Equipment damage assessment method based on equipment structure data
By constructing coupled grayscale images and noise reduction processing of equipment structure data, combined with tactical and technical indicator matrix, rapid and accurate assessment of equipment damage is achieved, and the problems of inaccurate and low efficiency in the existing technology are solved.
Patent Information
- Application Number
- CN202411311466.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-19
- Publication Date
- 2024-12-13
AI Technical Summary
The existing equipment damage assessment methods only rely on combat technical indicators and fail to fully consider equipment structure data, resulting in low evaluation accuracy and efficiency, and cannot meet the fast, accurate and efficient evaluation requirements.
By obtaining the equipment's structural data radar grayscale images, optical grayscale images and low-light grayscale images, constructing structural data coupled grayscale images, and performing three-dimensional rotation noise reduction processing, combining the equipment tactical matrix and technical indicator matrix, optimizing weighting is adopted Evaluation formula determines the degree of damage.
The accuracy and efficiency of equipment damage assessment are improved, and the accuracy and speed of assessment are improved through the comprehensive utilization and weighting adjustment of a variety of imaging data, and the problems of incomplete evaluation and unscientific weighting coefficients are solved.
Smart Images
Figure CN119130880A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of equipment damage assessment, and in particular to an equipment damage assessment method based on equipment structure data. Background Art
[0002] At present, equipment damage assessment is only completed by testing the equipment's combat and technical indicators. This method does not include the equipment's structural data in the scope of basic assessment data, and cannot comprehensively assess the equipment's damage. In addition, this method has the problems of long testing time, low assessment accuracy and efficiency, and cannot meet current requirements for fast, accurate and efficient assessment. Summary of the invention
[0003] The purpose of this application is to provide an equipment damage assessment method based on equipment structure data, which can improve the accuracy and efficiency of equipment damage assessment.
[0004] To achieve the above objectives, this application provides the following solutions:
[0005] The present application provides an equipment damage assessment method based on equipment structure data, comprising:
[0006] Acquire the radar grayscale image of the structural data, the optical grayscale image of the structural data and the low-light grayscale image of the structural data of the equipment to be evaluated;
[0007] constructing a structural data coupled grayscale image according to the structural data radar grayscale image, the structural data optical grayscale image and the structural data low-light grayscale image;
[0008] Performing three-dimensional rotation noise reduction processing on the structure data coupled grayscale image to obtain a structure data denoised coupled grayscale image;
[0009] Obtain the equipment tactical matrix and technical indicator matrix of the equipment to be evaluated;
[0010] The damage degree of the equipment to be evaluated is determined based on the structural data denoised coupled grayscale image, the equipment tactical matrix and the technical indicator matrix.
[0011] Optionally, the degree of injury includes mild, moderate and severe.
[0012] Optionally, the grayscale value of any pixel in the structural data coupled grayscale image is:
[0013]
[0014] Among them, p i,j represents the gray value of the pixel (i, j) in the structure data coupled gray image, α1 represents the weight of the structure data radar gray image, represents the gray value of the pixel (i, j) in the structural data radar gray image, α2 represents the weight of the structural data optical gray image, represents the gray value of the pixel (i, j) in the optical gray image of the structural data, α3 represents the weight of the low-light gray image of the structural data, Represents the grayscale value of the pixel (i, j) in the low-light grayscale image of the structural data.
[0015] Optionally, the grayscale value of any pixel in the structure data denoised coupled grayscale image is:
[0016]
[0017] in, Represents the grayscale value of the pixel (i, j) in the structure data denoised coupled grayscale image.
[0018] Optionally, determining the damage degree of the equipment to be evaluated based on the structure data denoised coupled grayscale image, the equipment tactical matrix and the technical indicator matrix includes:
[0019] Performing a softening process on the equipment tactical matrix to obtain a softened equipment tactical matrix;
[0020] Performing a softening process on the technical indicator matrix to obtain a softened technical indicator matrix;
[0021] Based on the structure data denoised coupled grayscale image, the softened equipment tactical matrix and the softened equipment tactical matrix, an optimized weighted evaluation formula is used to determine an optimized weighted evaluation value of each pixel in the structure data denoised coupled grayscale image;
[0022] Determining a determination amount based on optimized weighted evaluation values of all pixels in the structure data denoised coupled grayscale image;
[0023] When the determination value is less than a first threshold, determining that the damage degree of the equipment to be evaluated is slight;
[0024] When the determination amount is greater than or equal to a first threshold value and the determination amount is less than a second threshold value, it is determined that the damage degree of the equipment to be evaluated is moderate; and the first threshold value is less than the second threshold value;
[0025] When the determination value is greater than or equal to the second threshold, it is determined that the damage degree of the equipment to be evaluated is severe.
[0026] Optionally, the flexible equipment tactical matrix is:
[0027] m 1,r =m1·p d1 ;
[0028] Among them, m 1,r is the softening equipment tactical matrix, m1 is the equipment tactical matrix, p d1 It is the softening parameter matrix of the equipment tactical matrix.
[0029] Optionally, the softening technical indicator matrix is:
[0030] m 2,r =m2·p d2 ;
[0031] Among them, m 2,r is the softening technical indicator matrix, m2 is the technical indicator matrix, p d2 It is the softening parameter matrix of the technical indicator matrix.
[0032] Optionally, the optimization weighted evaluation formula is:
[0033]
[0034] Among them, e i,j It represents the optimized weighted evaluation value of pixel point (i, j), and mount(*) represents pixel point extraction.
[0035] Optionally, determining the determination amount based on the optimized weighted evaluation values of all pixels in the structure data denoised coupled grayscale image includes:
[0036] The optimized weighted evaluation values of all pixels in the structure data denoised coupled grayscale image are respectively input as independent variables into the function abs(*) to obtain a plurality of pending determination values; abs(*) represents taking the absolute value;
[0037] The maximum value among all pending judgment values is determined as the judgment value.
[0038] Optionally, the structural data radar grayscale image weight α1=0.6;
[0039] The structural data radar optical image weight α2=0.3;
[0040] The structural data radar low-light image weight α3=0.1;
[0041] The first threshold is 5; the second threshold is 10.
[0042] According to the specific embodiments provided in this application, this application discloses the following technical effects:
[0043] The present application provides an equipment damage assessment method based on equipment structure data, which constructs a structure data coupled grayscale image according to a structure data radar grayscale image, a structure data optical grayscale image and a structure data low-light grayscale image; performs three-dimensional rotation noise reduction processing on the structure data coupled grayscale image to obtain a structure data denoised coupled grayscale image; determines the damage degree of the equipment to be assessed based on the structure data denoised coupled grayscale image, an equipment tactical matrix and a technical indicator matrix, incorporates imaging data of the equipment structure in various ways such as optics, radar, and low-light into the basic data for damage assessment, and optimizes and adjusts the weighting coefficients in the assessment process, thereby improving the accuracy of equipment damage assessment. Furthermore, since the structure data is incorporated into the process of damage assessment, the process of collecting a large number of equipment parameters itself is avoided, the collection speed of the basic assessment data is improved, the test collection time of the data is reduced, the efficiency of damage assessment is improved, and the problems of inaccurate assessment results caused by incomplete basic assessment data and unscientific assessment weighting coefficients are solved. BRIEF DESCRIPTION OF THE DRAWINGS
[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0045] Figure 1 This is a flow chart of an equipment damage assessment method based on equipment structure data in one embodiment of the present application. DETAILED DESCRIPTION
[0046] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0047] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.
[0048] In an exemplary embodiment, Figure 1 As shown, a method for equipment damage assessment based on equipment structure data is provided, comprising:
[0049] Step 101: Acquire a radar grayscale image of structural data, an optical grayscale image of structural data, and a low-light grayscale image of structural data of the equipment to be evaluated.
[0050] Step 102: construct a structure data coupled grayscale image based on the structure data radar grayscale image, the structure data optical grayscale image and the structure data low light grayscale image. The grayscale value of any pixel in the structure data coupled grayscale image is:
[0051]
[0052] Among them, p i,j represents the gray value of the pixel (i, j) in the structure data coupled gray image, α1 represents the weight of the structure data radar gray image, represents the gray value of the pixel (i, j) in the structural data radar gray image, α2 represents the weight of the structural data optical gray image, represents the gray value of the pixel (i, j) in the optical gray image of the structural data, α3 represents the weight of the low-light gray image of the structural data, Represents the gray value of the pixel (i, j) in the structure data low-light gray image. Weight of structure data radar gray image α1 = 0.6. Weight of structure data radar optical image α2 = 0.3. Weight of structure data radar low-light image α3 = 0.1.
[0053] Step 103: Perform three-dimensional rotation noise reduction processing on the structure data coupled grayscale image to obtain a structure data denoised coupled grayscale image. The grayscale value of any pixel in the structure data denoised coupled grayscale image is:
[0054]
[0055] in, Represents the grayscale value of the pixel (i, j) in the structure data denoised coupled grayscale image.
[0056] Through three-dimensional rotation noise reduction processing, the scattering points of the three image data are aligned to facilitate the subsequent use of structural data.
[0057] Step 104: Obtain the equipment tactical matrix and technical indicator matrix of the equipment to be evaluated.
[0058] Step 105: Based on the structure data denoising coupled grayscale image, the equipment tactical matrix and the technical indicator matrix, determine the damage degree of the equipment to be evaluated. The damage degree includes mild, moderate and severe.
[0059] Step 105 includes:
[0060] Step 105-1: Soften the equipment tactical matrix to obtain a softened equipment tactical matrix. The softened equipment tactical matrix is:
[0061] m 1,r =m1·p d1 .
[0062] Among them, m 1,r is the softening equipment tactical matrix, m1 is the equipment tactical matrix, p d1 It is the softening parameter matrix of the equipment tactical matrix.
[0063] Step 105-2: Soften the technical indicator matrix to obtain a softened technical indicator matrix. The softened technical indicator matrix is:
[0064] m 2,r =m2·p d2 .
[0065] Among them, m 2,r is the softening technical indicator matrix, m2 is the technical indicator matrix, p d2 It is the softening parameter matrix of the technical indicator matrix.
[0066] The equipment tactical matrix and technical indicator matrix are softened based on the prior damage probability. Through the softening process, the data matrix of combat technical indicators and the image data are aligned and matched, thus meeting the conditions for comprehensive weighted evaluation.
[0067] Step 105-3: Based on the structure data denoised coupled grayscale image, the softened equipment tactical matrix and the softened equipment tactical matrix, the optimized weighted evaluation formula is used to determine the optimized weighted evaluation value of each pixel in the structure data denoised coupled grayscale image. The optimized weighted evaluation formula is:
[0068]
[0069] Among them, e i,j It represents the optimized weighted evaluation value of pixel point (i, j), and mount(*) represents pixel point extraction.
[0070] The optimized weighted evaluation process achieves rapid calculation of equipment damage information evaluation data by integrating combat technical indicators with image structure data information.
[0071] Step 105 - 4 : Determine the judgment value based on the optimized weighted evaluation values of all pixels in the structure data denoised coupled grayscale image.
[0072] Step 105 - 5 : When the determination value is less than the first threshold value, it is determined that the damage degree of the equipment to be evaluated is slight.
[0073] Step 105-6: When the determination value is greater than or equal to the first threshold value and the determination value is less than the second threshold value, the damage degree of the equipment to be evaluated is determined to be moderate. The first threshold value is less than the second threshold value. The first threshold value is 5. The second threshold value is 10.
[0074] Step 105 - 7 : When the determination value is greater than or equal to the second threshold, the damage degree of the equipment to be evaluated is determined to be severe.
[0075] Step 105-4 includes:
[0076] Step 105-4-1: Input the optimized weighted evaluation values of all pixels in the structure data denoised coupled grayscale image as independent variables into the function abs(*) to obtain multiple pending judgment values. abs(*) represents taking the absolute value.
[0077] Step 105-4-2: Determine the maximum value among all pending determination values as the determination value.
[0078] The present application also provides an application scenario, which applies the above-mentioned equipment damage assessment method based on equipment structure data. Specifically: the equipment damage assessment method based on equipment structure data provided in this embodiment can be applied in the formation equipment control scenario. The formation equipment control scenario includes the formation equipment data collection link, the formation equipment status assessment link and the formation control link; the equipment damage assessment method based on equipment structure data provided in this embodiment belongs to the equipment damage degree link in the formation equipment status assessment link.
[0079] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.
Claims
1. A method for equipment damage assessment based on equipment structure data, characterized in that: include: Acquire the radar grayscale image of the structural data, the optical grayscale image of the structural data and the low-light grayscale image of the structural data of the equipment to be evaluated; constructing a structural data coupled grayscale image according to the structural data radar grayscale image, the structural data optical grayscale image and the structural data low-light grayscale image; Performing three-dimensional rotation noise reduction processing on the structure data coupled grayscale image to obtain a structure data denoised coupled grayscale image; Obtain the equipment tactical matrix and technical indicator matrix of the equipment to be evaluated; The damage degree of the equipment to be evaluated is determined based on the structural data denoised coupled grayscale image, the equipment tactical matrix and the technical indicator matrix.
2. The equipment damage assessment method based on equipment structure data according to claim 1 is characterized in that: The severity of the injury includes mild, moderate and severe.
3. The equipment damage assessment method based on equipment structure data according to claim 1, characterized in that: The grayscale value of any pixel in the structure data coupled grayscale image is: Among them, p i,j represents the gray value of the pixel (i, j) in the structure data coupled gray image, α1 represents the weight of the structure data radar gray image, represents the gray value of the pixel (i, j) in the structural data radar gray image, α2 represents the weight of the structural data optical gray image, represents the gray value of the pixel (i, j) in the optical gray image of the structural data, α3 represents the weight of the low-light gray image of the structural data, Represents the grayscale value of the pixel (i, j) in the low-light grayscale image of the structural data.
4. The equipment damage assessment method based on equipment structure data according to claim 3 is characterized in that: The gray value of any pixel in the structure data denoised coupled gray image is: in, Represents the grayscale value of the pixel (i, j) in the structure data denoised coupled grayscale image.
5. The equipment damage assessment method based on equipment structure data according to claim 4 is characterized in that: Determining the damage degree of the equipment to be evaluated based on the structure data denoised coupled grayscale image, the equipment tactical matrix and the technical indicator matrix, including: Performing a softening process on the equipment tactical matrix to obtain a softened equipment tactical matrix; Performing a softening process on the technical indicator matrix to obtain a softened technical indicator matrix; Based on the structure data denoised coupled grayscale image, the softened equipment tactical matrix and the softened equipment tactical matrix, an optimized weighted evaluation formula is used to determine an optimized weighted evaluation value of each pixel in the structure data denoised coupled grayscale image; Determining a determination amount based on optimized weighted evaluation values of all pixels in the structure data denoised coupled grayscale image; When the determination value is less than a first threshold, determining that the damage degree of the equipment to be evaluated is slight; When the determination amount is greater than or equal to a first threshold value and the determination amount is less than a second threshold value, it is determined that the damage degree of the equipment to be evaluated is moderate; and the first threshold value is less than the second threshold value; When the determination value is greater than or equal to the second threshold, it is determined that the damage degree of the equipment to be evaluated is severe.
6. The equipment damage assessment method based on equipment structure data according to claim 5 is characterized in that: The tactical matrix of the softening equipment is: m 1,r =m1·p d1 ; Among them, m 1,r is the softening equipment tactical matrix, m1 is the equipment tactical matrix, p d1 It is the softening parameter matrix of the equipment tactical matrix.
7. The equipment damage assessment method based on equipment structure data according to claim 6 is characterized in that: The softening technical indicator matrix is: m 2,r =m2·p d2 ; Among them, m 2,r is the softening technical indicator matrix, m2 is the technical indicator matrix, p d2 It is the softening parameter matrix of the technical indicator matrix.
8. The equipment damage assessment method based on equipment structure data according to claim 7 is characterized in that: The optimization weighted evaluation formula is: Among them, e i,j It represents the optimized weighted evaluation value of pixel point (i, j), and mount(*) represents pixel point extraction.
9. The equipment damage assessment method based on equipment structure data according to claim 8, characterized in that: Determining a determination amount based on the optimized weighted evaluation values of all pixels in the structure data denoised coupled grayscale image includes: The optimized weighted evaluation values of all pixels in the structure data denoised coupled grayscale image are respectively input as independent variables into the function abs(*) to obtain a plurality of pending determination values; abs(*) represents taking the absolute value; The maximum value among all pending judgment values is determined as the judgment value.
10. The equipment damage assessment method based on equipment structure data according to claim 5, characterized in that: The structural data radar grayscale image weight α1=0.6; The structural data radar optical image weight α2=0.3; The structural data radar low-light image weight α3=0.1; The first threshold is 5; the second threshold is 10.