Method for constructing imaging algorithm of transmission fitting ultrasonic detection device

Abstract

The construction method comprises the following steps: generating and optimizing an ultrasonic evanescent wave signal through a wedge-shaped probe, collecting an evanescent wave signal and a propagation wave signal of a power transmission fitting, and carrying out noise reduction processing on the collected signal by using an anti-interference algorithm; carrying out multi-modal fusion processing on the evanescent wave and propagation wave signals after noise reduction, and carrying out defect classification and prediction on signal features based on a deep learning model; three-dimensional imaging of the interior of the hardware fitting is realized through a super-resolution reconstruction algorithm, regional feature extraction is performed on a three-dimensional imaging result, hierarchical data is generated, intelligent segmentation and defect labeling are performed on the hierarchical data, and meanwhile, a generated detection result is uploaded to a remote server, so that scene analysis is realized. According to the method, efficient detection can be carried out in a complex field environment, and technical support can be provided for state monitoring and fault prediction of the power transmission fitting through remote data processing and analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of ultrasonic detection of power transmission fittings, and in particular to a method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings. Background Art

[0002] With the rapid development of the power industry, transmission fittings play a key role in connection and conduction in the power grid, and their quality directly affects the safe operation of the power system. However, the existing transmission fitting detection technology mainly relies on appearance inspection, grip test or X-ray inspection, which have certain limitations. For example, appearance inspection cannot reflect the internal structural state of the fittings; the grip test is a destructive test and is only suitable for batch sampling before installation; and the X-ray detection equipment is bulky, complicated to operate, and difficult to use in the field high-altitude working environment. In addition, the imaging of traditional detection methods is mostly two-dimensional plane images, which is difficult to fully reflect the three-dimensional structural characteristics of the internal defects of the fittings, limiting the accuracy and refinement of defect analysis. Therefore, it is particularly important to develop an efficient three-dimensional imaging method suitable for the internal structure detection of transmission fittings. Summary of the invention

[0003] In view of the above existing problems, the present invention is proposed.

[0004] Therefore, the present invention provides a method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings. In view of the technical limitations of existing power transmission fitting detection methods, a method for constructing an imaging algorithm based on an ultrasonic detection device is proposed to solve the following technical problems: first, how to achieve high-resolution detection of the complex internal structure of power transmission fittings through optimized ultrasonic evanescent wave and propagation wave signal acquisition technology; second, how to improve the quality and reliability of signals and eliminate noise interference in complex environments through anti-interference signal processing algorithms; third, how to achieve accurate classification and extended prediction of defects through multimodal fusion algorithms and deep learning models; finally, how to comprehensively reconstruct the internal structure model of power transmission fittings through super-resolution three-dimensional imaging and intelligent stratification technology, and mark and locate defects to meet the application needs of on-site detection and remote collaboration.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings, comprising:

[0006] Generate and optimize ultrasonic evanescent wave signals through wedge-shaped probes, collect evanescent wave signals and propagation wave signals of power transmission fittings, and use anti-interference algorithms to reduce noise on the collected signals;

[0007] Perform multimodal fusion processing on the de-noised evanescent wave and propagation wave signals, and classify and predict defects based on the signal features based on the deep learning model;

[0008] The super-resolution reconstruction algorithm is used to achieve three-dimensional imaging inside the hardware, and regional features are extracted from the three-dimensional imaging results to generate layered data. The layered data is then intelligently segmented and defect labeled. At the same time, the generated inspection results are uploaded to a remote server to achieve scenario-based analysis.

[0009] As a preferred solution of the method for constructing the imaging algorithm of the ultrasonic detection device for power transmission fittings described in the present invention, wherein: the generating and optimizing the ultrasonic evanescent wave signal includes using an adaptive wedge probe to dynamically adjust the ultrasonic incident angle to a critical angle according to the detection environment to form an evanescent wave field;

[0010] The frequency and pulse width of the ultrasonic wave are adjusted, and combined with a nine-square electromagnetic induction array collector, the evanescent wave signal in the near field of the hardware surface is collected with high sensitivity.

[0011] As a preferred solution of the method for constructing the imaging algorithm of the ultrasonic detection device for power transmission fittings described in the present invention, wherein: the acquisition of the evanescent wave signal and the propagation wave signal of the power transmission fitting includes: a sensor array designed for multi-band signal acquisition, and simultaneously acquiring evanescent wave signals and propagation wave signals of different frequencies; a high-viscosity coupling material is used between the signal acquisition device and the power transmission fitting to ensure stable signal transmission; and the acquisition time of the evanescent wave signal and the propagation wave signal is calibrated through a signal synchronization device to maintain signal synchronization.

[0012] As a preferred solution of the method for constructing the imaging algorithm of the ultrasonic detection device for power transmission fittings described in the present invention, the anti-interference algorithm includes using sparse representation decomposition technology to split the input ultrasonic signal into sparse components and interference components, and dynamically adjusts the frequency range through an adaptive bandpass filter to filter non-target noise signals, and uses multidimensional wavelet transform technology to separate and suppress interference signals from the time domain, frequency domain and directional domain.

[0013] As a preferred solution of the method for constructing the imaging algorithm of the ultrasonic detection device for power transmission fittings described in the present invention, the multimodal fusion processing includes constructing a multi-input convolutional neural network model, inputting the signal data of the evanescent wave and the propagation wave into the neural network respectively, setting a dynamic weighting mechanism in the network structure, adjusting the fusion ratio of the evanescent wave and the propagation wave signals according to the signal type and characteristics, and extracting the time series characteristics and spatial distribution characteristics in the signal through the time-space domain feature extraction module.

[0014] As a preferred solution of the method for constructing the imaging algorithm of the ultrasonic detection device for power transmission fittings described in the present invention, the defect classification and prediction of signal features includes: using transfer learning technology to construct a deep learning classification model, pre-training the model through industrial ultrasonic detection data, using a generative adversarial network to generate different types of defect simulation samples, expanding the training data set of the classification model, and using a recursive neural network to analyze the time series characteristics contained in the ultrasonic signal to predict the development trend of the defects.

[0015] As a preferred solution of the method for constructing the imaging algorithm of the ultrasonic detection device for power transmission fittings described in the present invention, the super-resolution reconstruction algorithm includes optimizing the spatial resolution of the ultrasonic signal based on the eigenvalue decomposition of the time reversal matrix, and dividing the depth information of the ultrasonic signal into two-dimensional image slices, each slice representing signal data at a specific depth, and reconstructing the slice image into a complete three-dimensional structural model of the power transmission fitting through layer-by-layer superposition technology.

[0016] As a preferred solution of the method for constructing the imaging algorithm of the ultrasonic detection device for power transmission fittings described in the present invention, the generating layered data includes segmenting the generated three-dimensional model in a set area using a deep learning segmentation algorithm, and dividing the three-dimensional model into multiple independent layers according to material properties and signal characteristics, including a metal substrate layer, a crack layer and a corrosion layer;

[0017] Perform preliminary data structuring on the stratified results to form a data model for defect analysis.

[0018] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, steps of a method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings are implemented.

[0019] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of a method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings are implemented.

[0020] Beneficial effects of the present invention: The present invention provides an efficient, accurate and intelligent imaging algorithm construction method for ultrasonic detection devices of power transmission fittings. Through innovative evanescent wave signal optimization and multimodal fusion technology, high-resolution detection of internal defects of fittings is achieved; combined with anti-interference signal processing and deep learning algorithms, the quality of signals and the accuracy of defect classification are significantly improved; based on super-resolution three-dimensional imaging technology, the internal structure of fittings can be completely reconstructed, and through intelligent stratification and defect labeling technology, complex defects can be accurately identified and classified. The method of the present invention is simple to operate and has strong adaptability. It can not only perform efficient detection in complex environments in the field, but also provide technical support for status monitoring and fault prediction of power transmission fittings through remote data processing and analysis, significantly improving the safety and reliability of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0022] Figure 1 A schematic flow chart of a method for constructing an imaging algorithm for an ultrasonic detection device for power transmission fittings provided in accordance with an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0024] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0025] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0026] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0027] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0028] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0029] Example 1, reference Figure 1 , which is the first embodiment of the present invention, provides a method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings, comprising:

[0030] S1: Generate and optimize ultrasonic evanescent wave signals through a wedge probe, collect evanescent wave signals and propagation wave signals of power transmission fittings, and use anti-interference algorithms to reduce noise on the collected signals.

[0031] S2: Perform multimodal fusion processing on the de-noised evanescent wave and propagation wave signals, and classify and predict defects based on the signal features based on the deep learning model.

[0032] S3: The super-resolution reconstruction algorithm is used to achieve three-dimensional imaging inside the hardware, and regional features are extracted from the three-dimensional imaging results to generate layered data. The layered data is then intelligently segmented and defect labeled. At the same time, the generated test results are uploaded to a remote server to achieve scenario-based analysis.

[0033] Generating and optimizing the ultrasonic evanescent wave signal includes using an adaptive wedge-shaped probe to dynamically adjust the ultrasonic incident angle to a critical angle according to the detection environment to form an evanescent wave field;

[0034] The frequency and pulse width of the ultrasonic wave are adjusted, and combined with a nine-square electromagnetic induction array collector, the evanescent wave signal in the near field of the hardware surface is collected with high sensitivity.

[0035] The method of collecting the evanescent wave signal and the propagation wave signal of the power transmission fitting includes: designing a sensor array for multi-band signal collection to simultaneously obtain the evanescent wave signals and the propagation wave signals of different frequencies; using a high-viscosity coupling material between the signal collection device and the power transmission fitting to ensure stable signal transmission; and calibrating the collection time of the evanescent wave signal and the propagation wave signal through a signal synchronization device to maintain signal synchronization.

[0036] The anti-interference algorithm includes using sparse representation decomposition technology to split the input ultrasonic signal into sparse components and interference components, and dynamically adjusting the frequency range through an adaptive bandpass filter to filter non-target noise signals. At the same time, multi-dimensional wavelet transform technology is used to separate and suppress interference signals from the time domain, frequency domain and directional domain.

[0037] The multimodal fusion processing includes constructing a multi-input convolutional neural network model, inputting the signal data of the evanescent wave and the propagation wave into the neural network respectively, setting a dynamic weighting mechanism in the network structure, adjusting the fusion ratio of the evanescent wave and the propagation wave signals according to the signal type and characteristics, and extracting the time series characteristics and spatial distribution characteristics in the signal through the spatiotemporal domain feature extraction module.

[0038] The defect classification and prediction of signal features includes: using transfer learning technology to build a deep learning classification model, pre-training the model through industrial ultrasonic detection data, using a generative adversarial network to generate different types of defect simulation samples, expanding the training data set of the classification model, and using a recursive neural network to analyze the time series features contained in the ultrasonic signal to predict the development trend of the defects.

[0039] The super-resolution reconstruction algorithm includes optimizing the spatial resolution of the ultrasonic signal based on the eigenvalue decomposition of the time reversal matrix, and dividing the depth information of the ultrasonic signal into two-dimensional image slices, each slice representing the signal data at a specific depth. At the same time, through the layer-by-layer superposition technology, the slice image is reconstructed into a complete three-dimensional structural model of the power transmission fitting.

[0040] Generating layered data includes segmenting the generated three-dimensional model into a set area using a deep learning segmentation algorithm, and dividing the three-dimensional model into multiple independent layers according to material properties and signal characteristics, including a metal substrate layer, a crack layer, and a corrosion layer;

[0041] Perform preliminary data structuring on the stratified results to form a data model for defect analysis.

[0042] According to the geometric characteristics of the 3D model, the boundary information of the defect area is extracted and annotated. Based on the signal characteristics of the defect, the classification algorithm is used to classify the annotated area and generate type labels of defects such as cracks, pores or corrosion. The spatial coordinate information of the defect area is attached to the 3D model to form a complete defect annotation model.

[0043] The 3D imaging data and its annotation information are transmitted to the remote server through the communication module; the data is parsed on the server side and a visual inspection report including the 3D model and defect annotations is generated; a remote collaboration interface is provided to allow operators to conduct further analysis and processing based on the uploaded data and generate decision support data.

[0044] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0045] Embodiment 2, the second embodiment of the present invention, is different from the previous embodiment in that:

[0046] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0047] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0048] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0049] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0050] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0051] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for constructing an imaging algorithm for an ultrasonic detection device for power transmission fittings, characterized in that: include, Generate and optimize ultrasonic evanescent wave signals through wedge-shaped probes, collect evanescent wave signals and propagation wave signals of power transmission fittings, and use anti-interference algorithms to reduce noise on the collected signals; Perform multimodal fusion processing on the de-noised evanescent wave and propagation wave signals, and classify and predict defects based on the signal features based on the deep learning model; The super-resolution reconstruction algorithm is used to achieve three-dimensional imaging inside the hardware, and regional features are extracted from the three-dimensional imaging results to generate layered data. The layered data is then intelligently segmented and defect labeled. At the same time, the generated inspection results are uploaded to a remote server to achieve scenario-based analysis.

2. The method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings according to claim 1, characterized in that: Generating and optimizing the ultrasonic evanescent wave signal includes using an adaptive wedge probe to dynamically adjust the ultrasonic incident angle to a critical angle according to the detection environment to form an evanescent wave field; The frequency and pulse width of the ultrasonic wave are adjusted, and combined with a nine-square electromagnetic induction array collector, the evanescent wave signal in the near field of the hardware surface is collected with high sensitivity.

3. The method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings according to claim 2, characterized in that: The method of collecting the evanescent wave signal and the propagation wave signal of the power transmission fitting includes: designing a sensor array for multi-band signal collection to simultaneously obtain the evanescent wave signals and the propagation wave signals of different frequencies; using a high-viscosity coupling material between the signal collection device and the power transmission fitting to ensure stable signal transmission; and calibrating the collection time of the evanescent wave signal and the propagation wave signal through a signal synchronization device to maintain signal synchronization.

4. The method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings according to claim 3, characterized in that: The anti-interference algorithm includes using sparse representation decomposition technology to split the input ultrasonic signal into sparse components and interference components, and dynamically adjusting the frequency range through an adaptive bandpass filter to filter non-target noise signals. At the same time, multi-dimensional wavelet transform technology is used to separate and suppress interference signals from the time domain, frequency domain and directional domain.

5. The method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings according to claim 4, characterized in that: The multimodal fusion processing includes constructing a multi-input convolutional neural network model, inputting the signal data of the evanescent wave and the propagation wave into the neural network respectively, setting a dynamic weighting mechanism in the network structure, adjusting the fusion ratio of the evanescent wave and the propagation wave signals according to the signal type and characteristics, and extracting the time series characteristics and spatial distribution characteristics in the signal through the spatiotemporal domain feature extraction module.

6. The method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings according to claim 5, characterized in that: The defect classification and prediction of signal features includes: using transfer learning technology to build a deep learning classification model, pre-training the model through industrial ultrasonic detection data, using a generative adversarial network to generate different types of defect simulation samples, expanding the training data set of the classification model, and using a recursive neural network to analyze the time series features contained in the ultrasonic signal to predict the development trend of the defects.

7. The method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings according to claim 6, characterized in that: The super-resolution reconstruction algorithm includes optimizing the spatial resolution of the ultrasonic signal based on the eigenvalue decomposition of the time reversal matrix, and dividing the depth information of the ultrasonic signal into two-dimensional image slices, each slice representing the signal data at a specific depth. At the same time, through the layer-by-layer superposition technology, the slice image is reconstructed into a complete three-dimensional structural model of the power transmission fitting.

8. The method for constructing an imaging algorithm of an ultrasonic detection device for power transmission fittings according to claim 7, characterized in that: Generating layered data includes segmenting the generated three-dimensional model into a set area using a deep learning segmentation algorithm, and dividing the three-dimensional model into multiple independent layers according to material properties and signal characteristics, including a metal substrate layer, a crack layer, and a corrosion layer; Perform preliminary data structuring on the stratified results to form a data model for defect analysis.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

Images