Natural gas pipeline multi-angle jet fire heat radiation calculation method and system

Abstract

The invention provides a natural gas pipeline multi-angle jet fire heat radiation calculation method and system. The method comprises the following steps: acquiring jet fire visible light images and jet angles of jet fire at different angles at the current moment; for any jet fire visible light image, based on the jet angle of the corresponding jet fire, the segmentation window size of any jet fire visible light image is determined and segmentation is carried out, and then binarization is carried out on each visible light sub-image to obtain an initial segmentation image; inputting the initial segmentation image and any jet fire visible light image into an image segmentation model to obtain a segmentation image of the jet fire visible light image; and performing multi-view stereo matching based on the segmented image of each jet fire visible light image to obtain a depth map of the jet fire, performing three-dimensional reconstruction based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire so as to determine the surface area of the jet fire, and calculating thermal radiation at any position based on the surface area of the jet fire. And the calculation precision of heat radiation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal radiation calculation, and in particular to a method and system for calculating thermal radiation of multi-angle jet fires in a natural gas pipeline. Background Art

[0002] During the service life of a natural gas pipeline, it may be broken due to third-party damage, corrosion, human factors or construction quality problems, which may lead to natural gas leakage and cause serious consequences. When natural gas leaks from the pipeline, it will form a high-speed jet and spread. If the leak point is ignited, a jet flame will be generated. Jet flame is the most common and representative type of fire in gas pipeline fire accidents. It mainly affects the surrounding environment through thermal radiation, causing surrounding objects to burn and deform, and even causing casualties. Therefore, accurate calculation of thermal radiation is crucial.

[0003] Among them, the flame surface area is a key parameter in thermal radiation calculation, but since the flame shape is mostly irregular and the different injection angles of the leak port significantly affect the shape of the injection flame, it increases the difficulty of estimating the flame surface area. Therefore, a method that can accurately extract the flame shape to improve the accuracy of thermal radiation calculation is urgently needed. Summary of the invention

[0004] The present invention provides a method and system for calculating thermal radiation of multi-angle jet fire in a natural gas pipeline, which are used to improve the calculation accuracy of thermal radiation.

[0005] The present invention provides a method for calculating heat radiation of multi-angle jet fire in a natural gas pipeline, comprising: Acquire jet fire visible light images at different angles at the current moment, and determine the jet angle of the jet fire in each jet fire visible light image; For any jet fire visible light image, determining a segmentation window size of the any jet fire visible light image based on a jet angle of the corresponding jet fire, and segmenting the any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; Determine the segmentation threshold of each visible light sub-image respectively, and binarize each visible light sub-image based on the corresponding segmentation threshold to obtain an initial segmented image; Inputting the initial segmented image and any one of the jet fire visible light images into an image segmentation model to obtain a segmented image of any one of the jet fire visible light images output by the image segmentation model; Performing multi-view stereo matching based on the segmented images of the visible light images of each jet fire to obtain a depth map of the jet fire, and performing three-dimensional reconstruction based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; Based on the three-dimensional point cloud of the jet fire, the surface area of ​​the jet fire is determined, and the thermal radiation at any position is calculated based on the surface area of ​​the jet fire.

[0006] According to a method for calculating thermal radiation of multi-angle jet fires in a natural gas pipeline provided by the present invention, the method of determining the segmentation window size of any jet fire visible light image based on the jet angle of the corresponding jet fire comprises: The segmentation window size of any jet fire visible light image is determined based on the following formula:

[0007] in, is the segmentation window size of any jet fire visible light image, is the minimum window size, is the maximum window size, is the jet angle of the jet fire, It is the maximum spray angle of jet fire.

[0008] According to a method for calculating thermal radiation of multi-angle jet fire in a natural gas pipeline provided by the present invention, the image segmentation model is constructed based on an encoder-decoder model; Inputting the initial segmented image and any one of the jet fire visible light images into an image segmentation model to obtain a segmented image of any one of the jet fire visible light images output by the image segmentation model, comprising: Extracting features from the initial segmented image and any jet fire visible light image based on a plurality of downsampling layers of different scales of the first encoder in the image segmentation model to obtain a visible light feature map; Extracting features of the infrared image registered with any jet fire visible light image based on multiple downsampling layers of different scales of the second encoder in the image segmentation model to obtain an infrared feature map; Based on the feature fusion module in the image segmentation model, the visible light feature map and the infrared feature map are fused to obtain a jet fire fusion feature map; The jet fire fusion feature map is decoded based on multiple upsampling layers of different scales in a decoder in the image segmentation model to obtain the segmented image.

[0009] According to a method for calculating thermal radiation of multi-angle jet fires in a natural gas pipeline provided by the present invention, feature extraction is performed on the initial segmented image and any jet fire visible light image based on multiple downsampling layers of different scales of the first encoder in the image segmentation model to obtain a visible light feature map, including: Based on the first downsampling layer, feature extraction is performed on the initial segmentation image and any one of the jet fire visible light images to obtain an initial segmentation feature map and an initial visible light feature map; Based on the feature values ​​of each feature point in the initial segmentation feature map, weighting the feature values ​​of corresponding feature points in the initial visible light feature map to obtain a fused visible light feature map; Feature extraction is performed on the fused visible light feature map based on the remaining downsampling layers to obtain the visible light feature map.

[0010] According to a method for calculating thermal radiation of multi-angle jet fires in a natural gas pipeline provided by the present invention, the downsampling layer of the second encoder includes multiple convolutional layers and fusion layers, and the multiple convolutional layers use convolution kernels in different directions; the fusion layer is used to perform weighted fusion on feature maps output by the multiple convolutional layers based on weights corresponding to the multiple convolutional layers; wherein the weights corresponding to the multiple convolutional layers are determined based on the jet angles of the corresponding jet fires.

[0011] According to a method for calculating thermal radiation of multi-angle jet fire in a natural gas pipeline provided by the present invention, any upsampling layer is jump-connected with a downsampling layer of the same scale in the first encoder and a downsampling layer of the same scale in the second encoder.

[0012] According to a method for calculating thermal radiation of multi-angle jet fire in a natural gas pipeline provided by the present invention, the segmentation threshold of any visible light sub-image is the average value of the pixel value of each pixel point in the any visible light sub-image.

[0013] The present invention also provides a natural gas pipeline multi-angle jet fire heat radiation calculation system, comprising: An image acquisition unit, used to acquire visible light images of jet fire at different angles at the current moment, and determine the jet angle of the jet fire in each jet fire visible light image; a segmentation unit, configured to determine, for any jet fire visible light image, a segmentation window size of the any jet fire visible light image based on a jet angle of the corresponding jet fire, and segment the any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; A binarization unit is used to determine the segmentation threshold of each visible light sub-image respectively, and binarize each visible light sub-image based on the corresponding segmentation threshold to obtain an initial segmented image; a segmentation unit, configured to input the initial segmented image and any one of the jet fire visible light images into an image segmentation model, and obtain a segmented image of any one of the jet fire visible light images output by the image segmentation model; a three-dimensional reconstruction unit, configured to perform multi-view stereo matching based on the segmented images of the visible light images of each jet fire to obtain a depth map of the jet fire, and perform three-dimensional reconstruction based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; The heat radiation calculation unit is used for determining the surface area of ​​the jet fire based on the three-dimensional point cloud of the jet fire, and calculating the heat radiation at any position based on the surface area of ​​the jet fire.

[0014] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any one of the above-mentioned methods for calculating the thermal radiation of multi-angle jet fire in a natural gas pipeline is implemented.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned methods for calculating thermal radiation of multi-angle jet fire in a natural gas pipeline.

[0016] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-mentioned methods for calculating thermal radiation of multi-angle jet fire in a natural gas pipeline.

[0017] The method and system for calculating the thermal radiation of multi-angle jet fires in a natural gas pipeline provided by the present invention obtain visible light images of jet fires at different angles at the current moment, and determine the jet angle of the jet fire in each visible light image of the jet fire; for any jet fire visible light image, based on the jet angle of the corresponding jet fire, determine the segmentation window size of any jet fire visible light image, and segment any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; respectively determine the segmentation threshold of each visible light sub-image, and binarize each visible light sub-image based on the corresponding segmentation threshold to obtain an initial segmented image; and convert the initial segmented image into a binary image; and any jet fire visible light image are input into the image segmentation model to obtain a segmented image of any jet fire visible light image output by the image segmentation model; multi-view stereo matching is performed based on the segmented images of each jet fire visible light image to obtain a depth map of the jet fire, and three-dimensional reconstruction is performed based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; based on the three-dimensional point cloud of the jet fire, the surface area of ​​the jet fire is determined, and the thermal radiation at any position is calculated based on the surface area of ​​the jet fire. This scheme can be applied to the analysis of jet fire field test results as a data reference for optimizing a theoretical model for jet fire thermal radiation calculation, thereby improving the calculation accuracy of thermal radiation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a flow chart of a method for calculating the thermal radiation of multi-angle jet fire in a natural gas pipeline provided by the present invention; Figure 2 It is a structural schematic diagram of the image segmentation model provided by the present invention; Figure 3 It is a structural schematic diagram of a natural gas pipeline multi-angle jet fire heat radiation calculation device provided by the present invention; Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Figure 1 FIG. 1 is a flow chart of a method for calculating the thermal radiation of multi-angle jet fire in a natural gas pipeline provided by the present invention. Figure 1 As shown, the method includes: Step 110, obtaining visible light images of jet fire at different angles at the current moment, and determining the jet angle of the jet fire in each jet fire visible light image; Step 120, for any jet fire visible light image, determining a segmentation window size of the any jet fire visible light image based on a jet angle of the corresponding jet fire, and segmenting the any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; Step 130, determining the segmentation threshold of each visible light sub-image respectively, and binarizing each visible light sub-image based on the corresponding segmentation threshold to obtain an initial segmented image; Step 140, inputting the initial segmented image and any one of the jet fire visible light images into an image segmentation model, and obtaining a segmented image of any one of the jet fire visible light images output by the image segmentation model; Step 150, performing multi-view stereo matching based on the segmented images of each jet fire visible light image to obtain a depth map of the jet fire, and performing three-dimensional reconstruction based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; In step 160 , the surface area of ​​the jet fire is determined based on the three-dimensional point cloud of the jet fire, and the thermal radiation at any position is calculated based on the surface area of ​​the jet fire.

[0022] Here, the jet fire visible light images at different angles (i.e., different directions of the jet fire scene) at the current moment can be captured in real time based on a high-speed camera, and the jet angle of the jet fire relative to the horizontal direction in each jet fire visible light image can be determined. It should be noted that the jet fire visible light image can be obtained through field tests or through CFD simulations, and the embodiments of the present invention do not specifically limit this. Among them, the jet angle of the jet fire in each jet fire visible light image can be estimated based on the direction of the leakage port of the natural gas pipeline and the position and camera parameters of the camera that captures each jet fire visible light image. In addition, the edge of the flame area in the jet fire visible light image can also be extracted by an edge detection algorithm to determine the main direction of the flame area and determine the jet angle of the jet fire, and the embodiments of the present invention do not specifically limit this.

[0023] Considering that there is a messy background in the visible light image of the jet fire, which will interfere with the extraction of the flame area, and the edge of the flame (such as the flame tip) has the problem of edge blur, which reduces the accuracy of capturing the flame shape and the calculation accuracy of the flame surface area. Therefore, a more accurate flame segmentation scheme is needed to accurately extract the flame area for subsequent quantification of the flame surface area. Here, for any jet fire visible light image, the flame area can be roughly extracted first, and then the jet fire visible light image and the roughly extracted flame area can be jointly learned using a deep learning mechanism, and the shape information, edge information and texture information of the flame provided in the roughly extracted flame area can be used to assist in extracting image semantics, so as to improve the accuracy of flame area segmentation.

[0024] Specifically, considering the different edge morphologies (e.g., edge smoothness) and background noise interference levels of jet fires at different injection angles, in order to improve the accuracy of the rough extraction of the flame area, for any jet fire visible light image, the segmentation window size of the jet fire visible light image can be determined based on the injection angle of the corresponding jet fire, and the jet fire visible light image can be segmented based on the segmentation window size to obtain multiple visible light sub-images. The larger the injection angle, the smaller the segmentation window size.

[0025] In some embodiments, the segmentation window size of any jet fire visible light image may be determined based on the following formula:

[0026] in, is the segmentation window size of the jet fire visible light image, is the minimum window size, is the maximum window size, is the jet angle of the jet fire, It is the maximum spray angle of jet fire.

[0027] Subsequently, the segmentation threshold of each visible light sub-image is determined respectively, and each visible light sub-image is binarized based on the corresponding segmentation threshold to obtain an initial segmented image. The segmentation threshold of any visible light sub-image is the average value of the pixel value of each pixel in the visible light sub-image. Based on the segmentation threshold of any visible light sub-image, the binary pixel value of the pixel point in the visible light sub-image with a pixel value higher than the segmentation threshold can be set to 1, and the flame area can be determined from the visible light sub-image based on the pixel point with a binary pixel value of 1. The pixel values ​​of the pixel points in the non-flame area in each visible light sub-image are set to 0 and then integrated to obtain the initial segmented image corresponding to the jet fire visible light image, thereby achieving a rough extraction of the flame area.

[0028] An initial segmented image corresponding to any jet fire visible light image and the jet fire visible light image are input together into an image segmentation model based on a deep learning mechanism to obtain a segmented image of the jet fire visible light image output by the image segmentation model.

[0029] In some embodiments, an image segmentation model can be constructed based on an encoder-decoder model. It should be noted that in order to improve the accuracy of flame segmentation, the rich temperature information in the infrared image can be introduced to assist in segmenting the flame area. Figure 2 As shown, an encoder branch can be introduced into the encoder-decoder model, that is, a model structure including two encoders and one decoder is formed. For the convenience of explanation, the encoder responsible for the semantic encoding of the visible light image is called the first encoder, and the encoder responsible for the semantic encoding of the infrared image is called the second encoder.

[0030] Among them, multiple downsampling layers of different scales in the first encoder are used to extract features from any jet fire visible light image and its corresponding initial segmented image to obtain a visible light feature map; multiple downsampling layers of different scales (consistent with the scale of the downsampling layer in the first encoder) in the second encoder are used to extract features from the infrared image registered with the jet fire visible light image to obtain an infrared feature map. The image segmentation model also includes a feature fusion module for fusing the visible light feature map and the infrared feature map to obtain a jet fire fusion feature map. In some embodiments, the visible light feature map and the infrared feature map can be fused by channel, that is, the feature sub-maps of the same channel in the visible light feature map and the infrared feature map are superimposed to achieve feature map fusion. Subsequently, multiple upsampling layers of different scales (corresponding to the scale of the downsampling layer) in the decoder decode the jet fire fusion feature map to obtain a segmented image of the jet fire visible light image. In some embodiments, a UNet network can be referred to to establish a jump connection between the decoder and the encoder to improve the performance of the decoder, but unlike the UNet network, in the image segmentation model in the embodiment of the present invention, any upsampling layer is simultaneously jump-connected to the downsampling layer of the same scale in the first encoder and the downsampling layer of the same scale in the second encoder to utilize the image features of the visible light image and the image features of the infrared image generated in the two encoders. Specifically, the input of the upsampling layer includes the feature map output by the previous upsampling layer (if it is the first upsampling layer, it is the jet fire fusion feature map), the feature map output by the downsampling layer of the same scale in the first encoder, and the feature map output by the downsampling layer of the same scale in the second encoder.

[0031] In some embodiments, when the multiple downsampling layers of different scales of the first encoder perform feature extraction on the jet fire visible light image and its corresponding initial segmentation image, feature extraction can be performed on the initial segmentation image and the jet fire visible light image based on the first downsampling layer to obtain an initial segmentation feature map and an initial visible light feature map. Subsequently, based on the feature values ​​of each feature point in the initial segmentation feature map, the feature values ​​of the corresponding feature points in the above initial visible light feature map are weighted to obtain a fused visible light feature map. Then, feature extraction is performed on the fused visible light feature map based on the remaining downsampling layers to obtain a visible light feature map. It should be noted that the image semantics (such as edge information, shape information, and texture information, etc.) contained in the roughly extracted flame area are relatively low-level image semantics, so only adding it to the encoding process of the shallow downsampling layer can better guide the semantic encoding of the first encoder and reduce the encoding operation of the first encoder, thereby improving the encoding efficiency while improving the semantic encoding capability.

[0032] In other embodiments, considering that the temperature distribution in the infrared image has directional characteristics, and the direction of change of the temperature distribution is strongly related to the injection angle of the jet fire, in order to improve the encoding ability of the second encoder for the infrared image, the downsampling layer of the second encoder can be designed as a combination of multiple convolutional layers and fusion layers. Among them, the multiple convolutional layers use convolution kernels with different directions, and the fusion layer is used to perform weighted fusion of the feature maps output by the multiple convolutional layers based on the weights corresponding to the multiple convolutional layers. Here, the weights corresponding to the multiple convolutional layers are determined based on the injection angle of the corresponding jet fire. The closer the direction of the convolution kernel used in any convolutional layer is to the injection angle of the corresponding jet fire, the higher the weight corresponding to the convolutional layer.

[0033] After obtaining the segmented images of each jet fire visible light image output by the image segmentation model, a multi-view image matching model, such as CasMVSNet, can be used to perform multi-view stereo matching on the segmented images of each jet fire visible light image to obtain a depth map of the jet fire. Subsequently, a three-dimensional model tool library, such as Open3D, is used to perform three-dimensional reconstruction of the depth map of the jet fire, and the depth map of the jet fire is converted into a three-dimensional point cloud, and then the surface area of ​​the jet fire is determined based on the three-dimensional point cloud of the jet fire. After obtaining the surface area of ​​the jet fire, the thermal radiation at any position can be calculated based on the thermal radiation calculation formula. For example, thermal radiation calculation can be performed based on the thermal radiation formula of the Thornton model. It should be noted that based on the image segmentation scheme and the three-dimensional reconstruction scheme given in the above embodiment, the morphology of the jet flame can be captured more accurately, and then the thermal radiation result can be calculated based on the theoretical model of thermal radiation calculation. The thermal radiation result can be used as a reference for the theoretical model, which helps to optimize the accuracy of the estimation of the surface area of ​​the jet fire in the theoretical model, thereby improving the calculation accuracy of the theoretical model for the thermal radiation of the jet fire.

[0034] In summary, the method provided by the embodiment of the present invention obtains jet fire visible light images at different angles at the current moment, and determines the jet angle of the jet fire in each jet fire visible light image; for any jet fire visible light image, based on the jet angle of the corresponding jet fire, determines the segmentation window size of any jet fire visible light image, and segments any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; determines the segmentation threshold of each visible light sub-image, and binarizes each visible light sub-image based on the corresponding segmentation threshold to obtain an initial segmented image; and compares the initial segmented image with any jet fire visible light image. The visible light image is input into the image segmentation model to obtain a segmented image of any jet fire visible light image output by the image segmentation model; multi-view stereo matching is performed based on the segmented images of each jet fire visible light image to obtain a depth map of the jet fire, and three-dimensional reconstruction is performed based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; based on the three-dimensional point cloud of the jet fire, the surface area of ​​the jet fire is determined, and the thermal radiation at any position is calculated based on the surface area of ​​the jet fire. This scheme can be applied to the analysis of jet fire field test results as a data reference for optimizing the theoretical model for jet fire thermal radiation calculation, thereby improving the calculation accuracy of thermal radiation.

[0035] The following is a description of the device for calculating the thermal radiation of multi-angle jet fire in a natural gas pipeline provided by the present invention. The device for calculating the thermal radiation of multi-angle jet fire in a natural gas pipeline described below and the method for calculating the thermal radiation of multi-angle jet fire in a natural gas pipeline described above can be referred to each other.

[0036] Based on any of the above embodiments, Figure 3 Schematic diagram of the structure of the multi-angle jet fire heat radiation calculation device for natural gas pipeline provided by the present invention. Figure 3 As shown, the device comprises: The image acquisition unit 310 is used to acquire visible light images of jet fire at different angles at the current moment, and determine the jet angle of the jet fire in each jet fire visible light image; a segmentation unit 320, configured to determine, for any jet fire visible light image, a segmentation window size of the any jet fire visible light image based on a jet angle of the corresponding jet fire, and segment the any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; A binarization unit 330 is used to determine the segmentation threshold of each visible light sub-image respectively, and binarize each visible light sub-image based on the corresponding segmentation threshold to obtain an initial segmented image; A segmentation unit 340 is used to input the initial segmented image and any one of the jet fire visible light images into an image segmentation model to obtain a segmented image of any one of the jet fire visible light images output by the image segmentation model; A 3D reconstruction unit 350 is used to perform multi-view stereo matching based on the segmented images of each jet fire visible light image to obtain a depth map of the jet fire, and perform 3D reconstruction based on the depth map of the jet fire to obtain a 3D point cloud of the jet fire; The heat radiation calculation unit 360 is used to determine the surface area of ​​the jet fire based on the three-dimensional point cloud of the jet fire, and calculate the heat radiation at any position based on the surface area of ​​the jet fire.

[0037] The device provided by the embodiment of the present invention obtains jet fire visible light images at different angles at the current moment, and determines the jet angle of the jet fire in each jet fire visible light image; for any jet fire visible light image, based on the jet angle of the corresponding jet fire, determines the segmentation window size of any jet fire visible light image, and segments any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; determines the segmentation threshold of each visible light sub-image, and binarizes each visible light sub-image based on the corresponding segmentation threshold, to obtain an initial segmented image; and compares the initial segmented image with any jet fire visible light image. The optical image is input into the image segmentation model to obtain a segmented image of any jet fire visible light image output by the image segmentation model; multi-view stereo matching is performed based on the segmented images of each jet fire visible light image to obtain a depth map of the jet fire, and three-dimensional reconstruction is performed based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; based on the three-dimensional point cloud of the jet fire, the surface area of ​​the jet fire is determined, and the thermal radiation at any position is calculated based on the surface area of ​​the jet fire. This scheme can be applied to the analysis of the results of jet fire field tests as a data reference for optimizing the theoretical model for jet fire thermal radiation calculation, thereby improving the calculation accuracy of thermal radiation.

[0038] Based on any of the above embodiments, determining the segmentation window size of any jet fire visible light image based on the jet angle of the corresponding jet fire includes: The segmentation window size of any jet fire visible light image is determined based on the following formula:

[0039] in, is the segmentation window size of any jet fire visible light image, is the minimum window size, is the maximum window size, is the jet angle of the jet fire, It is the maximum spray angle of jet fire.

[0040] Based on any of the above embodiments, the image segmentation model is constructed based on an encoder-decoder model; Inputting the initial segmented image and any one of the jet fire visible light images into an image segmentation model to obtain a segmented image of any one of the jet fire visible light images output by the image segmentation model, comprising: Extracting features from the initial segmented image and any jet fire visible light image based on a plurality of downsampling layers of different scales of the first encoder in the image segmentation model to obtain a visible light feature map; Extracting features of the infrared image registered with any jet fire visible light image based on multiple downsampling layers of different scales of the second encoder in the image segmentation model to obtain an infrared feature map; Based on the feature fusion module in the image segmentation model, the visible light feature map and the infrared feature map are fused to obtain a jet fire fusion feature map; The jet fire fusion feature map is decoded based on multiple upsampling layers of different scales in a decoder in the image segmentation model to obtain the segmented image.

[0041] Based on any of the above embodiments, performing feature extraction on the initial segmented image and any of the jet fire visible light images based on multiple downsampling layers of different scales of the first encoder in the image segmentation model to obtain a visible light feature map includes: Based on the first downsampling layer, feature extraction is performed on the initial segmentation image and any one of the jet fire visible light images to obtain an initial segmentation feature map and an initial visible light feature map; Based on the feature values ​​of each feature point in the initial segmentation feature map, weighting the feature values ​​of corresponding feature points in the initial visible light feature map to obtain a fused visible light feature map; Feature extraction is performed on the fused visible light feature map based on the remaining downsampling layers to obtain the visible light feature map.

[0042] Based on any of the above embodiments, the downsampling layer of the second encoder includes multiple convolutional layers and fusion layers, the multiple convolutional layers use convolution kernels in different directions; the fusion layer is used to perform weighted fusion on the feature maps output by the multiple convolutional layers based on the weights corresponding to the multiple convolutional layers; wherein the weights corresponding to the multiple convolutional layers are determined based on the injection angle of the corresponding jet fire.

[0043] Based on any of the foregoing embodiments, any upsampling layer is jump-connected to a downsampling layer of the same scale in the first encoder and a downsampling layer of the same scale in the second encoder.

[0044] Based on any of the above embodiments, the segmentation threshold of any visible light sub-image is an average value of the pixel value of each pixel point in the any visible light sub-image.

[0045] Figure 4is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 4 As shown, the electronic device may include: a processor 410, a memory 420, a communications interface 430 and a communication bus 440, wherein the processor 410, the memory 420 and the communications interface 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 420 to execute the method for calculating the thermal radiation of multi-angle jet fires in a natural gas pipeline, the method comprising: obtaining visible light images of jet fires at different angles at the current moment, and determining the jet angle of the jet fire in each jet fire visible light image; for any jet fire visible light image, based on the jet angle of the corresponding jet fire, determining the segmentation window size of any jet fire visible light image, and segmenting any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; determining the segmentation threshold of each visible light sub-image respectively, and based on Binarizing each visible light sub-image at a corresponding segmentation threshold to obtain an initial segmented image; inputting the initial segmented image and any one of the jet fire visible light images into an image segmentation model to obtain a segmented image of any one of the jet fire visible light images output by the image segmentation model; performing multi-view stereo matching based on the segmented images of each of the jet fire visible light images to obtain a depth map of the jet fire, and performing three-dimensional reconstruction based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; determining the surface area of ​​the jet fire based on the three-dimensional point cloud of the jet fire, and calculating the thermal radiation at any position based on the surface area of ​​the jet fire.

[0046] In addition, the logic instructions in the above-mentioned memory 420 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0047] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, and when the program instructions are executed by a computer, the computer can execute the method for calculating the thermal radiation of multi-angle jet fires in a natural gas pipeline provided by the above methods, the method comprising: acquiring visible light images of jet fires at different angles at the current moment, and determining the jet angle of the jet fire in each jet fire visible light image; for any jet fire visible light image, based on the jet angle of the corresponding jet fire, determining the size of a segmentation window of the any jet fire visible light image, and segmenting the any jet fire visible light image based on the segmentation window size The method comprises the steps of: performing multi-view stereo matching based on the segmented images of each jet fire visible light image to obtain a depth map of the jet fire, and performing three-dimensional reconstruction based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; determining the surface area of ​​the jet fire based on the three-dimensional point cloud of the jet fire, and calculating the thermal radiation at any position based on the surface area of ​​the jet fire.

[0048] On the other hand, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to execute the above-mentioned natural gas pipeline multi-angle jet fire thermal radiation calculation method, the method comprising: obtaining jet fire visible light images at different angles at the current moment, and determining the jet angle of the jet fire in each jet fire visible light image; for any jet fire visible light image, based on the jet angle of the corresponding jet fire, determining the segmentation window size of any jet fire visible light image, and segmenting any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; respectively Determine a segmentation threshold of each visible light sub-image, and binarize each visible light sub-image based on the corresponding segmentation threshold to obtain an initial segmented image; input the initial segmented image and any jet fire visible light image into an image segmentation model to obtain a segmented image of any jet fire visible light image output by the image segmentation model; perform multi-view stereo matching based on the segmented images of each jet fire visible light image to obtain a depth map of the jet fire, and perform three-dimensional reconstruction based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; determine the surface area of ​​the jet fire based on the three-dimensional point cloud of the jet fire, and calculate the thermal radiation at any position based on the surface area of ​​the jet fire.

[0049] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0050] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating heat radiation of multi-angle jet fire in a natural gas pipeline, characterized in that: include: Acquire jet fire visible light images at different angles at the current moment, and determine the jet angle of the jet fire in each jet fire visible light image; For any jet fire visible light image, determining a segmentation window size of the any jet fire visible light image based on a jet angle of the corresponding jet fire, and segmenting the any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; Determine the segmentation threshold of each visible light sub-image respectively, and binarize each visible light sub-image based on the corresponding segmentation threshold to obtain an initial segmented image; Inputting the initial segmented image and any one of the jet fire visible light images into an image segmentation model to obtain a segmented image of any one of the jet fire visible light images output by the image segmentation model; Performing multi-view stereo matching based on the segmented images of the visible light images of each jet fire to obtain a depth map of the jet fire, and performing three-dimensional reconstruction based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; Based on the three-dimensional point cloud of the jet fire, the surface area of ​​the jet fire is determined, and the thermal radiation at any position is calculated based on the surface area of ​​the jet fire.

2. The method for calculating heat radiation of multi-angle jet fire in a natural gas pipeline according to claim 1 is characterized in that: The determining of the segmentation window size of any jet fire visible light image based on the jet angle of the corresponding jet fire comprises: The segmentation window size of any jet fire visible light image is determined based on the following formula: in, is the segmentation window size of any jet fire visible light image, is the minimum window size, is the maximum window size, is the jet angle of the jet fire, It is the maximum spray angle of jet fire.

3. The method for calculating heat radiation of multi-angle jet fire in a natural gas pipeline according to claim 1 or 2, characterized in that: The image segmentation model is constructed based on an encoder-decoder model; Inputting the initial segmented image and any one of the jet fire visible light images into an image segmentation model to obtain a segmented image of any one of the jet fire visible light images output by the image segmentation model, comprising: Extracting features from the initial segmented image and any jet fire visible light image based on a plurality of downsampling layers of different scales of the first encoder in the image segmentation model to obtain a visible light feature map; Extracting features of the infrared image registered with any jet fire visible light image based on multiple downsampling layers of different scales of the second encoder in the image segmentation model to obtain an infrared feature map; Based on the feature fusion module in the image segmentation model, the visible light feature map and the infrared feature map are fused to obtain a jet fire fusion feature map; The jet fire fusion feature map is decoded based on multiple upsampling layers of different scales in a decoder in the image segmentation model to obtain the segmented image.

4. The method for calculating heat radiation of multi-angle jet fire in a natural gas pipeline according to claim 3 is characterized in that: The method further comprises: extracting features of the initial segmented image and any jet fire visible light image based on a plurality of downsampling layers of different scales of the first encoder in the image segmentation model to obtain a visible light feature map, including: Based on the first downsampling layer, feature extraction is performed on the initial segmentation image and any one of the jet fire visible light images to obtain an initial segmentation feature map and an initial visible light feature map; Based on the feature values ​​of each feature point in the initial segmentation feature map, weighting the feature values ​​of corresponding feature points in the initial visible light feature map to obtain a fused visible light feature map; Feature extraction is performed on the fused visible light feature map based on the remaining downsampling layers to obtain the visible light feature map.

5. The method for calculating heat radiation of multi-angle jet fire in a natural gas pipeline according to claim 3 is characterized in that: The downsampling layer of the second encoder includes multiple convolutional layers and fusion layers, the multiple convolutional layers use convolution kernels in different directions; the fusion layer is used to perform weighted fusion on the feature maps output by the multiple convolutional layers based on the weights corresponding to the multiple convolutional layers; wherein the weights corresponding to the multiple convolutional layers are determined based on the injection angle of the corresponding jet fire.

6. The method for calculating heat radiation of multi-angle jet fire in a natural gas pipeline according to claim 3 is characterized in that: Any upsampling layer is jump-connected to a downsampling layer of the same scale in the first encoder and a downsampling layer of the same scale in the second encoder.

7. The method for calculating heat radiation of multi-angle jet fire in a natural gas pipeline according to claim 1 or 2, characterized in that: The segmentation threshold of any visible light sub-image is the average value of the pixel value of each pixel point in the any visible light sub-image.

8. A natural gas pipeline multi-angle jet fire heat radiation calculation system, characterized in that: include: An image acquisition unit, used to acquire visible light images of jet fire at different angles at the current moment, and determine the jet angle of the jet fire in each jet fire visible light image; a segmentation unit, configured to determine, for any jet fire visible light image, a segmentation window size of the any jet fire visible light image based on a jet angle of the corresponding jet fire, and segment the any jet fire visible light image based on the segmentation window size to obtain a plurality of visible light sub-images; A binarization unit is used to determine the segmentation threshold of each visible light sub-image respectively, and binarize each visible light sub-image based on the corresponding segmentation threshold to obtain an initial segmented image; a segmentation unit, configured to input the initial segmented image and any one of the jet fire visible light images into an image segmentation model, and obtain a segmented image of any one of the jet fire visible light images output by the image segmentation model; a three-dimensional reconstruction unit, configured to perform multi-view stereo matching based on the segmented images of the visible light images of each jet fire to obtain a depth map of the jet fire, and perform three-dimensional reconstruction based on the depth map of the jet fire to obtain a three-dimensional point cloud of the jet fire; The heat radiation calculation unit is used for determining the surface area of ​​the jet fire based on the three-dimensional point cloud of the jet fire, and calculating the heat radiation at any position based on the surface area of ​​the jet fire.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for calculating the thermal radiation of multi-angle jet fire in a natural gas pipeline as described in any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for calculating the thermal radiation of multi-angle jet fire in a natural gas pipeline as claimed in any one of claims 1 to 7 is implemented.

Images