Boiler pressure vessel inspection and detection method

Abstract

The invention relates to a boiler pressure vessel inspection and detection method, and relates to the technical field of pressure detection. The method mainly comprises the following steps: acquiring an outer surface image of a boiler pressure vessel to which magnetic powder or penetrating fluid is applied; determining whether the outer surface of the boiler pressure vessel has cracks according to the outer surface image; if it is determined that the outer surface of the boiler pressure vessel does not have cracks, whether cracks appear on the inner surface of the boiler pressure vessel or not is determined according to the ultrasonic data and the ray data of the boiler pressure vessel; if cracks appear on the inner surface of the boiler pressure vessel and / or cracks appear on the outer surface of the boiler pressure vessel, carrying out analog simulation according to the operation data and the overall physical data of the boiler pressure vessel to obtain an analog simulation model, inputting the physical data of the position area of the crack area into an analog simulation model for analog simulation to obtain an analog simulation crack result; and determining a final crack result of the boiler pressure vessel according to the simulation crack result and the crack appearing in the position area.

Description

Technical Field

[0001] This invention relates to the field of pressure testing technology, and in particular to a method for inspecting and testing boiler pressure vessels. Background Technology

[0002] With the continuous development of my country's industrial technology, the application of boilers and pressure vessels is becoming increasingly widespread, and their safe operation is receiving more and more attention. To ensure the safe operation of boilers and pressure vessels, regular inspections are essential. However, in actual inspections, due to the complex structure of boilers and pressure vessels, various malfunctions are prone to occur, leading to accidents. Therefore, to effectively avoid accidents, it is crucial to strengthen the regular inspection of boilers and pressure vessels to ensure their safe operation.

[0003] In the manufacturing process of boilers and pressure vessels, a large amount of materials and components are typically used, and they operate under high temperature and high pressure conditions. Once cracks appear, they can cause serious accidents. Therefore, cracks are one of the main failures of boilers and pressure vessels.

[0004] Currently, boiler and pressure vessel inspection departments rely entirely on manual labor to inspect the internal and external surfaces of boilers and pressure vessels. Inspectors use flashlights and hammers to continuously shine light on and knock on the surfaces. As a result, the inspection efficiency of existing boiler and pressure vessels is relatively low. Summary of the Invention

[0005] The present invention aims to provide a method for inspecting and testing boilers and pressure vessels to overcome the shortcomings of the existing technology. The technical problem to be solved by the present invention is achieved through the following technical solution.

[0006] This invention provides a method for inspecting and testing boilers and pressure vessels, the method comprising:

[0007] Apply magnetic powder or penetrant to the outer surface of the boiler pressure vessel to obtain an image of the outer surface of the boiler pressure vessel to which the magnetic powder or penetrant has been applied;

[0008] Determine whether cracks appear on the outer surface of the boiler pressure vessel based on the outer surface image;

[0009] If it is determined that no cracks appear on the outer surface of the boiler pressure vessel, then the ultrasonic data and X-ray data of the boiler pressure vessel are acquired.

[0010] Determine whether cracks appear on the inner surface of the boiler pressure vessel based on the ultrasonic and radiographic data of the boiler pressure vessel.

[0011] If cracks appear on the inner surface of the boiler pressure vessel and / or on the outer surface of the boiler pressure vessel, then obtain the regional physical data of the location area of ​​the cracks on the inner and / or outer surfaces of the boiler pressure vessel.

[0012] The simulation model is obtained by simulating the operating data and overall physical data of the boiler pressure vessel. The physical data of the location of the cracked area is then input into the simulation model to obtain the simulation crack result.

[0013] The final crack result of the boiler pressure vessel is determined based on the simulated crack results and the cracks appearing in the specified location area.

[0014] In an optional embodiment, determining whether cracks appear on the outer surface of the boiler pressure vessel based on the outer surface image includes:

[0015] The outer surface image is divided into N sub-outer surface images of the same unit size, and each sub-outer surface image corresponds to an image position relationship;

[0016] M non-adjacent sub-outer surface images are randomly selected from the N sub-outer surface images;

[0017] Determine whether cracks appear in M ​​non-adjacent sub-exterior surface images;

[0018] If cracks appear in the M extracted sub-external surface images, then determine whether cracks appear in the sub-external surface images of the surrounding area based on the sub-external surface image with cracks.

[0019] If no cracks are found in the M extracted sub-exterior surface images, then M non-adjacent sub-exterior surface images are randomly selected from the remaining NM sub-exterior surface images, until all sub-exterior surface images are extracted or a sub-exterior surface image with cracks is extracted.

[0020] In an optional embodiment, determining whether a crack appears in the sub-outer surface image of the region surrounding the cracked sub-outer surface image includes:

[0021] Obtain the outer surface images of the surrounding 8 adjacent regions of the sub-outer surface image where the crack appears;

[0022] Determine whether cracks appear in the outer surface images of the eight surrounding adjacent regions;

[0023] If no cracks appear in the outer surface images of the surrounding 8 adjacent regions, then the outer surface images of the surrounding 8 adjacent regions of the next cracked sub-outer surface image are obtained, and it is determined whether cracks appear in the outer surface images of the surrounding 8 adjacent regions, until the outer surface images of the surrounding 8 adjacent regions of all cracked sub-outer surface images are obtained.

[0024] If cracks appear in the outer surface images of the eight surrounding adjacent regions, the outer surface image with cracks is determined as the sub-outer surface image with cracks, and the process jumps to the step of obtaining the outer surface images of the eight surrounding adjacent regions of the sub-outer surface image with cracks to continue execution.

[0025] In an optional embodiment, determining whether cracks appear in M ​​non-adjacent sub-outer surface images includes:

[0026] Preprocess the images of M non-adjacent sub-outer surfaces;

[0027] The preprocessed M non-adjacent sub-exterior surface images are input into the crack recognition model to obtain the crack recognition result corresponding to each sub-exterior surface image.

[0028] In an optional embodiment, determining whether cracks appear on the inner surface of the boiler pressure vessel based on ultrasonic and radiographic data includes:

[0029] The first crack result is determined based on the ultrasonic data of the boiler pressure vessel; the second crack result is determined based on the X-ray data of the boiler pressure vessel; and the third crack result is determined based on the ultrasonic data and X-ray data of the boiler pressure vessel.

[0030] Based on the first crack result, the second crack result, and the third crack result, determine whether cracks have appeared on the inner surface of the boiler pressure vessel.

[0031] In an optional embodiment, determining the first crack result based on the ultrasonic data of the boiler pressure vessel includes:

[0032] The ultrasonic transverse velocity, ultrasonic longitudinal velocity, and flight time are calculated based on the ultrasonic data of the boiler pressure vessel.

[0033] The first crack result is determined by the transverse velocity of the wave, the longitudinal velocity of the ultrasonic wave, and the flight time. The first crack result includes the crack location.

[0034] In an optional embodiment, determining the second crack result based on the radiographic data of the boiler pressure vessel includes:

[0035] Acquire the X-ray data of the boiler pressure vessel and obtain a projection image based on the X-ray data;

[0036] The projected image is subjected to image enhancement processing, contrast enhancement processing, edge processing, and noise reduction processing;

[0037] The result of the second crack was determined based on the processed projection image.

[0038] In an optional embodiment, determining the third crack result based on the ultrasonic and radiographic data of the boiler pressure vessel includes:

[0039] The ultrasonic and X-ray data of the boiler pressure vessel are converted into feature vectors;

[0040] The feature vector is input into the internal crack identification model to obtain the third crack result of the boiler pressure vessel.

[0041] In an optional embodiment, determining the final crack result of the boiler pressure vessel based on the simulated crack results and the cracks appearing in the location region includes:

[0042] The simulated crack results and the cracks appearing in the location area are matched and merged to obtain the final crack results of the boiler pressure vessel.

[0043] This invention provides a boiler and pressure vessel inspection and testing device, the device comprising:

[0044] The acquisition module is used to apply magnetic powder or penetrating liquid to the outer surface of the boiler pressure vessel in order to obtain an image of the outer surface of the boiler pressure vessel with applied magnetic powder or penetrating liquid.

[0045] A determination module is used to determine whether cracks appear on the outer surface of the boiler pressure vessel based on the outer surface image.

[0046] The acquisition module is further configured to acquire ultrasonic data, X-ray data, and pressure data of the boiler pressure vessel if it is determined that no cracks have appeared on the outer surface of the boiler pressure vessel.

[0047] The determining module is also used to determine whether cracks appear on the inner surface of the boiler pressure vessel based on the ultrasonic data, X-ray data and pressure data of the boiler pressure vessel.

[0048] The acquisition module is further configured to acquire regional physical data of the location area of ​​the crack on the inner surface and / or outer surface of the boiler pressure vessel if a crack appears on the inner surface and / or the outer surface of the boiler pressure vessel.

[0049] The simulation module is used to perform simulation based on the operating data and overall physical data of the boiler pressure vessel to obtain a simulation model, and input the physical data of the location of the cracked area into the simulation model to obtain the simulation crack result.

[0050] The determining module is further configured to determine the final crack result of the boiler pressure vessel based on the simulated crack result and the cracks appearing in the location area.

[0051] The embodiments of the present invention have the following advantages:

[0052] This invention provides a method and apparatus for inspecting and testing boiler pressure vessels. First, magnetic powder or penetrating liquid is applied to the outer surface of the boiler pressure vessel to obtain an image of the outer surface. Then, based on the image, it is determined whether cracks appear on the outer surface. If no cracks are found, ultrasonic and radiographic data of the boiler pressure vessel are acquired. Next, based on the ultrasonic and radiographic data, it is determined whether cracks appear on the inner surface of the boiler pressure vessel. If cracks appear on the inner and / or outer surfaces, regional physical data of the crack locations are acquired. A simulation model is obtained based on the boiler pressure vessel's operating data and overall physical data. The physical data of the crack locations are input into the simulation model to obtain simulated crack results. Finally, the final crack result of the boiler pressure vessel is determined based on the simulated crack results and the crack locations. Compared with the current method of manually inspecting boiler pressure vessels, this application inspects the outer surface of the boiler pressure vessel based on acquired external surface images, and inspects the inner surface of the boiler pressure vessel using ultrasonic and X-ray data. Then, based on the inspection results and simulated crack results, the final crack result of the boiler pressure vessel is obtained. Thus, this application can improve the efficiency and accuracy of pressure vessel inspection. Attached Figure Description

[0053] Figure 1 This is a flowchart of a boiler pressure vessel inspection and testing method provided in an embodiment of the present invention;

[0054] Figure 2 This is a flowchart of a method for detecting cracks on the outer surface of a boiler pressure vessel provided in an embodiment of the present invention;

[0055] Figure 3 This is a schematic diagram of the structure of a boiler pressure vessel inspection and testing device provided in an embodiment of the present invention. Detailed Implementation

[0056] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0057] Please see Figure 1 This invention provides a method for inspecting and testing boiler pressure vessels, specifically comprising steps S101-S107:

[0058] S101, apply magnetic powder or penetrating liquid to the outer surface of the boiler pressure vessel to obtain an image of the outer surface of the boiler pressure vessel to which magnetic powder or penetrating liquid has been applied.

[0059] Specifically, in this embodiment, magnetic powder or penetrating liquid is uniformly distributed on the surface of the boiler pressure vessel. During the inspection process, the shape and size of defects are revealed by utilizing the flow of the carrier liquid and the attraction of the leakage magnetic field to the magnetic powder. Applying magnetic powder or penetrating liquid is suitable for detecting minute surface defects, such as fatigue cracks and grinding cracks. After applying magnetic powder or penetrating liquid to the outer surface of the boiler pressure vessel, a certain period of time is waited, and then the outer surface of the filter vessel is photographed to obtain an image of the outer surface of the filter pressure vessel.

[0060] In this embodiment, the external surface image includes multiple angles and positions, so that the captured external surface image covers all positions of all boiler pressure vessels, and then the external surface image is used to determine whether cracks have appeared on the external surface of the boiler pressure vessel.

[0061] S102, determine whether cracks appear on the outer surface of the boiler pressure vessel based on the external surface image.

[0062] Specifically, in this embodiment, the external surface image can be identified using an image recognition method to determine whether cracks have appeared on the external surface of the boiler pressure vessel; or the external surface image can be input into the neural network model to predict the crack identification result. This embodiment does not limit the method of determining external surface cracks.

[0063] like Figure 2 As shown, determining whether cracks appear on the outer surface of the boiler pressure vessel based on the outer surface image includes:

[0064] S201, the outer surface image is divided into N sub-outer surface images of the same unit size, and each sub-outer surface image corresponds to an image position relationship.

[0065] The number of N can be set according to actual needs, and its specific value can be determined based on the outer surface area of ​​the boiler pressure vessel. In this embodiment, the image position relationship can be represented by numbers, such as 1-N. It also includes the position relationship of adjacent sub-outer surface images. For example, for the 5th sub-outer surface image, there are 8 adjacent sub-outer surface images, that is, 3 sub-outer surface images above and below, and 1 sub-outer surface image to the left and right.

[0066] S202, randomly select M non-adjacent sub-exterior surface images from N sub-exterior surface images.

[0067] The quantity of M is less than that of N. M can be determined based on the quantity of N. The larger the quantity of N, the larger M can be set, that is, M and N are directly proportional.

[0068] S203, determine whether cracks appear in M ​​non-adjacent sub-surface images respectively.

[0069] In one optional embodiment provided in this application, determining whether cracks appear in M ​​non-adjacent sub-exterior surface images includes: preprocessing the M non-adjacent sub-exterior surface images; inputting the preprocessed M non-adjacent sub-exterior surface images into the crack recognition model to obtain the crack recognition result corresponding to each sub-exterior surface image.

[0070] The preprocessing includes image enhancement, image denoising, edge detection, and geometric transformation, which are not specifically limited in this embodiment. In this embodiment, after preprocessing the sub-outer surface image, the M preprocessed non-adjacent sub-outer surface images are input into the crack recognition model to obtain the crack recognition result corresponding to each sub-outer surface image. The crack recognition result marks the corresponding crack location, crack size, and probability of crack occurrence in the corresponding sub-surface image.

[0071] It should be noted that the crack recognition model in this embodiment is trained based on sample data and sample labels. The sample data is an image containing cracks, and the sample labels are the crack location, crack size, etc. marked in the image.

[0072] S204, If cracks appear in the M extracted sub-external surface images, determine whether cracks appear in the sub-external surface images of the surrounding area based on the sub-external surface image with cracks.

[0073] For example, if cracks appear in the 1st and 10th sub-exterior surface images among the M extracted sub-exterior surface images, it is necessary to obtain the sub-exterior surface images of the surrounding areas corresponding to the 1st and 10th sub-exterior surface images respectively, and then determine whether cracks appear in the sub-exterior surface images of the surrounding areas.

[0074] In one optional embodiment provided in this application, determining whether a crack appears in the sub-outer surface image of the region surrounding the cracked sub-outer surface image includes:

[0075] S2041, Obtain the outer surface images of the surrounding 8 adjacent regions of the sub-outer surface image where the crack appears.

[0076] S2042, determine whether cracks appear in the outer surface images of the surrounding 8 adjacent areas.

[0077] S2043, If no cracks appear in the outer surface images of the surrounding 8 adjacent regions, then obtain the outer surface images of the surrounding 8 adjacent regions of the next outer surface image with cracks, and determine whether cracks appear in the outer surface images of the surrounding 8 adjacent regions, until the outer surface images of the surrounding 8 adjacent regions of all outer surface images with cracks are obtained.

[0078] S2044, If cracks appear in the outer surface images of the eight surrounding adjacent regions, the outer surface image with cracks is determined as the sub-outer surface image with cracks, and the process jumps to the step of obtaining the outer surface images of the eight surrounding adjacent regions of the sub-outer surface image with cracks to continue execution.

[0079] S205, if no cracks are found in the M sub-exterior surface images extracted, then M non-adjacent sub-exterior surface images are randomly extracted from the remaining NM sub-exterior surface images, until all sub-exterior surface images are extracted or a sub-exterior surface image with cracks is extracted.

[0080] In this embodiment, based on the physical characteristics of cracks, it is first determined whether cracks appear in the M extracted sub-external surface images. If cracks appear, the cracked sub-external surface image is used as the center to gradually spread outwards to quickly obtain the location area of ​​the crack in the boiler pressure vessel. Thus, this embodiment can improve the detection efficiency of boiler pressure vessels.

[0081] S103, if it is determined that there are no cracks on the outer surface of the boiler pressure vessel, then acquire the ultrasonic data and X-ray data of the boiler pressure vessel.

[0082] In this embodiment, the characteristic of ultrasonic waves to propagate in a straight line during propagation through a medium is utilized. If the medium is non-uniform, the acoustic impedance of the ultrasonic waves will differ during propagation, resulting in refraction, reflection, and projection phenomena. These refracted and reflected signals are collected by an instrument and converted into electrical signals to obtain ultrasonic data. This ultrasonic data is then used to determine defects in boiler pressure vessels.

[0083] Irradiating boiler pressure vessels with X-rays or gamma rays is a method that utilizes the strong penetrating power of these rays to penetrate the vessel's wall thickness and expose the material on film. During the inspection process, it is crucial to ensure the stability of the radiation source and appropriate exposure levels to obtain clear radiation data.

[0084] S104. Determine whether cracks appear on the inner surface of the boiler pressure vessel based on ultrasonic and radiographic data.

[0085] In one optional embodiment provided in this application, determining whether cracks have appeared on the inner surface of the boiler pressure vessel based on the ultrasonic data and X-ray data of the boiler pressure vessel includes: determining a first crack result based on the ultrasonic data of the boiler pressure vessel, determining a second crack result based on the X-ray data of the boiler pressure vessel, determining a third crack result based on the ultrasonic data and X-ray data of the boiler pressure vessel; and determining whether cracks have appeared on the inner surface of the boiler pressure vessel based on the first crack result, the second crack result, and the third crack result.

[0086] Optionally, determining the first crack result based on the ultrasonic data of the boiler pressure vessel includes: calculating the transverse and longitudinal ultrasonic velocities and flight time based on the ultrasonic data of the boiler pressure vessel; determining the first crack result using the transverse and longitudinal ultrasonic velocities and flight time, wherein the first crack result includes the crack location.

[0087] Specifically, the process of determining the first crack result in this embodiment can be as follows: First, the transverse velocity and longitudinal velocity of the ultrasonic wave are obtained. The propagation speed of ultrasonic waves is different for different materials, so it is necessary to know the sound speed of the material being tested, such as the sound speed of steel, which is approximately 5900 m / s. Then, the flight time is measured. An ultrasonic flaw detector is used to emit ultrasonic pulses to the material and receive the echo signal reflected back from the crack. By measuring the time interval (round trip time) from emission to reception of the ultrasonic wave, the distance the ultrasonic wave propagates in the material can be calculated. Afterward, based on the propagation speed of the ultrasonic wave in the material and the measured flight time, the position of the crack from the probe can be calculated. This position is half of the propagation path of the ultrasonic wave in the material because the ultrasonic wave needs to be reflected back at the crack.

[0088] The specific calculation formula is: Crack distance = (Speed ​​of sound × Flight time) / 2. Wherein, flight time refers to the total time it takes for the ultrasonic wave to travel from the probe to the crack and back to the probe.

[0089] In one optional embodiment provided in this application, the computational load can be reduced while ensuring the accuracy of the defect location. Specifically, a region information partitioning technique is used to divide information with the same characteristics into two components. Based on this region information partitioning, assuming the weak signal characteristic of the first half of the location information is 'a' and the signal of the second half is 'b', the mapping of the global complete defect location signal echo characteristics is as follows:

[0090]

[0091] In the formula, r ab This represents the mapping of the global complete defect location signal echo characteristics, where n is the total amount of crack location feedback signals, and i and j are the number of weak signals characteristic of the location information in the first and second halves, respectively. When the coefficient value corresponding to the total amount of feedback signals is less than 0, it indicates that a crack exists on the surface within the detection area. In this case, considering the uniqueness of the distribution location within this area, the following calculation formula is used to determine the specific location of the defect:

[0092]

[0093] In the formula, d represents the specific location of the defect; D represents the total length of the defect detection surface of the boiler pressure vessel; v represents the transmission velocity (i.e., the transverse velocity of the wave and the longitudinal velocity of the ultrasonic wave); and Δt represents the crack information distribution location parameter. These parameters collectively determine the specific location of the crack in the pipeline. By accurately calculating these parameters, the defect can be precisely located, providing strong support for subsequent repair work. In summary, efficient and accurate pressure vessel defect location is achieved by employing regional information partitioning technology.

[0094] The transverse velocity and longitudinal velocity of the ultrasonic wave are calculated using the following formulas:

[0095]

[0096] In the formula, V S V is the transverse wave velocity of the ultrasonic wave. L ρ is the longitudinal wave velocity of the ultrasonic wave, in km / s; E is the elastic modulus; ρ is the density; μ is Poisson's ratio.

[0097] Optionally, determining the second crack result based on the X-ray data of the boiler pressure vessel includes: acquiring the X-ray data of the boiler pressure vessel and obtaining a projection image based on the X-ray data; performing image enhancement processing, contrast enhancement processing, edge processing, and noise reduction processing on the projection image; and determining the second crack result based on the processed projection image.

[0098] Optionally, determining the third crack result based on the ultrasonic and X-ray data of the boiler pressure vessel includes: converting the ultrasonic and X-ray data of the boiler pressure vessel into feature vectors; and inputting the feature vectors into an internal crack identification model to obtain the third crack result of the boiler pressure vessel. The internal crack identification model is a neural network model used to identify cracks through ultrasonic and X-ray data; its sample data consists of sample feature vectors converted from ultrasonic and X-ray data, and the sample labels include the crack location, crack size, etc.

[0099] S105, if cracks appear on the inner surface of the boiler pressure vessel and / or on the outer surface of the boiler pressure vessel, then obtain the regional physical data of the location area of ​​the cracks on the inner and / or outer surfaces of the boiler pressure vessel.

[0100] The physical data of this region can include the material's density, elastic modulus, Poisson's ratio, yield strength, tensile strength, corrosion resistance, etc.; as well as the basic dimensions of the corresponding region, such as length, width, height, wall thickness, diameter, and volume. This embodiment does not impose specific limitations on these dimensions.

[0101] S106. Based on the operating data of the boiler pressure vessel and the overall physical data, a simulation model is obtained by simulation. The physical data of the area where the crack appears is input into the simulation model to obtain the simulation crack result.

[0102] The operational data includes pressure data, temperature data, and medium data. Pressure data includes operating pressure, design pressure, and maximum operating pressure. Changes in pressure directly affect the stress state and deformation of the equipment; therefore, accurate pressure parameters must be set in the simulation. For example, when simulating overpressure conditions, it is crucial to ensure that the simulation model accurately reflects the stress distribution and deformation trend of the equipment under overpressure.

[0103] Temperature data includes the normal operating temperature range, maximum operating temperature, and rate of temperature change. Temperature variations cause thermal expansion and stress in materials, and also affect their mechanical properties. Simulations need to consider the impact of temperature on the equipment's structure and performance, such as simulating changes in the temperature field and the resulting thermal stress using a thermal analysis module.

[0104] For boiler pressure vessels, the internal medium may be water, steam, air, gas mixtures, or other chemical substances. The physical properties (such as density, viscosity, specific heat capacity, thermal conductivity, etc.) and chemical properties (such as corrosivity, reactivity, etc.) of the medium will affect the stress, heat transfer, and corrosion of the equipment's internal surface. In simulation, appropriate boundary conditions and loads need to be set according to the characteristics of the medium.

[0105] S107, Based on the simulated crack results and the cracks appearing in the location area, determine the final crack results of the boiler pressure vessel.

[0106] Specifically, determining the final crack result of the boiler pressure vessel based on the simulated crack result and the cracks appearing in the location area includes: matching and merging the simulated crack result and the cracks appearing in the location area to obtain the final crack result of the boiler pressure vessel.

[0107] It should be noted that since very fine cracks cannot be identified through external surface images, ultrasonic data, and X-ray data, meaning that the end of a crack may be unidentifiable, this embodiment addresses this problem by simulating the continuous physical characteristics of cracks. Based on the operating data of the boiler pressure vessel and the overall physical data, a simulation model is obtained. The physical data of the crack location area is then input into the simulation model to obtain the simulated crack result. This simulation further determines whether even finer cracks exist in the area where the crack appears. If so, the simulated crack result is matched and merged with the cracks in the specified location area to obtain the final crack result for the boiler pressure vessel. Therefore, this embodiment improves the accuracy of crack identification.

[0108] This embodiment provides a method for inspecting and testing boiler pressure vessels. First, magnetic powder or penetrating liquid is applied to the outer surface of the boiler pressure vessel to obtain an image of the outer surface. Then, based on the outer surface image, it is determined whether cracks appear on the outer surface of the boiler pressure vessel. If no cracks are found on the outer surface, ultrasonic and radiographic data of the boiler pressure vessel are acquired. Based on the ultrasonic and radiographic data, it is determined whether cracks appear on the inner surface of the boiler pressure vessel. If cracks appear on the inner surface and / or the outer surface, the physical data of the location of the cracks on the inner and / or outer surfaces are acquired. A simulation model is obtained based on the boiler pressure vessel's operating data and overall physical data. The physical data of the location of the cracked area is input into the simulation model to obtain the simulated crack result. Finally, the final crack result of the boiler pressure vessel is determined based on the simulated crack result and the cracks appearing in the location area. Compared with the current method of manually inspecting boiler pressure vessels, this application inspects the outer surface of the boiler pressure vessel based on acquired external surface images, and inspects the inner surface of the boiler pressure vessel using ultrasonic and X-ray data. Then, based on the inspection results and simulated crack results, the final crack result of the boiler pressure vessel is obtained. Thus, this application can improve the efficiency and accuracy of pressure vessel inspection.

[0109] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0110] In one embodiment, a boiler pressure vessel inspection and testing device is provided. For example... Figure 3 As shown, the functional modules of this boiler and pressure vessel inspection and testing device are described in detail below:

[0111] The acquisition module 31 is used to apply magnetic powder or penetrating liquid to the outer surface of the boiler pressure vessel in order to obtain an image of the outer surface of the boiler pressure vessel with applied magnetic powder or penetrating liquid.

[0112] The determination module 32 is used to determine whether cracks appear on the outer surface of the boiler pressure vessel based on the outer surface image;

[0113] The acquisition module 31 is further configured to acquire ultrasonic data, X-ray data and pressure data of the boiler pressure vessel if it is determined that no cracks appear on the outer surface of the boiler pressure vessel.

[0114] The determining module 32 is also used to determine whether cracks appear on the inner surface of the boiler pressure vessel based on the ultrasonic data, X-ray data and pressure data of the boiler pressure vessel.

[0115] The acquisition module 31 is further configured to acquire regional physical data of the location area of ​​the crack on the inner surface and / or outer surface of the boiler pressure vessel if a crack appears on the inner surface and / or the outer surface of the boiler pressure vessel.

[0116] The simulation module 33 is used to perform simulation based on the operating data and overall physical data of the boiler pressure vessel to obtain a simulation model, and input the physical data of the location of the cracked area into the simulation model to obtain the simulation crack result.

[0117] The determining module 32 is further configured to determine the final crack result of the boiler pressure vessel based on the simulated crack result and the cracks appearing in the location area.

[0118] In an optional embodiment, the determining module 32 is specifically used for:

[0119] The outer surface image is divided into N sub-outer surface images of the same unit size, and each sub-outer surface image corresponds to an image position relationship;

[0120] M non-adjacent sub-outer surface images are randomly selected from the N sub-outer surface images;

[0121] Determine whether cracks appear in M ​​non-adjacent sub-exterior surface images;

[0122] If cracks appear in the M extracted sub-external surface images, then determine whether cracks appear in the sub-external surface images of the surrounding area based on the sub-external surface image with cracks.

[0123] If no cracks are found in the M extracted sub-exterior surface images, then M non-adjacent sub-exterior surface images are randomly selected from the remaining NM sub-exterior surface images, until all sub-exterior surface images are extracted or a sub-exterior surface image with cracks is extracted.

[0124] In an optional embodiment, the determining module 32 is specifically used for:

[0125] Obtain the outer surface images of the surrounding 8 adjacent regions of the sub-outer surface image where the crack appears;

[0126] Determine whether cracks appear in the outer surface images of the eight surrounding adjacent regions;

[0127] If no cracks appear in the outer surface images of the surrounding 8 adjacent regions, then the outer surface images of the surrounding 8 adjacent regions of the next cracked sub-outer surface image are obtained, and it is determined whether cracks appear in the outer surface images of the surrounding 8 adjacent regions, until the outer surface images of the surrounding 8 adjacent regions of all cracked sub-outer surface images are obtained.

[0128] If cracks appear in the outer surface images of the eight surrounding adjacent regions, the outer surface image with cracks is determined as the sub-outer surface image with cracks, and the process jumps to the step of obtaining the outer surface images of the eight surrounding adjacent regions of the sub-outer surface image with cracks to continue execution.

[0129] In an optional embodiment, the determining module 32 is specifically used for:

[0130] Preprocess the images of M non-adjacent sub-outer surfaces;

[0131] The preprocessed M non-adjacent sub-exterior surface images are input into the crack recognition model to obtain the crack recognition result corresponding to each sub-exterior surface image.

[0132] In an optional embodiment, the determining module 32 is specifically used for:

[0133] The first crack result is determined based on the ultrasonic data of the boiler pressure vessel; the second crack result is determined based on the X-ray data of the boiler pressure vessel; and the third crack result is determined based on the ultrasonic data and X-ray data of the boiler pressure vessel.

[0134] Based on the first crack result, the second crack result, and the third crack result, determine whether cracks have appeared on the inner surface of the boiler pressure vessel.

[0135] In an optional embodiment, the determining module 32 is specifically used for:

[0136] The ultrasonic transverse velocity, ultrasonic longitudinal velocity, and flight time are calculated based on the ultrasonic data of the boiler pressure vessel.

[0137] The first crack result is determined by the transverse velocity of the wave, the longitudinal velocity of the ultrasonic wave, and the flight time. The first crack result includes the crack location.

[0138] In an optional embodiment, the determining module 32 is specifically used for:

[0139] Acquire the X-ray data of the boiler pressure vessel and obtain a projection image based on the X-ray data;

[0140] The projected image is subjected to image enhancement processing, contrast enhancement processing, edge processing, and noise reduction processing;

[0141] The result of the second crack was determined based on the processed projection image.

[0142] In an optional embodiment, the determining module 32 is specifically used for:

[0143] The ultrasonic and X-ray data of the boiler pressure vessel are converted into feature vectors;

[0144] The feature vector is input into the internal crack identification model to obtain the third crack result of the boiler pressure vessel.

[0145] In an optional embodiment, the determining module 32 is specifically used for:

[0146] The simulated crack results and the cracks appearing in the location area are matched and merged to obtain the final crack results of the boiler pressure vessel.

[0147] It should be noted that the above detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0148] Specific limitations regarding the testing and inspection equipment for boilers and pressure vessels can be found in the limitations of the testing and inspection methods for boilers and pressure vessels described above, and will not be repeated here. Each module in the aforementioned equipment can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0149] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0150] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A boiler pressure vessel inspection and testing method, characterized in that: The method comprises: Applying magnetic powder or penetrant liquid to the outer surface of the boiler pressure vessel to obtain an image of the outer surface of the boiler pressure vessel to which the magnetic powder or penetrant liquid is applied; determining whether cracks occur on the outer surface of the boiler pressure vessel according to the outer surface image; If it is determined that no cracks occur on the outer surface of the boiler pressure vessel, then obtaining ultrasonic data and X-ray data of the boiler pressure vessel; Determining whether cracks occur on the inner surface of the boiler pressure vessel according to the ultrasonic data and the X-ray data of the boiler pressure vessel; If cracks appear on the inner surface of the boiler pressure vessel and / or cracks appear on the outer surface of the boiler pressure vessel, obtaining regional physical data of the location area where the cracks appear on the inner surface and / or the outer surface of the boiler pressure vessel; Performing simulation based on the operation data and overall physical data of the boiler pressure vessel to obtain a simulation model, and inputting the physical data of the area where the crack occurs into the simulation model to perform simulation to obtain a simulation crack result; The final crack result of the boiler pressure vessel is determined according to the simulated crack result and the cracks occurring in the location area.

2. The method according to claim 1, characterized in that The determining, according to the outer surface image, whether cracks occur on the outer surface of the boiler pressure vessel comprises: Splitting the outer surface image into a plurality of N outer surface sub-images having the same unit size, each of which has a corresponding image position relationship; Randomly extracting M sub-external surface images whose positions are not adjacent from the N sub-external surface images; Determine respectively whether cracks appear in M ​​sub-external surface images that are not adjacent to each other; If cracks appear in the extracted M sub-external surface images, then determine whether cracks appear in the sub-external surface images in the surrounding area according to the sub-external surface image where the cracks appear; If no cracks appear in the extracted M sub-external surface images, M non-adjacent sub-external surface images are randomly extracted again from the remaining NM sub-external surface images until all sub-external surface images are extracted or a sub-external surface image with cracks is extracted.

3. The method according to claim 2, characterized in that The step of determining whether cracks appear in the sub-external surface images of the surrounding areas according to the sub-external surface image where cracks appear includes: Obtaining the outer surface images of eight adjacent areas around the sub-outer surface image where the crack appears; Determine whether cracks appear in the outer surface images of the eight adjacent regions; If no cracks appear in the outer surface images of the eight surrounding adjacent areas, then obtain the outer surface images of the eight surrounding adjacent areas of the next sub-external surface image with cracks, and determine whether cracks appear in the outer surface images of the eight surrounding adjacent areas, until all outer surface images of the eight surrounding adjacent areas of the sub-external surface image with cracks are obtained; If cracks appear in the outer surface image of the surrounding 8 adjacent areas, the outer surface image of the area where the cracks appear is determined as the sub-outer surface image where the cracks appear, and the process jumps to the step of obtaining the outer surface images of the surrounding 8 adjacent areas of the sub-outer surface image where the cracks appear and continues.

4. The method according to claim 2 or 3, characterized in that: The step of respectively determining whether cracks occur in M ​​non-adjacent sub-external surface images comprises: Preprocessing M sub-external surface images that are not adjacent to each other; The preprocessed M sub-external surface images that are not adjacent to each other are respectively input into the crack recognition model to obtain the crack recognition results corresponding to each sub-external surface image.

5. The method according to claim 1, characterized in that The determining whether cracks occur on the inner surface of the boiler pressure vessel according to the ultrasonic data and the ray data of the boiler pressure vessel comprises: Determine a first crack result according to the ultrasonic data of the boiler pressure vessel, determine a second crack result according to the ray data of the boiler pressure vessel, and determine a third crack result according to the ultrasonic data and the ray data of the boiler pressure vessel; Whether cracks occur on the inner surface of the boiler pressure vessel is determined according to the first crack result, the second crack result, and the third crack result.

6. The method according to claim 5, characterized in that The determining of the first crack result according to the ultrasonic data of the boiler pressure vessel comprises: Calculating the ultrasonic transverse velocity, ultrasonic longitudinal velocity and flight time according to the ultrasonic data of the boiler pressure vessel; The first crack result is determined by the wave transverse velocity, ultrasonic longitudinal velocity and flight time, and the first crack result includes the crack position.

7. The method according to claim 5, characterized in that The determining of the second crack result according to the ray data of the boiler pressure vessel comprises: Acquiring radiation data of the boiler pressure vessel, and obtaining a projection image according to the radiation data; Performing image enhancement processing, contrast enhancement processing, edge processing, and noise reduction processing on the projected image; The second crack result is determined according to the processed projection image.

8. The method according to claim 5, characterized in that The determining of the third crack result according to the ultrasonic data and the X-ray data of the boiler pressure vessel comprises: Converting ultrasonic data and ray data of the boiler pressure vessel into feature vectors; The characteristic vector is input into an internal crack identification model to obtain a third crack result of the boiler pressure vessel.

9. The method according to claim 1, characterized in that: The determining the final crack result of the boiler pressure vessel according to the simulated crack result and the cracks occurring in the position area includes: The simulated crack results and the cracks occurring in the location area are matched and combined to obtain the final crack results occurring in the boiler pressure vessel.

10. A boiler pressure vessel inspection and detection device, characterized in that: The device comprises: An acquisition module, used for applying magnetic powder or penetrant liquid to the outer surface of the boiler pressure vessel to acquire an image of the outer surface of the boiler pressure vessel to which the magnetic powder or penetrant liquid is applied; a determination module, configured to determine whether cracks occur on the outer surface of the boiler pressure vessel according to the outer surface image; The acquisition module is further configured to acquire ultrasonic data, X-ray data and pressure data of the boiler pressure vessel if it is determined that no cracks occur on the outer surface of the boiler pressure vessel; The determination module is further used to determine whether cracks appear on the inner surface of the boiler pressure vessel according to the ultrasonic data, the ray data and the pressure data of the boiler pressure vessel; The acquisition module is further configured to acquire regional physical data of a location area where cracks appear on the inner surface and / or the outer surface of the boiler pressure vessel if cracks appear on the inner surface of the boiler pressure vessel and / or cracks appear on the outer surface of the boiler pressure vessel; A simulation module, used to perform simulation according to the operation data and overall physical data of the boiler pressure vessel to obtain a simulation model, and input the physical data of the area where the crack occurs into the simulation model to perform simulation to obtain a simulation crack result; The determination module is further used to determine the final crack result of the boiler pressure vessel according to the simulated crack result and the cracks appearing in the location area.

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