Gas discharge image reconstruction method and device and computer program product

Abstract

The invention discloses a gas discharge image reconstruction method and device and a computer program product, and the method comprises the steps: S1, synchronously obtaining the frame image data of a high-speed camera and the event stream data of a dynamic visual sensor; s2, performing time window integral processing on the event stream data, and counting the event occurrence frequency of each pixel point in preset integral time; step S3, retaining the position information of the pixel points of which the event occurrence frequency is greater than or equal to a preset event counting threshold value; and S4, converting the position information of the screened pixel points into a binary image, and generating a discharge reconstruction image based on the event stream. According to the gas discharge image reconstruction method based on the dynamic visual sensor, the technical bottlenecks of a traditional high-speed camera in the aspects of dynamic range, data storage and environmental adaptability are effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a gas discharge image reconstruction method, device and computer program product. Background Art

[0002] Optical monitoring of gas discharge phenomena is an important means of studying its physical mechanisms. Traditional visible light-based monitoring technologies rely primarily on high-speed cameras, but these technologies face significant technical bottlenecks: the limited exposure tolerance of their charge-coupled devices (CCDs) makes it difficult to simultaneously capture both the weak luminescence channels of the pre-discharge phase and the intense luminescence areas of the main discharge phase. Furthermore, traditional high-speed cameras utilize a frame-synchronized acquisition mode, requiring large-capacity storage devices. These devices are bulky and susceptible to interference in complex electromagnetic environments, making online monitoring difficult in the field or at industrial sites.

[0003] Early morphological recording techniques, including film and dust methods, achieved submillimeter spatial resolution but could only capture static images at discrete time points. Rotating cameras and image converter cameras achieved dynamic process recording through scanning or framing. However, film storage media resulted in inefficient data processing and the scanning mode failed to retain complete spatial information. While Schlieren technology can observe weakly ionized leader channels in the early stages of a discharge, its limited field of view and low system sensitivity make it difficult to monitor long-gap discharges.

[0004] Ultrahigh-speed cameras developed in recent years have achieved nanosecond-level temporal resolution and megapixel-level spatial resolution, enabling recording of the entire discharge process. However, these devices still suffer from the following drawbacks: 1) the use of a global shutter results in insufficient dynamic range; 2) the high data generation rate requires a dedicated data storage system; and 3) the limitations of the mechanical shutter structure make miniaturization difficult. These issues render existing technologies suitable only for laboratory environments and unable to meet practical needs such as online monitoring of power transmission and distribution equipment.

[0005] Dynamic Vision Sensors (DVS), a brain-inspired sensing device, utilize an asynchronous event-driven mechanism to independently respond to brightness changes at each pixel, achieving μs-level temporal resolution and a dynamic range exceeding 120 dB. This technology utilizes event stream encoding, reducing data transmission to 1 / 100th to 1 / 1000th of that of traditional frame cameras, providing a new path for portable discharge monitoring. However, existing DVS devices still have limitations in low-light response and multi-scale feature fusion, limiting their application in gas discharge monitoring. Summary of the Invention

[0006] The technical problem to be solved by the embodiments of the present invention is to provide a gas discharge image reconstruction method, device and computer program product to achieve high temporal and spatial resolution, lightweight and reliable reconstruction of discharge morphology.

[0007] To solve the above technical problems, the present invention provides a gas discharge image reconstruction method, comprising:

[0008] Step S1, synchronously acquiring frame image data from a high-speed camera and event stream data from a dynamic vision sensor;

[0009] Step S2, performing time window integration processing on the event stream data, and counting the number of events occurring at each pixel within a preset integration time;

[0010] Step S3, retaining the pixel location information for which the number of events occurring is greater than or equal to a preset event counting threshold;

[0011] Step S4: converting the filtered pixel position information into a binary image to generate a discharge reconstruction image based on the event stream.

[0012] Preferably, the method further comprises: quantitatively evaluating the consistency between the discharge reconstruction image and the frame image data by means of structural similarity and mean square error.

[0013] Preferably, step S1 is implemented by a pre-built three-electrode structure, which includes two parallel planar electrodes and a needle electrode installed vertically at the center of the lower planar electrode, and the needle electrode is insulated from the planar electrode by a polytetrafluoroethylene insulation layer.

[0014] Preferably, the high-speed camera saves frame image data in *.cine format, and the dynamic vision sensor saves event stream data in *.aedat4 format.

[0015] Preferably, the preset integration time is the same as the exposure time of the high-speed camera.

[0016] Preferably, the CountImage encoding method is used to count the location information of the event, and the preset event counting threshold C is 1.

[0017] The present invention also provides a gas discharge image reconstruction device, comprising:

[0018] one or more processors;

[0019] Memory;

[0020] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to perform the gas discharge image reconstruction method.

[0021] The present invention also provides a computer program product, comprising computer instructions, wherein the computer instructions instruct a computer device to execute operations corresponding to the method.

[0022] The implementation of the present invention has the following beneficial effects: the present invention constructs a gas discharge image reconstruction method by introducing a dynamic visual sensor, which effectively solves the technical bottlenecks of traditional high-speed cameras in terms of dynamic range, data storage and environmental adaptability. Specifically, it breaks through the dynamic range limitations of CCD devices on weak luminous areas (pre-discharge stage) and strong luminous areas (main discharge stage), and realizes the synchronous capture of multi-scale discharge phenomena; significantly reduces data storage requirements through event stream coding technology; synchronously collected high-speed camera frame images and DVS event stream data form a multimodal verification system to ensure the credible reconstruction of discharge morphological characteristics; successfully records the complete discharge process in a typical discharge experiment, and provides a new means for extracting key parameters such as discharge initiation criteria and channel development laws. While maintaining laboratory-level monitoring accuracy, the present invention significantly improves the environmental adaptability and data processing efficiency of the discharge monitoring system, and has important scientific significance and engineering application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 This is a flow chart of a gas discharge image reconstruction method according to an embodiment of the present invention.

[0025] Figure 2 Schematic diagram of the structure of the three-electrode system established in the embodiment of the present invention. DETAILED DESCRIPTION

[0026] The following descriptions of the embodiments refer to the accompanying drawings to illustrate specific embodiments in which the present invention may be implemented.

[0027] Please refer to Figure 1 As shown, the first embodiment of the present invention provides a gas discharge image reconstruction method, including:

[0028] Step S1, synchronously acquiring frame image data from a high-speed camera and event stream data from a dynamic vision sensor;

[0029] Step S2, performing time window integration processing on the event stream data, and counting the number of events occurring at each pixel within a preset integration time;

[0030] Step S3, retaining the pixel location information for which the number of events occurring is greater than or equal to a preset event counting threshold;

[0031] Step S4: Convert the filtered pixel position information into a binary image to generate a discharge reconstruction image based on the event stream.

[0032] Specifically, in order to obtain a complex discharge optical image, the present invention first constructs a DC "three-electrode" structure. The credibility of high-speed camera pictures and event restoration images is studied through the three-electrode structure. As Figure 2 shown, the "three-electrode" structure consists of two parallel planar electrodes (diameter 250 mm) and a needle electrode. The gap between the two planes is 30 mm. The needle electrode is located at the center of the lower planar electrode and is insulated from the planar electrode by a layer of polytetrafluoroethylene. As an example, the planar electrode is made of copper material, and the needle electrode is made of tungsten steel with a tip curvature radius of 50 μm to ensure discharge concentration.

[0033] Synchronously trigger the high-speed camera and the dynamic vision sensor (DVS) to obtain frame image data and event stream data respectively. The high-speed camera continuously shoots at a frame rate of 10,000 frames per second to generate a *.cine format file; the DVS records the brightness change of each pixel point in an asynchronous event-driven mode, and the data is stored in the *.aedat4 format. Since the DVS cannot directly obtain the discharge image from the original data, the work of image restoration needs to be carried out using the data stream. Select t = 100 μs as the integration time, which is the same as the exposure time of the high-speed camera.

[0034] Import the *.aedat4 format data output by the DVS into the processing system and set an integration time window that matches the exposure time of the high-speed camera. Count the number of events N i ,y i ) of each pixel point within this time window to form an event count matrix. The selection of the integration time needs to ensure that the event density reaches the threshold of the reconstructable image while avoiding oversaturation. E Set an event count threshold C according to the experimental noise characteristics and traverse all pixel points in the event count matrix. Retain the effective pixel positions where the number of events N

[0035] ≥ C, and filter out the noise points where N E < C. The setting of the event count threshold C needs to balance the image integrity and the noise suppression effect. In this embodiment, due to the short integration time and low background noise, a fixed threshold C = 1 is used for screening. E < C.

[0036] The embodiment of the present invention adopts the CountImage coding method to map the filtered effective pixel coordinates to a two-dimensional image plane. Assign a preset gray value (such as 255) to the corresponding position and set the rest to zero to generate a binary discharge reconstruction image. This process realizes the spatial visualization of event stream data through matrix operations.

[0037] To morphologically demonstrate the comparability between high-speed camera images and event data reconstructed images, this embodiment of the present invention uses structural similarity and mean squared error as evaluation metrics. The Structural Similarity Index (SSIM) is a metric used to measure the similarity between two images, with values ranging from (0, 1). A value closer to 1 indicates more similar image features. The SSIM value can be used to reflect the similarity between high-speed camera and DVS images. The mean squared error (MSE) is a commonly used metric for measuring differences between values or images; smaller values indicate smaller image differences.

[0038] The SSIM and MSE values of the three discharge results of the high-speed camera image and the event data reconstruction image are compared, and the results are shown in Table 1.

[0039] Table 1 Discharge result data table

[0040]

[0041]

[0042] As can be seen from Table 1, the SSIM values of the three discharge results are all over 0.91, indicating that the event stream reconstructed image and the high-speed camera frame image are highly consistent in terms of discharge channel morphology, branch structure and other features. The MSE values are all less than 0.05, verifying the ability of the event stream data to accurately restore the discharge luminous intensity distribution. The SSIM / MSE of the three sets of data show a negative correlation (the higher the SSIM, the lower the MSE), which verifies the rationality of the evaluation index system. While maintaining high spatiotemporal resolution, the present invention can effectively suppress background noise (for example, the MSE value of group C of 0.0426 is still better than the typical error level of traditional frame cameras), providing technical support for discharge monitoring in complex electromagnetic environments.

[0043] Corresponding to the gas discharge image reconstruction method described in the first embodiment of the present invention, the second embodiment of the present invention further provides a gas discharge image reconstruction device, including:

[0044] one or more processors;

[0045] Memory;

[0046] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the gas discharge image reconstruction method described in the aforementioned embodiment 1 of the present invention.

[0047] Corresponding to the gas discharge image reconstruction method described in the aforementioned embodiment 1 of the present invention, embodiment 3 of the present invention further provides a computer program product, including computer instructions, which instruct a computer device to perform operations corresponding to the gas discharge image reconstruction method described in the aforementioned embodiment 1 of the present invention.

[0048] Preferably, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may be any conventional processor. The processor is the control center of the device, and various parts of the device are connected using various interfaces and lines.

[0049] The memory mainly includes a program storage area and a data storage area, wherein the program storage area can store an operating system, an application program required for at least one function, etc., and the data storage area can store related data, etc. In addition, the memory can be a high-speed random access memory, or a non-volatile memory, such as a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, and a flash card, etc., or the memory can also be other volatile solid-state storage devices.

[0050] It should be noted that the above-mentioned device may include but is not limited to a processor and a memory, which can be understood by those skilled in the art.

[0051] For the working principle and process of the above embodiment, please refer to the description of the above embodiment of the present invention, which will not be repeated here.

[0052] It can be seen from the above description that, compared with the prior art, the beneficial effects of the present invention are: the present invention constructs a gas discharge image reconstruction method by introducing a dynamic visual sensor, which effectively solves the technical bottlenecks of traditional high-speed cameras in terms of dynamic range, data storage and environmental adaptability. Specifically, it breaks through the dynamic range limitations of CCD devices on weak luminous areas (pre-discharge stage) and strong luminous areas (main discharge stage), and realizes the synchronous capture of multi-scale discharge phenomena; significantly reduces data storage requirements through event stream coding technology; synchronously collected high-speed camera frame images and DVS event stream data form a multimodal verification system to ensure the credible reconstruction of discharge morphological characteristics; successfully records the complete discharge process in a typical discharge experiment, and provides a new means for extracting key parameters such as discharge initiation criteria and channel development laws. While maintaining laboratory-level monitoring accuracy, the present invention significantly improves the environmental adaptability and data processing efficiency of the discharge monitoring system, and has important scientific significance and engineering application prospects.

[0053] The above disclosure is merely a preferred embodiment of the present invention and is not intended to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A gas discharge image reconstruction method, characterized in that: include: Step S1, synchronously acquiring frame image data from a high-speed camera and event stream data from a dynamic vision sensor; Step S2, performing time window integration processing on the event stream data, and counting the number of events occurring at each pixel within a preset integration time; Step S3, retaining the pixel location information for which the number of events occurring is greater than or equal to a preset event counting threshold; Step S4: converting the filtered pixel position information into a binary image to generate a discharge reconstruction image based on the event stream.

2. The method according to claim 1, characterized in that Also includes: The consistency between the discharge reconstructed image and the frame image data is quantitatively evaluated by structural similarity and mean square error.

3. The method according to claim 1, characterized in that The step S1 is implemented by a pre-built three-electrode structure, which includes two parallel planar electrodes and a needle electrode installed vertically at the center of the lower planar electrode. The needle electrode is insulated from the planar electrode by a polytetrafluoroethylene insulation layer.

4. The method according to claim 1, wherein The high-speed camera saves the frame image data in *.cine format, and the dynamic vision sensor saves the event stream data in *.aedat4 format.

5. The method according to claim 1, wherein The preset integration time is the same as the exposure time of the high-speed camera.

6. The method according to claim 1, wherein The CountImage encoding method is used to count the location information of the event, and the preset event counting threshold C is 1.

7. A gas discharge image reconstruction device, characterized in that: include: one or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the gas discharge image reconstruction method according to any one of claims 1 to 6.

8. A computer program product, characterized in that The method comprises computer instructions, wherein the computer instructions instruct a computer device to perform operations corresponding to the method according to any one of claims 1 to 6.

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