CN113805015A - Arc image form detection method for multi-cavity arc extinguishing device - Google Patents
Arc image form detection method for multi-cavity arc extinguishing device Download PDFInfo
- Publication number
- CN113805015A CN113805015A CN202110904424.0A CN202110904424A CN113805015A CN 113805015 A CN113805015 A CN 113805015A CN 202110904424 A CN202110904424 A CN 202110904424A CN 113805015 A CN113805015 A CN 113805015A
- Authority
- CN
- China
- Prior art keywords
- arc
- image
- gray
- value
- pixel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title abstract description 11
- 238000000034 method Methods 0.000 claims abstract description 60
- 238000012360 testing method Methods 0.000 claims abstract description 36
- 238000003860 storage Methods 0.000 claims abstract description 9
- 238000012545 processing Methods 0.000 claims description 26
- 238000001914 filtration Methods 0.000 claims description 22
- 238000004364 calculation method Methods 0.000 claims description 16
- 230000002146 bilateral effect Effects 0.000 claims description 12
- 238000004422 calculation algorithm Methods 0.000 claims description 8
- 125000001475 halogen functional group Chemical group 0.000 claims description 8
- 239000003990 capacitor Substances 0.000 claims description 6
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N Silicon Chemical compound [Si] XUIMIQQOPSSXEZ-UHFFFAOYSA-N 0.000 claims description 5
- 238000011161 development Methods 0.000 claims description 5
- 230000018109 developmental process Effects 0.000 claims description 5
- 229910052710 silicon Inorganic materials 0.000 claims description 5
- 239000010703 silicon Substances 0.000 claims description 5
- 230000000877 morphologic effect Effects 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 claims description 3
- 230000008030 elimination Effects 0.000 claims description 2
- 238000003379 elimination reaction Methods 0.000 claims description 2
- 238000009826 distribution Methods 0.000 abstract description 8
- 230000006870 function Effects 0.000 description 19
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 9
- 229910052802 copper Inorganic materials 0.000 description 9
- 239000010949 copper Substances 0.000 description 9
- 238000010891 electric arc Methods 0.000 description 8
- 210000003128 head Anatomy 0.000 description 6
- 238000005259 measurement Methods 0.000 description 4
- 230000001105 regulatory effect Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 238000010791 quenching Methods 0.000 description 3
- 230000000171 quenching effect Effects 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 208000025274 Lightning injury Diseases 0.000 description 2
- 230000001276 controlling effect Effects 0.000 description 2
- 238000003384 imaging method Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 241000143252 Idaea infirmaria Species 0.000 description 1
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical group [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 1
- 206010034960 Photophobia Diseases 0.000 description 1
- 208000027418 Wounds and injury Diseases 0.000 description 1
- 230000002238 attenuated effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000013329 compounding Methods 0.000 description 1
- 239000002322 conducting polymer Substances 0.000 description 1
- 229920001940 conductive polymer Polymers 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000005672 electromagnetic field Effects 0.000 description 1
- 238000009863 impact test Methods 0.000 description 1
- 208000013469 light sensitivity Diseases 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 229920000642 polymer Polymers 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000011179 visual inspection Methods 0.000 description 1
- 238000004804 winding Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1218—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing using optical methods; using charged particle, e.g. electron, beams or X-rays
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Image Analysis (AREA)
Abstract
The invention provides a method for detecting arc image forms of a multi-chamber arc extinguishing device, belonging to the technical field of impact arc image form detection; the method for detecting the arc image form of the multi-chamber arc extinguishing device is based on a test loop consisting of an impact current generator, a capacitive voltage divider, a rogowski coil, a digital storage oscilloscope, a high-speed camera and a data processor; according to the image form detection method for the arc of the multi-chamber arc extinguishing device, the image form characteristics and the distribution of the cut-off arc of the arc are extracted, the moment when the arc is completely sprayed out of the chamber is determined according to the total gray level of the arc, the arc cut-off moment and the position distribution of the cut-off arc have important significance for researching the dissipation characteristic of the arc, and the method plays a guiding role in optimizing the layout of a chamber nozzle.
Description
Technical Field
The invention relates to the technical field of impact arc image form detection, in particular to an arc image form detection method of a multi-chamber arc extinguishing device.
Background
The frequent occurrence of lightning accidents can cause great threat to the safe operation of a power grid, and along with the rapid increase of the scale of the power grid and the continuous improvement of the reliability requirement, the lightning protection level of a reinforced circuit is imperative. In the process of discharging electricity to the ground by thunderclouds, the rapid change of the electromagnetic field of the space around the discharge channel can generate induced overvoltage on a nearby overhead line, the thunderclouds can even directly hit a power distribution overhead line to generate extremely high lightning overvoltage, when the lightning overvoltage exceeds a certain value, the flashover and even disconnection of the power distribution line can be caused, the damage of a power supply network is caused, and the reliability of power supply of a power distribution system is directly influenced.
The multi-cavity arc extinguishing device is applied to quenching of electric arcs generated by a lightning stroke line of a power transmission line, and faults of power equipment caused by lightning strokes are reduced. Arc quenching tests of multi-chamber arc extinguishing devices are often conducted in laboratories to study the dissipation characteristics of the arc. Shooting of the discharge area, the arc development and the dissipation process is the most important part in the test process, however, in the actual test, the tester mainly depends on the visual inspection of the arc generation to the dissipation whole process, and because the air gap discharge is usually in the microsecond level, the tester cannot capture the arc shape at a certain transient in the discharge process only by naked eyes. Aiming at the problem, Wuhan university provides a method for shooting an arc path by using a single-lens reflective view-finding camera instead of visual observation of human eyes, but in the method, the whole process of arc generation and dissipation cannot be shot at high speed due to insufficient performance of the camera, shooting time needs to be manually set before shooting, the interval of each shooting time is long, and instantaneous synchronous starting shooting when the arc occurs cannot be realized. The Meihongwei of Qinghua university adopts a mirror image method to shoot a discharge path of an air gap by using a high-speed camera, the distance from the camera to a virtual image in a mirror surface is twice that of an actual arc, the image is easy to shrink, and the arc path can only be roughly judged.
Disclosure of Invention
The invention provides an arc image form detection method of a multi-chamber arc extinguishing device, aiming at overcoming the defect of extracting arc characteristic quantities for a plurality of arcs in the multi-chamber arc extinguishing process in the prior art.
The technical scheme adopted by the invention is as follows:
a multi-chamber arc extinguishing device arc image form detection method is based on a test loop consisting of an impact current generator, a capacitive voltage divider, a Rogowski coil, a digital storage oscilloscope, a high-speed camera and a data processor, wherein the impact current generator comprises an intelligent control system, a voltage regulator, a boosting transformer, a silicon stack, a wave modulation resistor R, a wave modulation inductor L, a pulse capacitor bank and an ignition ball gap; the method specifically comprises the following steps:
step 3, checking whether the impulse current waveform meets the requirements;
step 4, adjusting shooting parameters of the high-speed camera;
step 6, image processing, namely performing image graying processing, gray image filtering processing and arc halo elimination processing on the multi-chamber arc image;
step 7, selecting different arc areas;
and 8, solving the total gray level of the arc region and extracting the arc morphological characteristics.
Further, the method for detecting the arc image form of the multi-chamber arc extinguishing device can be used for researching the dissipation characteristic of the arc and optimizing the chamber nozzle layout of the multi-chamber arc extinguishing device.
Further, a weighted average method is adopted in the image graying processing, and the gray value calculation formula of each pixel point is as follows:
g(i，j)＝0.2989R+0.5870G+0.1140B
where g (i, j) is a gray scale value with pixel coordinates (i, j), and R, G, B represents the three primary color values of each pixel.
Further, bilateral filtering is adopted for filtering the gray level image in the filtering processing of the gray level image; the method specifically comprises the following steps: and performing segmentation or classification on the neighborhood to be used for filtering according to the pixel value, giving relatively higher weight to the class to which the point belongs, and performing neighborhood weighted summation to obtain a final result.
Further, the kernel function of bilateral filtering is a Gaussian kernel function related to the spatial distance multiplied by a Gaussian function related to the gray scale distance;
the spatial distance related Gaussian kernel function calculation formula is as follows:
wherein (k, l) is the center pixel coordinate of the processing window; (i, j) are the coordinates of the other pixels of the processing window; sigmadIs the standard deviation of the gaussian function;
the gray scale distance related Gaussian function calculation formula is as follows:
where f (i, j) is the gray value of the pixel at coordinate (i, j), f (k, l) is the gray value of the pixel at coordinate (k, l), σrAs a standard deviation of a Gaussian function with respect to gray scale；
The calculation formula of the product of the two is as follows:
the gray value of each pixel obtained by calculating the bilateral filtering kernel function is as follows:
g (i, j) is the pixel gray value at coordinate (i, j).
Further, an iterative algorithm is adopted to obtain an optimal threshold value T in the process of eliminating the arc halo so as to eliminate the arc peripheral halo; the method specifically comprises the following steps: assuming a threshold value, then calculating the foreground and background central values under the threshold value, and stopping iteration if the average value of the foreground and background central values and the assumed threshold value are converged, and carrying out binarization processing according to the value.
Further, the iterative algorithm firstly carries out initial threshold value solving, then divides the image into a foreground and a background according to the initial threshold value, and respectively solves the average gray value of the foreground and the background; finally, iterative solution is carried out until convergence;
the initial threshold value is calculated by the formula:
in the formula glIs the maximum gray value of the image, guIs the minimum gray value of the image;
the average gray value of the foreground and the background is calculated by the formula:
wherein g represents the gray value of the pixel, h (g) is the weight corresponding to different gray values, AbIs the mean gray value of the foreground, AfIs the background average gray value;
the formula for the iterative solution is:
in the formula TkObtaining a gray threshold value for the Kth iteration;
the expression until convergence is:
Tk+1-Tk＜ε
where ε is the computational accuracy of the iteration.
Further, in step 7, selecting different arc areas by adopting a two-pass scanning algorithm, scanning the image from left to right and from top to bottom, and connecting adjacent pixels with the same pixel value to form a connected domain; and extracting and marking the arc areas, and recording the number of the arc areas and the boundary coordinates of the connected domains.
Further, step 8, obtaining the total gray level of the arc area according to the arc area determined in step 7, extracting the corresponding arc area from the gray level image by using the recorded coordinate data, calculating the total gray level value of the arc area, obtaining the gray level characteristics of the arc at different development moments, and reflecting the moment that the arc is completely sprayed out of the chamber according to the gray level change;
the formula for solving the total gray level of the arc area is as follows:
the invention has the beneficial effects that:
the method for detecting the arc image form of the multi-chamber arc extinguishing device is based on a test loop consisting of an impact current generator, a capacitive voltage divider, a rogowski coil, a digital storage oscilloscope, a high-speed camera and a data processor; according to the image form detection method for the arc of the multi-chamber arc extinguishing device, the image form characteristics and the distribution of the cut-off arc of the arc are extracted, the moment when the arc is completely sprayed out of the chamber is determined according to the total gray level of the arc, the arc cut-off moment and the position distribution of the cut-off arc have important significance for researching the dissipation characteristic of the arc, and the method plays a guiding role in optimizing the layout of a chamber nozzle.
Drawings
FIG. 1 is a flow chart of a method for detecting arc image morphology of the multi-chamber arc extinguishing device;
FIG. 2 is a schematic diagram of the connection of the test loop;
FIG. 3 is a graphical representation of an arc region during dissipation of an arc;
FIG. 4 is a photograph of the arc morphology at different times after halo removal;
FIG. 5 is a histogram of the total amount of gray scale at each moment of the image during arc dissipation;
in FIG. 2, 1-impulse current generator, 2-capacitive voltage divider, 3-digital storage oscilloscope, 4-rogowski coil, 5-high speed camera, 6-data processor, 7-test sample.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings of the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive effort based on the embodiments of the present invention, are within the scope of the present invention.
The impact test device of the multi-chamber arc extinguishing chamber and the impact arc image detection method are characterized in that an impact current discharge test platform of a self-energy multi-chamber arc extinguishing chamber is built, a high-speed camera is used for observing the process from the movement to the extinguishing of an impact arc sprayed out of the self-energy multi-chamber arc extinguishing chamber, the form detection method of the impact arc image is improved, and the moment when the arc is completely sprayed out of the chamber is determined by extracting the gray scale characteristics of the arc image; the whole process simplifies the test steps, the shooting imaging efficiency is high, the effect is good, parameters such as airflow speed in the chamber are obtained, the change rule is researched, and the experimental effect of arc dissipation characteristics in the self-energy multi-chamber arc extinguishing chamber is effectively improved.
The method for detecting the arc image form of the multi-chamber arc extinguishing device is based on a test loop consisting of an impact current generator 1, a capacitive voltage divider 2, a rogowski coil 4, a digital storage oscilloscope 3, a high-speed camera 5 and a data processor 6. The Impulse Current Generator 1 (ICG) can generate a double-exponential Current wave with adjustable amplitude of 8-200 kA, variable wavefront time of 1.2-20 mus and variable wave tail time of 20-1000 mus. The surge current generator 1 mainly includes: the intelligent control system, a voltage regulator, a step-up transformer, a silicon stack, a wave modulation resistor R, a wave modulation inductor L, a pulse capacitor bank and an ignition ball gap. In the test, a 380V alternating current power supply is connected with a 380V power frequency power supply through a boosting terminal and a wire inlet terminal of a voltage regulator, and a wire outlet terminal of the voltage regulator is connected with the primary side of a boosting transformer through a wire; the secondary side of the step-up transformer is connected with the silicon stack through a wire, the silicon stack is rectified to charge the pulse capacitor bank, and when the charging voltage reaches a preset value, the ignition ball gap applies ignition pulses through the pulse ignition device to realize breakdown discharge, so that the impact current injected into the test article 7 is formed. By changing the wave modulation inductance and the wave modulation resistance in the test circuit, the impulse current waveforms with different wave front time and half peak time can be obtained; by controlling the charging voltage of the capacitor bank, inrush currents with different peak values can be obtained.
In order to realize the precise measurement of the impact current and the impact current value and provide measurement data for triggering the shooting of the high-speed camera 5, a core-through current sensor and a digital storage oscilloscope 3 are adopted to form a current measurement system. The core-through current sensor consists of a non-magnetic framework, a copper coil, an integrating circuit, a signal transmission interface and a polymer insulating shell. The non-magnetic conducting framework is a circular ring made of a non-magnetic conducting polymer, the inner diameter of the circular ring is 2-10 cm, the outer diameter of the circular ring is 2.5-12 cm, the diameter of the cross section of the circular ring is 1-4 cm, the copper coil is fixed, and meanwhile, the iron core of the sensor is prevented from being saturated when measuring impact large current. The copper coil is uniformly wound on a circular non-magnetic-conductive framework by a copper enameled wire with the wire diameter of 0.44-1.67 mm, the number of winding turns is 50-1000 turns, and outgoing lines at two ends of the copper coil are connected with the input end of an integrating circuit and used for integrating induced electromotive force, so that the change of current along with time t is obtained. The capacitive voltage divider 2 and the digital storage oscilloscope 3 form a voltage measuring system, and the voltage division ratio is 1000: 1. and measuring voltage signals with the amplitude of-400 kV and the frequency of 0-1 MHz, wherein the measured signals are not attenuated and deformed. The oscilloscope is powered by an independent power supply, voltage signals with the amplitude of-400V and the frequency of 0-100 MHz are simultaneously acquired through 2 signal acquisition channels, the sampling frequency is 0-10 GS/s, the storage capacity is 0-100 MB, the accuracy and the length of the acquired signals can be guaranteed, once an air gap in the multi-cavity arc extinguishing device is broken down, the oscilloscope sends a trigger signal at the same moment to trigger the high-speed camera 5 to start shooting the process of the appearance, the development and the dissipation of the electric arc to acquire an electric arc image. The high-speed camera 5 is provided with a 12-bit monochromatic chip (36-bit RGB color), 20-micron pixel points, the frame rate can be adjusted according to pixels and can reach 1000000fps at most, and shooting parameters are controlled through software.
The method for detecting the arc image form of the multi-chamber arc extinguishing device is shown in fig. 1 and specifically comprises the following steps:
Firstly, parameters of a test loop element are determined, namely wave head time and wave tail time of an impact current waveform are determined. And determining according to the wave head time and the wave tail time of the actual lightning current and the simulation proportion n. The method comprises the steps of dividing the wave head time and the wave tail time of actual lightning current by a simulation proportion n, calculating the wave head time and the wave tail time of impulse current of a simulation test, and changing the sizes of a wave regulating resistor R and a wave regulating inductor L in a loop of an impulse current generator 1 to achieve the calculated wave head time and the calculated wave tail time of the impulse current.
And 2, connecting the test devices and directly connecting two ends of the test product 7 to connect the test loops as shown in figure 2.
The negative pole of the pulse capacitor bank is grounded by using a braided copper strip as a connecting wire, the current output end of the impulse current generator 1 is connected with a wave regulating inductor and a wave regulating resistor by using the braided copper strip as the connecting wire, the braided copper strip needs to penetrate through the rogowski coil 4 and is connected with a test sample 7, the high-voltage end of the test sample 7 is connected with the capacitive voltage divider 2 for voltage measurement, and meanwhile, the two ends of the test sample 7 are firstly short-circuited so as to check whether the waveform is correct or not in the subsequent process. The rogowski coil 4 and the capacitive voltage divider 2 are connected with an oscilloscope input channel by a coaxial shielded cable, and an oscilloscope trigger signal output end is connected with the high-speed camera 5 to ensure that the high-speed camera 5 can shoot immediately when electric arcs appear. In the test line connection process, attention is paid to the fact that the signal line and the woven copper strip are prevented from contacting and spaced at a proper distance, whether the line is correct or not and whether the connection is good or not are finally checked, and the next step can be carried out only when all the connecting lines are connected well.
Step 3, checking whether the impulse current waveform meets the requirements
Under the condition of short circuit, starting the impact current generator 1 to output impact current, and judging whether the current waveform meets the requirement or not through the waveform displayed by the oscilloscope.
Step 4, adjusting shooting parameters of the high-speed camera 5
The high-speed camera 5 is of a photon FASTCAM SA5 model, is provided with a 12-bit monochromatic chip (36-bit RGB color), 20-micron pixel points, has adjustable frame rate according to pixels, can reach 1000000fps at most, and is controlled to shoot by Photon's Fastcam Viewer (PFV) software. The frame rate is set to 15000fps through control software, the trigger mode is set to be parameters required by central point triggering, ISO light sensitivity and the like, a focusing lens is not additionally arranged on the high-speed camera 5, and the focal length is adjusted to enable the sample 7 to be clear in an imaging area.
Removing short-circuit connection wires at two ends of the test article 7, setting a charging voltage value of the impulse current generator 1, and setting charging time according to the impulse voltage value to start charging; after charging, the impact current generator 1 is triggered to check whether the synchronous trigger sends out a trigger signal or not, and the high-speed camera 5 shoots an arc image. And adjusting the frame rate of the control software according to the condition of the shot image, and repeating the test for multiple times.
And 6, processing the image, wherein the processing steps are as follows:
graying of an image: the arc image obtained by the high-speed camera 5 is an RGB image which cannot reflect morphological characteristics of the image, and only color blending is performed in an optical principle, and the actual reflection of the image characteristics is the brightness of the image; meanwhile, in order to reduce the matrix memory space in the computer calculation process and improve the image processing speed, the weighted average method is used for carrying out gray processing on the original image.
The gray value calculation formula of each pixel point is as follows:
g(i，j)＝0.2989R+0.5870G+0.1140B
where g (i, j) is a gray scale value with pixel coordinates (i, j), and R, G, B represents the three primary color values of each pixel.
And (3) filtering the gray level image: the principle of using bilateral filtering to carry out gray level image filtering can reserve the edge characteristics of an arc area, and comprises the steps of firstly carrying out segmentation or classification on the neighborhood to be used for filtering according to a pixel value, then giving a relatively higher weight to the category of the point, and then carrying out neighborhood weighted summation to obtain a final result. The kernel function of bilateral filtering is a gaussian kernel function related to spatial distance multiplied by a gaussian function related to gray scale distance. The weight of the gray information is added in the bilateral filtering, namely, in the neighborhood, the point with the gray value closer to the gray value of the central point has a larger weight, and the point with the larger gray value difference has a smaller weight. The weight is determined by a value range gaussian function. And multiplying the spatial distance correlation and the gray value correlation weight coefficient to obtain the final kernel function.
The spatial distance-dependent gaussian kernel function calculation formula is as follows:
wherein (k, l) is the center pixel coordinate of the processing window; (i, j) are the coordinates of the other pixels of the processing window; sigmadIs the standard deviation of the gaussian function.
The gray scale distance related Gaussian function calculation formula is as follows:
where f (i, j) is the gray value of the pixel at coordinate (i, j), f (k, l) is the gray value of the pixel at coordinate (k, l), σrIs the standard deviation of the gaussian function with respect to gray scale.
The calculation formula of the product of the two is as follows:
the gray value of each pixel obtained by calculating the bilateral filtering kernel function is as follows:
wherein g (i, j) represents the pixel gray value after the bilateral filtering kernel function is calculated.
The arc generation and dissipation process of the original image after graying and bilateral filtering is shown in fig. 3, and the edge of the arc is clear and obvious and the image distortion is not obvious.
Eliminating arc halo: the arc is accompanied by a strong gas ionization phenomenon in the process from formation to dissipation, the gas ionization generates a large number of photons to be dissipated around the arc, a circle of halation exists around the visible arc in a shot arc image, and an optimal threshold value T is obtained by adopting an iterative algorithm to eliminate the halation around the arc. Assuming a threshold value, then calculating the foreground and background central values under the threshold value, and stopping iteration if the average value of the foreground and background central values and the assumed threshold value are converged, and carrying out binarization processing according to the value.
The maximum and minimum gray scale values of the image are determined and denoted as glAnd guThe initial threshold is:
in the formula glIs the maximum gray value of the image, guIs the minimum gray value of the image.
Dividing the image into a foreground and a background according to an initial threshold, and respectively solving the average gray value of the foreground and the background:
wherein g represents the gray value of the pixel, and h (g) represents the weight corresponding to different gray values. A. thebIs the mean gray value of the foreground, AfIs the background mean gray value.
Iterative solution
Until convergence, Tk+1-Tk＜ε。
In the formula TkAnd obtaining a gray threshold value for the K iteration, wherein epsilon is the calculation precision of the iteration.
Step 7, selecting different arc areas
Selection of different arc regions: it can be seen from the figure that the arcs ejected by a plurality of nozzles of the multi-chamber arc-extinguishing device at the initial stage of quenching the arc are mutually connected to present a gradually enlarged plasma cluster, when the arc is developed to begin to dissipate, the arc is cut into a plurality of small arc areas, each arc area corresponds to a connected domain in the image, after the aperture is eliminated in the previous step, the area consists of foreground pixel points with the same pixel value and adjacent positions, the image is scanned from left to right and from top to bottom by adopting a two-pass scanning algorithm, and the adjacent pixels with the same pixel value are connected to form the connected domain. The arc areas are extracted and marked, the number of the arc areas and the boundary coordinates of the communication areas are recorded, and it can be found in both fig. 3 and fig. 4 that the arc sprayed by the multi-chamber arc extinguishing device is not in the process of overall uniform dissipation along with the dissipation of the arc, the arc at the middle position is dissipated quickly, and the upper end and the lower end of the arc are not easy to dissipate. Therefore, the arc interruption time and the position distribution of the interruption arc have important significance for researching the dissipation characteristic of the arc and play a guiding role in optimizing the layout of the chamber nozzle.
Step 8, calculating the total gray level of the arc region
And (3) calculating the total gray level of the arc region: the gray value of the original image after graying processing reflects the brightness of the electric arc, photons are generated along with gas ionization in the process from generation to dissipation of the electric arc, the dissociating effect is enhanced along with continuous compounding and diffusion of charged particles in the electric arc, and the brightness is gradually weakened along with the development of the electric arc, so that the time when the brightness of an electric arc area reaches the maximum, namely the time when the electric arc is completely sprayed out of a chamber, is the time. And determining an arc area, namely determining a calculation interval in the gray-scale image according to the boundary coordinates of the plurality of the truncated arcs recorded in the last step. And sequentially traversing the pixel points in the area to accumulate the gray values of the pixel points, and determining the moment when the arc is completely sprayed out from the nozzle and begins to extinguish according to the gradually reduced change trend after the total gray value of the arc is rapidly increased.
The formula for solving the total gray level of the arc area is as follows:
it can be seen from the gray total histogram of fig. 5 that at the time of 160 μ s, the gray total of the image reaches a maximum, indicating that the arc brightness is highest at this time, the arc reaction releases a large number of photons, and at the time the gray total of the arc image begins to drop, indicating that the arc has completely ejected the chamber, so that the arc is broken and begins to dissipate as energy is released.
Claims (9)
1. A method for detecting arc image forms of a multi-chamber arc extinguishing device is characterized by comprising the following steps: the method for detecting the arc image form of the multi-cavity arc extinguishing device is based on a test loop consisting of an impact current generator, a capacitive voltage divider, a rogowski coil, a digital storage oscilloscope, a high-speed camera and a data processor, wherein the impact current generator comprises an intelligent control system, a voltage regulator, a step-up transformer, a silicon stack, a wave modulation resistor R, a wave modulation inductor L, a pulse capacitor bank and an ignition ball gap; the method specifically comprises the following steps:
step 1, determining parameters of a test loop element, namely determining wave head time and wave tail time of an impulse current waveform;
step 2, directly connecting two ends of the test article with a test loop;
step 3, checking whether the impulse current waveform meets the requirements;
step 4, adjusting shooting parameters of the high-speed camera;
step 5, carrying out repeated tests for many times, and adjusting the frame rate of the control software;
step 6, image processing, namely performing image graying processing, gray image filtering processing and arc halo elimination processing on the multi-chamber arc image;
step 7, selecting different arc areas;
and 8, solving the total gray level of the arc region and extracting the arc morphological characteristics.
2. The method of claim 1, wherein the method comprises: the method for detecting the arc image form of the multi-chamber arc extinguishing device can be used for researching the dissipation characteristic of the arc and optimizing the chamber nozzle layout of the multi-chamber arc extinguishing device.
3. The method of claim 1, wherein the method comprises: a weighted average method is adopted in the image graying processing, and the gray value calculation formula of each pixel point is as follows:
g(i，j)＝0.2989R+0.5870G+0.1140B
where g (i, j) is a gray scale value with pixel coordinates (i, j), and R, G, B represents the three primary color values of each pixel.
4. The method of claim 1, wherein the method comprises: bilateral filtering is adopted in the filtering processing of the gray level image to filter the gray level image; the method specifically comprises the following steps: and performing segmentation or classification on the neighborhood to be used for filtering according to the pixel value, giving relatively higher weight to the class to which the point belongs, and performing neighborhood weighted summation to obtain a final result.
5. The method of claim 4, wherein the method comprises: the kernel function of bilateral filtering is the multiplication of a Gaussian kernel function related to the spatial distance and a Gaussian function related to the gray scale distance;
the spatial distance related Gaussian kernel function calculation formula is as follows:
wherein (k, 1) is the center pixel coordinate of the processing window; (i, j) are the coordinates of the other pixels of the processing window; sigmadIs the standard deviation of the gaussian function;
the gray scale distance related Gaussian function calculation formula is as follows:
where f (i, j) is the gray value of the pixel at coordinate (i, j), f (k, l) is the gray value of the pixel at coordinate (k, 1), σrIs a gaussian function standard deviation with respect to gray scale;
the calculation formula of the product of the two is as follows:
the gray value of each pixel obtained by calculating the bilateral filtering kernel function is as follows:
g (i, j) is the pixel gray value at coordinate (i, j).
6. The method of claim 1, wherein the method comprises: in the process of eliminating the arc halo, an iterative algorithm is adopted to obtain an optimal threshold value T so as to eliminate the halo around the arc; the method specifically comprises the following steps: assuming a threshold value, then calculating the foreground and background central values under the threshold value, and stopping iteration if the average value of the foreground and background central values and the assumed threshold value are converged, and carrying out binarization processing according to the value.
7. The method of claim 6, wherein the method comprises: the iterative algorithm firstly carries out initial threshold value calculation, then divides the image into a foreground and a background according to the initial threshold value, and respectively calculates the average gray value of the foreground and the background; finally, iterative solution is carried out until convergence;
the initial threshold value is calculated by the formula:
in the formula glIs the maximum gray value of the image, guIs the minimum gray value of the image;
the average gray value of the foreground and the background is calculated by the formula:
wherein g represents the gray value of the pixel, h (g) is the weight corresponding to different gray values, AbIs the mean gray value of the foreground, AfIs the background average gray value;
the formula for the iterative solution is:
in the formula TkObtaining a gray threshold value for the Kth iteration;
the expression until convergence is:
Tk+1-Tk＜ε
where ε is the computational accuracy of the iteration.
8. The method of claim 1, wherein the method comprises: step 7, selecting different arc areas, scanning the image from left to right and from top to bottom by adopting a two-pass scanning algorithm, and connecting adjacent pixels with the same pixel value to form a connected domain; and extracting and marking the arc areas, and recording the number of the arc areas and the boundary coordinates of the connected domains.
9. The method of claim 8, wherein the method further comprises the steps of: step 8, solving the total gray level of the arc area, extracting the corresponding arc area from the gray level image by using the recorded coordinate data, calculating the total gray level value of the arc area, obtaining the gray level characteristics of the arc at different development moments, and reflecting the moment when the arc is completely sprayed out of the chamber according to gray level changes;
the formula for solving the total gray level of the arc area is as follows:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110904424.0A CN113805015A (en) | 2021-08-06 | 2021-08-06 | Arc image form detection method for multi-cavity arc extinguishing device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110904424.0A CN113805015A (en) | 2021-08-06 | 2021-08-06 | Arc image form detection method for multi-cavity arc extinguishing device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113805015A true CN113805015A (en) | 2021-12-17 |
Family
ID=78942955
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110904424.0A Pending CN113805015A (en) | 2021-08-06 | 2021-08-06 | Arc image form detection method for multi-cavity arc extinguishing device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113805015A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117031262A (en) * | 2023-06-26 | 2023-11-10 | 国网安徽省电力有限公司电力科学研究院 | Isolating switch arcing monitoring system and method |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110349153A (en) * | 2019-07-24 | 2019-10-18 | 南京大树智能科技股份有限公司 | The image method tobacco based on multi-feature fusion detection method of rate containing stalk |
| CN110517226A (en) * | 2019-07-24 | 2019-11-29 | 南京大树智能科技股份有限公司 | The offal method for extracting region of multiple features texture image fusion based on bilateral filtering |
| CN111398748A (en) * | 2020-03-12 | 2020-07-10 | 山西耀源电力工程有限公司 | Impulse arc image edge detection method and device |
-
2021
- 2021-08-06 CN CN202110904424.0A patent/CN113805015A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110349153A (en) * | 2019-07-24 | 2019-10-18 | 南京大树智能科技股份有限公司 | The image method tobacco based on multi-feature fusion detection method of rate containing stalk |
| CN110517226A (en) * | 2019-07-24 | 2019-11-29 | 南京大树智能科技股份有限公司 | The offal method for extracting region of multiple features texture image fusion based on bilateral filtering |
| CN111398748A (en) * | 2020-03-12 | 2020-07-10 | 山西耀源电力工程有限公司 | Impulse arc image edge detection method and device |
Non-Patent Citations (2)
| Title |
|---|
| 夏天等: "潜供电弧模拟实验图像边缘检测与形态特征分析", 中国电机工程学报, vol. 39, no. 3, pages 923 - 932 * |
| 张永新: "基于边缘保持滤波的多聚焦图像融合算法研究", 31 March 2021, 新华出版社, pages: 41 - 42 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117031262A (en) * | 2023-06-26 | 2023-11-10 | 国网安徽省电力有限公司电力科学研究院 | Isolating switch arcing monitoring system and method |
| CN117031262B (en) * | 2023-06-26 | 2024-08-30 | 国网安徽省电力有限公司电力科学研究院 | Isolating switch arcing monitoring system and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111398748A (en) | Impulse arc image edge detection method and device | |
| Takami et al. | Characteristics of direct lightning strokes to phase conductors of UHV transmission lines | |
| Fuchs et al. | Lightning current and magnetic field parameters caused by lightning strikes to tall structures relating to interference of electronic systems | |
| Takami et al. | Observational results of lightning current on transmission towers | |
| Borghetti et al. | Influence of the return stroke current waveform on the lightning performance of distribution lines | |
| Paulino et al. | The peak value of lightning-induced voltages in overhead lines considering the ground resistivity and typical return stroke parameters | |
| CN113805015A (en) | Arc image form detection method for multi-cavity arc extinguishing device | |
| Gao et al. | PD pattern recognition for stator bar models with six kinds of characteristic vectors using BP network | |
| Long et al. | Identification of direct lightning strike faults based on mahalanobis distance and S-transform | |
| CN215813146U (en) | Test observation device for transient gas discharge in semi-closed micro-cavity | |
| CN103954858A (en) | Airborne antenna lightning testing system and method | |
| Chisholm et al. | Lightning arc damage to optical fiber ground wires (OPGW): parameters and test methods | |
| Visacro et al. | Features of upward lightning measured in a tropical region and their potential to cause hazardous effects | |
| Montañés et al. | An improvement for the selection of surge arresters based on the evaluation of the failure probability | |
| CN111814355B (en) | High-voltage transmission line lightning shielding failure protection method and device and terminal equipment | |
| Kisielewicz et al. | Dimensioning of SPD for the protection against surges due to lightning to LV overhead lines | |
| Chen et al. | The damage effects on surge protective devices caused by the ground potential rise during the initial long continuous current processes of triggered lightning events | |
| CN113406450A (en) | Test observation device and method for transient gas discharge in semi-closed micro-cavity | |
| Napolitano et al. | Estimation of the expected annual number of flashovers in power distribution lines due to negative and positive lightning | |
| Chang et al. | Online source recognition of partial discharge for gas insulated substations using independent component analysis | |
| Sun et al. | Corona characteristics of aerial conductors under switching impulse voltages | |
| CN109164359A (en) | The filming apparatus in X-ray penetration soil spark discharge channel | |
| CN110082650A (en) | A kind of devices and methods therefor suitable for the assessment of hydroscopic high-molecular resin resistance-lowering material resistance-reducing efficiency | |
| Wang et al. | Model test on the effect of hillside on lightning shielding performance of±1100 kV transmission lines | |
| CN111337796A (en) | Power transmission line lightning shielding failure model test platform and method considering mountain terrain |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |