CN109488888B - Metal pipeline leakage monitoring method based on infrared temperature field multivariate analysis - Google Patents
Metal pipeline leakage monitoring method based on infrared temperature field multivariate analysis Download PDFInfo
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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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- 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 metal pipeline leakage monitoring method based on infrared temperature field multivariate analysis, which comprises the following steps: shooting a monitoring area by using an infrared camera to obtain an infrared thermal image and temperature parameters of the pipeline and the surrounding environment of the pipeline; establishing a position-gray matrix and a position-temperature matrix of the infrared thermography according to the gray level and temperature information of each pixel point; determining an area with abnormal temperature change by using the position-temperature matrix, marking the area as a suspected leakage area P1, and simultaneously searching an area with contour characteristics matched with a preset leakage object shape by using the position-gray matrix, and marking the area as a suspected leakage area P2; and (4) calculating the coincidence ratio of the P1 and the P2, if the coincidence ratio is greater than the preset coincidence ratio, determining the coincidence area as a leakage area, and sending an alarm signal to the outside. According to the metal pipeline leakage monitoring method, the leakage is monitored by only using the infrared camera and jointly using the temperature and the image, all kinds of transported objects can be detected, and the accuracy of leakage detection is high.
Description
Technical Field
The invention relates to the field of equipment monitoring, and particularly provides a metal pipeline leakage monitoring method based on infrared temperature field multivariate analysis.
Background
Because the metal material pipeline has a high heat transfer speed, the temperature of the pipeline wall can be rapidly increased when high-temperature and high-pressure solid, liquid or gas is conveyed, and the risk of leakage of transported substances can exist in a complex working environment.
Currently, the pipeline is usually monitored in real time by the following two methods: firstly, a sensor is utilized to directly measure the temperature of the outer wall of a pipeline, the method is most direct but can only monitor the temperature condition of part of pipelines due to the inconvenience of measurement arrangement, and the leakage point cannot be accurately determined; secondly, by using an infrared thermal imaging technology, for example, the chinese invention patent CN107992857A discloses an automatic inspection identification method for high-temperature steam leakage, gas leakage detection is performed by using two cameras of visible light and infrared, a robot is used to automatically inspect a complex scene, and a shot image is compared with an image in an image library for analysis to determine a steam leakage area.
Therefore, it is a problem to be solved urgently that a metal pipeline leakage monitoring method suitable for all kinds of transportation objects, capable of avoiding the influence caused by temperature error and free of visible light and infrared cameras is developed.
Disclosure of Invention
In view of the above, the present invention aims to provide a metal pipeline leakage monitoring method based on multivariate analysis of infrared temperature fields, so as to solve the problems that the existing monitoring method is not suitable for all kinds of transports, false detection is easily caused due to the error between the temperature field obtained by a thermal infrared imager and the actual temperature field, the requirements on the pipeline environment and the lighting conditions in the scene are high, the accuracy is low, and the like.
The technical scheme provided by the invention is as follows: a metal pipeline leakage monitoring method based on infrared temperature field multivariate analysis comprises the following steps:
s1: shooting a monitoring area by using an infrared camera to obtain an infrared thermal image and temperature parameters of the pipeline and the surrounding environment of the pipeline;
s2: according to the infrared thermography and the temperature parameters obtained in the S1, establishing a position-gray matrix and a position-temperature matrix of the infrared thermography according to the gray scale and temperature information of each pixel point;
s3: determining an area with abnormal temperature change by using the position-temperature matrix, marking the area as a suspected leakage area P1, and simultaneously searching an area with contour characteristics matched with a preset leakage object shape by using the position-gray matrix, and marking the area as a suspected leakage area P2;
s4: and (4) calculating the coincidence ratio of the P1 and the P2, if the coincidence ratio is greater than the preset coincidence ratio, determining the coincidence area as a leakage area, and sending an alarm signal to the outside.
Preferably, in S3, the specific steps of determining the area with abnormal temperature change by using the position-temperature matrix, and marking as the suspected leakage area P1, are as follows:
s301: utilizing the position-temperature matrix to make difference between the position-temperature matrices of two adjacent frames of images to obtain a temperature change matrix;
s302: and traversing the temperature change matrix obtained in the step S301 by using a temperature change threshold template, determining an area with abnormal temperature change, obtaining position information of a communication area with abnormal temperature change, and marking as a suspected leakage area P1, wherein the temperature change threshold template is a 3 x 3 template established by a set temperature change threshold.
More preferably, the temperature change threshold T is set as follows:
gas and liquid: t2 ═ T (T)From-TRing (C)) /3, wherein, TFromIndicating the temperature, T, of the material transported in the pipelineRing (C)Representing the average ambient temperature acquired by the infrared camera;
solid: t ═ T (T)From-TRing (C)) /2, wherein, TFromIndicating the temperature, T, of the material transported in the pipelineRing (C)Representing the average ambient temperature acquired by the infrared camera.
Further preferably, in S3, the specific steps of finding a region with contour characteristics matching the preset shape of the leaking object by using the position-grayscale matrix, and marking as the suspected leaking region P2, are as follows:
s311: filtering and denoising the infrared image and extracting an edge by using the position-gray matrix to obtain edge contour information;
s312: the edge contour obtained in S311 is identified by the classifier, and a region whose contour feature matches the shape of the predetermined leaking object is found and is marked as a suspected leaking region P2.
Further preferably, the predetermined shape of the leak is a ball or a long cone.
Further preferably, in S311, a median filtering method is used to perform filtering and denoising processing on the infrared image, and a first order differential operator Sobel is used to perform edge extraction on the processed image.
Further preferably, in S312, the Hough transform is used to perform feature extraction on the image; the classifier adopts a Fisher classifier.
Further preferably, if the suspected leakage area P2 is found in S312, the method further includes, after S312, the step of further determining the suspected leakage area P2:
s313: obtaining a gray level change matrix by utilizing the difference between the position-gray level matrix of the current frame image and the position-gray level matrix of the previous frame image;
s314: and finding out an area with the gray change value larger than a preset gray change threshold value through the gray change matrix obtained in the step S313, and taking the intersection of the area and the suspected leakage area P2 in the step S312 as a new suspected leakage area P2.
Preferably, the preset gray level change threshold is determined by a constant temperature calibration object in the field of view of the infrared camera, the temperature of the designated calibration object is obtained by the infrared camera, and the temperature difference between the front frame and the rear frame of the calibration object is converted into the infrared image gray level change threshold by using a temperature-to-gray level conversion interface of the infrared camera.
The metal pipeline leakage monitoring method based on the infrared temperature field multivariate analysis is suitable for all kinds of transported objects, can realize all-weather real-time monitoring on pipelines, can determine the local temperature change abnormal area of the pipelines through infrared temperature data, avoids the error detection easily caused by the error between the temperature field obtained by a thermal infrared imager and the actual temperature field, can determine the area with leakage danger through image contour information, monitors the leakage point through combining temperature and image information, has higher accuracy, and particularly comprises the following steps: when the local temperature change abnormal area of the pipeline is superposed with the area with leakage danger and the superposition rate is greater than the preset superposition rate, the superposition area is determined as a leakage area, and an alarm signal is sent to the outside.
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The invention is described in further detail below with reference to the following figures and embodiments:
fig. 1 is a flowchart of a metal pipeline leakage monitoring method based on multivariate analysis of infrared temperature fields provided by the invention.
Detailed Description
The invention will be further explained with reference to specific embodiments, without limiting the invention.
As shown in fig. 1, the present invention provides a metal pipeline leakage monitoring method based on multivariate analysis of infrared temperature field, comprising the following steps:
s1: shooting a monitoring area by using an infrared camera to obtain an infrared thermal image and temperature parameters of the pipeline and the surrounding environment of the pipeline;
s2: according to the infrared thermography and the temperature parameters obtained in the S1, establishing a position-gray matrix and a position-temperature matrix of the infrared thermography according to the gray scale and temperature information of each pixel point;
s3: determining an area with abnormal temperature change by using the position-temperature matrix, marking the area as a suspected leakage area P1, and simultaneously searching an area with contour characteristics matched with a preset leakage object shape by using the position-gray matrix, and marking the area as a suspected leakage area P2;
s4: and (4) calculating the coincidence ratio of the P1 and the P2, if the coincidence ratio is greater than the preset coincidence ratio, determining the coincidence area as a leakage area, and sending an alarm signal to the outside.
This metal pipeline leakage monitoring method based on to infrared temperature field multiple analysis, be applicable to all kinds of transports, can realize the all-weather real-time supervision to the pipeline, can determine the unusual region of pipeline local temperature variation through infrared temperature data, avoided because the temperature field that the thermal infrared imager obtained has the error and the easy false retrieval that causes with the actual temperature field, can confirm through image profile information that there is the region of revealing danger, this metal pipeline leakage monitoring method based on to infrared temperature field multiple analysis monitors the leakage point through joint temperature and image information, the rate of accuracy is higher, specifically: when the local temperature change abnormal area of the pipeline is superposed with the area with leakage danger and the superposition rate is greater than the preset superposition rate, the superposition area is determined as a leakage area, and an alarm signal is sent to the outside.
The preset coincidence rate is preferably 85%, the value is obtained through a large number of experiments, and when the value is selected, the false alarm rate of detection is low, and the accuracy rate is high.
In S3, the position-temperature matrix is used to determine an area with abnormal temperature change, and the specific steps of marking as the suspected leakage area P1 are as follows:
s301: utilizing the position-temperature matrix to make difference between the position-temperature matrices of two adjacent frames of images to obtain a temperature change matrix;
s302: and traversing the temperature change matrix obtained in the step S301 by using a temperature change threshold template, determining an area with abnormal temperature change, obtaining position information of a communication area with abnormal temperature change, and marking as a suspected leakage area P1, wherein the temperature change threshold template is a 3 x 3 template established by a set temperature change threshold.
Because the temperature obtained by the thermal infrared imager has errors with the actual temperature, if the temperature obtained by the thermal infrared imager is directly compared with the preset threshold value to determine the suspected leakage area, the error of the data acquired by the equipment can greatly influence the result.
The setting method of the temperature change threshold T is as follows:
gas and liquid: t2 ═ T (T)From-TRing (C)) /3, wherein, TFromIndicating the temperature, T, of the material transported in the pipelineRing (C)Representing the average ambient temperature acquired by the infrared camera;
solid: t ═ T (T)From-TRing (C)) /2, wherein, TFromIndicating the temperature, T, of the material transported in the pipelineRing (C)Representing the average ambient temperature acquired by the infrared camera.
Different temperature change thresholds need to be set for different transports, and suspected leakage areas of the different transports can be determined by using the temperature change.
In S3, a region whose contour features conform to a preset shape of a leaking object is found by using the position-grayscale matrix, and the specific steps of marking as a suspected leaking region P2 are as follows:
s311: filtering and denoising the infrared image and extracting an edge by using the position-gray matrix to obtain edge contour information;
s312: the edge contour obtained in S311 is identified by the classifier, and a region whose contour feature matches the shape of the predetermined leaking object is found and is marked as a suspected leaking region P2.
In the above steps, by finding the shape in the image similar to the shape of the leak, the suspected leak region P2 can be quickly found out by the ejection shape of the leak at the moment of the leak, and the region at which the risk of the leak exists can be determined.
Wherein, in S3, the preset leakage shape is set according to the property of the transported object, and the leakage shape is generally set to be a ball shape or a long cone shape; filtering and denoising by adopting median filtering; the edge extraction method adopts a first-order differential operator Sobel; performing feature extraction on the image by using Hough transformation; the classifier adopts a Fisher classifier.
If the suspected leakage area P2 is found in S312, step S312 further includes the step of determining the suspected leakage area P2:
s313: obtaining a gray level change matrix by utilizing the difference between the position-gray level matrix of the current frame image and the position-gray level matrix of the previous frame image;
s314: and finding out an area with the gray change value larger than a preset gray change threshold value through the gray change matrix obtained in the step S313, and taking the intersection of the area and the suspected leakage area P2 in the step S312 as a new suspected leakage area P2.
By the above method, the suspected leaking region P2 is re-determined, and it can be further determined whether the region with the contour feature corresponding to the preset shape of the leaking object found in S312 is a region with a suddenly appearing leaking object, so as to eliminate the influence caused by environmental factors such as light.
Because the image obtained by the infrared camera can be mixed with relatively serious noise caused by the environmental temperature, the invention preferably determines the gray level change threshold value of the infrared image through a constant temperature calibration object in the field of view of the infrared camera, namely obtains the temperature of the specified calibration object through the infrared camera, and converts the temperature difference of two frames before and after the calibration object into the gray level change threshold value of the infrared image by utilizing a temperature-to-gray level conversion interface of the infrared camera.
The embodiments of the present invention have been written in a progressive manner with emphasis placed on the differences between the various embodiments, and similar elements may be found in relation to each other.
The embodiments of the present invention have been described in detail with reference to the drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
Claims (9)
1. The metal pipeline leakage monitoring method based on the infrared temperature field multivariate analysis is characterized by comprising the following steps of:
s1: shooting a monitoring area by using an infrared camera to obtain an infrared thermal image and temperature parameters of the pipeline and the surrounding environment of the pipeline;
s2: according to the infrared thermography and the temperature parameters obtained in the S1, establishing a position-gray matrix and a position-temperature matrix of the infrared thermography according to the gray scale and temperature information of each pixel point;
s3: determining an area with abnormal temperature change by using the position-temperature matrix, marking the area as a suspected leakage area P1, and simultaneously searching an area with contour characteristics matched with a preset leakage object shape by using the position-gray matrix, and marking the area as a suspected leakage area P2;
s4: and (4) calculating the coincidence ratio of the P1 and the P2, if the coincidence ratio is greater than the preset coincidence ratio, determining the coincidence area as a leakage area, and sending an alarm signal to the outside.
2. The metal pipeline leakage monitoring method based on the multivariate analysis on the infrared temperature field as set forth in claim 1, characterized in that:
in S3, the location-temperature matrix is used to determine the area with abnormal temperature change, which is marked as the suspected leakage area P1, and the specific steps are as follows:
s301: utilizing the position-temperature matrix to make difference between the position-temperature matrices of two adjacent frames of images to obtain a temperature change matrix;
s302: and traversing the temperature change matrix obtained in the step S301 by using a temperature change threshold template, determining an area with abnormal temperature change, obtaining position information of a communication area with abnormal temperature change, and marking as a suspected leakage area P1, wherein the temperature change threshold template is a 3 x 3 template established by a set temperature change threshold.
3. The metal pipeline leakage monitoring method based on the multivariate analysis on the infrared temperature field as set forth in claim 2, characterized in that: the temperature change threshold T is set as follows:
gas and liquid: t2 ═ T (T)From-TRing (C)) /3, wherein, TFromIndicating the temperature, T, of the material transported in the pipelineRing (C)Representing the average ambient temperature acquired by the infrared camera;
solid: t ═ T (T)From-TRing (C)) /2, wherein, TFromIndicating the temperature, T, of the material transported in the pipelineRing (C)Representing the average ambient temperature acquired by the infrared camera.
4. The metal pipeline leakage monitoring method based on the multivariate analysis on the infrared temperature field as set forth in claim 1, characterized in that:
in S3, a region whose contour features conform to the shape of the predetermined leakage is searched by using the position-grayscale matrix, and the specific steps of marking as a suspected leakage region P2 are as follows:
s311: filtering and denoising the infrared image and extracting an edge by using the position-gray matrix to obtain edge contour information;
s312: the edge contour obtained in S311 is identified by the classifier, and a region whose contour feature matches the shape of the predetermined leaking object is found and is marked as a suspected leaking region P2.
5. The method for monitoring the leakage of the metal pipeline based on the multivariate analysis of the infrared temperature field as set forth in claim 4, wherein: the preset shape of the leakage is a ball shape or a long cone shape.
6. The method for monitoring the leakage of the metal pipeline based on the multivariate analysis of the infrared temperature field as set forth in claim 4, wherein: in S311, a median filtering method is used to perform filtering and denoising processing on the infrared image, and a first order differential operator Sobel is used to perform edge extraction on the processed image.
7. The method for monitoring the leakage of the metal pipeline based on the multivariate analysis of the infrared temperature field as set forth in claim 4, wherein: in S312, Hough transformation is used for carrying out feature extraction on the image; the classifier adopts a Fisher classifier.
8. The method for monitoring the leakage of the metal pipeline based on the multivariate analysis of the infrared temperature field as set forth in claim 4, wherein: if the suspected leakage area P2 is found in S312, step S312 further includes the step of determining the suspected leakage area P2:
s313: obtaining a gray level change matrix by utilizing the difference between the position-gray level matrix of the current frame image and the position-gray level matrix of the previous frame image;
s314: and finding out an area with the gray change value larger than a preset gray change threshold value through the gray change matrix obtained in the step S313, and taking the intersection of the area and the suspected leakage area P2 in the step S312 as a new suspected leakage area P2.
9. The method for monitoring the leakage of the metal pipeline based on the multivariate analysis of the infrared temperature field as set forth in claim 8, wherein: the preset gray level change threshold is determined by a constant temperature calibration object in the field of view of the infrared camera, the temperature of the designated calibration object is obtained by the infrared camera, and the temperature difference between the front frame and the rear frame of the calibration object is converted into the infrared image gray level change threshold by utilizing a temperature-to-gray level conversion interface of the infrared camera.
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