Detection image acquisition method and basin-type insulator automatic detection system

Abstract

The invention provides a detection image acquisition method, which comprises the following steps of: planning a plurality of detection partitions according to the size of an object to be detected; formulating a detection path according to the distribution of the detection partitions; the detection instrument moves along the detection path to sequentially collect image information of the multiple detection partitions; and splicing the acquired image information of the plurality of detection partitions to obtain complete image detection data. By controlling the detection unit to accurately move, infrared thermal imaging automatic partition detection can be completed, the detection efficiency is greatly improved, the problems that the consistency of detection results is poor and the reinspection analysis difficulty of products is large are solved, and under the condition of infrared thermal imaging partition detection of the basin-type insulator, by fitting the circular contour line segments of the multi-partition basin-type insulator, the detection accuracy is greatly improved. And comparison is carried out according to the theoretical position calculated by the position of the mechanical arm, so that image splicing of partition detection results can be efficiently and accurately completed.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of image detection, and in particular to a detection image acquisition method and an automatic detection system for a basin-type insulator. BACKGROUND

[0002] In recent years, with the wide application of gas insulated switchgear (GIS) in power systems, the stability and reliability of the basin-type insulator, as one of the key components, are crucial to the safety of the power grid. However, due to the internal micro-defects of the insulator and the aging problem after long-term operation, accidents such as flashover, breakdown and burst often occur. Therefore, accurately diagnosing the actual insulation state of the basin-type insulator becomes an important basis for evaluating the operation of the equipment. The infrared thermal imaging technology, as a new non-destructive testing technology, has the advantages of non-contact, fast response and intuitive image display, and is very suitable for the rapid detection of large-area components such as basin-type insulators.

[0003] In order to ensure that the detection image has sufficient spatial resolution, the single detection area of the infrared thermal imaging should not be too large, so the detection of large basin-type insulators needs to be carried out in multiple zones, and finally the multi-zone result images are spliced into a whole image with high pixels and high resolution.

[0004] However, there is no perfect automatic infrared thermal imaging detection device at present, and the traditional manual operation to adjust the position and angle of the detection device is very time-consuming and inaccurate, which brings difficulties to the subsequent image splicing work. In addition, the manual operation is low in efficiency, poor in consistency of detection results, and difficult in product recheck analysis, which is difficult to meet the needs of daily detection of power grid insulators. SUMMARY

[0005] Therefore, the technical problem to be solved by the present application is to solve the problem of time-consuming and inaccurate splicing when adjusting the position and angle of the detection device under manual operation when detecting large basin-type insulators (1).

[0006] The above technical problem is solved by the following technical scheme: the present application provides a detection image acquisition method, which comprises,

[0007] planning multiple detection zones according to the size of the object to be detected;

[0008] formulating a detection path according to the distribution of the detection zones;

[0009] moving the detection instrument along the detection path to sequentially acquire image information of the multiple detection zones;

[0010] splicing the acquired image information of the multiple detection zones to obtain complete image detection data.

[0011] In a preferred embodiment of the detection image acquisition method, when the object to be detected is circular, the number of detection zones is determined according to the diameter of the object to be detected and the pixel size of the detection instrument.

[0012] In a preferred embodiment of the detection image acquisition method, the type of detection path includes Z-shaped, S-shaped, M-shaped, W-shaped and interval jumping type.

[0013] In a preferred embodiment of the detection image acquisition method, the step of splicing the image information of the plurality of detection zones includes the following steps:

[0014] extracting the circular contour line of the object to be detected from the image information of each detection zone;

[0015] using a circular equation (X-a) 2 +(Y-b) 2 =r 2 fitting the extracted circular contour line, wherein r is the known radius of the object to be detected, X corresponds to the horizontal coordinate of the pixel point in the infrared image, Y corresponds to the vertical coordinate of the pixel point in the infrared image, a corresponds to the horizontal coordinate of the center of the circle in the image, and b corresponds to the vertical coordinate of the center of the circle in the image;

[0016] a plurality of (a, b) values are calculated by fitting, and the (a, b) value is the required overlap pixel size for image splicing;

[0017] The fitted circular contour is compared with the theoretical position of the circular contour in the field of view of the detector to reduce the fitting error.

[0018] The overlap rate is determined according to the overlap pixel size, and the multi-zone image splicing is completed.

[0019] In a preferred embodiment of the detection image acquisition method, the pixel size of the detection instrument is 640*512.

[0020] In a preferred embodiment of the detection image acquisition method, when the diameter of the object to be detected is in the range of 256-512 mm, the detection is performed in four regions; when the diameter of the object to be detected is in the range of 512-768 mm, the detection is performed in nine regions.

[0021] The present application also provides an automatic detection system for a basin-type insulator, which detects the basin-type insulator by using the above-mentioned detection image acquisition method.

[0022] The positioning unit is used for positioning the basin-type insulator.

[0023] a detection unit for collecting image information of the basin-type insulator;

[0024] an adjusting unit, the detection unit is installed on the adjusting unit, and the detection unit is driven to move along a detection path by the adjusting unit.

[0025] In a preferred embodiment of the basin-type insulator automatic detection system, the detection unit is an infrared thermal imager, and the detection unit can uniformly heat the basin-type insulator and collect image information.

[0026] In a preferred embodiment of the basin-type insulator automatic detection system, the adjusting unit is a mechanical arm, and the mechanical arm is provided with a six-axis joint.

[0027] In a preferred embodiment of the basin-type insulator automatic detection system, the detection unit and the adjusting unit are both installed on a detection table.

[0028] The present application has the advantages that: by controlling the accurate movement of the detection unit, the infrared thermal imaging automatic partition detection can be completed, the detection efficiency is greatly improved, the problems of poor consistency of detection results and difficulty in product re-inspection analysis are solved, and under the condition of infrared thermal imaging partition detection of the basin-type insulator, by fitting the multi-partition basin-type insulator circular contour line segment and comparing the calculated theoretical position according to the mechanical arm position, the partition detection result image splicing can be efficiently and accurately completed. BRIEF DESCRIPTION OF DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings of the embodiments of the present application will be briefly introduced below. Obviously, the drawings described below only relate to some embodiments of the present application, and are not a limitation on the present application. Among them:

[0030] Figure 1 a distribution diagram of four detection partitions is shown;

[0031] Figure 2 a distribution diagram of nine detection partitions is shown;

[0032] Figure 3 a detection path diagram of Z type is shown;

[0033] Figure 4 a detection path diagram of interval jumping type is shown;

[0034] Figure 5 a first perspective view of the basin-type insulator automatic detection system is shown;

[0035] Figure 6 a second perspective view of the basin-type insulator automatic detection system is shown. Detailed Implementation

[0036] To enable those skilled in the art to better understand the present invention, the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0037] The terminology used in this invention is that which is currently widely used in the art in consideration of the function of the invention; however, these terms may vary according to the intent of those skilled in the art, precedent, or new technology in the art. Furthermore, specific terms may be chosen by the applicant, and in such cases, their detailed meanings will be described in the detailed description of the invention. Therefore, the terms used in this specification should not be construed as simple names, but rather based on their meanings and the overall description of the invention.

[0038] Reference Figure 1 This embodiment provides a detection image acquisition method, including the following steps:

[0039] S1. Plan multiple detection zones according to the size of the object to be detected;

[0040] Taking a circular object to be tested as an example, in this step, the number of detection zones is mainly determined based on the diameter of the object to be tested and the pixel size of the detection instrument.

[0041] When the object to be inspected is a basin-type insulator 1, the number of inspection zones is mainly determined by the diameter of the basin-type insulator 1 and the resolution of the inspection instrument. For example, the resolution of the inspection instrument is usually 640*512. Typically, the required spatial resolution for detecting defects such as cracks, pores, and foreign objects in the basin-type insulator 1 is 0.5mm.

[0042] The current testing instrument uses a 640*512 pixel detector, which is commonly used in the industry. Based on the aforementioned spatial resolution requirement of 0.5mm, the maximum permissible field of view of the detector can be calculated using "pixel count × spatial resolution".

[0043] Maximum horizontal field of view: 640 pixels × 0.5 mm / pixel = 320 mm;

[0044] Maximum vertical field of view: 512 pixels × 0.5 mm / pixel = 256 mm;

[0045] Therefore, the detector's field of view must be strictly controlled to no more than 320*256mm. If the field of view exceeds this size, the 0.5mm spatial resolution requirement cannot be met. The detector's field of view should not exceed 320*256mm. Since the diameter of the tested basin-type insulator 1 is greater than 320mm, multiple tests are required in different areas, and the results images should be stitched together after each test for easy observation.

[0046] Specifically, please refer to Figure 1 and Figure 2 , the diameter of the basin type insulator 1 is in the range of 256-512 mm, and the detection is divided into 4 regions, as shown in the schematic diagram; when the diameter of the basin type insulator 1 is in the range of 512-768 mm, the detection is divided into 9 regions, as shown in the schematic diagram. By setting multiple detection sub-zones, the field of view of the detection instrument can cover the entire basin type insulator 1, and it is convenient to collect more comprehensive image information of the basin type insulator 1.

[0047] S2, form a detection path according to the distribution of the detection sub-zones;

[0048] In this method, the movement of the detection instrument is driven by an automatically adjustable device. When planning the detection path, the detection path needs to meet two conditions: one is to shorten the movement distance of the detection instrument to improve the detection efficiency, and the other is to avoid the influence of heat diffusion of residual heat in adjacent detection sub-zones to ensure the detection signal-to-noise ratio and the overall gray consistency of the spliced image.

[0049] According to the distribution of the detection sub-zones, a detection path is formed, and the type of the detection path includes Z-shaped, S-shaped, M-shaped, W-shaped, and interval jumping type.

[0050] As shown in Figure 4 , the interval jumping type detection path is shown. Selecting this path can avoid the influence of heat diffusion of residual heat in adjacent regions, ensure the detection signal-to-noise ratio, and ensure the overall gray consistency of the spliced image. We will mark the nine detection sub-zones as (1,1), (1,2), (1,3), (2,1), (2,2), (2,3), (3,1), (3,2), and (3,3). When the interval jumping type detection path is used, the detection starts from the (1,1) detection sub-zone, and the detection sequence is (1,1), (1,3), (1,2), (2,1), (2,3), (2,2), (3,1), (3,3), and (3,2) in order.

[0051] As shown in Figure 3 , the Z-shaped detection path is shown. Selecting this path can reduce the movement distance of the detection instrument, thereby improving the detection efficiency.

[0052] S3, the detection instrument moves along the detection path to sequentially collect image information of the multiple detection sub-zones;

[0053] In this embodiment, the detection instrument uses an infrared thermal imaging detection instrument, which can uniformly heat the basin type insulator 1 and collect image information. The automatically adjustable device can use a mechanical arm. The mechanical arm drives the detection unit 200 to move to the target position of each detection sub-zone according to the preset detection sub-zone and path, adjusts the joint angle to calibrate the position and angle of the detection unit 200, and ensures that the field of view of the detector accurately covers the current sub-zone.

[0054] At each partition position, the mechanical arm keeps the detection unit 200 stable for a long time without shaking, while the detection unit 200 applies uniform thermal excitation to the current partition, synchronously completes the infrared thermal imaging image information collection of the partition, and after the collection of a single partition is completed, the mechanical arm drives the detection unit 200 to move to the next detection partition along the set path until the image information collection of all planned partitions is completed.

[0055] S4, the image information of the collected multiple detection partitions is spliced to obtain complete image detection data.

[0056] Splicing the image information of the collected multiple detection partitions includes the following steps:

[0057] S4.1, extracting the circular contour line of the object to be detected from the image information of each detection partition;

[0058] For the infrared image collected for each detection partition, the above-mentioned circular contour line is identified and extracted by an image edge detection algorithm such as Canny operator, and the effective contour with good contour continuity and no obvious noise interference is selected to ensure that the basic data for subsequent fitting calculation is accurate and reliable.

[0059] S4.2, using a circular equation (X-a) 2 +(Y-b) 2 =r 2 fitting the extracted circular contour line, wherein r is the known radius of the object to be detected, X corresponds to the horizontal direction coordinate of the pixel point in the infrared image, Y corresponds to the vertical direction coordinate of the pixel point in the infrared image, a corresponds to the horizontal direction coordinate of the center of the circle in the image, and b corresponds to the vertical direction coordinate of the center of the circle in the image;

[0060] By using a least square method or other fitting algorithm, the extracted contour pixel point coordinates (X, Y) are substituted into the equation to solve the center coordinates (a, b) of the circular contour in the current partition image. Each effective circular contour can calculate a corresponding set of (a, b) to provide core position parameters for subsequent splicing and alignment.

[0061] S4.3, a plurality of (a, b) values are obtained by fitting calculation, which are the overlapping pixel sizes required for image splicing;

[0062] In the images of different detection partitions, there will be common circular contours of the same basin-type insulator (1). By comparing the fitting center coordinates (a, b) of these cross-partition shared contours in different partition images, the coordinate difference value reflects the position offset amount of the two partition images in the horizontal and vertical directions, which is the overlapping pixel size required for image splicing.

[0063] For example, if the fitting center of a circular contour in detection zone 1 is (a1, b1 1) , and the fitting center of the same contour in detection zone 2 is (a2, b2 2) , then the horizontal direction overlapping pixel size is |a1-a2|, and the vertical direction overlapping pixel size is |b1-b2|. This process does not require manual adjustment of the overlap rate and is completely based on data automatic calculation.

[0064] S4.4, in combination with the theoretical position of the circular contour of the to-be-detected object in the field of view of the detector, comparing the fitted circular contour with the theoretical position to reduce the fitting error;

[0065] Since the positional relationship between the clamping unit and the mechanical arm in the detection system is fixed, and the actual radius r of the pot-type insulator 1 is known, during the planning of the detection zones in the early stage, the theoretical center position of each circular contour of the pot-type insulator 1 in the field of view of the detector in each zone image can be calculated in advance. The actual center coordinates (a, b) fitted in S4.2 are compared with the theoretical center position. If there is a deviation, the actual fitting coordinates are corrected based on the theoretical position to further reduce the fitting error of the center positioning and ensure the consistency of the contour positions in each zone image.

[0066] S4.5, determining the splicing overlap rate according to the overlapping pixel size, and completing the splicing of the multi-zone images.

[0067] According to the overlapping pixel size calculated in S4.3, in combination with the pixel size of the field of view of the detector, the splicing overlap rate of each adjacent zone image can be converted. The repetition rate calculation method is: overlapping pixel size / field of view pixel size of the detector x 100%.

[0068] Subsequently, according to the calculated overlap rate, the images of all detection zones are aligned and fused. Taking a zone such as the upper left corner zone as the starting point, the adjacent zone images are aligned according to the overlapping area, the image gaps or repeated redundancies between the zones are eliminated, and finally a complete infrared image covering the whole pot-type insulator 1 is spliced. The spliced image maintains a spatial resolution of 0.5 mm, which can clearly present the small defects such as cracks, pores, foreign matters and the like on the surface and inside of the insulator, and meets the subsequent detection and analysis requirements.

[0069] Please refer to Figure 5 to Figure 6 , the present application also provides a pot-type insulator automatic detection system, which detects the pot-type insulator 1 by using the above detection image acquisition method. The pot-type insulator automatic detection system comprises a positioning unit 100 for positioning the pot-type insulator 1. In this embodiment, the positioning unit 100 is a clamping mechanism, which can clamp and fix the pot-type insulator 1 to keep the position of the pot-type insulator 1 during detection, thereby ensuring the repeated detection accuracy.

[0070] The automatic detection system of the basin type insulator further comprises a detection unit 200 for collecting image information of the basin type insulator 1; the detection unit 200 adopts an infrared thermal imager, the detection unit 200 can uniformly heat stimulate the basin type insulator 1 and collect image information, that is, the detection unit 200 is also matched with a stimulating heat source.

[0071] The automatic detection system of the basin type insulator further comprises an adjusting unit 300, the detection unit 200 is installed on the adjusting unit 300, the detection unit 200 can be driven to move along a detection path through the adjusting unit 300, the adjusting unit 300 adopts a mechanical arm, the mechanical arm is provided with a six-axis joint, and the position and angle are adjusted through the mechanical arm, and the uniform heat stimulation for a long time is stable and does not shake, and the image data collection is realized.

[0072] The system further comprises a detection table 400, the positioning unit 100 and the adjusting unit 300 are both installed on the detection table 400, and the detection table 400 provides installation space for the mechanical arm and the clamping mechanism.

[0073] Finally, it should be pointed out that the above detailed description of the method and the device is only an embodiment, and those skilled in the art can modify the embodiment in different ways without departing from the scope of the present application.

Claims

1. A method for detecting image acquisition, characterized in that: include, Multiple detection zones are planned based on the size of the object to be inspected; Develop detection paths based on the distribution of detection zones; The detection instrument moves along the detection path and sequentially acquires image information from multiple detection zones; The image information from multiple detection zones is stitched together to obtain complete image detection data.

2. The detection image acquisition method according to claim 1, characterized in that: When the object to be detected is circular, the number of detection zones is determined based on the diameter of the object and the pixel size of the detection instrument.

3. The detection image acquisition method according to claim 1, characterized in that: The detection path is determined based on the distribution of the detection zones. The types of detection paths include Z-shaped, S-shaped, M-shaped, W-shaped, and interval skipping types.

4. The detection image acquisition method according to claim 2 or 3, characterized in that: The process of stitching together image information from multiple detection zones includes the following steps: Extract the circular outline of the object to be detected from the image information of each detection zone; Using the circular equation (Xa) 2 +(Yb) 2 =r 2 The extracted circular contour is fitted, where r is the known radius of the object to be detected, X corresponds to the horizontal coordinate of the pixel in the infrared image, Y corresponds to the vertical coordinate of the pixel in the infrared image, a corresponds to the horizontal coordinate of the center of the circle in the image, and b corresponds to the vertical coordinate of the center of the circle in the image. Multiple (a,b) values ​​are obtained through fitting calculations, and these (a,b) values ​​are the overlapping pixel sizes required for image stitching. By combining the theoretical position of the circular outline of the object to be detected within the detector's field of view, the fitted circular outline is compared with the theoretical position to reduce fitting error; The overlapping rate is determined based on the size of the overlapping pixels to complete the stitching of multi-partition images.

5. The detection image acquisition method according to claim 2, characterized in that: The pixel size of the detection instrument is 640*512.

6. The detection image acquisition method according to claim 5, characterized in that: When the diameter of the object to be tested is in the range of 256 to 512 mm, the test is carried out in 4 areas; when the diameter of the object to be tested is in the range of 512 to 768 mm, the test is carried out in 9 areas.

7. An automated testing system for basin-type insulators, characterized in that: The detection image acquisition method according to any one of claims 1 to 6 is used to detect the basin-type insulator (1), and the automated detection system for the basin-type insulator includes, Positioning unit (100) is used to position the basin insulator (1); The detection unit (200) is used to acquire image information of the basin insulator (1); The adjustment unit (300) is used to move the detection unit (200) along the detection path. The detection unit (200) is installed on the adjustment unit (300).

8. The automated testing system for basin-type insulators according to claim 7, characterized in that: The detection unit (200) uses an infrared thermal imager, which can uniformly thermally excite the basin insulator (1) and acquire image information.

9. The automated testing system for basin-type insulators according to claim 7, characterized in that: The adjustment unit (300) is a robotic arm equipped with a six-axis joint.

10. The automated testing system for basin-type insulators according to claim 7, characterized in that: It also includes a testing platform (400), on which both the positioning unit (100) and the adjustment unit (300) are mounted.

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