A health status safety detection method for ring network boxes

Abstract

The present invention relates to the technical field of breakdown voltage testing, and specifically to a method for health status safety detection of a ring main box. The method comprises: acquiring spectrum data, curve fitting to obtain a spectrum curve, and segmenting the minimum values ​​to obtain an analysis frequency band; within the same analysis frequency band, determining the possible degree of noise based on the numerical distribution of the maximum amplitude values ​​at different powers; then screening and eliminating the noise frequency band to obtain a discharge frequency band; forming a spatial region with the eight closest microphones, connecting the center of the region in the spatial region with the microphones, and extending rays outward, taking a preset number of microphones closest to the region center on the ray as an analysis group, and determining the possible degree of discharge in the spatial region based on the amplitude changes of different microphones in the same analysis group in each discharge frequency band; and then screening the spatial region to obtain an abnormal discharge region where local abnormal discharge occurs. The present invention can improve the accuracy of health status detection of the ring main box.

Description

Technical Field

[0001] The present invention relates to the technical field of breakdown voltage testing, and in particular to a health status safety detection method for a ring network box. Background Art

[0002] A ring main unit (RME) is a device used in power distribution systems, typically installed between distribution transformers and distribution cabinets. It serves to tap, distribute, and protect the power system. It taps power from high-voltage cables to low-voltage cables, and vice versa, enabling power distribution and regulation within the power system. Furthermore, the RMU provides protection, detecting faults and anomalies in the power system and promptly shutting down faulty circuits to protect electrical equipment and personnel.

[0003] Traditional methods detect discharge in ring main boxes by comparing audio signals. This method does not take into account the difference between the distance between the sound source and the microphone during reference audio recording and the distance between the discharge position and the microphone during actual detection. The power of the ring main box is different during discharge audio recording, which will cause the obtained audio amplitude curve matching result to be inconsistent with the actual one, resulting in low accuracy in the health status detection of the ring main box. Summary of the Invention

[0004] In order to solve the technical problem that the detection of discharge in the ring main box by comparing audio signals in the related art does not take into account the difference between the distance between the sound position and the microphone during the reference audio recording and the distance between the discharge position and the microphone during the actual detection, and the different power of the ring main box during the discharge audio recording, which will lead to the inconsistency between the obtained audio amplitude curve matching result and the actual one, thereby resulting in low accuracy in the health status detection of the ring main box, the present invention provides a health status safety detection method for the ring main box, and the technical solutions adopted are as follows:

[0005] The present invention proposes a health status safety detection method for a ring network box, wherein multiple pickups are evenly arranged in the ring network box. The method includes:

[0006] Obtaining spectrum data collected by each microphone at different ring network box powers, performing curve fitting on the spectrum data of each microphone at each power to obtain a spectrum curve, segmenting the spectrum curve according to minimum values, and dividing the spectrum curve into different analysis frequency bands;

[0007] In the same analysis frequency band, the probability of the analysis frequency band belonging to the noise frequency band is determined based on the numerical distribution of the maximum amplitude values ​​at different powers; the noise frequency band is screened and eliminated based on the noise probability to obtain the discharge frequency band;

[0008] The eight closest pickups are grouped into a spatial region. The center of the region is connected to the pickups, and rays are extended outward. A preset number of pickups on the ray closest to the region center are taken as an analysis group. Based on the amplitude changes of different pickups in the same analysis group in each discharge frequency band, the possibility of local abnormal discharge in the spatial region is determined.

[0009] According to the discharge possibility degree, an abnormal discharge region where local abnormal discharge occurs is screened from the spatial region.

[0010] Furthermore, in the ring network box, each interval of a preset height is divided into a layer, and a*a pickups are evenly arranged in a grid form on each layer, where a is a positive integer and a is greater than or equal to 5.

[0011] Furthermore, curve fitting is performed on the spectrum data of each pickup at each power to obtain a spectrum curve, including:

[0012] The Savitzky-Golay smoothing algorithm is used with the window size set to 7 and the order set to 2. The spectrum data obtained under each power condition of the ring network box is smoothed, and the spectrum curve is obtained by curve fitting.

[0013] Furthermore, the spectrum curve is segmented according to the minimum value, and the spectrum curve is divided into different analysis frequency bands, including:

[0014] The spectrum curve between the two nearest minimum values ​​is regarded as an analysis frequency band.

[0015] Furthermore, based on the numerical distribution of the maximum amplitude values ​​at different powers, the possible degree of noise in the analysis frequency band belonging to the noise frequency band is determined, including:

[0016] Determine the standard deviation of the maximum amplitude values ​​of the spectrum curves of all pickups at all powers in the same analysis frequency band as the amplitude dispersion characteristic index;

[0017] Negative correlation mapping is performed on the amplitude discrete characteristic index and normalized to obtain the noise possibility degree that the analysis frequency band belongs to the noise frequency band.

[0018] Furthermore, according to the possible degree of noise, the noise frequency band is screened and eliminated to obtain the discharge frequency band, including:

[0019] The frequency band in which the noise level is likely to be greater than a preset noise threshold is used as the noise frequency band;

[0020] The noise frequency band is deleted to obtain the remaining discharge frequency band.

[0021] Furthermore, based on the amplitude changes of different pickups in the same analysis group in each discharge frequency band, the possibility of local abnormal discharge in the spatial region is determined, including:

[0022] The pickups are divided into front and back according to the distance from the starting point of the ray. The closer the distance, the closer the pickup is to the front.

[0023] Calculate the average amplitude of the overall discharge frequency band of each pickup at all powers as the discharge impact value of the corresponding pickup;

[0024] In the same analysis group and the same discharge frequency band, the difference in discharge impact values ​​between the first pickup and the second pickup of the two closest pickups is taken as the impact difference;

[0025] The discharge possibility degree of the spatial region is determined based on all the influence differences in different analysis groups in the spatial region and the discharge influence value of the pickup.

[0026] Furthermore, the discharge possibility of the spatial region is determined based on all the influence differences in different analysis groups in the spatial region and the discharge influence values ​​of the pickups, including:

[0027] Calculate the sum of all impact differences in the same analysis group to obtain the group impact index of the analysis group;

[0028] The standard deviations of the group impact indicators of all analysis groups in the same spatial region were negatively correlated and normalized to obtain the regional impact indicator;

[0029] Calculate the mean of the discharge influence values ​​of all pickups in the spatial region to obtain the regional discharge mean;

[0030] The product of the regional discharge mean and the regional impact index is normalized and used as the discharge possibility degree of local abnormal discharge in the spatial region.

[0031] Furthermore, based on the degree of discharge possibility, an abnormal discharge region where local abnormal discharge occurs is screened from the spatial region, including:

[0032] The spatial region where the discharge possibility is greater than a preset discharge threshold is regarded as an abnormal discharge region.

[0033] Furthermore, the preset number is 3.

[0034] The present invention has the following beneficial effects:

[0035] The present invention obtains the spectrum data collected by each microphone at different ring network box powers as the data basis, and then performs spectrum noise analysis based on the numerical distribution of the maximum amplitude at different powers to filter out the noise frequency band and obtain the discharge frequency band. This part is mainly based on the characteristics that the noise change does not change with the power, while the discharge change changes with the power, and accurately analyzes the discharge frequency band; then, through the amplitude changes of different microphones in the analysis group, discharge analysis is performed to determine the discharge possibility of local abnormal discharge in the spatial area. This part determines the accurate and reliable discharge possibility based on the amplitude change characteristics generated by the discharge position for different microphones in space; finally, according to the discharge possibility, the abnormal discharge area where local abnormal discharge occurs is screened from the spatial area. In summary, the embodiment of the present invention determines a more accurate abnormal discharge area through noise analysis and spatial amplitude change analysis, thereby improving the accuracy of the ring network box health status detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. 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.

[0037] Figure 1 A flow chart of a health status safety detection method for a ring main box provided by one embodiment of the present invention;

[0038] Figure 2 A schematic diagram of a spectrum diagram provided by an embodiment of the present invention;

[0039] Figure 3 A schematic diagram of a frequency spectrum curve provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a method for detecting the health status and safety of a ring main box according to the present invention, including its specific implementation, structure, features, and effectiveness. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0041] Unless defined otherwise, 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 belongs.

[0042] The following describes in detail a specific scheme of a health status safety detection method for a ring main box provided by the present invention with reference to the accompanying drawings.

[0043] See also Figure 1 , which shows a flow chart of a health status safety detection method for a ring network box provided by an embodiment of the present invention, the method comprising:

[0044] S101: Acquire spectrum data collected by each microphone at different ring network box powers, perform curve fitting on the spectrum data of each microphone at each power to obtain a spectrum curve, segment the spectrum curve according to minimum values, and divide the spectrum curve into different analysis frequency bands.

[0045] A ring main box (RMB) is a device used in power distribution systems, typically installed between distribution transformers and distribution cabinets. It is primarily used for tapping, distributing, and protecting the power system. It can tap the power from high-voltage cables to low-voltage cables, and vice versa, enabling the distribution and regulation of the power system.

[0046] The present invention uses a microphone to complete the recording of sound data. The microphone selected in the experiment should be able to meet the effect of collecting sounds from multiple angles and ensure that complete information of the discharge sound is collected.

[0047] It's important to note that within the ring main unit, each layer is defined by a preset height, and within each layer, a*a microphones are evenly arranged in a grid, where a is a positive integer greater than or equal to 5. Specifically, consider the entire ring main unit as a rectangular parallelepiped. Within the structure, every 30 cm is considered a layer, and within that layer, microphones are placed at intervals of 30 cm x 30 cm x 30 cm. Overall, eight adjacent microphones act as the eight vertices of a 30 cm x 30 cm x 30 cm cube, forming a microphone matrix.

[0048] Of course, the above-mentioned arrangement of the microphones is only an exemplary arrangement. In other embodiments of the present invention, a rectangular arrangement or other regular arrangement may also be performed, and there is no limitation to this.

[0049] The sound pickup converts the acquired sound signal into an electrical signal and sends it to the sound card, which transmits the signal in the sound card to the computer to obtain spectrum data. The spectrum data can be specifically, for example, a spectrum graph, such as Figure 2 As shown, Figure 2 A schematic diagram of a spectrum diagram provided by an embodiment of the present invention.

[0050] In order to facilitate the analysis of the spectrum graph, the spectrum data can be curve fitted to obtain a spectrum curve, including: using the Savitzky-Golay smoothing algorithm, setting the window size to 7 and the order to 2; smoothing the spectrum data obtained under each power condition of the ring network box, and curve fitting to obtain a spectrum curve.

[0051] The Savitzky-Golay smoothing algorithm is well known to those skilled in the art and will not be described in detail. By using the smoothing algorithm, curve fitting can be performed to obtain a spectrum curve, such as Figure 3 As shown, Figure 3 This is a schematic diagram of a spectrum curve provided by an embodiment of the present invention. The smoothed spectrum curve can better show the aggregation and separation of different frequency amplitudes.

[0052] After determining the spectrum curve, the spectrum curve can be specifically segmented. In the embodiment of the present invention, segmentation is performed based on the minimum value. Specifically, the spectrum curve is segmented based on the minimum value, and the spectrum curve is divided into different analysis frequency bands, including: the spectrum curve between the two closest minimum values ​​is used as an analysis frequency band.

[0053] In this embodiment of the present invention, the processed curve can be used to obtain the minimum value through the derivative method. The minimum point is located at the separation point where two frequency amplitudes converge. Using the obtained minimum value as the segmentation method for the frequency band to be analyzed by the spectrum curve can more reasonably segment the frequency bands caused by different reasons.

[0054] It should be noted that, since the spectrum curve of each pickup at different powers may correspond to different analysis frequency bands, in an embodiment of the present invention, a specific analysis can be performed on the analysis frequency band corresponding to the spectrum curve of the pickup closest to the center point of the ring network box at maximum power (the difference between noise and discharge sound is the greatest at maximum power), and this can be used as an overall segmentation method to achieve frequency band segmentation of the spectrum curve of each pickup at different powers. Alternatively, a unified analysis frequency band segmentation method can be determined through other integration methods to facilitate subsequent spectrum curve analysis.

[0055] S102: In the same analysis frequency band, determine the noise probability of the analysis frequency band belonging to the noise frequency band according to the numerical distribution of the maximum amplitude values ​​at different powers; filter and eliminate the noise frequency band according to the noise probability to obtain the discharge frequency band.

[0056] When partial discharge occurs in a ring main unit (RME), the corresponding amplitude changes in the corresponding frequency band detected by the microphone. In actual operation, a ring main unit (RME) often produces various noises, such as the air disturbance sound caused by the ventilator and the friction sound of the machine. These noises often occur in different frequency bands from the partial discharge sound.

[0057] In order to facilitate the analysis of the audio obtained by different pickups and obtain the specific location of the discharge anomaly, the frequency bands expressing partial discharge caused by aging over time, manufacturing problems, excessive voltage stress breaking through the insulating material, etc. should be screened to remove the interference frequency bands of noise.

[0058] Furthermore, in some embodiments of the present invention, the degree to which the analysis frequency band is likely to belong to the noise frequency band is determined based on the numerical distribution of the maximum amplitude values ​​at different powers, including: determining the standard deviation of the maximum amplitude values ​​of the spectrum curves of all pickups in the same analysis frequency band at all powers as an amplitude discrete characteristic index; performing negative correlation mapping and normalization processing on the amplitude discrete characteristic index to obtain the degree to which the analysis frequency band is likely to belong to the noise frequency band.

[0059] Among them, the negative correlation mapping means that there is an inverse relationship between the independent variable and the dependent variable, that is, the smaller the independent variable is, the larger the dependent variable is. In other words, the larger the value of the amplitude discrete characteristic index is, the smaller the value of the possible degree of noise obtained through mapping is.

[0060] In an embodiment of the present invention, the standard deviation is directly used as a discrete feature analysis. The smaller the value of the amplitude discrete feature index, the smaller the change in the same analysis frequency band under different powers. This means that the analysis frequency band is less affected by the ring network box itself and is more likely to be a noise frequency band. Therefore, negative correlation mapping and normalization processing are performed to obtain the degree of noise probability that the analysis frequency band belongs to the noise frequency band. The normalization method in the embodiment of the present invention can be specifically, for example, maximum and minimum value linear normalization, which is not limited to this.

[0061] Furthermore, in some embodiments of the present invention, noise frequency bands are screened and eliminated according to the possible degree of noise to obtain discharge frequency bands, including: taking frequency bands with a possible degree of noise greater than a preset noise threshold as noise frequency bands; and deleting the noise frequency bands to obtain remaining discharge frequency bands.

[0062] The preset noise threshold is a threshold value of the noise potential level, which can be specifically 0.7, for example. That is, the frequency band with a noise potential level greater than 0.7 is regarded as the noise frequency band; the noise frequency band is deleted to obtain the remaining discharge frequency band.

[0063] S103: The eight closest microphones are grouped into a spatial region. The center of the spatial region is connected to the microphones, and rays are extended outward. A preset number of microphones closest to the center of the region on the rays are taken as an analysis group. Based on the amplitude changes of different microphones in the same analysis group in each discharge frequency band, the possibility of local abnormal discharge in the spatial region is determined.

[0064] The amplitude in the spectrum often correlates with the distance between the discharge device and the pickup. As sound waves propagate from the vibration source to locations farther from the source, their amplitude gradually decreases. This is because the energy of the sound wave disperses and attenuates during propagation, resulting in a decrease in amplitude. The amplitude of a sound wave is inversely proportional to the transmission distance. Therefore, the farther the discharge location in the ring network box is from the pickup, the smaller the amplitude of the discharge frequency band in the pickup. Therefore, the discharge location can be determined based on the amplitude changes in the audio recorded by different pickups.

[0065] Referring to the detailed description of step S101, for ease of analysis, in this embodiment of the present invention, eight adjacent microphones are used as the eight vertices of a 30cm×30cm×30cm cube to form a microphone matrix. This means that each spatial region is a cube. The eight adjacent microphone positions form a smaller cube analysis space within the ring network box.

[0066] Among them, the regional center and the microphone in the spatial area are connected, and rays are extended outward. The starting point of the ray is the regional center. During the extension process, the ray will coincide with the positions of other microphones. Then, a preset number of microphones closest to the regional center on the ray will be taken as an analysis group, where the preset number is 3.

[0067] Combined with the analysis of specific discharge scenarios, when the amplitude intensity of the discharge frequency band in the spectrum curve obtained from each pickup far away from the center of the area to the center of the area in a group of analysis groups gradually increases, it can be proved that there is a local discharge problem in the analyzed cube analysis space, resulting in an increase in amplitude.

[0068] Based on the above analysis, the possibility of local abnormal discharge in the spatial region is determined according to the amplitude changes of different pickups in the same analysis group in each discharge frequency band, including: dividing the pickups into front and back according to the distance from the starting point of the ray, the closer the distance, the closer the pickup is to the front; calculating the amplitude mean of the overall discharge frequency band of each pickup at all powers as the discharge influence value of the corresponding pickup; in the same analysis group and the same discharge frequency band, the difference between the discharge influence values ​​of the front pickup and the back pickup of the two closest pickups is used as the influence difference; based on all the influence differences in different analysis groups in the spatial region and the discharge influence values ​​of the pickups, the possibility of discharge in the spatial region is determined.

[0069] It can be understood that if the discharge position is inside the spatial region, then in all analysis groups in the spatial region, each corresponding influence difference is greater than 0, while in other spatial regions, there will be a situation where the influence difference in some analysis groups is less than 0; in addition, the closer the distance to the discharge position, the greater the corresponding amplitude reduction effect, that is, the larger the value of the influence difference, based on this, the possibility of discharge is analyzed.

[0070] Furthermore, in some embodiments of the present invention, the degree of discharge possibility in a spatial region is determined based on all influence differences in different analysis groups in the spatial region and the discharge influence values ​​of the microphones, including: calculating the sum of all influence differences in the same analysis group to obtain the group influence index of the analysis group; performing negative correlation mapping and normalization on the standard deviation of the group influence indicators of all analysis groups in the same spatial region to obtain the regional influence index; calculating the mean of the discharge influence values ​​of all microphones in the spatial region to obtain the regional discharge mean; and normalizing the product value of the regional discharge mean and the regional influence index as the discharge possibility degree of local abnormal discharge in the spatial region.

[0071] Among them, the standard deviation of the group influence index is negatively correlated and normalized to obtain the regional influence index. The regional influence index represents the numerical consistency of different analysis groups in the spatial region. That is, the larger the value of the regional influence index, the more similar the amplitude changes of different analysis groups in the spatial region are, and the more consistent it is with the characteristics of amplitude changes caused by the central position, and the greater the possibility of discharge.

[0072] Combined with the above analysis, the larger the value of the influence difference, the greater the corresponding amplitude reduction effect, which indicates that the discharge position is closer. In the embodiment of the present invention, the product value of the direct regional discharge mean and the regional influence index is normalized and used as the discharge possibility degree of local abnormal discharge in the spatial region.

[0073] S104: According to the degree of discharge possibility, an abnormal discharge region where local abnormal discharge occurs is screened from the spatial region.

[0074] As can be seen from the analysis in step S103, a larger value for the discharge likelihood indicates a greater likelihood of local abnormal discharge occurring in the spatial region, and screening can be performed based on the discharge likelihood. Furthermore, in some embodiments of the present invention, screening spatial regions based on the discharge likelihood to identify abnormal discharge regions where local abnormal discharge occurs includes identifying spatial regions where the discharge likelihood exceeds a preset discharge threshold as abnormal discharge regions.

[0075] The preset discharge threshold is a threshold value for the likelihood of discharge. In the embodiment of the present invention, the preset discharge threshold can be, for example, 0.8. This means that a spatial region with a likelihood of discharge greater than 0.8 is considered an abnormal discharge region. This allows the discharge location to be precisely located within a specific spatial region, facilitating subsequent analysis directly within that spatial region.

[0076] During subsequent analysis, when the system detects a discharge, it sends the location code corresponding to the discharge area and the potential level of discharge to the staff's communication device. Staff then conduct a detailed inspection of the abnormal discharge area to determine the cause of the discharge, such as overload, overvoltage, poor contact, or aging. They then address the cause with appropriate solutions, such as replacing insulation materials if aging or damage is detected. The audio signals obtained by each pickup corresponding to different discharge causes are also stored in a database in a table format, which can be used as a reference for identifying the cause of the discharge in the event of a subsequent fault.

[0077] The present invention obtains the spectrum data collected by each microphone at different ring network box powers as the data basis, and then performs spectrum noise analysis based on the numerical distribution of the maximum amplitude at different powers to filter out the noise frequency band and obtain the discharge frequency band. This part is mainly based on the characteristics that the noise change does not change with the power, while the discharge change changes with the power, and accurately analyzes the discharge frequency band; then, through the amplitude changes of different microphones in the analysis group, discharge analysis is performed to determine the discharge possibility of local abnormal discharge in the spatial area. This part determines the accurate and reliable discharge possibility based on the amplitude change characteristics generated by the discharge position for different microphones in space; finally, according to the discharge possibility, the abnormal discharge area where local abnormal discharge occurs is screened from the spatial area. In summary, the embodiment of the present invention determines a more accurate abnormal discharge area through noise analysis and spatial amplitude change analysis, thereby improving the accuracy of the ring network box health status detection.

[0078] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0079] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A health status safety detection method for a ring network box, characterized in that: A plurality of pickups are evenly arranged in a ring network box, and the method comprises: Obtaining spectrum data collected by each microphone at different ring network box powers, performing curve fitting on the spectrum data of each microphone at each power to obtain a spectrum curve, segmenting the spectrum curve according to minimum values, and dividing the spectrum curve into different analysis frequency bands; In the same analysis frequency band, the probability of the analysis frequency band belonging to the noise frequency band is determined based on the numerical distribution of the maximum amplitude values ​​at different powers; the noise frequency band is screened and eliminated based on the noise probability to obtain the discharge frequency band; The eight closest pickups are grouped into a spatial region. The center of the region is connected to the pickups, and rays are extended outward. A preset number of pickups on the ray closest to the region center are taken as an analysis group. Based on the amplitude changes of different pickups in the same analysis group in each discharge frequency band, the possibility of local abnormal discharge in the spatial region is determined. According to the degree of discharge possibility, an abnormal discharge region where local abnormal discharge occurs is screened from the spatial region; Based on the amplitude changes of different pickups in the same analysis group in each discharge frequency band, the possibility of local abnormal discharge in the spatial area is determined, including: The pickups are divided into front and back according to the distance from the starting point of the ray. The closer the distance, the closer the pickup is to the front. Calculate the average amplitude of the overall discharge frequency band of each pickup at all powers as the discharge impact value of the corresponding pickup; In the same analysis group and the same discharge frequency band, the difference in discharge impact values ​​between the first pickup and the second pickup of the two closest pickups is taken as the impact difference; Determine the discharge possibility of the spatial region based on all the influence differences in different analysis groups in the spatial region and the discharge influence values ​​of the pickups; Based on all the influence differences in different analysis groups in the spatial region and the discharge influence values ​​of the pickups, the possible degree of discharge in the spatial region is determined, including: Calculate the sum of all impact differences in the same analysis group to obtain the group impact index of the analysis group; The standard deviations of the group impact indicators of all analysis groups in the same spatial region were negatively correlated and normalized to obtain the regional impact indicator; Calculate the mean of the discharge influence values ​​of all pickups in the spatial region to obtain the regional discharge mean; The product of the regional discharge mean and the regional impact index is normalized and used as the discharge possibility degree of local abnormal discharge in the spatial region.

2. A health status safety detection method for a ring main box according to claim 1, characterized in that: In the ring network box, each interval of a preset height is divided into a layer, and a*a pickups are evenly arranged in a grid form on each layer, where a is a positive integer and a is greater than or equal to 5.

3. A health status safety detection method for a ring main box according to claim 1, characterized in that: Performing curve fitting on the spectrum data of each pickup at each power to obtain a spectrum curve, including: The Savitzky-Golay smoothing algorithm is used with the window size set to 7 and the order set to 2. The spectrum data obtained under each power condition of the ring network box is smoothed, and the spectrum curve is obtained by curve fitting.

4. A health status safety detection method for a ring main box according to claim 1, characterized in that: The spectrum curve is segmented according to the minimum value, and the spectrum curve is divided into different analysis frequency bands, including: The spectrum curve between the two nearest minimum values ​​is regarded as an analysis frequency band.

5. The health status safety detection method for a ring main box according to claim 1, characterized in that: Based on the numerical distribution of the maximum amplitude at different power levels, determine the likelihood that the analysis frequency band belongs to the noise band, including: Determine the standard deviation of the maximum amplitude values ​​of the spectrum curves of all pickups at all powers in the same analysis frequency band as the amplitude dispersion characteristic index; Negative correlation mapping is performed on the amplitude discrete characteristic index and normalized to obtain the noise possibility degree that the analysis frequency band belongs to the noise frequency band.

6. A health status safety detection method for a ring main box according to claim 1, characterized in that: According to the possible degree of noise, the noise frequency band is screened and eliminated to obtain the discharge frequency band, including: The frequency band in which the noise level is likely to be greater than a preset noise threshold is used as the noise frequency band; The noise frequency band is deleted to obtain the remaining discharge frequency band.

7. A health status safety detection method for a ring main box according to claim 1, characterized in that: According to the discharge possibility degree, an abnormal discharge area where local abnormal discharge occurs is screened from the spatial area, including: The spatial region where the discharge possibility is greater than a preset discharge threshold is regarded as an abnormal discharge region.

8. The health status safety detection method for a ring main box according to claim 1, characterized in that: The preset number is 3.

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