations, modifications, alterations, additions and sub-combinations thereof.
Claims (10)
1. An infrared temperature measurement data processing method is characterized by comprising the following steps:
acquiring infrared temperature measurement data; the infrared temperature measurement data comprise target equipment temperature data and environment temperature data;
detecting the infrared temperature measurement data to obtain a detection result; the detection result represents the accuracy of the infrared temperature measurement data;
when the detection result meets a preset condition, updating original data by using the infrared temperature measurement data; the original data represents initial temperature data of the target equipment obtained through measurement and corresponding initial environment temperature data; and
and generating an updating log according to the infrared temperature measurement data.
2. The infrared temperature measurement data processing method according to claim 1, further comprising:
when the detection result does not meet the preset condition, performing data cleaning on the infrared temperature measurement data;
detecting the cleaned infrared temperature measurement data to obtain a secondary detection result;
when the re-detection result meets the preset condition, updating original data by using the cleaned infrared temperature measurement data; and
and generating a cleaning log according to the cleaned infrared temperature measurement data.
3. The infrared temperature measurement data processing method of claim 2, wherein the data cleaning of the infrared temperature measurement data comprises:
and carrying out any one or more of the following operations on the infrared temperature measurement data: setting missing values and modifying error values.
4. The infrared thermometry data processing method of claim 1, further comprising, prior to the detecting the infrared thermometry data:
preprocessing the infrared temperature measurement data to obtain preprocessed infrared temperature measurement data;
the detecting the infrared temperature measurement data comprises:
and detecting the preprocessed infrared temperature measurement data.
5. The infrared temperature measurement data processing method of claim 4, wherein the preprocessing the infrared temperature measurement data comprises:
and modifying the format of the infrared temperature measurement data into a standard data format.
6. The infrared temperature measurement data processing method of claim 1, wherein before the data updating of the original data with the infrared temperature measurement data, the method further comprises:
and carrying out duplicate removal cleaning on the infrared temperature measurement data.
7. The infrared temperature measurement data processing method of claim 6, wherein the performing the de-duplication cleaning on the infrared temperature measurement data comprises:
and inputting the infrared temperature measurement data into a convolutional neural network model to remove repeated data or similar data in the infrared temperature measurement data.
8. The infrared temperature measurement data processing method of claim 1, wherein the detecting the infrared temperature measurement data to obtain a detection result comprises:
selecting at least one evaluation mode; the evaluation mode comprises accuracy evaluation, precision evaluation, recall evaluation and an F1 value;
acquiring real data; wherein the real data characterizes real temperature data of the target device and real temperature data of the corresponding environment; and
and calculating to obtain the detection result according to the infrared temperature measurement data and the real data based on the evaluation mode.
9. The infrared thermometry data processing method of claim 1, further comprising, after the updating of the raw data with the infrared thermometry data, the step of:
and uploading the infrared temperature measurement data to a database and generating a return log.
10. An infrared temperature measurement data processing device, characterized by, includes:
the data acquisition module is used for acquiring infrared temperature measurement data; the infrared temperature measurement data comprise target equipment temperature data and environment temperature data;
the data detection module is used for detecting the infrared temperature measurement data to obtain a detection result; the detection result represents the accuracy of the infrared temperature measurement data;
the data updating module is used for updating original data by the infrared temperature measurement data when the detection result meets a preset condition; the original data represent measured initial temperature data of the target equipment and corresponding initial environment temperature data; and
and the first log module is used for generating an update log according to the infrared temperature measurement data.
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