A method and system for spatiotemporal evolution analysis of muzzle electric arc energy and centroid

Abstract

The application discloses a time-space evolution analysis method and system for muzzle electric arc energy and centroid, relates to the technical field of muzzle electric arc analysis, and comprises the following steps: building an electromagnetic track launching muzzle electric arc simulation experiment platform, acquiring a muzzle electric arc image by using a high-speed photography system, obtaining an electric arc contour image based on a local adaptive threshold segmentation and a morphological gradient extraction algorithm, and improving the integrity and robustness of electric arc contour extraction; based on a robust centroid tracking algorithm of multi-connected energy fusion and time sequence consistency constraint, obtaining a final electric arc centroid, realizing stable positioning and tracking of the electric arc energy centroid in the whole evolution stage; and based on the muzzle electric arc images under different muzzle velocities, quantitatively analyzing the time-domain evolution characteristics of the high-light area of the muzzle electric arc and the law of the spatial motion trajectory of the centroid. The application provides an effective means for quantitative characterization of the muzzle electric arc, and provides experimental basis and theoretical reference for muzzle structure optimization, anti-ablation design and launch working condition regulation of an electromagnetic launching system.

Description

Technical Field

[0001] This invention relates to the field of muzzle arc analysis technology, and in particular to a method and system for spatiotemporal evolution analysis of muzzle arc energy and centroid. Background Technology

[0002] Electromagnetic railguns utilize the Lorentz force generated by high-energy pulsed power discharge in their armatures to rapidly accelerate the projectile within the barrel, propelling it at high speed. During firing, the high-speed motion of the armature within the barrel generates intense friction, accompanied by transition phenomena and a secondary electric arc after the armature exits the barrel. The arc ablation problem in the muzzle region is particularly prominent. The intensely burning arc not only severely damages the rail but also alters the ballistic elasticity, affecting firing accuracy. Furthermore, the metal debris generated by the ablation can enter the system, causing malfunctions in other components, significantly shortening the service life of the firing device, and increasing maintenance costs and operational risks. Therefore, research on the formation and extinguishing characteristics of the muzzle arc is of great significance for extending rail life and optimizing the design of the firing system.

[0003] In recent years, experts and scholars have used various simulation methods to study the formation characteristics of muzzle arcs, particularly achieving significant results in simulating the flow field, temperature distribution, and plasma behavior characteristics of muzzle arcs. However, for muzzle arcs in open environments, their motion characteristics are affected by natural conditions and system operating conditions, and arc simulation cannot completely replace experiments. Moreover, muzzle arcs are influenced by multiple physics fields, and simulation studies have significant limitations in setting boundary conditions. Therefore, simulation experiments are currently the most fundamental and necessary choice for studying muzzle arcs.

[0004] Currently, some studies utilize high-speed photography and spectrophotometry to record the muzzle and breech eruption processes during railgun firing, analyzing the motion and temperature of the ion beams at the muzzle and breech throughout the firing process, and proposing the phenomenon of high-temperature gas backflow during electromagnetic railgun firing. Other studies address the muzzle arc problem during electromagnetic railgun firing, designing and analyzing a muzzle arc suppression device based on gap arc discharge. Still other studies have conducted experimental and theoretical research on the muzzle voltage of electromagnetic railguns.

[0005] However, existing studies have only preliminarily analyzed the typical motion characteristics of the borehole arc, but have not quantitatively extracted characteristic parameters that intuitively reflect the arc's ignition and extinguishing characteristics, such as arc area and transport distance, and have not explored the arc formation mechanism under different working conditions in sufficient depth. Summary of the Invention

[0006] To address the aforementioned issues, this invention proposes a method and system for spatiotemporal evolution analysis of muzzle arc energy and centroid. Based on an image processing method using local adaptive threshold segmentation and morphological gradient extraction, the completeness and robustness of arc contour extraction are effectively improved. A robust centroid tracking algorithm based on multi-connected domain energy fusion and temporal consistency constraints achieves stable positioning and tracking of the arc energy centroid throughout the entire evolution phase. Based on muzzle arc images under different exit velocities, the temporal evolution characteristics of the bright areas of the muzzle arc and the spatial trajectory of its centroid are quantitatively analyzed.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] In a first aspect, the present invention provides a method for spatiotemporal evolution analysis of muzzle arc energy and centroid, comprising:

[0009] Acquire images of the muzzle arc at different muzzle velocities;

[0010] The muzzle arc image is segmented using an adaptive threshold to obtain a binarized image. The binarized image is then processed by edge detection to obtain the arc contour image. This allows us to obtain the evolution of the arc area over time at different muzzle exit velocities.

[0011] After superimposing the binarized image with the bore arc image, the energy value of the connected components in the obtained single-frame arc image is calculated. Connected components with energy values ​​greater than or equal to a preset energy threshold are used to form a set of effective connected components, thereby reconstructing the observed arc centroid of the single-frame arc image.

[0012] Based on the comparison results of the observed arc centroids of adjacent arc images, the observed arc centroid of the current arc image is corrected to obtain the final arc centroid, thereby obtaining the trajectory of the arc centroid over time at different muzzle velocities.

[0013] As an alternative implementation, based on pixels in the muzzle arc image Mean gray value within the neighborhood with standard deviation Determine the adaptive threshold : k is the correction factor. R This is the grayscale dynamic range constant;

[0014] The arc contour image is obtained by differential processing of the binarized image through morphological dilation and erosion operations. , ; and These represent dilation and erosion operations, respectively. S is a 3×3 circular structuring element, and B is the binarized image.

[0015] As an alternative implementation method, the process of calculating the energy value includes:

[0016] Let the first t There are K independent connected regions Ω in the frame arc image. K Then the k-th connected component zeroth moment and first moment for:

[0017] ;

[0018] In the formula, These are the pixel coordinates. For the first t The grayscale weights of the corresponding pixels in the frame arc image; p and q are the orders of the moments in the x-axis and y-axis directions, respectively.

[0019] As an alternative implementation method, the first t Energy threshold of frame arc image for:

[0020] ;

[0021] In the formula, η The energy suppression coefficient; Represents the k-th connected component The sum of the grayscale values ​​of all pixels within the range.

[0022] As an alternative implementation method, the first t Observation of the centroid of the electric arc in a frame image for:

[0023] ; ;

[0024] in, A set of valid connected components; Let be the zeroth moment of the k-th connected component; Let be the first moment of the k-th connected domain.

[0025] As an alternative implementation method, for the first t Observation of the centroid of the electric arc in a frame image The correction is as follows:

[0026] ;

[0027] In the formula, For the first t The final arc centroid after frame arc image correction. for The final arc centroid after frame arc image correction; for The estimated velocity vector of the frame; Δ t This refers to the inter-frame time interval. α This is the confidence factor, with a value of 0 < α <1.

[0028] Secondly, the present invention provides a spatiotemporal evolution analysis system for muzzle arc energy and centroid, comprising:

[0029] The acquisition module is configured to acquire images of the muzzle arc at different muzzle velocities.

[0030] The image processing module is configured to segment the muzzle arc image according to an adaptive threshold to obtain a binarized image, and then perform edge detection on the binarized image to obtain an arc contour image, thereby obtaining the evolution law of the arc area over time under different muzzle exit velocities.

[0031] The centroid calculation module is configured to overlay the binarized image with the bore arc image, calculate the energy value of the connected components in the obtained single-frame arc image, and form a set of effective connected components with energy values ​​greater than or equal to a preset energy threshold, thereby reconstructing the observed arc centroid of the single-frame arc image.

[0032] The centroid tracking module is configured to correct the observed arc centroid of the current frame arc image based on the comparison results of the observed arc centroids of adjacent frame arc images, and obtain the final arc centroid, thereby obtaining the motion trajectory of the arc centroid over time at different exit velocities.

[0033] Thirdly, the present invention provides an electronic device including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the first aspect.

[0034] Fourthly, the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in the first aspect.

[0035] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0037] To address the challenge of quantitatively characterizing muzzle arcs, this invention proposes a method and system for spatiotemporal evolution analysis of muzzle arc energy and centroid. A simulated experimental platform for electromagnetic orbital launch muzzle arcs is constructed, employing a high-speed photography system to acquire muzzle arc images and simultaneously collect muzzle current data. For common problems in muzzle arc images such as center overexposure, weak edge luminescence, and fragmented multi-connected domains, an image processing method combining local adaptive threshold segmentation and morphological gradient extraction is proposed, effectively improving the completeness and robustness of arc contour extraction. Furthermore, a robust centroid tracking algorithm based on multi-connected domain energy fusion and temporal consistency constraints is constructed, achieving stable positioning and tracking of the arc energy centroid throughout its entire evolution phase.

[0038] This invention, based on high-speed photographic experiments under different muzzle velocities, quantitatively analyzes the temporal evolution characteristics of the bright region of the muzzle arc and the spatial trajectory of its centroid. Results show that with increasing muzzle velocity, the bright region exhibits more intense arc expansion, more significant thermal inertia, and a pronounced long-tail attenuation. Simultaneously, the arc's spatial motion pattern shifts from restricted swirling and stagnation at low speeds to directional jetting and long-distance transport at high speeds. Combined with synchronously acquired muzzle current waveforms, the formation mechanism of the macroscopic morphological differences in the muzzle arc is revealed from aspects such as inductive energy storage and release, thermal hysteresis effects, and the competition between aerodynamic drag and electromagnetic confinement forces. This invention provides an effective means for the quantitative characterization of muzzle arcs and can provide experimental basis and theoretical reference for muzzle structure optimization, ablation resistance design, and launch condition control in electromagnetic launch systems.

[0039] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0041] Figure 1 The flowchart shows the spatiotemporal evolution analysis method of the muzzle arc energy and the center of mass provided in Embodiment 1 of the present invention.

[0042] Figure 2 This is a circuit topology diagram of the electromagnetic orbital launch muzzle arc simulation experimental platform provided in Embodiment 1 of the present invention;

[0043] Figure 3This is a flowchart of the muzzle arc image processing provided in Embodiment 1 of the present invention;

[0044] Figure 4 This is a flowchart of the centroid tracking algorithm provided in Embodiment 1 of the present invention;

[0045] Figure 5 This is a time-domain evolution curve of the area of ​​the high-brightness region of the muzzle arc under different muzzle velocities provided in Embodiment 1 of the present invention;

[0046] Figure 6 This is a sequence diagram of the evolution of the muzzle arc morphology under a working condition of 175 m / s provided in Embodiment 1 of the present invention;

[0047] Figure 7 This is a diagram showing the trajectory of the centroid of the muzzle electric arc under a working condition of 175 m / s, provided in Embodiment 1 of the present invention.

[0048] Figure 8 This is a sequence diagram of the evolution of the muzzle arc morphology under a working condition of 375 m / s provided in Embodiment 1 of the present invention;

[0049] Figure 9 This is a diagram showing the trajectory of the centroid of the muzzle electric arc under a working condition of 375 m / s, provided in Embodiment 1 of the present invention.

[0050] Figure 10 This is a waveform diagram showing the change of muzzle current at different exit velocities provided in Embodiment 1 of the present invention;

[0051] Figure 11 for Figure 10 Enlarged view of the curve in section A. Detailed Implementation

[0052] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0053] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0054] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form as well. Furthermore, it should be understood that the terms “comprising” and “including”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0055] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0056] Example 1

[0057] This embodiment provides a method for analyzing the spatiotemporal evolution of muzzle arc energy and centroid, such as... Figure 1 As shown, it includes:

[0058] Acquire images of the muzzle arc at different muzzle velocities;

[0059] The muzzle arc image is segmented using an adaptive threshold to obtain a binarized image. The binarized image is then processed by edge detection to obtain the arc contour image. This allows us to obtain the evolution of the arc area over time at different muzzle exit velocities.

[0060] After superimposing the binarized image with the bore arc image, the energy value of the connected components in the obtained single-frame arc image is calculated. Connected components with energy values ​​greater than or equal to a preset energy threshold are used to form a set of effective connected components, thereby reconstructing the observed arc centroid of the single-frame arc image.

[0061] Based on the comparison results of the observed arc centroids of adjacent arc images, the observed arc centroid of the current arc image is corrected to obtain the final arc centroid, thereby obtaining the trajectory of the arc centroid over time at different muzzle velocities.

[0062] like Figure 2 The circuit topology of the electromagnetic orbital launch muzzle arc simulation experimental platform built in this embodiment is as follows: In the high-voltage charging and rectification module, the step-up transformer of model TDM-10 / 100 steps up the 220V AC power to about 2000V to 4000V. After passing through a full-wave rectifier silicon stack composed of high reverse voltage diodes connected in series, the stepped-up AC power is rectified into DC power for unidirectional conduction and charging of the energy storage module.

[0063] Among them, capacitor C with a capacitance of 4mF and a rated voltage of 5kV and capacitor... Composition of energy storage module, charging current limiting resistor This limits the maximum charging current to 500mA. Connected in series in their respective charging circuits, these switches limit the inrush current during the initial charging phase, protecting the silicon stack. They also determine the capacitor's charging time constant τ=RC=40s, with a full charge typically taking around 5τ=200s. Isolation and gating switches K and... The charging and discharging process allows for flexible control, selective connection of capacitors on both sides, and adjustment of total energy storage and pulse width while maintaining a constant voltage. (Discharge resistor) It is connected in parallel with a capacitor branch for rapid discharge to prevent high voltage residue.

[0064] The pulse current shaping and transmission module is a typical RLC discharge network. The remote control system controls the conduction of the discharge thyristor D1. The total capacitance of the capacitor bank and the tuning inductor L form an LC oscillation circuit, regulating the current rise rate and providing energy buffering. A freewheeling diode D2 is connected in reverse parallel across the transmitter, allowing the magnetic energy stored in the inductor L and the track inductor to flow through the D2 load circuit. This not only prevents reverse charging of the capacitors from breaking down the dielectric but also utilizes the remaining magnetic energy to maintain the track current, improving transmission efficiency and extending the arc observation window. A high-voltage digital meter is connected to a 1000:1 voltage divider to monitor the charging voltage U0 of the capacitor bank in real time, determining the transmission energy E = 1 / 2 * CU0. 2 The oscilloscope, acting as a data acquisition terminal, simultaneously records the voltage waveform from the P6015A high-voltage probe and the current waveform from the Rogowski coil CT.

[0065] To meet the requirements for image resolution and temporal resolution, the experiment used a FASTCAM NOVA S20 high-speed camera equipped with a Canon EF zoom lens as the observation device. The shutter speed can reach 0.2μs, and the captured arc grayscale image has a resolution of 1024×1024 and a frame rate of 25000 frames / s.

[0066] During electromagnetic orbit launch, the muzzle arc is a high-temperature, high-pressure non-equilibrium plasma. Its high-speed photographic images have characteristics such as overexposure of the center brightness, blurred edge details, complex background noise, and drastic morphological changes. Traditional image processing methods are difficult to effectively suppress strong light interference while preserving the weak edge details of the arc.

[0067] To address this, this embodiment proposes a local adaptive threshold segmentation and morphological gradient edge extraction algorithm to achieve accurate segmentation of the arc morphology. Based on this, a robust centroid tracking algorithm based on multi-connected domain energy fusion and temporal consistency constraints is constructed to quantitatively analyze the spatiotemporal evolution of the arc energy center.

[0068] Specifically:

[0069] 1. Compared with the image extraction algorithm that combines the Otsu's method and the Canny edge detection algorithm, the local adaptive threshold segmentation and morphological gradient edge extraction algorithm mainly consists of three parts: image preprocessing based on Gaussian smoothing filter, adaptive threshold image segmentation based on local statistics, and image edge extraction based on morphological gradient. This algorithm significantly improves the adaptability and robustness to complex flow field morphology.

[0070] (1) Image preprocessing.

[0071] High-speed cameras inevitably introduce thermal noise in high-gain mode, and there are also minute turbulent textures inside the electric arc. To avoid interference from these high-frequency components in subsequent edge detection, the acquired RGB image of the borehole arc is first converted into a grayscale image. Then, Gaussian weighted filtering is used to preprocess the grayscale image; among which, the grayscale image... The scale adopted is Gaussian kernel function Perform convolution operations to obtain a smoothed image. :

[0072] (1);

[0073] (2);

[0074] in, This represents the convolution operation.

[0075] This step effectively preserves the low-frequency profile information of the electric arc while smoothing out background clutter.

[0076] (2) Adaptive threshold image segmentation.

[0077] Traditional global thresholding methods often result in the loss of the diffused region of weak arc emission or the adhesion of the bright core region. Therefore, this embodiment introduces an adaptive thresholding segmentation algorithm based on local statistical characteristics. This algorithm dynamically determines the adaptive threshold by calculating the statistical features within the neighborhood of each pixel, balancing the segmentation accuracy of both the core and edge regions.

[0078] For any pixel in the preprocessed muzzle arc image Define its neighborhood window mean gray level within with standard deviation Then the adaptive threshold of that pixel. Defined as:

[0079] (3).

[0080] This leads to the binarized image. :

[0081] (4);

[0082] In the formula, k is a correction coefficient, which typically takes a range of values. ; R This is the grayscale dynamic range constant, usually taken as 128.

[0083] This improvement strategy utilizes local standard deviation. It enhances the sensitivity to areas of contrast variation, thereby enabling complete extraction of the blurred edges of the electric arc.

[0084] (3) Morphological gradient edge extraction.

[0085] Due to the irregularity of electric arcs as a fluid-like morphology, conventional Canny edge detection algorithms are prone to generating broken edges or spurious noise points. This embodiment employs a morphological gradient algorithm to extract the arc contour. By differentiating between morphological dilation and erosion operations, an edge region with a certain thickness and good closure is obtained.

[0086] Define structural element S (selecting a 3×3 circular structure), arc contour image. for:

[0087] (5);

[0088] In the formula, and These represent the expansion and erosion operations, respectively.

[0089] This method uses an expansion operation to fill the voids inside the electric arc and an corrosion operation to filter out external burrs. The difference between the two is the morphological outer contour of the electric arc, which effectively solves the problem of edge continuity in complex backgrounds.

[0090] like Figure 3 As shown, Figure 3 (a) in the image is a grayscale image. Figure 3 Image (b) is the image after Gaussian weighted filtering. Figure 3 In the image, (c) represents the binarized image after adaptive thresholding. Figure 3 In the image, (d) represents the edge-extracted image. Figure 3 (e) in the image is the arc profile.

[0091] 2. Robust centroid tracking algorithm based on multi-connected domain energy fusion and temporal consistency constraints.

[0092] The trajectory of an electric arc under the coupling of Lorentz force and aerodynamics is key to revealing its dynamic characteristics. However, in the later stages of its evolution, the arc often breaks up due to turbulence, forming multiple discrete highlight regions. At this point, if the centroid is calculated based solely on the entire image, distant sparks or faint residual arcs will significantly interfere with the stability of the centroid location.

[0093] To this end, this embodiment proposes a global gray-scale weighted fusion algorithm based on connected domain energy screening, which achieves robust tracking of the arc energy centroid throughout the entire time period by dynamically eliminating low-energy fragments.

[0094] like Figure 4 As shown, specifically:

[0095] (1) Extraction of multi-connected components.

[0096] Using binarized images Combined with the original grayscale image. Let the first... t There are K independent connected regions in the frame arc image, denoted as Ω1, Ω2, ..., Ω K .

[0097] Let the image sensor collect grayscale values Positively correlated with the plasma energy density at that location, the concept of image moments is introduced to calculate each connected region separately. The local zeroth moment (energy integral) and first moment :

[0098] (6);

[0099] In the formula, For pixel coordinates, For the first t The grayscale weights of the corresponding pixels in the frame arc image; p and q are the orders of the moments in the x-axis and y-axis directions, respectively.

[0100] (2) Adaptive energy screening mechanism.

[0101] To eliminate the impact of low-energy splash noise on trajectory smoothness, an adaptive screening criterion based on the maximum energy ratio is established. Define the... t The main energy threshold of the frame arc image value:

[0102] (7);

[0103] In the formula, η Let be the energy suppression coefficient, and take . η =0.1 0.15, which means ignoring tiny fragments with energy less than 10% of the main arc cluster; Represents the k-th connected component The sum of the grayscale values ​​of all pixels within the range.

[0104] Will Greater than or equal to The connected components are determined to be valid arcs, and a set of valid connected components is constructed accordingly. :

[0105] (8);

[0106] And less than Connected components are treated as splash noise and their corresponding connected components are removed. This step ensures that the algorithm focuses only on the arc body carrying the main energy and its main split blocks, eliminating random discrete noise.

[0107] (3) Global weighted fusion centroid calculation.

[0108] Based on the filtered set of valid connected components By utilizing the linear superposition property of moments, the effective first-order moments and zeroth-order moments of the entire field are reconstructed, and then the 1st-order moments are solved. t Global observation of arc centroid in frame arc image :

[0109] (9);

[0110] (10).

[0111] (4) Timing consistency constraints.

[0112] Although energy-based fusion algorithms can effectively suppress spatial discrete noise, single-frame arc image processing can still be affected by high-frequency arc flicker or extremely short-duration non-physical jumps, resulting in high-frequency jitter in the trajectory. Considering that arc plasma is a macroscopic substance, its motion under the action of Lorentz force has physical inertia and spatiotemporal continuity, and its center of mass position will not change abruptly between adjacent frames.

[0113] Therefore, this embodiment introduces a temporal consistency constraint mechanism based on the single-frame arc image processing. By utilizing the motion correlation between consecutive arc images, an inertial smoothing model is constructed to correct the observed arc centroid.

[0114] Let the first t The original observed arc centroid of the frame arc image is The corrected smooth arc centroid is An adaptive weighted moving average strategy is adopted:

[0115] (11);

[0116] In the formula, This is the correction position for the previous frame; The estimated velocity vector from the previous frame; Δ t This refers to the inter-frame time interval. Confidence factor (value 0 < α <1), when a drastic fluctuation in the energy of the connected components in the current frame is detected, reduce... The value increases with greater reliance on historical trajectory predictions, and vice versa. The value is used in response to the current observation.

[0117] The criterion for drastic energy fluctuations is:

[0118] Let the global grayscale zero-order moment of the arc image in frame t be... Define the relative rate of change of energy. as follows:

[0119] (12);

[0120] The energy mutation threshold is set to 0.4; when When the value is less than or equal to 0.4, it indicates that the change in the global grayscale zero-order moment is within the range of physical continuity, the arc evolution is stable, and increasing the value... Value; when A value greater than 0.4 indicates a non-physical surge or drop in the zeroth moment, reducing its magnitude. value.

[0121] The following analysis examines the spatiotemporal evolution morphological characteristics of the muzzle arc.

[0122] The pulse current waveform that drives the electromagnetic launch system varies significantly under different launch conditions, leading to different acceleration effects on the armature and ultimately different exit velocities. Armature velocity, as a macroscopic representation of the system's operating conditions, has a significant impact on the morphology of the muzzle arc.

[0123] This embodiment uses time-series images of electric arc morphology captured by high-speed photography to quantitatively characterize the muzzle arc under different speed conditions from a macroscopic morphological perspective. The study focuses on the temporal area evolution of the bright region of the arc and the spatial trajectory of the arc's centroid in the muzzle flow field to reveal its spatiotemporal distribution patterns.

[0124] 1. Temporal evolution characteristics of the high-brightness region of the bore arc.

[0125] To accurately capture the development pattern of the arc plasma core, an improved image segmentation algorithm was used to process the original grayscale image acquired by high-speed photography. This algorithm effectively eliminated interference from low-brightness smoke and ambient light through adaptive threshold filtering and morphological denoising, accurately extracting the high-brightness arc region representing the high-temperature plasma core. Specifically, it analyzed the area of ​​white pixels in the arc contour image obtained by edge detection from the binarized image. Figure 5 The evolution curves of the area of ​​the high-brightness region of the electric arc are shown under three different firing conditions, namely armature exit velocities of 175 m / s, 282.5 m / s and 375 m / s.

[0126] Although the arc under all three operating conditions went through three evolutionary cycles of arc initiation surge, secondary arc maintenance and dissipation and extinction, a comparison of the arc area curves at different exit velocities shows that the armature velocity corresponds to different exit energy states, which has a decisive influence on the morphological evolution intensity and maintenance characteristics of the arc.

[0127] In the initial stage of arc initiation, the arc area under the three different operating conditions is specifically reflected in the peak area and the rise rate. Under the high-speed condition of 375 m / s, the bright area of ​​the arc exhibits explosive growth, with an extremely high rate of increase, reaching its peak at approximately 0.32 ms, with a maximum area of ​​approximately 3.01 × 10⁻⁶. 4 Pixels. In contrast, the arc initiation process is relatively smooth under medium and low speed conditions, and both reach their peak value relatively quickly. The peak area at 282.5 m / s is 1.65 × 10⁻⁶. 4 Pixels, while the peak area at a low speed of 175m / s is only 0.96×10 4 Approximately Pixels. This shows that the peak area differs by more than three times between high and low speed conditions. This indicates that higher exit velocity corresponds to a stronger initial energy release, causing the plasma column to expand rapidly and form a larger high-temperature core region.

[0128] During the arc sustaining phase, the area curve under high-speed conditions did not transition smoothly, but instead showed a distinct secondary peak near t=0.4ms. This non-monotonic change suggests that the arc was subjected to strong gas dynamic disturbances in the high-energy flow field, possibly resulting in local reignition or the splitting and reaccumulation of the plasma cluster. The curve under medium-speed conditions was relatively flat, indicating that energy injection and heat dissipation were in a brief dynamic equilibrium, while the curve under low-speed conditions exhibited a single parabola shape with a relatively smooth area change.

[0129] During the arc extinction phase, the zero-return path of the curve reveals the difference in plasma heat capacity. Even though the absolute value of the arc area is largest at the high-speed condition of 375 m / s, its decay process is the longest, exhibiting a significant long-tail effect. Until 1.2 ms, the blue line remains at 1.95 × 10⁻⁶. 4 The high position of Pixels. Meanwhile, the arc area under the low-speed condition of 175m / s rapidly dissipates to 0.5×10 after 0.8ms. 4 Below the pixel level, it tends to disappear. This difference indicates that high-energy arcs have stronger thermal inertia, and the plasma core generated under high-speed conditions has a higher temperature and larger volume, resulting in a longer time required for heat exchange and recombination deionization processes with the ambient gas, thus exhibiting a significant area decay hysteresis.

[0130] 2. Spatial motion trajectory characteristics of the centroid of the borehole electric arc.

[0131] Besides the temporal area changes, the spatial migration characteristics of the electric arc in the muzzle flow field, as a high-temperature fluid, also have significant physical implications. The trajectory of the arc's center of mass in the muzzle flow field directly characterizes the direction of energy transport.

[0132] This embodiment utilizes a centroid frame-by-frame solution algorithm to extract the geometric center of the high-brightness region of the electric arc obtained by high-speed photography, constructs a spatial coordinate system at different times, and compares and analyzes the centroid motion characteristics under different working conditions.

[0133] (1) Regional limitation and gyration stagnation characteristics under low-speed conditions.

[0134] Figures 6-7 The morphological evolution sequence (A1 to A10) of the bright region of the arc at the borehole under a speed of 175 m / s and the corresponding scatter plots of the centroid's motion trajectory are shown. The scale bar in the figures is 72.67 pixels / cm. It can be seen that under low-speed conditions, the spatial motion of the arc's centroid is strictly physically restricted, exhibiting spatially confined and disordered cyclonic dynamics. From the perspective of horizontal transport, the arc's centroid is always confined to 1.0 cm. Within a narrow near-field region of 2.1 cm at the muzzle, despite an observation window as long as 480 μs, the centroid did not exhibit a monotonic trend of migrating towards the far field outside the muzzle. Further tracing the time-series connection from A1 to A10 revealed a complex nonlinear loop structure. In the middle stage of evolution (A4-A8), the centroid exhibited an anomalous retraction phenomenon, with data showing that the horizontal coordinate retreated from 1.8 cm to around 1.6 cm, while the Y coordinate significantly increased (4.1 cm → 4.35 cm). This indicates that the arc had now entered the backflow zone formed at the muzzle. Constrained by relatively weak axial momentum, the plasma cluster underwent overturning and backflow under the entrainment of the Karman vortex street or large-scale turbulent vortices, causing the arc core to oscillate randomly within a localized area. This diffusion-dominated stagnation mode easily leads to localized heat accumulation at the guide rail end face, thereby exacerbating the ablation damage to the material.

[0135] (2) Characteristics of directional injection and long-distance transport under high-speed conditions.

[0136] When the armature exit velocity increases to 375 m / s or even higher, the motion pattern of the arc's center of mass changes. Figures 8-9The morphological evolution sequence (B1 to B10) of the bright region of the arc at the muzzle under a speed of 375 m / s and the corresponding scatter plot of the centroid's motion trajectory are shown. It can be seen that the arc centroid exhibits a significant long-distance horizontal transport capability, with the horizontal coordinate monotonically increasing from 1.9 cm at the initial B1 to 3.8 cm at B10, a horizontal displacement span of nearly 2.0 cm, approximately twice the displacement under low-speed conditions. Furthermore, the overall trajectory shows a linear extension trend to the lower right, highly consistent with the streamline direction of the free jet at the muzzle, indicating that the arc has a strong flow field following ability. Although there is a local longitudinal jump in the B3-B6 stage, i.e., the vertical position changes from 4.64 cm to 4.75 cm, this reflects the transient disturbance of the flow field by the local high-pressure zone during shock wave reconstruction, but does not change the dominant outward transport direction of the arc as a whole.

[0137] The morphological analysis above shows that armature velocity significantly alters the macroscopic area and trajectory of the muzzle arc. The following analysis, combining synchronously acquired muzzle current waveforms and fluid dynamics theory, will dissect the underlying mechanisms leading to these morphological differences, and analyze the changes in the muzzle arc area and the transmission mechanism.

[0138] 1. Effect of muzzle current phase shift.

[0139] The generation of muzzle arc is essentially the release of inductive energy triggered by the forced disconnection of a high-current circuit at the moment the armature detaches from the guide rail. To reveal... Figure 5 The root cause of the differences in arc morphology is analyzed in depth in this embodiment by combining synchronously acquired electrical parameters. Figure 10 The waveform changes of the muzzle current after the armature leaves the barrel are shown under three typical speed conditions.

[0140] (1) Energy injection caused by current phase shift.

[0141] analyze Figures 10-11 It is known that the driving current of electromagnetic launch exhibits typical pulse waveform characteristics, and the driving intensity and movement time of the armature within the track determine its position on the current waveform at the moment of exiting the muzzle. At high speeds, due to the rapid acceleration of the armature and its short movement time, the exit time is advanced to 4.20ms, while the pulse power supply is still in the high-energy release phase, with the muzzle current reaching as high as 8.0kA. In contrast, at medium speeds, the armature exit time is delayed to 4.52ms, corresponding to the current decaying to 6.4kA along the falling edge of the waveform; at low speeds, the armature movement time is the longest, with the exit time lagging to 5.96ms, at which point the pulse current has entered its final decay phase, and the muzzle current drops to 3.2kA. This shift in time-domain phase forces the muzzle under high-speed conditions to withstand an initial current impact several times greater than that under low-speed conditions, leading to… Figure 5 The area of ​​the bright region of the electric arc during the initial stage of arc initiation experienced explosive growth.

[0142] Further analysis of the process of the current dropping to zero the instant it leaves the barrel reveals that when the armature flies away from the muzzle, the disappearance of the physical contact interface forces the current path to shift to the gaseous medium. Constrained by the inherent inductance of the circuit, the current cannot undergo a sudden change, and the magnetic energy stored in the inductor ( E m ∝ i 2 It must be released by creating an arc path through air breakdown. For example... Figure 10 It is evident that the stronger the initial current, the longer the arc maintains the circuit conduction time. Under high-speed conditions, the instantaneous current of up to 8.0kA has a huge inductive energy storage, which means that the arc must continue to burn for about 0.37ms to complete the current discharge and return to zero; while under low-speed conditions of 175m / s, this process only takes 0.16ms.

[0143] (2) Thermal hysteresis effect caused by current phase shift.

[0144] Will Figure 5 Optical measurement data and Figure 10 Cross-validation of electrical measurement data allows us to deduce the thermal inertia phenomenon of plasma. Under high-speed conditions, the muzzle current completely returns to zero at 4.57 ms, marking the end of external energy injection. However, the corresponding area of ​​the bright arc region does not disappear synchronously at this moment, but remains at 2.8 × 10⁻⁶. 4 The high Pixels followed by a slow decay over the next 0.6 ms exhibit a significant hysteresis effect of current cutoff and residual photothermal energy. This phenomenon confirms that the core region of the high-energy arc possesses extremely high heat capacity. After the high current is cut off, the high-temperature plasma cannot cool instantly and can only dissipate residual heat to the surrounding environment through relatively slow radiation and convection processes. This is the physical essence of the long-tailed decay characteristic of the arc under high initial velocity conditions.

[0145] 2. Transport mechanism under the competition between pneumatic towing and electromagnetic confinement.

[0146] The difference in the centroid trajectory of the muzzle arc observed above can be explained by the aerodynamic drag force in the muzzle flow field. F drag With electromagnetic constraint force F em This can be explained by the dynamic evolution of the competitive relationship between them. Different speed conditions actually represent different equilibrium states of these two dominant forces.

[0147] At a low operating speed of 175 m / s, the dynamic pressure generated by the exhaust gas is relatively small. At this point, the aerodynamic drag force acting on the arc plasma is insufficient to overcome the electromagnetic anchoring effect of the arc root on the guide rail surface. F drag < F emThe center of mass cannot acquire sufficient axial momentum to escape the constraint. Within the electromagnetic force constraint range, the electric arc is limited by the passive oscillation of the local turbulent vortex street, resulting in a cyclical stagnation phenomenon in the trajectory of the arc's center of mass. This diffusion-dominated stagnation mode causes heat to accumulate locally on the guide rail end face, which to some extent exacerbates the ablation damage of the material.

[0148] When the armature velocity increases to 375 m / s, the aerodynamic pressure generated by the high-speed wake far exceeds the restraining force of the track end face on the root of the arc. F drag > F em The powerful inertial airflow elongates the electric arc and forcibly separates it from the muzzle region, forcing the high-temperature plasma core to migrate rapidly to the far field with the flow field, forming... Figure 8 Long-distance transport trajectories in China.

[0149] However, rapid migration of the center of mass does not necessarily mean a reduced risk of ablation. The long extension of the center of mass trajectory indicates the presence of an extremely high-energy-density plasma jet in the muzzle region. Figure 9 As shown, the arc centroid was transported nearly 2.0 cm horizontally, indicating that the high-temperature arc root most likely underwent severe dragging and slippage along the guide rail end face or the surface of the insulating support under aerodynamic drag. This dynamic slippage, accompanied by a high current density (8.0 kA exit current), not only failed to alleviate the heat load through heat diffusion, but also significantly extended the effective range of the transient high heat flux along the exit direction, resulting in more severe sweeping ablation than under low-speed conditions. Therefore, under high-speed conditions, the combined effects of sweeping motion, high-energy heat flow injection, and backflow effect lead to more severe ablation at the track end compared to low-speed conditions.

[0150] This embodiment addresses the challenges of quantitative characterization and complex evolution mechanisms of the muzzle arc during electromagnetic orbital launch. By combining high-speed photography experiments, synchronous measurement of electrical parameters, and intelligent image processing methods, it studies the spatiotemporal evolution characteristics of the muzzle arc under different exit velocities. The main conclusions are as follows:

[0151] (1) In view of the characteristics of high brightness overexposure, weak edge blur and multi-connected domain fragmentation in the image of the bore arc, the local adaptive threshold segmentation and morphological gradient extraction method proposed in this embodiment can effectively preserve the overall outline of the arc; the centroid tracking algorithm based on multi-connected domain energy fusion and temporal consistency constraints significantly suppresses the influence of splash noise and transient flicker on trajectory stability, and realizes reliable positioning of the arc energy centroid at all times.

[0152] (2) The study revealed the significant impact of muzzle velocity on the temporal morphology of the muzzle arc. Under different speed conditions, the muzzle arc undergoes three stages: arc initiation, maintenance, and extinction. However, the peak area, growth rate, and decay characteristics of the bright region differ significantly. Under high-speed conditions, due to the earlier exit phase and larger current amplitude, the arc initiation stage exhibits explosive expansion and obvious thermal hysteresis and long-tail decay characteristics.

[0153] (3) The multi-field coupling mechanism of the arc space transport mode at the nozzle was elucidated. Under low-speed conditions, the aerodynamic drag force is insufficient to overcome the electromagnetic anchoring effect at the arc root, and the arc centroid exhibits restricted rotation and local stagnation characteristics; while under high-speed conditions, the strong wake aerodynamic effect dominates, and the arc core is forcibly stripped and undergoes long-distance directional transport along the flow field direction. Although this transport mode enhances the arc's outward migration capability, under the action of high current density, it may instead trigger a more severe risk of sweeping ablation.

[0154] In summary, the macroscopic evolution of the muzzle arc is the result of the combined effects of inductive energy storage and release, thermal inertia, and competition between aerodynamic and electromagnetic forces. The experimental methods and image analysis framework established in this embodiment provide new research tools for a deeper understanding of the muzzle plasma behavior of electromagnetic launch systems. Future work can further combine numerical simulations and material ablation experiments to conduct a more in-depth quantitative study of the arc-structure interaction mechanism, supporting the engineering application of highly reliable electromagnetic launch systems.

[0155] Example 2

[0156] This embodiment provides a spatiotemporal evolution analysis system for muzzle arc energy and centroid, including:

[0157] The acquisition module is configured to acquire images of the muzzle arc at different muzzle velocities.

[0158] The image processing module is configured to segment the muzzle arc image according to an adaptive threshold to obtain a binarized image, and then perform edge detection on the binarized image to obtain an arc contour image, thereby obtaining the evolution law of the arc area over time under different muzzle exit velocities.

[0159] The centroid calculation module is configured to overlay the binarized image with the bore arc image, calculate the energy value of the connected components in the obtained single-frame arc image, and form a set of effective connected components with energy values ​​greater than or equal to a preset energy threshold, thereby reconstructing the observed arc centroid of the single-frame arc image.

[0160] The centroid tracking module is configured to correct the observed arc centroid of the current frame arc image based on the comparison results of the observed arc centroids of adjacent frame arc images, and obtain the final arc centroid, thereby obtaining the motion trajectory of the arc centroid over time at different exit velocities.

[0161] It should be noted that the above modules correspond to the steps described in Embodiment 1, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1. It should also be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer-executable instructions.

[0162] In further embodiments, the following is also provided:

[0163] An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in Embodiment 1. For brevity, further details are omitted here.

[0164] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0165] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0166] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in Embodiment 1.

[0167] The method in Example 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0168] A computer program product includes a computer program that, when executed by a processor, implements the method described in Embodiment 1.

[0169] The present invention also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which execute in a device on a target real or virtual processor to perform the processes / methods described above. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or divided among program modules as needed. The machine-executable instructions for the program modules can execute within a local or distributed device. In a distributed device, the program modules can reside in both local and remote storage media.

[0170] The computer program code used to implement the methods of the present invention may be written in one or more programming languages. This computer program code may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the computer or other programmable data processing device, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and partially on a remote computer, or entirely on a remote computer or server.

[0171] In the context of this invention, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and the like. Examples of signals may include electrical, optical, radio, sound, or other forms of propagation signals, such as carrier waves, infrared signals, etc.

[0172] Those skilled in the art will recognize that the units and algorithm steps described in connection with the various examples of this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.

[0173] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for spatiotemporal evolution analysis of muzzle arc energy and center of mass, characterized in that, include: Acquire images of the muzzle arc at different muzzle velocities; The muzzle arc image is segmented using an adaptive threshold to obtain a binarized image. The binarized image is then processed by edge detection to obtain the arc contour image. This allows us to obtain the evolution of the arc area over time at different muzzle exit velocities. After superimposing the binarized image with the bore arc image, the energy value of the connected components in the obtained single-frame arc image is calculated. Connected components with energy values ​​greater than or equal to a preset energy threshold are used to form a set of effective connected components, thereby reconstructing the observed arc centroid of the single-frame arc image. Among them, the t Energy threshold of frame arc image for: ； No. t Observation of the centroid of the electric arc in a frame image for: ； ； In the formula, η The energy suppression coefficient; A set of valid connected components; Let be the zeroth moment of the k-th connected component; Let be the first moment of the k-th connected component; K is the number of connected components. Based on the comparison results of the observed arc centroids of adjacent arc images, the observed arc centroid of the current arc image is corrected to obtain the final arc centroid, thereby obtaining the trajectory of the arc centroid over time at different muzzle velocities. Among them, for the first t Observation of the centroid of the electric arc in a frame image The correction is as follows: ； In the formula, For the first t The final arc centroid after frame arc image correction. for The final arc centroid after frame arc image correction; for The estimated velocity vector of the frame; Δ t This refers to the inter-frame time interval. α This is the confidence factor, with a value of 0 < α <1.

2. The spatiotemporal evolution analysis method for muzzle arc energy and centroid as described in claim 1, characterized in that, Based on the pixels in the muzzle arc image Mean gray value within the neighborhood with standard deviation Determine the adaptive threshold : k is the correction factor. R This is the grayscale dynamic range constant; The arc contour image is obtained by differential processing of the binarized image through morphological dilation and erosion operations. , ; and These represent dilation and erosion operations, respectively. S is a 3×3 circular structuring element, and B is the binarized image.

3. The spatiotemporal evolution analysis method for muzzle arc energy and centroid as described in claim 1, characterized in that, The process of calculating energy values ​​includes: Let the first t There are K independent connected components Ω in the frame arc image. K Then the k-th connected component zeroth moment and first moment for: ； In the formula, These are the pixel coordinates. For the first t The grayscale weights of the corresponding pixels in the frame arc image; p and q are the orders of the moments in the x-axis and y-axis directions, respectively.

4. A spatiotemporal evolution analysis system for muzzle arc energy and center of mass, characterized in that, include: The acquisition module is configured to acquire images of the muzzle arc at different muzzle velocities. The image processing module is configured to segment the muzzle arc image according to an adaptive threshold to obtain a binarized image, and then perform edge detection on the binarized image to obtain an arc contour image, thereby obtaining the evolution law of the arc area over time under different muzzle exit velocities. The centroid calculation module is configured to overlay the binarized image with the bore arc image, calculate the energy value of the connected components in the obtained single-frame arc image, and form a set of effective connected components with energy values ​​greater than or equal to a preset energy threshold, thereby reconstructing the observed arc centroid of the single-frame arc image. Among them, the t Energy threshold of frame arc image for: ； No. t Observation of the centroid of the electric arc in a frame image for: ； ； In the formula, η The energy suppression coefficient; A set of valid connected components; Let be the zeroth moment of the k-th connected component; Let be the first moment of the k-th connected component; K is the number of connected components. The centroid tracking module is configured to correct the observed arc centroid of the current frame arc image based on the comparison results of the observed arc centroids of adjacent frames of arc images, and obtain the final arc centroid, thereby obtaining the motion trajectory of the arc centroid over time at different exit velocities. Among them, for the first t Observation of the centroid of the electric arc in a frame image The correction is as follows: ； In the formula, For the first t The final arc centroid after frame arc image correction. for The final arc centroid after frame arc image correction; for The estimated velocity vector of the frame; Δ t This refers to the inter-frame time interval. α This is the confidence factor, with a value of 0 < α <1.

5. An electronic device, characterized in that, It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the method according to any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, perform the method described in any one of claims 1-3.

7. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the method described in any one of claims 1-3.

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