CN-122023322-A - Converter valve platinum electrode scaling thickness detection method based on image gray level analysis

CN122023322ACN 122023322 ACN122023322 ACN 122023322ACN-122023322-A

Abstract

The invention discloses a method for detecting the scaling thickness of a platinum electrode of a converter valve based on image gray level analysis, and belongs to the technical field of nondestructive detection of converter valve equipment. The electrode is dismantled to the inefficiency that must shut down in order to measure the scale deposit thickness and equipment damage problem that the prior art leads to aim at solving. The method comprises the steps of firstly obtaining an X-ray transmission image of a platinum electrode and preprocessing the image, then interactively determining a measuring line segment penetrating through a scaling area on the image, then extracting gray values of all pixel points on the line segment to form gray distribution data, then analyzing the data to identify two characteristic points representing the boundary between a scaling layer and an electrode substrate, and finally calculating the actual physical thickness of the scaling layer according to the pixel distance between the two characteristic points and a system calibration coefficient. The technical scheme can detect the scaling thickness of the surface of the platinum electrode in the cooling system of the converter valve on line, nondestructively and accurately, and provides basis for state evaluation and maintenance decision.

Inventors

ZHAO XUNFAN
LIU LI
GUO ANQI
Rao Youyuan
MA HAOPENG
Zhu Mengjiong
XU XIN
HAN YUHAO

Assignees

国网浙江省电力有限公司舟山供电公司

Dates

Publication Date: 20260512
Application Date: 20260128

Claims (10)

1. The method for detecting the scaling thickness of the platinum electrode of the converter valve based on the image gray level analysis is characterized by comprising the following steps of: S1, acquiring an X-ray transmission digital image of a platinum electrode to be detected, and carrying out noise reduction and contrast enhancement treatment on the digital image to obtain a preprocessed image; S2, determining a measuring line segment penetrating through the scaling area on the surface of the electrode on the pretreatment image; S3, extracting gray values of all pixel points on the measuring line segment to form gray distribution data; s4, analyzing the gray distribution data, and identifying a first characteristic point and a second characteristic point which characterize the boundary between the scaling layer and the electrode substrate; S5, calculating to obtain the actual physical thickness of the scaling layer according to the pixel distance between the first characteristic point and the second characteristic point on the measuring line segment and the pixel size calibration coefficient of the system.
2. The method for detecting the thickness of a platinum electrode scale of a converter valve based on image gray scale analysis according to claim 1, wherein in step S1, the X-ray transmission digital image is acquired by a 16-bit depth flat panel detector, and the noise reduction and contrast enhancement processing includes smoothing the image by gaussian filtering.
3. The method for detecting thickness of a platinum electrode of a converter valve according to claim 2, wherein in step S1, the contrast enhancement process further comprises performing a morphological top hat transformation on the image after noise reduction to correct background non-uniformity and highlight edge features of a scale region.
4. The method for detecting the scaling thickness of the platinum electrode of the converter valve based on the image gray scale analysis according to claim 2, wherein in the step S1, the contrast enhancement process further comprises obtaining a gray scale average value of a scaling-free region in the image as a reference value, dividing the gray scale range of the image into a plurality of intervals based on the reference value, applying different gray scale transformation coefficients to different intervals, and finally normalizing the result to a preset range.
5. The method for detecting the scaling thickness of the platinum electrode of the converter valve based on the image gray scale analysis according to claim 4, wherein in the step S1, the plurality of sections comprise a first section lower than a reference value, a second section surrounding the reference value and a third section higher than the reference value, gray scale stretching is performed on the first section and the third section by respectively adopting different linear transformation coefficients, and gray scale is kept unchanged or low-intensity transformation is performed on the second section.
6. The method for detecting the scaling thickness of the platinum electrode of the converter valve based on the image gray scale analysis according to claim 1, wherein the step S4 specifically comprises: s4.1, searching a gray minimum point in the gray distribution data, and marking the gray minimum point as a scaling thickest point; S4.2, selecting a gray level distribution data subset on one side of the scale deposit thickest point serving as a reference; s4.3, calculating gray differential absolute value sequences of adjacent data points in the gray distribution data subset; S4.4, in the differential absolute value sequence, two extreme points with the largest numerical value and the second largest numerical value are determined, and are respectively marked as the first characteristic point and the second characteristic point.
7. The method for detecting the scaling thickness of the platinum electrode of the converter valve based on the image gray scale analysis according to claim 1, wherein in the step S5, the actual physical thickness T is calculated or equivalent converted based on an X-ray attenuation model by the following formula: Wherein, the For the linear attenuation coefficient of the fouling material for a particular energy X-ray, Is the reference gray value of the electrode substrate area without scaling, Is the gray scale value of the fouled area.
8. The method for detecting the scaling thickness of the platinum electrode of the converter valve based on the image gray scale analysis according to claim 1, wherein in the step S5, the pixel size calibration coefficient of the system is used in combination with the imaging angle parameter, and the actual physical thickness is obtained by multiplying the pixel distance by the pixel size calibration coefficient and dividing by the cosine value of the imaging angle.
9. The method for detecting the scaling thickness of the platinum electrode of the converter valve based on the image gray scale analysis according to claim 8, wherein the pixel size calibration coefficient is obtained by taking an X-ray image of a standard calibration block of a known physical size and calculating the ratio of the pixel size of the calibration block in the image to the actual physical size thereof.
10. The method for detecting the thickness of a platinum electrode of a converter valve according to claim 1, further comprising the step of comparing the calculated actual physical thickness with a pre-stored reference threshold or historical measurement data, automatically adjusting the noise reduction parameter or the contrast enhancement parameter in step S1, or the boundary recognition parameter in step S4, or a combination thereof if the deviation exceeds the allowable range, and re-executing the thickness detection process based on the adjusted parameters.

Description

Converter valve platinum electrode scaling thickness detection method based on image gray level analysis Technical Field The invention relates to the technical field of nondestructive testing of converter valve equipment, in particular to a method for detecting the scaling thickness of a platinum electrode of a converter valve based on image gray level analysis. Background The converter valve is core equipment of the HVDC system, and stable operation of the converter valve is important. The platinum electrode in the valve cooling system can be surface scaled by adsorbing metal ions in the waterway during long-term operation. The scale layer has insulating property, and when the thickness of the scale layer is accumulated to a certain extent, the scale layer can lead to failure of a platinum electrode, trigger discharge flashover and seriously threaten the safety of a converter valve. Currently, the detection of the thickness of the scale of platinum electrodes is mainly faced with the following challenges: The method for detecting the water level of the water level sensor has the inherent defects that the method for detecting the water level of the water level sensor is generally adopted in the industry, and the method has the problems of complex flow, time and labor consumption, tension in maintenance window period and the like. Frequent disassembly can also damage the electrodes and their sealing structures, introducing new risks of failure. This has led to an urgent need for online non-destructive testing techniques. The precision and applicability of the existing nondestructive testing method are limited, and a method based on vision or radiographic imaging is explored in the related field for realizing the non-dismantling detection. However, in the specific application scenario of a converter valve, these methods face significant bottlenecks: The imaging condition is harsh, the platinum electrode is positioned in the pipeline, and X-rays need to penetrate through the pipeline wall and the medium, so that the imaging signal-to-noise ratio is low and the contrast ratio is poor. The scale layer has small gray scale difference from the metal electrode substrate, and the boundary appears as a blurred gradual transition in the image instead of a sharp geometric edge. Conventional image size measurement methods (e.g., edge detection based on Canny et al, simple thresholding) rely heavily on high contrast sharp boundaries. When the X-ray image is faced with the low contrast and gradual change boundary, the positioning accuracy is drastically reduced, the noise immunity is poor, and the repeatability is low. In addition, some methods rely on conditions that are difficult to guarantee in the field, such as "known accurate reference dimensions" or "ideal imaging angles". Or the measurement area is manually selected seriously depending on the experience of an operator, so that the subjectivity is strong, the efficiency is low, and the automation and the standardization are difficult to realize. The prior art mostly treats the image as pure two-dimensional information to be processed, and cannot fully mine the physical association (namely attenuation law) between gray values and material thickness and density in X-ray imaging. Meanwhile, the lack of systematic self-adaptive compensation and correction of interference factors such as unavoidable noise, uneven background, angle inclination and the like in the imaging process leads to insufficient physical accuracy and environmental robustness of measurement results. In view of the foregoing, there is a great need for a nondestructive testing method dedicated to the platinum electrode of a converter valve that can overcome the difficulty of low quality X-ray imaging, and achieve high accuracy, automation, and physical reliability of the scale thickness. Disclosure of Invention The invention aims to solve the technical problems and the technical task of improving the prior art, and provides a converter valve platinum electrode scaling thickness detection method based on image gray level analysis, which aims to realize online, nondestructive and high-precision detection of the converter valve platinum electrode scaling thickness. For this purpose, the present invention adopts the following technical scheme. A converter valve platinum electrode scaling thickness detection method based on image gray analysis comprises the following steps: S1, acquiring an X-ray transmission digital image of a platinum electrode to be detected, and carrying out noise reduction and contrast enhancement treatment on the digital image to obtain a preprocessed image; S2, determining a measuring line segment penetrating through the scaling area on the surface of the electrode on the pretreatment image; S3, extracting gray values of all pixel points on the measuring line segment to form gray distribution data; s4, analyzing the gray distribution data, and identifying a first characteristic point