CN112539838A - Database-based artificial intelligent infrared imaging temperature measurement system - Google Patents
Database-based artificial intelligent infrared imaging temperature measurement system Download PDFInfo
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- 238000003331 infrared imaging Methods 0.000 title claims abstract description 25
- 238000009529 body temperature measurement Methods 0.000 title claims abstract description 21
- 238000013473 artificial intelligence Methods 0.000 claims abstract description 24
- 238000004458 analytical method Methods 0.000 claims abstract description 21
- 238000012545 processing Methods 0.000 claims abstract description 12
- 238000000034 method Methods 0.000 claims description 15
- 238000003745 diagnosis Methods 0.000 claims description 14
- 238000013135 deep learning Methods 0.000 claims description 11
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- 238000003709 image segmentation Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 238000004861 thermometry Methods 0.000 claims 5
- 238000007689 inspection Methods 0.000 abstract description 16
- 238000007726 management method Methods 0.000 description 21
- 238000013461 design Methods 0.000 description 9
- 238000001931 thermography Methods 0.000 description 8
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Abstract
The invention discloses an artificial intelligence type infrared imaging temperature measurement system based on a database, which comprises: the infrared imaging module is used for photographing the running equipment to form an infrared image; the image processing module is used for associating the infrared image with the corresponding running equipment and forming corresponding image management information, wherein the image management information comprises: device name, temperature data, image data, time, trend, fault query; the database image management module is used for storing the image management information; and the fault analysis module is used for identifying the running equipment through the geographical position information and the equipment characteristic information and automatically carrying out fault discrimination analysis based on the infrared image. The embodiment of the invention can improve the inspection efficiency, and when a photographer shoots a picture, the photographer can go after shooting, and the artificial intelligent thermal imager can automatically judge the fault, so that the required time is shorter, and the report is faster.
Description
Technical Field
The invention relates to the technical field of thermal imaging, in particular to an artificial intelligent infrared imaging temperature measurement system based on a database.
Background
The temperature measurement of the power equipment is developed all the way, from the most original high-temperature wax sheet temperature measurement method, to the single-point temperature measurement method of the infrared point temperature gun, to the infrared thermal television with images, to the existing infrared thermal imager, through the development of decades, the use of the infrared thermal imager has been quite popularized in the power industry, and is also the most temperature measurement detection instrument used in the power industry at present. The infrared detector and the photoelectric technology are used to detect the infrared specific wave band signal of the object heat radiation, convert the signal into image and graph for human visual discrimination, and further calculate the temperature value. Infrared thermography techniques have been used to overcome visual barriers by humans, whereby one can see the temperature distribution on the surface of an object.
After the large-scale power industry application of the infrared thermal imager starts in 2000, the infrared thermal imager brings historical revolution to power temperature measurement work, power failure is not needed for detection of charged equipment, images are not easy to leak high-temperature heating points, so that the infrared thermal imaging technology enters a developed express way, the original 80 × 60 pixels are developed to the current 320 × 240, 640 × 480, 1024 × 768 and other pixels, when the pixels meet the temperature measurement requirement, the development of the infrared thermal imager enters a bottleneck period, the size of the infrared detector is continuously enlarged, more detection units are loaded, and the pixels are not necessary, and therefore the infrared thermal imager is better in use, more intelligent and simpler in operation, and the infrared detection efficiency is improved.
The temperature measurement accuracy of the industrial infrared thermometer used in the existing power industry is quite accurate, the imaging quality is greatly improved in earlier models, the weight is lighter and lighter, but certain defects are still existed, and the specific defects and problems are as follows: (1) the requirement on the specialty is high, and the labor cost is high; the use of infrared thermal imaging requires high professional requirements for detection personnel, because the use of thermal infrared imager needs personnel to carry and enter into the transformer substation to look for high temperature equipment, if the user of service does not have sufficient professional degree, it is unclear where generates heat easily, how much degree of generating heat is what fault state, even do not know equipment, just can't accomplish infrared inspection work. Need professional talent to patrol and examine, the human cost is higher. (2) The faults need to be manually judged, the traditional infrared thermal imager only can achieve the function of shooting infrared pictures, the faults need to be screened and judged manually after data are collected, the professional requirement on an analyst is high, the time consumption is long, the efficiency is low, and massive infrared data picture processing work cannot be met.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides the database-based artificial intelligent infrared imaging temperature measurement system, so that a patrol inspector only needs to aim at operating equipment to take a picture, and an intelligent artificial intelligent thermal imager can automatically identify detected electric equipment and automatically diagnose defects.
In order to solve the above problems, the present invention provides an artificial intelligence type infrared imaging temperature measurement system based on a database, which comprises:
the infrared imaging module is used for photographing the running equipment to form an infrared image;
the image processing module is used for associating the infrared image with the corresponding running equipment and forming corresponding image management information, wherein the image management information comprises: device name, temperature data, image data, time, trend, fault query;
the database image management module is used for storing the image management information;
and the fault analysis module is used for identifying the running equipment through the geographical position information and the equipment characteristic information and automatically carrying out fault discrimination analysis based on the infrared image.
The system further comprises:
and the automatic naming module is used for automatically naming based on the corresponding device characteristic information.
The system further comprises:
the database image management module is also used for automatically importing the automatically named photos into a database and automatically filing the automatically named photos according to time, fault types and equipment name elements.
The image processing module associates the infrared image with the corresponding running equipment by adopting a deep learning algorithm and forms corresponding image management information.
And the database image management module intelligently labels the identified images.
The fault discrimination analysis in the fault analysis module comprises: the method comprises the steps of image preprocessing, image segmentation, image feature extraction and identification, thermal fault diagnosis and diagnosis result acquisition.
In the embodiment of the invention, the transformer substation infrared inspection work can be completed by only one inspection worker based on the database artificial intelligent infrared imaging temperature measurement system without recording infrared photo numbers to correspond to equipment, so that the labor intensity is reduced and the efficiency is greatly improved; on the other hand, also can greatly improve to measurement personnel's quality requirement, convenient to popularize and use, measurement personnel will no longer need remember corresponding diagnosis standard firmly, perhaps possess professional electric power knowledge or abundant experience, and intelligent artificial intelligence thermal imaging system will can automatic identification the electrical equipment that is detected to automatic diagnosis is out the defect. Regarding data analysis and storage, database management software equipped with the artificial intelligent thermal imager has automatic analysis and automatic filing processing capabilities, and can perform work such as historical query, historical data comparison, rapid retrieval, fault summary and the like. It can reduce personnel's configuration, practices thrift the human cost. Only one common operator is needed to replace a person who needs professional electric power infrared inspection knowledge, an assistant inspection person who assists in recording the picture number and the equipment name, and a data processing person who has professional infrared analysis experience. Can improve and patrol and examine efficiency, when shooting personnel and shoot the photo, can shoot and just go, artificial intelligence type thermal imaging system can carry out automatic judgement to the trouble, and required time is shorter, and it is faster to report. The temperature of the equipment can be filed and stored, so that the data can be checked and compared, and the equipment can be analyzed in which season and in which time period and is easy to break down.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic structural diagram of an infrared imaging temperature measurement system based on database artificial intelligence in an embodiment of the present invention;
fig. 2 is a flow chart of a method of intelligent diagnostics in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an artificial intelligence infrared imaging temperature measurement system based on a database in an embodiment of the present invention, where the system includes:
the infrared imaging module is used for photographing the running equipment to form an infrared image;
the image processing module is used for associating the infrared image with the corresponding running equipment and forming corresponding image management information, wherein the image management information comprises: device name, temperature data, image data, time, trend, fault query;
the database image management module is used for storing the image management information;
and the fault analysis module is used for identifying the running equipment through the geographical position information and the equipment characteristic information and automatically carrying out fault discrimination analysis based on the infrared image.
The system further comprises:
and the automatic naming module is used for automatically naming based on the corresponding device characteristic information.
The system further comprises:
the database image management module is also used for automatically importing the automatically named photos into a database and automatically filing the automatically named photos according to time, fault types and equipment name elements.
The image processing module associates the infrared image with the corresponding running equipment by adopting a deep learning algorithm and forms corresponding image management information.
And the database image management module intelligently labels the identified images.
The fault discrimination analysis in the fault analysis module comprises: the method comprises the steps of image preprocessing, image segmentation, image feature extraction and identification, thermal fault diagnosis and diagnosis result acquisition.
The infrared imaging temperature measurement system based on the database adopts a relatively mature database image management technology to automatically associate the infrared image with the corresponding equipment, and uniformly integrates the data recorded with the factors such as equipment name, temperature data, image data, time, trend, fault query and the like to form database image management; in addition, in the aspect of intelligent automatic fault analysis, the most advanced current image contrast technology is mainly used for reference, the characteristics, position information and the like of each device are firstly collected and stored in a database, a task navigation packet is extracted according to an inspection task during subsequent inspection, the navigation packet is injected into an artificial intelligent infrared imaging detector, a tester only needs to follow a path planned by the task and align to shoot after the device is positioned, the artificial intelligent infrared imaging detector automatically focuses during shooting, the infrared shooting or infrared video recording function can be selected after the rapid recognition is completed through information identification devices such as geographical position information, device characteristics and the like, the current state of the device is collected, after the collection is completed, the work such as fault discrimination, photo naming and the like is automatically performed, and after the inspection task is completed, the inspection data is transferred into a database image comprehensive management system, automatic archiving is performed for management and inductive archiving.
The database-based artificial intelligent infrared imaging temperature measurement system has the following functions:
1. automatic naming
The photos shot by the artificial intelligent thermal infrared imager are named automatically, the inspection task can be completed without the cooperation of two persons, and the shot photos have names corresponding to the equipment.
2. Intelligent fault discrimination
The artificial intelligent thermal infrared imager can automatically judge faults, judge most fault types and quickly report fault information to related personnel.
3. Database management
The artificial intelligent thermal infrared imager is provided with database management software, and the photos shot each time can be automatically imported into the database, automatically filed according to factors such as time, fault types and equipment names, and the required data can be quickly searched.
4. Simple in use
The artificial intelligent thermal infrared imager does not need professional knowledge, is provided with a task navigation package, can guide a shooting person to shoot at a corresponding position, and only needs to aim at equipment to press a shooting key after the shooting person reaches a task planning position. The focusing, naming and recording are all completed by the thermal infrared imager. After shooting is finished, the storage card is inserted into computer software to select the imported data, and the automatic fault defect analysis button is clicked, so that fault judgment can be rapidly carried out and a fault report can be generated. The imported data can be automatically filed, and the infrared use difficulty is greatly simplified.
5. Saving manpower and having higher efficiency
And two persons are not required to cooperate to finish the infrared inspection work, so that the labor cost is saved. The later data analysis work is not needed, and the method is more efficient.
6. Better image quality
By adopting the latest infrared detector and a special image gain technology, the image quality is greatly improved and is better than that of the thermal infrared imagers produced by most manufacturers.
An artificial intelligence implantation thermal imager mainly studies resources and algorithms of an instrument end and resources and algorithms of a cloud end, and mutual independence and mutual cooperation of a machine end and the cloud end. Starting from big data deep learning, training a deep learning algorithm, intelligently identifying power equipment, intelligently labeling an analysis region, and calling a criterion to perform intelligent diagnosis. The deep learning algorithm is suitable for most of power equipment, the recognition rate can reach more than 99%, and the recognition efficiency can reach ms level. Further, mutual data calling between the research instruments is achieved, the learning data volume is enlarged, deep learning of the instruments is continuously conducted, and the identification accuracy is continuously improved.
1. Function integration of artificial intelligence implanted artificial intelligence thermal imager system and database management system
a. Miniaturization problem of thermal infrared imager
b. Database intelligent management and learning problem
c. Problems of power consumption, volume and weight of thermal infrared imager and artificial intelligence discrimination system
1) Software and hardware compatibility design
The thermal infrared imager and the artificial intelligence discrimination system are two mutually independent devices, one relates to optics, the other relates to image recognition and artificial intelligence, and how to combine 2 devices into one under the condition of mutual noninterference leads to the condition of 1+1 to about 2.
Therefore, the software and hardware compatible design of the thermal imager and the artificial intelligence discrimination system is very complex, firstly, the principle of the infrared thermal imager and the image recognition artificial intelligence discrimination must be mastered, then, the design must be carried out according to the actual use condition and the aspects of appearance design, structural design, hardware design, software design, system design, application design and the like of the product, and meanwhile, interfaces and resources are required to be reserved for the artificial intelligence during the design.
2) Deep learning algorithm
The basis of deep learning is a large amount of experimental data and a specific learning algorithm. The collection of a large amount of experimental data is a very heavy task, and the more standard the collected data is, the more uniform the format is, the more representative the data is, and the more practical the result obtained by later training is. The specific learning algorithm is developed and optimized based on a standard learning algorithm and is suitable for unique requirements of the power industry. Regardless of data or learning algorithm, the final judgment criterion is the recognition accuracy, and if the accuracy is lower than 99%, the actual work cannot be satisfied, so for deep learning, how to achieve the recognition accuracy of at least 99% or more is difficult and challenging.
3) Intelligent label
Labeling is relatively simple for conventional image recognition, because conventional image recognition has extracted the pre-recognized image completely from the background, and programmers can algorithmically label the region of interest in the graph. In the image recognition based on the deep learning, all recognition processes are completed by the computer, so that a programmer loses control over intermediate quantity, and how to effectively label the recognition image and further serve intelligent diagnosis is the content of key research of the project.
4) Intelligent diagnostics
Intelligent diagnostics is a very convenient process to use, but is very complex to implement. Taking an infrared thermograph as an example, the whole intelligent diagnosis process simply comprises the following steps as shown in fig. 2: each process involves complex principles and algorithms, and the accuracy of each process will directly affect the final diagnosis result.
In the embodiment of the invention, the transformer substation infrared inspection work can be completed by only one inspection worker based on the database artificial intelligent infrared imaging temperature measurement system without recording infrared photo numbers to correspond to equipment, so that the labor intensity is reduced and the efficiency is greatly improved; on the other hand, also can greatly improve to measurement personnel's quality requirement, convenient to popularize and use, measurement personnel will no longer need remember corresponding diagnosis standard firmly, perhaps possess professional electric power knowledge or abundant experience, and intelligent artificial intelligence thermal imaging system will can automatic identification the electrical equipment that is detected to automatic diagnosis is out the defect. Regarding data analysis and storage, database management software equipped with the artificial intelligent thermal imager has automatic analysis and automatic filing processing capabilities, and can perform work such as historical query, historical data comparison, rapid retrieval, fault summary and the like. It can reduce personnel's configuration, practices thrift the human cost. Only one common operator is needed to replace a person who needs professional electric power infrared inspection knowledge, an assistant inspection person who assists in recording the picture number and the equipment name, and a data processing person who has professional infrared analysis experience. Can improve and patrol and examine efficiency, when shooting personnel and shoot the photo, can shoot and just go, artificial intelligence type thermal imaging system can carry out automatic judgement to the trouble, and required time is shorter, and it is faster to report. The temperature of the equipment can be filed and stored, so that the data can be checked and compared, and the equipment can be analyzed in which season and in which time period and is easy to break down.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, and the storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
The database-based artificial intelligence type infrared imaging temperature measurement system provided by the embodiment of the invention is described in detail, a specific example is adopted in the description to explain the principle and the implementation mode of the invention, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (6)
1. The utility model provides an infrared imaging temperature measurement system based on artificial intelligence of database which characterized in that, the system includes:
the infrared imaging module is used for photographing the running equipment to form an infrared image;
the image processing module is used for associating the infrared image with the corresponding running equipment and forming corresponding image management information, wherein the image management information comprises: device name, temperature data, image data, time, trend, fault query;
the database image management module is used for storing the image management information;
and the fault analysis module is used for identifying the running equipment through the geographical position information and the equipment characteristic information and automatically carrying out fault discrimination analysis based on the infrared image.
2. The database-based artificial intelligence infrared imaging thermometry system of claim 1, wherein the system further comprises:
and the automatic naming module is used for automatically naming based on the corresponding device characteristic information.
3. The database-based artificial intelligence infrared imaging thermometry system of claim 2, wherein the system further comprises:
the database image management module is also used for automatically importing the automatically named photos into a database and automatically filing the automatically named photos according to time, fault types and equipment name elements.
4. The database-based artificial intelligence infrared imaging thermometry system of claim 3, wherein the image processing module uses a deep learning algorithm to associate the infrared image with the corresponding operating device and form corresponding image management information.
5. The database-based artificial intelligence infrared imaging thermometry system of claim 4, wherein the database image management module intelligently labels the identified images.
6. The database-based artificial intelligence infrared imaging thermometry system of claim 5, wherein the fault discrimination analysis in the fault analysis module comprises: the method comprises the steps of image preprocessing, image segmentation, image feature extraction and identification, thermal fault diagnosis and diagnosis result acquisition.
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