CN109488888A - Based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field - Google Patents
Based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field Download PDFInfo
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- CN109488888A CN109488888A CN201811310612.5A CN201811310612A CN109488888A CN 109488888 A CN109488888 A CN 109488888A CN 201811310612 A CN201811310612 A CN 201811310612A CN 109488888 A CN109488888 A CN 109488888A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/02—Preventing, monitoring, or locating loss
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
- F17D—PIPE-LINE SYSTEMS; PIPE-LINES
- F17D5/00—Protection or supervision of installations
- F17D5/005—Protection or supervision of installations of gas pipelines, e.g. alarm
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N25/00—Investigating or analyzing materials by the use of thermal means
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Abstract
The invention discloses a kind of metallic conduit leakage monitoring method based on to the multivariate analysis of infrared temperature field, includes the following steps: to shoot monitoring area using thermal camera, obtain the Infrared Thermogram and temperature parameter of pipeline and its ambient enviroment；Gray scale and temperature information according to each pixel establish the position-gray matrix and position-temperature matrices of Infrared Thermogram；Using position-temperature matrices, the region of temperature variation abnormality is denoted as doubtful leakage region P1, while searching the region that contour feature is consistent with preset leakage shape using position-gray matrix, is denoted as doubtful leakage region P2；Overlapping region is then determined as leaking area, and outwardly issue alarm signal if more than preset coincidence factor by the registration for calculating P1 and P2.The metallic conduit leakage monitoring method is combined and is monitored using temperature and image to leakage merely with thermal camera, and the transport object of all kinds is able to detect, and the accuracy rate of leak detection is high.
Description
Technical field
The present invention relates to equipment monitoring fields, specifically provide a kind of metal tube based on to the multivariate analysis of infrared temperature field
Road leakage monitoring method.
Background technique
Due to metal material pipeline to heat transmitting speed quickly, conveying high temperature and pressure solid, liquid or gas
When body, pipeline wall temperature can be increased sharply, under complicated working environment, can there is the danger of transport object leakage.
Currently, often carrying out real-time monitoring to pipeline by the following two kinds method: one, directly being measured outside pipeline using sensor
Wall temperature, this method can only monitor the temperature conditions of section of tubing most directly but due to the inconvenience of measurement arrangement,
It can not accurately determine leakage point；Two, height is disclosed using infrared thermal imaging technique, such as Chinese invention patent CN107992857A
Warm steam leaks automatic detecting recognition methods, carries out gas leakage inspection using the method for visible light and infrared two kinds of cameras
It surveys, automatic detecting is carried out to complicated scene using robot, is analyzed using the image comparison in the image and image library of shooting,
Determine steam leakage region, however, using the method for visually adding infrared double vision, the method for only relying on image procossing, to pipe ring
Lighting condition in border, scene it is more demanding, cannot effectively be accurately obtained leak area in particular circumstances.
Therefore, one kind is developed to be suitable for all kinds transport object, can avoid the influence of temperature error bring, be not necessarily to visible light
With the metallic conduit leakage monitoring method of infrared two kinds of cameras, become people's urgent problem to be solved.
Summary of the invention
In consideration of it, the purpose of the present invention is to provide a kind of metallic conduit leakages based on to the multivariate analysis of infrared temperature field
Monitoring method is not suitable for all kinds transport object, due to the temperature of thermal infrared imager acquisition to solve existing monitoring method
There is error in field with actual temperature field and easily causes erroneous detection, to more demanding, the accuracy rate of the lighting condition in pipeline environment, scene
The problems such as low.
Present invention provide the technical scheme that a kind of metallic conduit leakage monitoring based on to the multivariate analysis of infrared temperature field
Method includes the following steps:
S1: monitoring area is shot using thermal camera, obtains the Infrared Thermogram and temperature of pipeline and its ambient enviroment
Parameter；
S2: Infrared Thermogram and temperature parameter according to obtained in S1, gray scale and temperature information according to each pixel
Establish the position-gray matrix and position-temperature matrices of Infrared Thermogram；
S3: utilizing position-temperature matrices, and the region of temperature variation abnormality is denoted as doubtful leakage region P1, while benefit
The region that contour feature is consistent with preset leakage shape is searched with position-gray matrix, is denoted as doubtful leakage region P2；
S4: overlapping region is then determined as leaking area if more than preset coincidence factor by the registration for calculating P1 and P2, and
Outwardly issue alarm signal.
It is preferred that utilizing position-temperature matrices in S3, the region of temperature variation abnormality is denoted as doubtful leakage region P1
Specific step is as follows:
S301: position-temperature matrices are utilized, position-temperature matrices of adjacent two field pictures are made the difference, temperature change is obtained
Matrix；
S302: template traversal is carried out to temperature change matrix obtained in S31 using temperature change threshold value template, determines temperature
The region for spending variation abnormality, obtains the location information of temperature change exception UNICOM domain, and be denoted as doubtful leakage region P1, wherein
Temperature change threshold value template is the 3*3 template established by the temperature change threshold value of setting.
Further preferably, the setting method of temperature change threshold value T is as follows:
Air-liquid body: T=2* (TFrom-TRing)/3, wherein TFromIndicate the temperature of transport object in pipeline, TRingIndicate thermal camera
The average ambient temperature got；
Solid: T=(TFrom-TRing)/2, wherein TFromIndicate the temperature of transport object in pipeline, TRingIndicate that thermal camera obtains
The average ambient temperature arrived.
Further preferably, search what contour feature was consistent with preset leakage shape using position-gray matrix in S3
Region, being denoted as doubtful leakage region P2, specific step is as follows:
S311: noise reduction process and edge extracting are filtered to infrared image using position-gray matrix, obtain edge wheel
Wide information；
S312: using edge contour obtained in classifier identification S311, contour feature and preset leakage shape are found out
The region that shape is consistent is denoted as doubtful leakage region P2.
Further preferably, preset leakage shape is that bulk or length are tapered.
Further preferably, in S311, noise reduction process is filtered to infrared image using median filter method, using single order
To treated, image carries out edge extracting to differential operator Sobel.
Further preferably, in S312, feature extraction is carried out to image using Hough transform；Classifier is using Fisher points
Class device.
It further preferably, further include further determining that doubtful let out after S312 if finding doubtful leakage region P2 in S312
The step of drain region P2:
S313: it is made the difference, is obtained using position-gray matrix of the frame image and position-gray matrix of previous frame image
Grey scale change matrix；
S314: the grey scale change matrix obtained by S313 finds out grey scale change value greater than preset grey scale change threshold value
Region, and it is taken into intersection with the doubtful leakage region P2 in S312, as new doubtful leakage region P2.
Further preferably, preset grey scale change threshold value is demarcated object by the constant temperature in thermal camera visual field and is determined, leads to
The temperature that thermal camera obtains specified calibration object is crossed, temperature is carried using thermal camera and turns gray scale interface, this is demarcated into object
The temperature difference of two frame of front and back is converted to infrared image grey scale change threshold value.
It is provided by the invention all based on being suitable for the metallic conduit leakage monitoring method of infrared temperature field multivariate analysis
Type transports object, it can be achieved that round-the-clock real-time monitoring to pipeline, can determine that pipeline part temperature by infrared temperature data
Variation abnormality region is spent, the mistake that there is error in the temperature field obtained due to thermal infrared imager with actual temperature field and easily caused is avoided
Inspection can determine that the region dangerous in the presence of leakage by image outline information, should be based on the gold to the multivariate analysis of infrared temperature field
Metal conduit leakage monitoring method is monitored leakage point by combined temperature and image information, and accuracy rate is higher, specifically: when
Pipeline local temperature variation abnormality region with there are the area coincidence of spillage risk and when coincidence factor is greater than preset coincidence factor, then
The coincidence area is regarded as into leaking area, and outwardly issues alarm signal.
Detailed description of the invention
With reference to the accompanying drawing and embodiment the present invention is described in further detail:
Fig. 1 is the process provided by the invention based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field
Figure.
Specific embodiment
The present invention is further explained below in conjunction with specific embodiment, but the not limitation present invention.
As shown in Figure 1, the present invention provides a kind of metallic conduit leakage monitorings based on to the multivariate analysis of infrared temperature field
Method includes the following steps:
S1: monitoring area is shot using thermal camera, obtains the Infrared Thermogram and temperature of pipeline and its ambient enviroment
Parameter；
S2: Infrared Thermogram and temperature parameter according to obtained in S1, gray scale and temperature information according to each pixel
Establish the position-gray matrix and position-temperature matrices of Infrared Thermogram；
S3: utilizing position-temperature matrices, and the region of temperature variation abnormality is denoted as doubtful leakage region P1, while benefit
The region that contour feature is consistent with preset leakage shape is searched with position-gray matrix, is denoted as doubtful leakage region P2；
S4: overlapping region is then determined as leaking area if more than preset coincidence factor by the registration for calculating P1 and P2, and
Outwardly issue alarm signal.
This is suitable for all kinds and is transported based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field
It is different to can determine that pipeline local temperature changes by infrared temperature data, it can be achieved that round-the-clock real-time monitoring to pipeline for object
Normal region avoids the erroneous detection that there is error in the temperature field obtained due to thermal infrared imager with actual temperature field and easily caused, passes through
Image outline information can determine that the region dangerous in the presence of leakage, should be based on letting out to the metallic conduit of infrared temperature field multivariate analysis
Leakage monitoring method is monitored leakage point by combined temperature and image information, and accuracy rate is higher, specifically: when pipeline part
Temperature change abnormal area with there are the area coincidence of spillage risk and when coincidence factor is greater than preset coincidence factor, then by the coincidence
Area regards as leaking area, and outwardly issues alarm signal.
Wherein, preset coincidence factor is preferably 85%, and the selection of the value is obtained by many experiments, when choosing the value,
The rate of false alarm of detection is lower, and accuracy rate is higher.
Wherein, position-temperature matrices are utilized in S3, the region of temperature variation abnormality is denoted as doubtful leakage region P1
Specific step is as follows:
S301: position-temperature matrices are utilized, position-temperature matrices of adjacent two field pictures are made the difference, temperature change is obtained
Matrix；
S302: template traversal is carried out to temperature change matrix obtained in S31 using temperature change threshold value template, determines temperature
The region for spending variation abnormality, obtains the location information of temperature change exception UNICOM domain, and be denoted as doubtful leakage region P1, wherein
Temperature change threshold value template is the 3*3 template established by the temperature change threshold value of setting.
Since thermal infrared imager temperature obtained and actual temperature have error, if directly obtained by thermal infrared imager
Temperature and preset threshold value are compared to determine that doubtful leakage region, the error of devices collect data will generate result very big
Influence, the present invention by calculate temperature change matrix, and utilize its temperature shifting region, can be big by jump in temperature value
It is detected in the region of preset temperature change threshold value, avoids and determined caused by having error with actual temperature due to temperature collection
Doubtful leakage region inaccuracy problem.
Wherein, the setting method of temperature change threshold value T is as follows:
Air-liquid body: T=2* (TFrom-TRing)/3, wherein TFromIndicate the temperature of transport object in pipeline, TRingIndicate thermal camera
The average ambient temperature got；
Solid: T=(TFrom-TRing)/2, wherein TFromIndicate the temperature of transport object in pipeline, TRingIndicate that thermal camera obtains
The average ambient temperature arrived.
For different transport objects, different temperature change threshold values need to be set, can determine difference using temperature change
Transport the doubtful leakage region of object.
Wherein, the region that contour feature is consistent with preset leakage shape, note are searched using position-gray matrix in S3
For doubtful leakage region P2, specific step is as follows:
S311: noise reduction process and edge extracting are filtered to infrared image using position-gray matrix, obtain edge wheel
Wide information；
S312: using edge contour obtained in classifier identification S311, contour feature and preset leakage shape are found out
The region that shape is consistent is denoted as doubtful leakage region P2.
It, can be by revealing moment by finding shape method similar with leakage shape in image in above-mentioned steps
The spray configuration of leakage rapidly finds out doubtful leakage region P2, and then determines there is the dangerous region of leakage.
Wherein, in S3, preset leakage shape is arranged according to the property of transport object, and leakage shape is usually arranged as rolling into a ball
Shape or length are tapered；It filters noise reduction process and uses median filtering；Edge extracting method uses first order differential operator Sobel；It uses
Hough transform carries out feature extraction to image；Classifier uses Fisher classifier.
It further include the step for further determining that doubtful leakage region P2 after S312 if finding doubtful leakage region P2 in S312
It is rapid:
S313: it is made the difference, is obtained using position-gray matrix of the frame image and position-gray matrix of previous frame image
Grey scale change matrix；
S314: the grey scale change matrix obtained by S313 finds out grey scale change value greater than preset grey scale change threshold value
Region, and it is taken into intersection with the doubtful leakage region P2 in S312, as new doubtful leakage region P2.
By the above method, doubtful leakage region P2 is redefined, can further judge the profile found out in S312 spy
Levy the region that is consistent with preset leakage shape whether be emergent leakage region, to realize elimination because of illumination etc.
Environmental factor bring influences.
Due to the image that thermal camera obtains, can be mixed with it is more serious by environment temperature bring noise, therefore, this
Invention preferably passes through the calibration object of the constant temperature in thermal camera visual field and determines infrared image grey scale change threshold value, i.e., is taken the photograph by infrared
Camera obtains the temperature of specified calibration object, carries temperature using thermal camera and turns gray scale interface, by two frames before and after this calibration object
Temperature difference, be converted to infrared image grey scale change threshold value.
A specific embodiment of the invention is write according to progressive mode, and each embodiment is highlighted
Difference, similar portion can be with cross-reference.
Embodiments of the present invention are elaborated above in conjunction with attached drawing, but the present invention is not limited to above-mentioned implementations
Mode within the knowledge of a person skilled in the art can also be without departing from the purpose of the present invention
Various changes can be made.
Claims (9)
1. based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field, which comprises the steps of:
S1: monitoring area is shot using thermal camera, obtains the Infrared Thermogram and temperature parameter of pipeline and its ambient enviroment；
S2: Infrared Thermogram and temperature parameter according to obtained in S1, gray scale and temperature information according to each pixel are established
Position-the gray matrix and position-temperature matrices of Infrared Thermogram；
S3: utilizing position-temperature matrices, and the region of temperature variation abnormality is denoted as doubtful leakage region P1, while utilizing position
Set-gray matrix searches the region that is consistent with preset leakage shape of contour feature, it is denoted as doubtful leakage region P2；
S4: calculating the registration of P1 and P2, if more than preset coincidence factor, then overlapping region is determined as leaking area, and outward
Boundary issues alarm signal.
2. according to described in claim 1 based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field, feature
It is:
Position-temperature matrices are utilized in S3, the region of temperature variation abnormality is denoted as the specific steps of doubtful leakage region P1
It is as follows:
S301: position-temperature matrices are utilized, position-temperature matrices of adjacent two field pictures are made the difference, temperature change square is obtained
Battle array；
S302: template traversal is carried out to temperature change matrix obtained in S31 using temperature change threshold value template, temperature becomes
Change abnormal region, obtains the location information of temperature change exception UNICOM domain, and be denoted as doubtful leakage region P1, wherein temperature
Change threshold template is the 3*3 template established by the temperature change threshold value of setting.
3. according to described in claim 2 based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field, feature
Be: the setting method of temperature change threshold value T is as follows:
Air-liquid body: T=2* (TFrom-TRing)/3, wherein TFromIndicate the temperature of transport object in pipeline, TRingIndicate that thermal camera obtains
The average ambient temperature arrived；
Solid: T=(TFrom-TRing)/2, wherein TFromIndicate the temperature of transport object in pipeline, TRingIndicate what thermal camera was got
Average ambient temperature.
4. according to described in claim 1 based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field, feature
It is:
The region that contour feature is consistent with preset leakage shape is searched using position-gray matrix in S3, is denoted as doubtful let out
Specific step is as follows by drain region P2:
S311: being filtered noise reduction process and edge extracting to infrared image using position-gray matrix, obtains edge contour letter
Breath；
S312: using edge contour obtained in classifier identification S311, contour feature and preset leakage shape phase are found out
The region of symbol is denoted as doubtful leakage region P2.
5. according to described in claim 4 based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field, feature
Be: preset leakage shape is that bulk or length are tapered.
6. according to described in claim 4 based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field, feature
It is: in S311, noise reduction process is filtered to infrared image using median filter method, using first order differential operator Sobel
To treated, image carries out edge extracting.
7. according to described in claim 4 based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field, feature
It is: in S312, feature extraction is carried out to image using Hough transform；Classifier uses Fisher classifier.
8. according to described in claim 4 based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field, feature
It is: if finding doubtful leakage region P2 in S312, further includes the steps that further determining that doubtful leakage region P2 after S312:
S313: it is made the difference using position-gray matrix of the frame image and position-gray matrix of previous frame image, obtains gray scale
Transformation matrices；
S314: the grey scale change matrix obtained by S313 finds out the area that grey scale change value is greater than preset grey scale change threshold value
Domain, and it is taken into intersection with the doubtful leakage region P2 in S312, as new doubtful leakage region P2.
9. according to described in claim 8 based on the metallic conduit leakage monitoring method to the multivariate analysis of infrared temperature field, feature
Be: preset grey scale change threshold value is demarcated object by the constant temperature in thermal camera visual field and is determined, is obtained by thermal camera
Fetching calibrates the temperature of earnest, carries temperature using thermal camera and turns gray scale interface, by the temperature of two frames before and after this calibration object
Difference is converted to infrared image grey scale change threshold value.
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| CN114323446A (en) * | 2022-01-06 | 2022-04-12 | 长鑫存储技术有限公司 | Liquid leakage detection method, device and equipment |
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| CN114723691A (en) * | 2022-03-28 | 2022-07-08 | 江苏新之阳新能源科技有限公司 | Method for detecting oil leakage fault degree of hydraulic system based on artificial intelligence |
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| CN113865168A (en) * | 2021-11-03 | 2021-12-31 | 广东百思特管业科技有限公司 | Dual-system micro-channel heat exchanger and control system thereof |
| CN114323446A (en) * | 2022-01-06 | 2022-04-12 | 长鑫存储技术有限公司 | Liquid leakage detection method, device and equipment |
| CN114577399A (en) * | 2022-01-18 | 2022-06-03 | 潍柴动力股份有限公司 | Engine air leakage detection method and detection device |
| CN114723691A (en) * | 2022-03-28 | 2022-07-08 | 江苏新之阳新能源科技有限公司 | Method for detecting oil leakage fault degree of hydraulic system based on artificial intelligence |
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| CN114838297A (en) * | 2022-04-14 | 2022-08-02 | 重庆七腾科技有限公司 | Crude oil pipeline leakage detection method, crude oil pipeline leakage detection device, storage medium and crude oil pipeline leakage detection system |
| CN114838297B (en) * | 2022-04-14 | 2024-03-15 | 七腾机器人有限公司 | Crude oil pipeline leakage detection method, device, storage medium and system |
| CN116823839A (en) * | 2023-08-31 | 2023-09-29 | 梁山中维热力有限公司 | Pipeline leakage detection method based on thermal infrared image |
| CN116823839B (en) * | 2023-08-31 | 2023-12-01 | 梁山中维热力有限公司 | Pipeline leakage detection method based on thermal infrared image |
| CN117114420A (en) * | 2023-10-17 | 2023-11-24 | 南京启泰控股集团有限公司 | Image recognition-based industrial and trade safety accident risk management and control system and method |
| CN117114420B (en) * | 2023-10-17 | 2024-01-05 | 南京启泰控股集团有限公司 | Image recognition-based industrial and trade safety accident risk management and control system and method |
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