A time-frequency characteristic-based recursive filtering parallel partial discharge detection method and system, computer device and storage medium

Abstract

The application relates to the technical field of partial discharge detection, and discloses a recursive filtering parallel partial discharge detection method and system based on time-frequency characteristics, computer equipment and a storage medium, wherein through the time-frequency characteristics of a partial discharge signal, after a series of collection, conversion, filtering, detection and analysis operations, efficient identification and positioning of the partial discharge can be automatically realized, the method and system are suitable for general detection of various partial discharges, have good adaptability and high reliability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of partial discharge detection, and in particular to a recursive filtering parallel partial discharge detection method and system based on time-frequency characteristics, a computer device and a storage medium. BACKGROUND

[0002] Partial discharge is an unwanted phenomenon that occurs on high voltage lines or cables. From a physical point of view, it is a leakage of electric charge caused by some kind of insulation weakness. Partial discharge causes energy loss, but most importantly, it causes the insulation to gradually age. The worse the insulation performance, the better the conditions for subsequent partial discharges. Therefore, the trend of partial discharge intensity can cause a chain reaction that eventually leads to complete insulation breakdown and short circuit in a relatively short period of time. It is therefore necessary to detect the presence of partial discharge at an early stage before complete insulation breakdown occurs.

[0003] There are several principles for partial discharge detection. Most of them are based on the partial discharge appearance in the voltage signal. In this case, partial discharge appears as a transient event with sudden onset and exponential decay. The key to some of the current mainstream methods is to detect the transient superimposed on the reference voltage signal, and there are countless papers that use discrete wavelet transform (DWT). DWT can indeed be successfully used to detect known-shaped transients, but when a general algorithm is needed to detect various types of partial discharge, it fails. The problem complexity is not only how to correctly detect the transient event, but also how to distinguish it from noise, because noise is often contaminated by similar transient events.

[0004] The above information is given as background information only to assist with an understanding of the present disclosure, and should not be taken as an acknowledgement or admission that any of the above information forms part of the prior art with respect to the present disclosure. SUMMARY

[0005] The present application provides a recursive filtering parallel partial discharge detection method and system based on time-frequency characteristics, a computer device and a storage medium to solve the problems in the prior art.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0007] In a first aspect, the present application provides a recursive filtering parallel partial discharge detection method based on time-frequency characteristics, which comprises:

[0008] Collecting an analog voltage signal on an electrical device and converting it into a digital signal;

[0009] Band-pass filtering the digital signal to eliminate noise and extract signal components related to partial discharge;

[0010] performing initial detection to identify partial discharge events;

[0011] two auxiliary signals, Aux1 and Aux2, are calculated from the band-pass filtered signal to meet the needs of initial detection and refined detection;

[0012] Aux1 and Aux2 are analyzed to detect non-stationary components in the filtered signal, and the results are stored in a spatial pool;

[0013] The initial detection time of the partial discharge is determined according to the time when Aux1 exceeds a set threshold;

[0014] The time of the start of the discharge is refined according to the local maximum value time of Aux2, that is, the accurate time point before and after the initial detection time is found;

[0015] The frequency spectrum part related to the partial discharge is separated from the voltage signal stored in the spatial pool.

[0016] Further, in the recursive filtering and parallel partial discharge detection method based on time-frequency characteristics, the step of collecting analog voltage signals on the electrical equipment and converting them into digital signals comprises:

[0017] Analog voltage signals on the electrical equipment are collected using the voltage sensing principle;

[0018] The collected analog voltage signals are converted into digital signals by a high sampling rate analog-to-digital converter.

[0019] Further, in the recursive filtering and parallel partial discharge detection method based on time-frequency characteristics, in the step of band-pass filtering the digital signal to eliminate noise and extract signal components related to partial discharge, the frequency range of the band-pass filtering is set to 400 kHz to 1.5 MHz.

[0020] Further, in the recursive filtering and parallel partial discharge detection method based on time-frequency characteristics, the method further comprises:

[0021] Output the detection results, including the detection signal and positioning information of the partial discharge.

[0022] In a second aspect, the present application provides a recursive filtering and parallel partial discharge detection system based on time-frequency characteristics, which comprises:

[0023] A signal acquisition module for collecting analog voltage signals on the electrical equipment and converting them into digital signals;

[0024] A signal filtering module for band-pass filtering the digital signal to eliminate noise and extract signal components related to partial discharge;

[0025] a discharge identification module for initial detection to identify partial discharge events;

[0026] an auxiliary signal module for calculating two auxiliary signals, Aux1 and Aux2, from the band-pass filtered signal to meet the needs of initial detection and refined detection;

[0027] an analysis storage module for analyzing Aux1 and Aux2, detecting non-steady components in the filtered signal, and storing the results in a spatial pool;

[0028] an initial time module for determining the initial detection time of partial discharge according to the time when Aux1 exceeds a set threshold;

[0029] a precise time module for refining the time of discharge initiation according to the time of local maximum of Aux2, i.e., finding the precise time point before and after the initial detection time;

[0030] a signal separation module for separating the frequency spectrum part related to partial discharge from the voltage signal stored in the spatial pool.

[0031] Further, in the recursive filtering parallel partial discharge detection system based on time-frequency characteristics, the signal acquisition module is specifically configured to:

[0032] acquire analog voltage signals on the electrical equipment by using the voltage sensing principle;

[0033] convert the acquired analog voltage signals into digital signals by using an analog-to-digital converter with a high sampling rate.

[0034] Further, in the recursive filtering parallel partial discharge detection system based on time-frequency characteristics, the frequency range of the band-pass filter is set to 400 kHz to 1.5 MHz.

[0035] Further, in the recursive filtering parallel partial discharge detection system based on time-frequency characteristics, the system further includes a result output module configured to:

[0036] output the detection results, including the detection signal and the positioning information of the partial discharge.

[0037] In a third aspect, the present application provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor implements the recursive filtering parallel partial discharge detection method based on time-frequency characteristics provided in the first aspect when executing the computer program.

[0038] In a fourth aspect, the present application provides a storage medium comprising computer executable instructions executed by a computer processor to implement the time-frequency characteristic based recursive filtering parallel partial discharge detection method according to the first aspect.

[0039] Compared with the prior art, the present application has the following beneficial effects:

[0040] The time-frequency characteristic based recursive filtering parallel partial discharge detection method, system, computer device and storage medium provided by the present application can automatically realize efficient identification and positioning of partial discharge after a series of collection, conversion, filtering, detection and analysis operations according to the time-frequency characteristics of the partial discharge signal, are suitable for general detection of various partial discharges, have good adaptability and high reliability.

[0041] The present application has other characteristics and advantages, which will be apparent or will be described in detail in the accompanying drawings and subsequent specific embodiments incorporated herein, which together serve to explain the specific principles of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the accompanying drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0043] Figure 1 is a flowchart of a time-frequency characteristic based recursive filtering parallel partial discharge detection method provided by the first embodiment of the present application;

[0044] Figure 2 is a laboratory non-periodic partial discharge example diagram;

[0045] Figure 3 is a field data partial discharge example diagram;

[0046] Figure 4 is a raw signal and corresponding filtered signal diagram;

[0047] Figure 5 is an auxiliary signal and original measurement signal, and the detected partial discharge starting point is highlighted;

[0048] Figure 6 is a corona type partial discharge detection result example diagram;

[0049] Figure 7is a significant partial discharge detection result example diagram;

[0050] Figure 8 is a functional module schematic diagram of a recursive filtering parallel partial discharge detection method system based on time-frequency characteristics provided by the second embodiment of the application;

[0051] Figure 9 is a structural schematic diagram of a computer device provided by the third embodiment of the application. DETAILED DESCRIPTION

[0052] To explain the possible application scenarios, technical principles, specific schemes that can be implemented, and the purposes and effects that can be achieved of the present application, the specific embodiments listed below are described in detail in conjunction with the accompanying drawings. The embodiments described in this document are only used to more clearly illustrate the technical solutions of the present application, and therefore only serve as examples, and cannot limit the protection scope of the present application.

[0053] In this document, the term "embodiment" means that the specific features, structures or characteristics described in conjunction with the embodiment can be included in at least one embodiment of the present application. The term "embodiment" appearing at various places in the specification does not necessarily refer to the same embodiment, and does not particularly limit the independence or association between other embodiments. In principle, in the present application, as long as there is no technical contradiction or conflict, the technical features mentioned in each embodiment can be combined in any way to form a corresponding implementable technical solution.

[0054] Unless otherwise defined, the meanings of the technical terms used in this document are the same as those commonly understood by those skilled in the art to which the present application belongs; the use of related terms in this document is only for the purpose of describing specific embodiments, and is not intended to limit the present application.

[0055] In the description of the present application, the phrase "and / or" is a description of the logical relationship between the objects, which means that there can be three relationships, for example, A and / or B, which means that there are three cases: A exists, B exists, and A and B exist at the same time. In addition, the character " / " in this document generally represents that the associated objects before and after are a "or" logical relationship.

[0056] In the present application, terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual quantity, primary and secondary or order relationship between the entities or operations.

[0057] In the present application, the terms "comprise", "contain", "have", or other similar phrases as used in a clause are intended to encompass non-exclusive inclusion, and these phrases do not exclude the possibility that additional elements can be present in the process, method or product comprising the stated elements, so that the process, method or product comprising a series of elements can not only include those defined elements, but also include other elements not explicitly listed, or also include elements inherent to such process, method or product.

[0058] In the present application, the terms "greater than", "less than", "exceed" and the like are understood as not including the number itself; the terms "above", "below", "within" and the like are understood as including the number itself. In addition, in the description of the embodiments of the present application, the meaning of "multiple" is more than two (including two), and similar expressions related to "multiple" are also understood in this way, for example, "multiple groups", "multiple times" and the like, unless otherwise explicitly specified.

[0059] In the description of the embodiments of the present application, the spatial-related expressions used, such as "center", "lengthwise", "transverse", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "vertical", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", and the like, indicate the orientation or positional relationship based on the orientation or positional relationship shown in the specific embodiments or the drawings, and are only for the convenience of describing the specific embodiments of the present application or for the reader to understand, and do not indicate or imply that the indicated device or component must have a specific position, a specific orientation, or be constructed or operated in a specific orientation, and therefore cannot be understood as a limitation on the embodiments of the present application.

[0060] Unless otherwise explicitly specified or limited, in the description of the embodiments of the present application, the terms "mount", "connect", "connect", "fix", "set", and the like should be understood broadly. For example, the "connection" can be a fixed connection, or a detachable connection, or an integral setting; it can be a mechanical connection, or an electrical connection, or a communication connection; it can be directly connected, or indirectly connected through an intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art to which the present application belongs, the specific meaning of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0061] Embodiment one

[0062] In view of the defects in the prior art, the applicant, based on years of rich practical experience and professional knowledge in this field, and combined with the use of theories, actively studies and innovates to create a technology that can solve the defects in the prior art. After continuous research, design, and repeated trial samples and improvements, the present invention is finally created, which has practical value.

[0063] Please refer to Figure 1 A flowchart of a recursive filtering and parallel partial discharge detection method based on time-frequency characteristics is provided for the first embodiment of the present invention. The method specifically includes the following steps:

[0064] S101, collect the analog voltage signal on the electrical equipment and convert it into a digital signal.

[0065] It should be noted that this step is to accurately collect the analog voltage signal from the electrical equipment, such as high-voltage lines or cables, and then use advanced analog-to-digital conversion technology to efficiently convert these analog signals into digital signals for subsequent digital signal processing.

[0066] In one embodiment of the present embodiment, the step S101 can be further refined to include the following content:

[0067] Collecting the analog voltage signal on the electrical equipment using the voltage sensing principle;

[0068] Converting the collected analog voltage signal into a digital signal through a high sampling rate analog-to-digital converter.

[0069] It should be noted that first, using the voltage sensing principle, carefully arrange the voltage sensor at the key position of the electrical equipment, so as to accurately collect the analog voltage signal generated on the electrical equipment. The core of this step is to ensure good contact between the voltage sensor and the electrical equipment, as well as the sensitivity and accuracy of the sensor, to ensure that the collected analog voltage signal can truly reflect the operating state of the electrical equipment.

[0070] Then, by equipping with a high sampling rate analog-to-digital converter (ADC), the carefully collected analog voltage signal is efficiently and accurately digitized. In this process, the choice of high sampling rate is crucial, as it can ensure that the detailed information of the signal is completely preserved during the conversion process, providing a high-quality data basis for subsequent digital signal processing. At the same time, the performance of the analog-to-digital converter also needs to meet the corresponding standards to ensure the accuracy and stability of the conversion process, avoiding the introduction of additional noise or errors.

[0071] In summary, by refining step S101, accurate collection and efficient conversion of the analog voltage signal on the electrical equipment are achieved, laying a solid foundation for subsequent signal processing, detection and analysis work.

[0072] S102. Bandpass filter is applied to the digital signal to eliminate noise and extract signal components related to partial discharge.

[0073] It should be noted that this step involves performing bandpass filtering on the acquired digital signal. The main purpose of this step is to effectively eliminate noise components in the signal and accurately extract signal components closely related to partial discharge phenomena, laying a solid foundation for subsequent detection and analysis.

[0074] In one embodiment of this invention, a specific frequency range is set for the bandpass filtering step to ensure accurate extraction of signal components related to partial discharge. Specifically, the frequency range of the bandpass filtering is set to 400 kHz to 1.5 MHz.

[0075] This frequency range was chosen based on a thorough understanding and analysis of the characteristics of partial discharge signals. Partial discharge typically generates electromagnetic waves within a specific frequency range, and 400 kHz to 1.5 MHz is the key interval within this range. By performing bandpass filtering within this frequency range, noise interference can be effectively eliminated, while signal components closely related to partial discharge can be accurately extracted.

[0076] Furthermore, the setting of this frequency range also takes into account the actual operating environment and signal transmission characteristics of the electrical equipment. In the complex and ever-changing operating environment of electrical equipment, signals may be subject to interference and influence from various factors. Setting a reasonable bandpass filter frequency range can reduce these interferences to a certain extent and improve the accuracy and reliability of signal detection.

[0077] In summary, by setting the bandpass filter frequency range from 400 kHz to 1.5 MHz in this embodiment, accurate extraction of partial discharge signals was achieved, providing strong support for subsequent signal analysis, detection, and localization.

[0078] From a signal processing perspective, there are many types of partial discharges, which differ in terms of discharge duration, rise slope, and overall shape. By selecting appropriate sensors to capture the oscillating partial discharge response from field data, it can be seen that additional low-frequency and high-frequency noise appears in the signal when switching from laboratory data to field data. Figure 2 This is an example diagram of a non-periodic partial discharge in the laboratory. Figure 3 This is an example diagram of partial discharge in field data. Partial discharge only manifests as local differences in the nature of signal oscillation. A suitable bandpass filter is used to separate the desired frequency band and remove other high-frequency and low-frequency noise components, retaining the frequency band that best represents the partial discharge response signal. Figure 4The original signal and the corresponding filtered signal are shown in the figure. The result of band-pass filtering is shown in Figure 4 The partial discharge response after filtering is very clear, while it is hardly visible in the original signal.

[0079] S103, initial detection is performed to identify partial discharge events.

[0080] It should be noted that the core task of this stage is to preliminarily identify and confirm the occurrence of partial discharge events, providing preliminary judgment basis for subsequent refinement detection. Although the accuracy in time, i.e. frequency, will be lower, important data may be lost, but the basic changes can be identified.

[0081] S104, two auxiliary signals, Aux1 and Aux2, are calculated from the band-pass filtered signal to meet the needs of initial detection and refinement detection.

[0082] It should be noted that after confirming the partial discharge event, two key auxiliary signals, Aux1 and Aux2, are further calculated from the band-pass filtered signal. The generation of these two auxiliary signals is to meet the diversified needs of the initial detection stage and the subsequent refinement detection stage, to ensure the accuracy and comprehensiveness of the detection process.

[0083] S105, the Aux1 and Aux2 are analyzed to detect the non-stationary components in the filtered signal, and the results are stored in the spatial pool.

[0084] It should be noted that this step is an in-depth analysis of Aux1 and Aux2. The main goal of this step is to detect the non-stationary components in the filtered signal, which are crucial for determining the precise time and characteristics of partial discharge. After analysis, the results are properly stored in the spatial pool for subsequent processing.

[0085] S106, the initial detection time of partial discharge is determined according to the time when Aux1 exceeds the set threshold.

[0086] It should be noted that this step is to determine the initial detection time of partial discharge according to the time point when Aux1 signal exceeds the set threshold. This step provides an important time reference for the subsequent accurate time positioning.

[0087] S107, the time of discharge start is refined according to the local maximum value time of Aux2, i.e. the accurate time point before and after the initial detection time is found.

[0088] It should be noted that this step is to further utilize the local maximum time of Aux2 signal to refine the discharge start time. Through this step, the key time point before and after the initial detection time can be accurately found, so as to realize accurate capture of the local discharge occurrence time.

[0089] In Figure 5 , the red asterisk in the auxiliary signal 1 represents the initial detection time of the partial discharge. The black asterisk in the auxiliary signal 2 represents the refined detection time. Figure 5 The blue asterisk in the original signal in the second figure also represents this time. It can be clearly seen that the algorithm can accurately determine the arrival time of the partial discharge.

[0090] Figure 6 The first example in shows the corona type partial discharge. The result of the partial discharge automatic detection algorithm is represented by a blue asterisk. It can be seen that the result is exactly at the starting point of each corona pulse. The characteristic of corona discharge is that there are a large number of rapid and continuous pulses, so the dead time of the detection algorithm must be as short as possible. Otherwise, the algorithm may miss some pulses, resulting in inaccurate results.

[0091] Figure 7 The second example in shows the obvious aperiodic partial discharge response superimposed on the underlying noise signal. It can be seen that the determined detection time is exactly in line with the starting time of the rising edge of the partial discharge. It should be noted that the location of this measurement is different from the previous one, but the detection method can still provide correct results. In fact, the only change is the frequency band of the band-pass filter, which is related to the measurement location.

[0092] S108, separate the frequency spectrum part related to the partial discharge from the voltage signal stored in the spatial pool.

[0093] It should be noted that this step is to separate and extract the frequency spectrum part directly related to the partial discharge from the voltage signal stored in the spatial pool. The completion of this step marks the full start of the time-frequency characteristic analysis of the partial discharge signal, and provides detailed data support for subsequent analysis and diagnosis.

[0094] In one specific implementation manner of the embodiment, in addition to the steps described before, an important link, i.e. outputting the detection result, is added after step S108. The specific content of this step is as follows:

[0095] After completing all signal acquisition, conversion, filtering, detection and analysis operations, the system outputs detailed detection results. These results include the detection signals of partial discharge, which are obtained after accurate processing and identification, and can clearly reflect the characteristics and state of partial discharge. At the same time, the detection results also include positioning information, i.e. the specific location of partial discharge in electrical equipment. These information is obtained through time-frequency analysis, feature extraction and matching of signals, etc., and has high accuracy and reliability.

[0096] The output of the detection results can be diverse, such as real-time display of the detection results on the display screen, or printing of the detection results in the form of reports for technical personnel to refer to and analyze. In addition, the detection results can also be transmitted and shared remotely through network and other communication means, so as to further analyze and process at different places and times.

[0097] In summary, by adding the step of outputting the detection results, we can intuitively present the detection signals and positioning information of partial discharge, and provide strong technical support and decision basis for technical personnel. At the same time, this step also reflects the practicality and application value of the invention in the field of partial discharge detection.

[0098] Although time-frequency, filtering, signal and other terms are used more in this application, the possibility of using other terms is not excluded. The use of these terms is only to facilitate the description and explanation of the essence of the invention; any additional limitation is contrary to the spirit of the invention.

[0099] The embodiment of the application provides a recursive filtering parallel partial discharge detection method based on time-frequency characteristics. Through the time-frequency characteristics of the partial discharge signal, a series of acquisition, conversion, filtering, detection and analysis operations can be automatically realized to efficiently identify and locate the partial discharge, which is not only suitable for various general detection scenes of partial discharge, but also shows excellent adaptability and high reliability, and provides strong technical support for fault diagnosis and maintenance of electrical equipment.

[0100] Embodiment two

[0101] Please refer to Figure 8 The embodiment two of the application provides a recursive filtering parallel partial discharge detection system based on time-frequency characteristics, which comprises:

[0102] The signal acquisition module 201 is used for acquiring analog voltage signals on the electrical equipment and converting them into digital signals;

[0103] The signal filtering module 202 is used for band-pass filtering the digital signals to eliminate noise and extract signal components related to partial discharge;

[0104] The discharge identification module 203 is used for initial detection to identify partial discharge events;

[0105] The auxiliary signal module 204 is used for calculating two auxiliary signals, Aux1 and Aux2, from the band-pass filtered signals to meet the needs of initial detection and refined detection;

[0106] The analysis storage module 205 is used for analyzing the Aux1 and Aux2, detecting the non-steady-state components in the filtered signals, and storing the results in a spatial pool;

[0107] The initial time module 206 is used for determining the initial detection time of the partial discharge according to the time when the Aux1 exceeds a set threshold;

[0108] The accurate time module 207 is used for refining the time of the discharge start according to the local maximum time of the Aux2, i.e., finding the accurate time point before and after the initial detection time;

[0109] The signal separation module 208 is used for separating the frequency spectrum part related to the partial discharge from the voltage signals stored in the spatial pool.

[0110] Preferably, the signal collection module 201 is specifically used for:

[0111] Collecting analog voltage signals on the electrical equipment by using the voltage sensing principle;

[0112] Converting the collected analog voltage signals into digital signals by using an analog-to-digital converter with a high sampling rate.

[0113] Preferably, the frequency range of the band-pass filtering is set to 400 kHz to 1.5 MHz.

[0114] Preferably, the system further comprises a result output module, which is used for:

[0115] Outputting the detection results, including the detection signals and positioning information of the partial discharge.

[0116] The parallel partial discharge detection system based on the recursive filtering and time-frequency characteristics provided by the embodiments of the present application can automatically realize efficient identification and positioning of the partial discharge after a series of collection, conversion, filtering, detection and analysis operations according to the time-frequency characteristics of the partial discharge signals, is suitable for general detection of various partial discharges, has good adaptability and high reliability.

[0117] The above system can execute the method provided by any embodiment of the present application, has the corresponding function modules and beneficial effects of executing the method.

[0118] Embodiment Three

[0119] Figure 9 FIG. 1 illustrates a diagram of a computer device according to an embodiment of the present application. Figure 9 FIG. 2 illustrates a diagram of a computer device according to an embodiment of the present application. Figure 9 The computer device 12 shown is merely one example and should not be taken as limiting the scope of functionality or use of embodiments of the present application.

[0120] As shown, the computer device 12 is in the form of a general-purpose computer device. Components of the computer device 12 can include, but are not limited to, one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components, including the system memory 28 to the processing unit 16. Figure 9 The bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics bus, a processor or local bus using any of a variety of bus architectures.

[0121] The computer device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by the computer device 12 and includes both volatile and non-volatile media, removable and non-removable media.

[0122] The system memory 28 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The computer device 12 can further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, a storage system 34 can be provided for reading from and writing to non-removable, non-volatile magnetic media (e.g., a "hard drive").

[0123] Although not shown, a magnetic disk drive can also be used to read from and write to a removable, non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive can be used to read from and write to a removable, non-volatile optical disk (e.g., a CD-ROM, DVD-ROM or other optical media). In such instances, each can be connected to the bus 18 by one or more data media interfaces. The memory 28 can include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the present application. Figure 9 Figure 9 The bus 18 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics bus, a processor or local bus using any of a variety of bus architectures.

[0124] ​Program / utility 40 having a set of programs / modules 42 can be stored in memory 28 by way of example, such programs / modules 42 include an operating system, one or more applications, other program modules, and program data, each of which or a combination thereof, can include implementation of a networking environment. Programs 42 generally carry out the functions and / or methodologies of embodiments of the application as described herein.

[0125] Computer device 12 can also communicate with one or more external devices 14 such as a keyboard or pointing device, a display 24, etc.; one or more devices that enable a user to interact with computer device 12; and / or any devices (e.g., network card, modem, etc.) that enable computer device 12 to communicate with one or more other computing devices. Such communication can occur via input / output (I / O) interface(s) 22. Still yet, computer device 12 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or the Internet) through network adapter 20. As an example, network adapter 20 can include a modem, a network card (wireless or wired), or other well-known interface devices. It is noted that these devices can be external to computer device 12, such as in the case of a network card, or can be internal to computer device 12, such as in the case of a modem or other device. Figure 9 It is noted that other hardware and / or software modules that can be used in conjunction with computer device 12 can also be utilized with computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival storage systems, etc.

[0126] Processing unit 16 performs various function applications and data processing by running programs stored in system memory 28, such as implementing the time-frequency characteristic based recursive filtering parallel partial discharge detection method provided by embodiments of the present application.

[0127] Embodiment four

[0128] Embodiment four of the present application provides a computer readable storage medium, which stores computer executable instructions, the instructions being executed by a processor to implement the time-frequency characteristic based recursive filtering parallel partial discharge detection method provided by all embodiments of the present application.

[0129] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0130] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0131] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0132] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0133] Finally, it should be noted that although the above embodiments have been described in the text and drawings of this application, this should not limit the scope of patent protection of this application. Any technical solutions that are based on the essential concept of this application and utilize the content described in the text and drawings of this application, resulting in equivalent structural or procedural substitutions or modifications, as well as the direct or indirect application of the technical solutions of the above embodiments to other related technical fields, are all included within the scope of patent protection of this application.

Claims

1. A time-frequency characteristic-based recursive filtering parallel partial discharge detection method, characterized in that, The method comprises: collecting analog voltage signals on the electrical equipment and converting them into digital signals; band-pass filtering the digital signals to eliminate noise and extract signal components related to partial discharge; performing initial detection to identify partial discharge events; calculating two auxiliary signals, Aux1 and Aux2, from the band-pass filtered signals to meet the needs of initial detection and refined detection; analyzing Aux1 and Aux2 to detect non-stationary components in the filtered signals and storing the results in a spatial pool; determining the initial detection time of partial discharge according to the time when Aux1 exceeds a set threshold; refining the time when discharge starts according to the local maximum time of Aux2, i.e. finding the accurate time point before and after the initial detection time; separating the frequency spectrum part related to partial discharge from the voltage signals stored in the spatial pool.

2. The time-frequency characteristic based recursive filtering parallel partial discharge detection method according to claim 1, characterized in that, The step of collecting analog voltage signals on the electrical equipment and converting them into digital signals comprises: collecting analog voltage signals on the electrical equipment using voltage sensing principles; converting the collected analog voltage signals into digital signals through an analog-to-digital converter with a high sampling rate.

3. The time-frequency characteristic based recursive filtering parallel partial discharge detection method according to claim 1, wherein, In the step of band-pass filtering the digital signals to eliminate noise and extract signal components related to partial discharge, the frequency range of band-pass filtering is set to 400 kHz to 1.5 MHz.

4. The time-frequency characteristic based recursive filtering parallel partial discharge detection method according to claim 1, wherein, The method further comprises: outputting the detection results, including the detection signals and positioning information of partial discharge.

5. A time-frequency characteristic based recursive filtering parallel partial discharge detection system, characterized in that, The system comprises: a signal collection module for collecting analog voltage signals on the electrical equipment and converting them into digital signals; a signal filtering module for band-pass filtering the digital signals to eliminate noise and extract signal components related to partial discharge; a discharge identification module for performing initial detection to identify partial discharge events; an auxiliary signal module for calculating two auxiliary signals, Aux1 and Aux2, from the band-pass filtered signals to meet the needs of initial detection and refined detection; an analysis and storage module for analyzing Aux1 and Aux2 to detect non-stationary components in the filtered signals and storing the results in a spatial pool; an initial time module for determining the initial detection time of partial discharge according to the time when Aux1 exceeds a set threshold; an accurate time module for refining the time when discharge starts according to the local maximum time of Aux2, i.e. finding the accurate time point before and after the initial detection time; a signal separation module for separating the frequency spectrum part related to partial discharge from the voltage signals stored in the spatial pool.

6. The recursive filter based time-frequency feature based partial discharge detection system of claim 5, wherein, The signal collection module is specifically used for: collecting analog voltage signals on the electrical equipment using voltage sensing principles; converting the collected analog voltage signals into digital signals through an analog-to-digital converter with a high sampling rate.

7. The recursive filter based time-frequency feature based partial discharge detection system of claim 5, wherein, The frequency range of band-pass filtering is set to 400 kHz to 1.5 MHz.

8. The recursive filter based time-frequency feature based partial discharge detection system of claim 5, wherein, The system further comprises a result output module for: outputting the detection results, including the detection signals and positioning information of partial discharge. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8 when the computer program is executed by the processor. The processor implements the time-frequency characteristic-based recursive filtering parallel partial discharge detection method of any one of claims 1-4 when executing the computer program.

10. A storage medium containing computer-executable instructions, wherein: The computer executable instructions are executed by a computer processor to implement the time-frequency characteristic-based recursive filtering parallel partial discharge detection method of any one of claims 1-4.

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