A large steel box girder flaw detection method and related products

Abstract

The present application relates to the field of nondestructive testing, in particular to a large steel box girder flaw detection method and related products, comprising importing a three-dimensional model of a large steel box girder and analyzing the three-dimensional model to obtain geometric characteristic information of the steel box girder; generating a scanning path of an ultrasonic probe based on the geometric characteristic information; controlling the ultrasonic probe to scan the large steel box girder according to the scanning path and collect ultrasonic echo signals; processing the ultrasonic echo signals to identify and locate the welding defect position of the steel box girder; the present application realizes automatic extraction of the detection area and the welding seam information by importing and analyzing the three-dimensional model of the steel box girder, and realizes efficient and full-coverage detection of large and complex structural parts by using an adaptive path planning algorithm to generate an optimized probe scanning path, thereby avoiding missed detection.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of non-destructive testing, in particular to a large steel box girder flaw detection method and related products. BACKGROUND

[0002] Large steel box girder structures are widely used in the fields of bridges, buildings, ships, etc. Ensuring the welding quality of large steel box girders is crucial for the safety of the structure. Currently, the detection of the welding quality of large steel box girders mainly relies on non-destructive testing technology.

[0003] Non-destructive testing technology can detect the internal or surface defects of an object without damaging it. Common non-destructive testing methods include radiographic testing, ultrasonic testing, magnetic particle testing, and penetrant testing. Among them, ultrasonic testing has been widely used in welding defect detection due to its advantages of being harmless to the human body, strong penetration ability, high sensitivity, easy operation, etc.

[0004] Existing ultrasonic testing technology for large steel box girders usually adopts manual operation or semi-automatic mode. Manual operation mode has high labor intensity, low efficiency, and the detection results are easily affected by personnel experience, and it is difficult to conduct comprehensive detection on large components. Although semi-automatic detection equipment improves the detection efficiency to some extent, it usually has problems such as low automation degree, poor adaptability to complex structures, and low intelligence level, which makes it difficult to meet the detection needs of large steel box girders in terms of efficiency, accuracy, and automation. SUMMARY

[0005] The technical problem to be solved by the present application is the high labor intensity and low efficiency of manual operation in the existing large steel box girder welding quality detection technology. The purpose is to provide a large steel box girder flaw detection method and related products, which realizes automatic, intelligent, high-precision, and high-efficiency detection of welding defects of large steel box girders.

[0006] The present application is realized by the following technical solutions:

[0007] A large steel box girder flaw detection method, comprising:

[0008] Importing a three-dimensional model of a large steel box girder and analyzing the three-dimensional model to obtain geometric feature information of the steel box girder;

[0009] Generating a scanning path of an ultrasonic probe based on the geometric feature information;

[0010] Controlling the ultrasonic probe to scan the large steel box girder according to the scanning path and collecting ultrasonic echo signals;

[0011] Processing the ultrasonic echo signals, identifying and locating the welding defect position of the steel box girder.

[0012] Optionally, the method for obtaining the geometric feature information of the steel box girder comprises:

[0013] reading a three-dimensional model of the large steel box girder, the three-dimensional model file being in STEP format or IGES format;

[0014] parsing the entities and relationships in the three-dimensional model file to obtain geometric information and topological information of the faces, geometric information and topological information of the edges, and coordinate information of the vertices of the large steel box girder;

[0015] calculating the plate thickness of the large steel box girder, identifying the weld position and determining the weld type, and identifying the position of the reinforcing rib based on the geometric information and topological information of the faces, the geometric information and topological information of the edges, and the coordinate information of the vertices.

[0016] Optionally, the method for calculating the plate thickness is:

[0017] calculating the distance between two opposite parallel faces of the large steel box girder;

[0018] The method for identifying the weld position is:

[0019] finding the adjacent faces of the large steel box girder;

[0020] calculating the included angle between the adjacent faces;

[0021] if the included angle is less than a first preset threshold value and the adjacent faces are connected by a common edge, it is determined as a potential weld;

[0022] judging the thickness of the geometric body on both sides of the potential weld, and if the thickness of the geometric body is less than a second preset threshold value, it is determined that the potential weld is a weld;

[0023] The method for determining the weld type is: setting a1, a2, and a3 as preset error angle values;

[0024] if the included angle of the faces on both sides of the weld is 180±a1 degrees, it is determined that the weld is a butt weld;

[0025] if the included angle of the faces on both sides of the weld is 90±a2 degrees, it is determined that the weld is a fillet weld;

[0026] if the edge of the face on one side of the weld is connected to the inside of the face on the other side, and the included angle of the two faces is 90±a3 degrees, it is determined that the weld is a T-type weld;

[0027] The method for identifying the position of the reinforcing rib is:

[0028] calculating the aspect ratio of each face in the three-dimensional model, and determining the face with an aspect ratio greater than a third preset threshold value as a thin plate structure;

[0029] finding the thin plate structure in the large steel box girder;

[0030] Determine whether the thin-plate structure is connected to the main board of the large steel box girder;

[0031] If the thin plate structure is connected to the main board, then the thin plate structure is determined to be a reinforcing rib.

[0032] Optionally, methods for generating the scanning path of an ultrasonic probe based on geometric feature information include:

[0033] Geometric feature information includes plate thickness, weld location, weld type, and stiffener location;

[0034] Determine the weld area that needs to be ultrasonically tested based on the weld location, and select the appropriate ultrasonic probe and scanning method based on the weld type.

[0035] Based on the weld area, plate thickness, ultrasonic probe, scanning method, and stiffener location, environmental modeling and function definition are completed to generate a scanning path for the ultrasonic probe that avoids the stiffener and other non-inspection areas.

[0036] Alternatively, methods for environment modeling and function definition include:

[0037] The detection area of ​​the large steel box girder is discretized into a grid map. ,in, For a set of grid nodes, each grid node The coordinates are , It is the set of edges that connect adjacent grid nodes;

[0038] Determine grid nodes State attributes ,in, Indicates free time. It indicates that the space is occupied by an obstacle. Indicates the weld area;

[0039] Determine grid nodes Normal vector of the surface ;

[0040] Define from grid nodes Move to adjacent grid node Cost function ,in, For grid nodes To grid node Euclidean distance, The cost of adjusting the probe's attitude. The penalty coefficient is determined by the weld type. To avoid the cost of obstacles, For weld priority cost, These are the weighting coefficients;

[0041] defining a heuristic function from a grid node to a target node wherein, is a cost of moving one distance unit, is a distance of the current node to the target node in three directions.

[0042] Optionally, the method of generating a scan path comprises:

[0043] initializing:

[0044] creating an OPEN list for storing nodes to be evaluated and a CLOSED list for storing nodes that have been evaluated;

[0045] adding a start node to the OPEN list, setting an initial cost , a total cost estimate , to the start node to the target node , a heuristic function, an initial cost function value, a total cost estimate of a path through the start node ;

[0046] iteratively searching:

[0047] performing the following steps in a loop until the OPEN list is empty or the target node is found:

[0048] selecting a node with the smallest total cost estimate value from the OPEN list, and determining whether it is the target node, if yes, completing the search; if no, moving from the OPEN list to the CLOSED list, and continuing the search;

[0049] traversing all adjacent nodes of and performing the following operations:

[0050] if is in the CLOSED list, skipping;

[0051] if is not in the CLOSED list, calculating an actual cost of reaching from the start point , a heuristic function from a grid node ​Move to the adjacent grid node of the cost function, for the start node to the node of the actual cost function;

[0052] If is not in the OPEN list, add to the OPEN list, set , and record the parent of as ;

[0053] If is in the OPEN list, and , update , and update the parent of as ;

[0054] Path backtracking:

[0055] Starting from the target node , backtrack to the start node according to the parent node recorded for each node, to generate a preliminary path;

[0056] Path smoothing:

[0057] The generated preliminary path is smoothed using a Bezier curve to obtain a scanning path.

[0058] Optionally, the method for performing ultrasonic scanning comprises:

[0059] The scanning device comprises a mobile platform, a mechanical arm and an ultrasonic probe, wherein the mechanical arm is installed on the mobile platform;

[0060] When performing ultrasonic scanning, the movement of the mobile platform and the mechanical arm is controlled so that the ultrasonic probe moves along a scanning path;

[0061] According to the type of the weld, a corresponding ultrasonic probe and scanning method are selected:

[0062] If the type of the weld is a butt weld, an inclined probe is selected to emit and receive ultrasonic waves, and transverse scanning is performed;

[0063] If the type of the weld is a fillet weld, a double-crystal probe or a TOFD probe is selected to emit and receive ultrasonic waves, and longitudinal scanning is performed;

[0064] If the type of the weld is a T-shaped weld, a climbing probe or a phased array probe is selected to emit and receive ultrasonic waves, and transverse or longitudinal scanning is performed.

[0065] Optionally, methods for identifying the location of welding defects include:

[0066] Discrete wavelet transform of ultrasonic echo signals ,in, These are wavelet coefficients. For scale parameters, For translation parameters, For the complex conjugate of wavelet basis functions, For signal length, It is an ultrasonic echo signal. For time;

[0067] Determine the scale wavelet coefficients threshold ,in, For scale The standard deviation of the noise For scale The number of wavelet coefficients;

[0068] Wavelet coefficients are processed using a soft thresholding function. ;

[0069] Processed wavelet coefficients Perform inverse discrete wavelet transform to obtain the denoised signal. ;

[0070] Construct TCG curves and analyze the denoised signal. Compensation is performed to obtain the final echo signal. ;

[0071] The final echo signal is extracted using short-time Fourier transform and continuous wavelet transform. The time-frequency characteristics in;

[0072] The time-frequency features are input into a pre-trained deep residual time-frequency network, and the output feature vector is... ;

[0073] The eigenvector is processed using the Softmax function. Classify and calculate which category it belongs to The probability value of each list ,in, This represents the actual number of defect categories. , Indicates no defects. Indicates various defect categories, For category The transpose of the weight vector, For category The bias, For category The transpose of the weight vector, For category The bias;

[0074] Set confidence threshold ,like Then discard the classification result, if Then its corresponding As a defect type;

[0075] After identifying the defect type along the scanning path, the defect is located in the weld where defects exist.

[0076] Optionally, methods for locating welding defects include:

[0077] For the final echo signal Perform continuous wavelet transform to obtain wavelet coefficients. And calculate the wavelet energy distribution. ,in, For scale parameters, These are translation parameters;

[0078] The time point corresponding to the maximum energy value is selected as the arrival time of the defect echo. ,in, For all scale parameters The maximum value of the energy distribution of the middle wavelet. To obtain the translation parameter corresponding to the maximum value ;

[0079] Calculate the depth of the location of welding defects. ,in, The ultrasonic propagation speed in large steel box girder materials;

[0080] Obtain the coordinates of the ultrasonic probe in the coordinate system of the large steel box girder. and attitude angle ,in, This is the roll angle. The pitch angle, Yaw angle;

[0081] Calculate the coordinates of the defect location in the probe coordinate system. , ;

[0082] The coordinates of the defect location are transformed from the probe coordinate system to the large steel box girder coordinate system to obtain the coordinates of the welding defect location. , ,in, Let be the rotation matrix determined by the attitude angle. ,in, To bypass Rotation matrix of the axis, Rotation matrix of the axis, Rotation matrix of the axis, Rotation matrix of the axis, Rotation matrix of the axis.

[0083] A computer program product comprising computer programs / instructions which, when executed by a processor, implement the method as described above.

[0084] Compared with the prior art, the present application has the following advantages and beneficial effects:

[0085] The present application realizes the automatic extraction of the detection area and the weld information by importing and analyzing the three-dimensional model of the steel box girder, generates an optimized probe scanning path by using an adaptive path planning algorithm, realizes the efficient and full-coverage detection of large and complex structural parts, avoids missed detection, processes the ultrasonic echo signal by constructing a deep residual time-frequency network and combining a plurality of time-frequency domain feature analysis methods, and realizes the comprehensive detection and evaluation of different types of defects. Finally, the labor cost is reduced, and the detection efficiency and consistency are improved. BRIEF DESCRIPTION OF DRAWINGS

[0086] The accompanying drawings illustrate exemplary embodiments of the present application and together with the general description of the application given above and the detailed description of the embodiments below, serve to explain the principles of the present application. These drawings are included herewith to provide further understanding of the present application and are incorporated in and constitute a part of this specification, illustrate embodiments of the present application and, together with the description, serve to explain the principles of the present application, and are included as part of this specification to provide further understanding of the present application, and are incorporated in and constitute part of this specification, and do not limit the embodiments of the present application.

[0087] Figure 1 is a flowchart of a large steel box girder flaw detection method according to the present application.

[0088] Figure 2 is a flowchart of a scanning path generation method according to the present application. DETAILED DESCRIPTION

[0089] In order to make the objects, technical solutions and advantages of the present application clearer, further detailed description will be made below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the related content, and not to limit the present application.

[0090] In addition, it should be noted that only the parts related to the present application are shown in the drawings for ease of description.

[0091] In the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0092] Example one, as Figure 1As shown, a large steel box girder flaw detection method is provided, comprising:

[0093] Model import and analysis: Import the three-dimensional model of the large steel box girder and analyze the three-dimensional model to obtain the geometric feature information of the steel box girder.

[0094] The three-dimensional model is usually in the format generated by CAD (Computer Aided Design) software, such as STEP, IGES, etc. After import, the model is automatically analyzed to extract the geometric feature information of the steel box girder, including the shape, size, position, direction, etc. of each component of the steel box girder (such as plates, welds, reinforcing bars, etc.).

[0095] Scan path generation: Generate the scan path of the ultrasonic probe based on the geometric feature information.

[0096] The path planning process takes into account multiple factors, such as: the position and type of welds that need to be detected. The overall structure of the steel box girder, avoiding collision between the probe and the steel box girder. The movement range and attitude adjustment ability of the probe. The detection efficiency and coverage requirements.

[0097] Scanning and signal acquisition: Control the ultrasonic probe to scan the large steel box girder according to the scan path, and collect the ultrasonic echo signal.

[0098] Control the scanning device (such as a mobile robot with a mechanical arm) to move the ultrasonic probe according to the generated scan path. While the probe is moving, the probe emits ultrasonic pulses into the steel box girder and receives ultrasonic echo signals reflected from the inside. The echo signal contains information about the internal structure of the steel box girder, including possible welding defects.

[0099] Signal processing and defect identification and positioning: Process the ultrasonic echo signal, identify and locate the welding defect position of the steel box girder.

[0100] Usually includes steps such as signal preprocessing (such as noise reduction, filtering, gain compensation, etc.), feature extraction, defect identification and defect positioning. By analyzing the characteristics of the echo signal, it can be determined whether there is a defect, the type of defect (such as porosity, crack, incomplete fusion, etc.), and the location and size of the defect.

[0101] The working principle of this embodiment is to use the reflection characteristics of ultrasonic waves propagating inside the material to detect defects. Through computer-aided design (CAD) model import and analysis, the geometric feature information of the steel box girder is obtained, realizing the automation of the preparation of detection; through intelligent path planning algorithm, the optimized probe scan path is generated; through automatic scanning device and signal processing technology, the detection of welding defects of large steel box girder is realized.

[0102] In the second embodiment, how to extract the key geometric feature information for the flaw detection from the three-dimensional CAD model of the large steel box girder is described in detail, including the plate thickness, the position and type of the weld, and the position of the stiffener. The whole process is divided into three main stages: model reading, model analysis and feature information calculation.

[0103] The method for obtaining the geometric feature information of the steel box girder comprises:

[0104] reading the three-dimensional model of the large steel box girder, the three-dimensional model file being in STEP format or IGES format;

[0105] analyzing the entities and relationships in the three-dimensional model file to obtain the geometric information and topological information of the faces, the geometric information and topological information of the edges, and the coordinate information of the vertices of the large steel box girder.

[0106] The geometric information of the face describes the shape (such as a plane or a curved surface), size, position, etc. of the face; the topological information of the face describes the connection relationship of the face with other faces, edges, and vertices. The geometric information of the edge describes the shape (such as a straight line or a curve), length, position, etc. of the edge; the topological information of the edge describes the connection relationship of the edge with the faces and vertices. The coordinate information of the vertex describes the position of the vertex in the three-dimensional space.

[0107] Based on the geometric information and topological information of the faces, the geometric information and topological information of the edges, and the coordinate information of the vertices, the plate thickness of the large steel box girder is calculated, the position of the weld is identified, the type of the weld is determined, and the position of the stiffener is identified, and the specific calculation method comprises:

[0108] The calculation method of the plate thickness is to calculate the distance between two opposite parallel faces of the large steel box girder.

[0109] The identification method of the weld position is to find the adjacent faces of the large steel box girder; to calculate the included angle between the adjacent faces; to determine a potential weld if the included angle is less than a first preset threshold value and the adjacent faces are connected by a common edge; and to determine the potential weld as a weld if the thickness of the geometric body on both sides of the potential weld is less than a second preset threshold value.

[0110] The determination method of the type of the weld is to set a1, a2, and a3 as preset error angle values; and to generally set them within 10 degrees.

[0111] If the included angle of the faces on both sides of the weld is 180±a1 degrees, the weld is determined as a butt weld.

[0112] If the included angle of the faces on both sides of the weld is 90±a2 degrees, the weld is determined as a fillet weld.

[0113] If the edge of the face on one side of the weld is connected to the inside of the face on the other side, and the included angle of the two faces is 90±a3 degrees, the weld is determined as a T-type weld.

[0114] The method for identifying the position of the reinforcing rib is:

[0115] Calculate the aspect ratio of each face in the three-dimensional model, and determine the face with an aspect ratio greater than a third preset threshold as a thin plate structure;

[0116] Finding the thin plate structure in the large steel box girder;

[0117] Determining whether the thin plate structure is connected to the main plate of the large steel box girder;

[0118] If the thin plate structure is connected to the main plate, the thin plate structure is determined as a reinforcing rib.

[0119] The working principle of the embodiment is to use the data structure and geometric modeling kernel of the CAD model, access and extract the geometric and topological information of the model through a programming interface, and automatically extract key information such as plate thickness, weld position, weld type and reinforcing rib position from the CAD model through a series of geometric calculations and logical judgments.

[0120] In embodiment three, it is explained how to generate the scanning path of the ultrasonic probe according to the previously extracted geometric feature information of the steel box girder (plate thickness, weld position, weld type, and reinforcing rib position). This process mainly includes two parts: the preliminary preparation of path planning (environment modeling and function definition) and path generation.

[0121] As shown in Figure 2 , the method for generating the scanning path of the ultrasonic probe based on the geometric feature information includes:

[0122] The geometric feature information includes plate thickness, weld position, weld type, and reinforcing rib position;

[0123] According to the weld position, determine the weld area that needs to be detected by ultrasonic detection, and according to the weld type, select the corresponding ultrasonic probe and scanning method;

[0124] Based on the weld area, plate thickness, ultrasonic probe, scanning method, and reinforcing rib position, complete the environment modeling and function definition, and generate the scanning path of the ultrasonic probe that avoids the reinforcing rib and other non-detection areas.

[0125] The preliminary preparation of path planning, i.e., the method for environment modeling and function definition, includes:

[0126] Divide the detection area (usually the weld and its surrounding area) of the large steel box girder into small, regular lattices, i.e., discretize the detection area of the large steel box girder into a grid map , wherein, is a set of grid nodes, and the coordinates of each grid node are , It is the set of edges that connect adjacent grid nodes.

[0127] Determine grid nodes State attributes ,in, This indicates that the area is idle and the probe can pass through. This indicates that the probe is blocked by an obstacle, such as a reinforcing rib; This indicates the weld area, which requires special attention during inspection.

[0128] Determine grid nodes Normal vector of the surface This refers to the orientation of the surface on which the grid is located. For the weld area, the normal vector represents the orientation of the weld surface.

[0129] Define from grid nodes Move to adjacent grid node Cost function ,in, For grid nodes To grid node Euclidean distance, The cost of adjusting the probe's attitude. The penalty coefficient is determined by the weld type. To avoid the cost of obstacles, For weld priority cost, These are the weighting coefficients;

[0130] Because welds may have different orientations, the probe needs to be adjusted to ensure that the ultrasonic waves are incident perpendicularly. Therefore, the cost of adjusting the probe orientation is related to the angle between the normal vectors of the two grids and is affected by different weld types. It is adjusted by a penalty coefficient, and the penalty coefficient is different for different types of welds.

[0131] If the target grid is an obstacle, the obstacle avoidance cost is infinite. If the target grid is a weld area, the weld priority cost is negative (encouraging the probe to prioritize scanning welds).

[0132] Define from grid nodes To the target node heuristic functions ,in, Cost per unit distance traveled This represents the distance from the current node to the target node in three directions.

[0133] After completing environment modeling and function definition (cost function and heuristic function), a search algorithm is used to generate the scan path. The generation methods include:

[0134] initialization:

[0135] Create an OPEN list to store nodes to be evaluated and a CLOSED list to store nodes that have already been evaluated;

[0136] Start node Add to the OPEN list and set its initial cost. Total cost estimate The cost from the starting node to itself is 0, and the estimated value is the cost from the starting node to the target node. Starting node To the target node Heuristic functions, The initial cost function value, For passing through the starting node The estimated total cost of the path.

[0137] Iterative search:

[0138] Repeat the following steps until the OPEN list is empty (indicating no path was found) or the target node is found (indicating a path was found):

[0139] Select the total cost estimate from the OPEN list. The node with the smallest value and judge Is this the target node? If yes, complete the search, end the iterative search, and enter the path backtracking phase. Otherwise, proceed... Move the node from the OPEN list to the CLOSED list (indicating that the node has already been evaluated and does not need to be considered again), and continue the search;

[0140] Traversal All neighboring nodes and perform the following operations:

[0141] if If it is in the CLOSED list, then skip it (because it has already been evaluated);

[0142] if If not in the CLOSED list, calculate from the starting point. arrive The actual cost , From grid nodes Move to adjacent grid node The cost function, Starting node To the node The actual cost function.

[0143] Next, we will consider two scenarios:

[0144] If is not in the OPEN list, then is added to the OPEN list, and is set to , and the parent of is set to ;

[0145] If is in the OPEN list, and , then is updated to , and the parent of is updated to ;

[0146] Path backtracking:

[0147] Starting from the target node , backtrack to the starting node according to the parent node recorded by each node to generate a preliminary path;

[0148] Path smoothing:

[0149] Due to the discreteness of the grid map, the preliminary path obtained by backtracking is usually composed of a series of broken line segments, which is not smooth enough. Therefore, the generated preliminary path is smoothed by using a Bezier curve to obtain a scanning path.

[0150] The working principle of the method in this embodiment is: based on the grid map, the cost function and the heuristic function, an iterative search algorithm is used to find the optimal path from the starting node to the target node. After finding the preliminary path, the Bezier curve is used for smoothing processing to obtain the final scanning path.

[0151] In Example Four, the actual ultrasonic scanning operation is performed according to the generated scanning path and the determined weld type by using a scanning device.

[0152] The method for performing ultrasonic scanning includes:

[0153] The scanning device includes a mobile platform, a mechanical arm and an ultrasonic probe, and the mechanical arm is installed on the mobile platform. The mobile platform provides the overall movement ability, so that the mechanical arm can reach different positions of the steel box girder. An omnidirectional mobile robot chassis (for example, a Mecanum wheel chassis, a differential wheel chassis, etc.) is used, and a positioning system (for example, a laser radar, a visual navigation, etc.) should be equipped to realize accurate autonomous navigation and positioning.

[0154] The mechanical arm is mounted on a mobile platform, providing precise positioning and attitude adjustment capabilities, enabling the probe to move along the scanning path. A six-axis or seven-axis industrial robot is used, with joint movements precisely controlled by a control system to achieve precise movement and attitude adjustment of the probe on the surface of the steel box girder.

[0155] Different types of probes are selected according to different weld types (butt, corner, T), such as oblique probes, double crystal probes, TOFD probes, climbing probes, and phased array probes. The ultrasonic probes are installed at the end of the mechanical arm, responsible for transmitting and receiving ultrasonic waves.

[0156] When performing ultrasonic scanning, the mobile platform and mechanical arm are controlled to move the ultrasonic probe along the scanning path. The mobile platform is responsible for large-scale movement, transporting the mechanical arm to different detection areas of the steel box girder. The mechanical arm is responsible for fine movement, enabling the probe to move precisely along the scanning path and adjusting the probe's attitude to ensure that the ultrasonic waves are incident at the optimal angle into the weld.

[0157] According to the type of weld, select the corresponding ultrasonic probe and scanning method:

[0158] If the weld type is butt weld, select an oblique probe to transmit and receive ultrasonic waves, and perform transverse scanning. The ultrasonic waves generated by the oblique probe are incident at a certain angle into the steel box girder, effectively detecting defects in the butt weld. The transverse scanning probe moves perpendicular to the direction of the weld.

[0159] If the weld type is corner weld, select a double crystal probe or a TOFD probe to transmit and receive ultrasonic waves, and perform longitudinal scanning. The double crystal probe transmits ultrasonic waves from one crystal and receives them from the other, suitable for detecting defects at the root and near the surface of the corner weld. The TOFD probe detects defects using the diffraction waves at the end points. Longitudinal scanning means that the probe moves parallel to the direction of the weld.

[0160] If the weld type is T-type weld, select a climbing probe or a phased array probe to transmit and receive ultrasonic waves, and perform transverse or longitudinal scanning. The climbing probe allows ultrasonic waves to propagate along the T-type weld's groove. The phased array probe can electronically control the deflection and focusing of the ultrasonic beam, and the scanning method depends on the geometry of the T-type weld and the possible location of the defects.

[0161] The working principle is to control the scanning device (mobile platform and mechanical arm) to move the ultrasonic probe along the pre-planned scanning path, and select the appropriate probe and scanning method according to the weld type during the movement.

[0162] In Example Five, the method of how to process and analyze the collected ultrasonic echo signals to identify whether there are defects and the type of defects is provided.

[0163] The method for identifying the position of a welding defect comprises:

[0164] Discrete wavelet transform is performed on the ultrasonic echo signal , wherein, is a wavelet coefficient, is a scale parameter, is a translation parameter, is a complex conjugate of a wavelet basis function, is a signal length, is an ultrasonic echo signal, is time;

[0165] A threshold value of the wavelet coefficient at the scale is determined, wherein, is a standard deviation of noise at the scale , and is a number of wavelet coefficients at the scale ;

[0166] The wavelet coefficients are processed using a soft threshold function ;

[0167] Inverse discrete wavelet transform is performed on the processed wavelet coefficients to obtain a denoised signal ;

[0168] Since the ultrasonic wave attenuates during propagation, the echo signal of a defect deep in the part is weak. In order to compensate for this attenuation, time gain compensation needs to be performed on the denoised signal. A TCG curve is constructed, and the denoised signal is compensated to obtain a final echo signal .

[0169] Time-frequency features in the final echo signal are extracted through short-time Fourier transform and continuous wavelet transform; for example, time-frequency energy distribution, instantaneous frequency, instantaneous bandwidth, wavelet entropy, time-frequency ridge, etc.

[0170] The time-frequency features are input into a deep residual time-frequency network that has been trained, and a feature vector is output; the deep residual time-frequency network is a deep learning model that is good at processing time series data and image data, and is composed of multiple residual blocks, each of which contains a convolutional layer, a batch normalization layer, a ReLU activation function, and an attention mechanism.

[0171] The feature vector To perform classification, the Softmax function can convert the feature vector into a probability distribution, representing the probability that the signal belongs to each defect class (including the "no defect" class).

[0172] The probability values belonging to the list of classes are calculated as wherein is the actual number of defect classes, , represents no defect, represents the various defect classes, is the transpose matrix of the weight vector of the class , is the bias of the class , is the transpose matrix of the weight vector of the class , is the bias of the class .

[0173] A confidence threshold is set, if the classification result is discarded, if the corresponding is taken as the defect type; if it is determined to be no defect, and equal to other values represents the presence of the corresponding defect.

[0174] After completing the identification of the defect type on the scanning path, the defect positioning of the weld with defects is performed, and the positioning method of the welding defect position includes:

[0175] The final echo signal is subjected to continuous wavelet transform to obtain wavelet coefficients , and the wavelet energy distribution is calculated, wherein is a scale parameter, is a translation parameter.

[0176] The time point corresponding to the maximum energy value is selected as the arrival time of the defect echo , wherein is the maximum value of the wavelet energy distribution in all scale parameters , and is the translation parameter corresponding to the maximum value .

[0177] The depth of the welding defect position is calculated as , wherein is the ultrasonic wave propagation speed in the material of the large steel box girder.

[0178] The coordinates of the ultrasonic probe in the large steel box girder coordinate system are obtained ​and the attitude angle wherein, is the roll angle, is the pitch angle, is the yaw angle; the steel box girder coordinate system takes a certain corner point of the large steel box girder as the origin and the length, width and height directions of the large steel box girder as the coordinate axes.

[0179] calculating the coordinates of the defect position in the probe coordinate system , ; the probe coordinate system takes the center of the ultrasonic probe as the origin, and the z-axis of the probe coordinate system is perpendicular to the ultrasonic probe, and the x-axis and y-axis of the probe coordinate system are parallel to the ultrasonic probe.

[0180] converting the defect position coordinates from the probe coordinate system to the large steel box girder coordinate system to obtain the welding defect position coordinates , wherein, is the rotation matrix determined by the attitude angle, wherein, is the rotation matrix around the axis, is the rotation matrix around the axis, is the rotation matrix around the axis.

[0181] Finally, a construction method of a TCG curve is provided.

[0182] constructing an initial TCG curve, wherein, is the propagation time of the ultrasonic wave, is the sound velocity of the ultrasonic wave in the material, is the frequency of the ultrasonic wave, is a constant for adjusting the overall gain level, is a frequency-dependent material attenuation coefficient.

[0183] Make a standard test block containing flat-bottom holes of known depths (or use actual workpieces with known depth defects).

[0184] Use the ultrasonic probe to scan the test block and record the echo signals of flat-bottom holes of different depths.

[0185] measure the amplitude of the echo signal of each flat-bottom hole , is the echo time corresponding to the th flat-bottom hole.

[0186] According to the theoretical model calculation, the theoretical amplitude without considering attenuation is .

[0187] Computing the amplitude difference .

[0188] Performing a curve fit (e.g., using a polynomial fit) to obtain a calibration curve .

[0189] Superimposing the calibration curve onto the initial TCG curve to obtain a final TCG curve: .

[0190] Performing gain compensation .

[0191] Embodiment six, a computer readable storage medium, the computer readable storage medium stores a computer program, the computer program is executed by a processor to realize the steps of the above-mentioned antenna interface unit test method.

[0192] Without loss of generality, the computer readable medium can include computer storage media and communication media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer readable instructions data structures, program modules or other data. Computer storage media includes RAM, ROM, EPROM, EEPROM, flash memory or other solid state storage technology, CD-ROM, DVD or other optical storage, magnetic cassette, magnetic tape, disk storage or other magnetic storage device. Of course, those skilled in the art can know that computer storage media is not limited to the above several. The above-mentioned system memory and mass storage device can be collectively referred to as memory.

[0193] A computer program product includes computer programs / instructions that, when executed by a processor, implement the steps of any of the above methods.

[0194] A computer program product includes computer programs or instruction sets for performing specific tasks or implementing specific functions. These programs or instructions are designed to be executed by a processor, so as to realize a series of predefined steps or operations. The program product can be stored in various forms of computer storage media, such as memory, hard disk, solid state drive, optical disc or other forms of digital storage device. It may exist in the form of compiled binary code, or in the form of script or bytecode executable by the interpreter. The program product is designed by careful algorithm and logic instruction, so that the processor can process data in a specific order and way, complete various functions such as data analysis, user interaction, device control, etc.

[0195] In the description of the specification, the description of the terms "one embodiment / way", "some embodiments / ways", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment / way or example are included in at least one embodiment / way or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment / way or example. Also, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments / ways or examples. In addition, the person skilled in the art can combine and combine the different embodiments / ways or examples described in the specification and the features of the different embodiments / ways or examples, without contradiction.

[0196] In addition, the terms "first", "second" are only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise specifically limited.

[0197] The person skilled in the art should understand that the above-mentioned embodiments are only for the purpose of clearly illustrating the present application, and are not intended to limit the scope of the present application. For those skilled in the art, other changes or modifications can be made on the basis of the above-mentioned application, and these changes or modifications are still within the scope of the present application.

Claims

1. A method for detecting defects in a large steel box girder, characterized by, The method comprises the following steps: Import a three-dimensional model of a large steel box girder, and analyze the three-dimensional model to obtain geometric characteristic information of the steel box girder; Generate a scanning path of an ultrasonic probe based on the geometric characteristic information; Control the ultrasonic probe to scan the large steel box girder according to the scanning path, and collect ultrasonic echo signals; Process the ultrasonic echo signals, identify and locate the welding defect position of the steel box girder; The method for generating the scanning path of the ultrasonic probe based on the geometric characteristic information comprises the following steps: The geometric characteristic information comprises plate thickness, welding seam position, welding seam type and reinforcing rib position; Determine a welding seam area needing ultrasonic detection according to the welding seam position, and select a corresponding ultrasonic probe and scanning mode according to the welding seam type; Based on the welding seam area, the plate thickness, the ultrasonic probe, the scanning mode and the reinforcing rib position, complete environment modeling and function definition, and generate the scanning path of the ultrasonic probe avoiding the reinforcing ribs and other non-detection areas; The method for environment modeling and function definition comprises the following steps: Discretize the region to be detected of a large steel box girder into a grid map wherein, is a set of grid nodes, each grid node has a coordinate , is a set of edges connecting adjacent grid nodes; determining the state attribute of a grid node of a grid node wherein represents free, represents occupied by an obstacle, represents a weld seam region; determining a grid node normal vector of the surface ; Definition from grid node Move to adjacent grid node Cost function wherein, is the Euclidean distance from grid node to grid node is the Euclidean distance from grid node is the probe pose adjustment cost, is a penalty coefficient determined by the weld type, is the obstacle avoidance cost, is the weld priority cost, is the weight coefficient; Define from grid nodes To the target node heuristic functions ,in, Cost per unit distance traveled This represents the distance from the current node to the target node in three directions.

2. The method according to claim 1, wherein, The method for obtaining the geometric characteristic information of the steel box girder comprises the following steps: Read a three-dimensional model of the large steel box girder, and the three-dimensional model file is in STEP format or IGES format; Analyze entities and relationships in the three-dimensional model file to obtain geometric information and topological information of faces, geometric information and topological information of edges, and coordinate information of vertices of the large steel box girder; Based on the geometric information and topological information of the faces, the geometric information and topological information of the edges, and the coordinate information of the vertices, calculate the plate thickness of the large steel box girder, identify the welding seam position, determine the welding seam type, and identify the reinforcing rib position.

3. The method according to claim 2, wherein The method for calculating the plate thickness comprises the following steps: Calculate the distance between two opposite parallel faces of the large steel box girder; The method for identifying the welding seam position comprises the following steps: Find adjacent faces of the large steel box girder; Calculate the included angle between the adjacent faces; If the included angle is less than a first preset threshold value and the adjacent faces are connected by a common edge, the potential welding seam is determined; Determine the thickness of the geometric bodies on both sides of the potential welding seam, and if the thickness is less than a second preset threshold value, the potential welding seam is determined as a welding seam; The method for determining the welding seam type comprises the following steps: Set a1, a2 and a3 as preset error angle values; If the included angle between the faces on both sides of the welding seam is 180±a1 degrees, the welding seam is determined as a butt joint welding seam; If the included angle between the faces on both sides of the welding seam is 90±a2 degrees, the welding seam is determined as a fillet welding seam; If the edge of the face on one side of the welding seam is connected to the inside of the face on the other side, and the included angle between the two faces is 90±a3 degrees, the welding seam is determined as a T-type welding seam; The method for identifying the reinforcing rib position comprises the following steps: Calculate the aspect ratio of each face in the three-dimensional model, and determine a face with an aspect ratio greater than a third preset threshold value as a thin plate structure; Find the thin plate structure in the large steel box girder; Determine whether the thin plate structure is connected to a main plate of the large steel box girder; 4. The method according to claim 1, wherein, If the thin plate structure is connected to the main plate, the thin plate structure is determined as a reinforcing rib. The method for generating the scanning path comprises the following steps: Initialization: Start node Add to the OPEN list and set its initial cost. Total cost estimate ; Starting node To the target node Heuristic functions, The initial cost function value, For passing through the starting node The estimated total cost of the path; Create an OPEN list for storing nodes to be evaluated and a CLOSED list for storing nodes that have been evaluated; Iterative search: selecting the total cost estimate from the open list the node with the smallest value and determining whether it is the goal node, if so the search is complete; if not the node is moved from the open list to the closed list and the search continues ​ traversing all adjacent nodes of and performing the following operations: If If in CLOSED list, skip; If not in the CLOSED list, then calculate the actual cost of reaching from the start node to the current node , the cost function of moving from grid node to adjacent grid node , the actual cost function from start node to node ; if If not in the OPEN list, then Add to OPEN list, settings , and record The parent node is , For nodes To the target node Heuristic functions, Starting node To any node The actual cost function, For the nodes The estimated total cost of the path; If is in the OPEN list, and is not in the CLOSED list, then update , , and update the parent of to ; Loop the following steps until the OPEN list is empty or the target node is found: From the target node Starting from the target node, backtrack to the start node according to the parent node recorded by each node , generate a preliminary path; Path backtracking: Path smoothing: The generated preliminary path is smoothed by using a Bezier curve to obtain a scanning path.

5. The method according to claim 3, wherein, The method for performing ultrasonic scanning comprises: The scanning device comprises a moving platform, a mechanical arm and an ultrasonic probe, wherein the mechanical arm is installed on the moving platform; When performing ultrasonic scanning, the moving platform and the mechanical arm are controlled to move so that the ultrasonic probe moves along the scanning path; According to the type of the weld, a corresponding ultrasonic probe and scanning method are selected: If the weld type is a butt joint, an inclined probe is selected to emit and receive ultrasonic waves, and transverse scanning is performed; If the weld type is a fillet joint, a double-crystal probe or a TOFD probe is selected to emit and receive ultrasonic waves, and longitudinal scanning is performed; If the weld type is a T-shaped joint, a climbing probe or a phased array probe is selected to emit and receive ultrasonic waves, and transverse or longitudinal scanning is performed.

6. The method according to claim 1, wherein, The method for identifying the position of a welding defect comprises: Discrete wavelet transform of an ultrasonic echo signal wherein is a wavelet coefficient, is a scale parameter, is a shift parameter, is a complex conjugate of a wavelet basis function, is a signal length, is an ultrasonic echo signal, is time; determining the scale wavelet coefficients threshold wherein is the scale standard deviation of the noise below the scale, is the number of wavelet coefficients below the scale ; wavelet coefficients are processed using a soft threshold function ; wavelet coefficients after processing performing inverse discrete wavelet transform to obtain the signal after noise reduction ; Constructing a TCG curve and applying a de-noising to the signal Compensating and obtaining a final echo signal ; extracting time-frequency features in the final echo signal by short-time fourier transform and continuous wavelet transform ​ inputting the time-frequency features into the deep residual time-frequency network which has been trained, and outputting a feature vector ; The feature vector is classified by a Softmax function to calculate probability values belonging to a list of classes wherein is the actual number of defect classes, , represents no defect, represents various defect classes, is the transpose matrix of the weight vector of the class , is the bias of the class , is the transpose matrix of the weight vector of the class , is the bias of the class . Setting a confidence threshold , if the classification result is discarded, if , the corresponding is taken as the defect type, is the maximum value of the probability value; After the type of the defect on the scanning path is identified, the weld with the defect is positioned.

7. The method according to claim 6, wherein, The method for positioning the position of a welding defect comprises: to the final echo signal performing a continuous wavelet transform to obtain wavelet coefficients and calculating a wavelet energy distribution wherein is a scale parameter, is a translation parameter; Select the time point corresponding to the maximum energy value as the arrival time of the defect echo wherein, is the maximum value of the wavelet energy distribution in all scale parameters , is the shift parameter corresponding to the maximum value ; Computing depth of a welding defect location wherein, is the ultrasonic wave propagation speed in the material of the large steel box girder; Obtaining coordinates of an ultrasonic probe in a coordinate system of a large steel box girder and an attitude angle wherein, is a roll angle, is a pitch angle, is a yaw angle; calculating coordinates of the defect location in the probe coordinate system , ; Convert the defect position coordinates from the probe coordinate system to the large steel box girder coordinate system to obtain the welding defect position coordinates , wherein, is a rotation matrix determined by the attitude angle, wherein, is a rotation matrix around axis, is a rotation matrix around axis, is a rotation matrix around axis.

8. A computer program product comprising computer programs or instructions, characterized in that, The computer program or instructions are executed by a processor to implement the method of any one of claims 1-7.

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