Recursive filtering parallel partial discharge detection method and system based on time-frequency characteristics, computer equipment and storage medium

Abstract

The invention relates to the technical field of partial discharge detection, and discloses a recursive filtering parallel partial discharge detection method and system based on a time-frequency characteristic, computer equipment and a storage medium. According to the time-frequency characteristic of a partial discharge signal, after a series of acquisition, conversion, filtering, detection and analysis operations are carried out, the partial discharge signal is obtained; the method can automatically realize efficient identification and positioning of partial discharge, is suitable for general detection of various partial discharges, and is good in adaptability and high in reliability.

Description

Technical Field

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

[0002] Partial discharge is an unwanted phenomenon on high-voltage lines or cables. From a physical point of view, it is a charge leakage caused by a certain isolation weakness. Partial discharge leads to energy loss, but most importantly, it causes a gradual aging of the isolation device. The worse the isolation performance, the better the conditions for subsequent partial discharge. Therefore, the trend of the intensity of partial discharge may lead to a chain reaction, eventually causing complete isolation destruction and short circuit in a relatively short time. It is necessary to detect the presence of partial discharge at an early stage before complete isolation destruction occurs.

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

[0004] The above information is presented as background information only to assist with understanding the present disclosure and no determination or admission is made as to whether any of the above may be used as prior art with respect to the present disclosure. Summary of the invention

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

[0006] To achieve the above object, the present invention provides the following technical solutions:

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

[0008] Collect analog voltage signals from electrical equipment and convert them into digital signals;

[0009] Performing bandpass filtering on the digital signal to eliminate noise and extract signal components related to partial discharge;

[0010] Perform initial testing to identify partial discharge events;

[0011] Two auxiliary signals, Aux1 and Aux2, are calculated from the bandpass filtered signal to meet the needs of initial detection and refined detection;

[0012] Analyze the Aux1 and Aux2, detect the non-steady-state components in the filtered signal, and store the results in a spatial pool;

[0013] Determine the initial detection time of partial discharge according to the time when Aux1 exceeds the set threshold;

[0014] Refining the time of discharge start according to the local maximum time of Aux2, that is, finding the precise time point before and after the initial detection time;

[0015] The spectral portion related to partial discharge is separated from the voltage signal stored in the spatial pool.

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

[0017] Using the voltage sensing principle, collect analog voltage signals on electrical equipment;

[0018] The collected analog voltage signal is converted into a digital signal through a high sampling rate analog-to-digital converter.

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

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

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

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

[0023] A signal acquisition module is used to collect analog voltage signals on electrical equipment and convert them into digital signals;

[0024] A signal filtering module, used for performing bandpass filtering on the digital signal to eliminate noise and extract signal components related to partial discharge;

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

[0026] Auxiliary signal module, used to calculate two auxiliary signals, Aux1 and Aux2, from the bandpass filtered signal to meet the needs of initial detection and refined detection;

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

[0028] An initial time module, used to determine the initial detection time of partial discharge according to the time when Aux1 exceeds a set threshold;

[0029] A precise time module, used to refine the time of discharge start according to the local maximum time of Aux2, that is, to find the precise time point before and after the initial detection time;

[0030] The signal separation module is used to separate the frequency spectrum part related to partial discharge from the voltage signal stored in the spatial pool.

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

[0032] Using the voltage sensing principle, collect analog voltage signals on electrical equipment;

[0033] The collected analog voltage signal is converted into a digital signal through a high sampling rate analog-to-digital converter.

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

[0035] Furthermore, in the recursive filtering parallel partial discharge detection system based on time-frequency characteristics, the system also includes a result output module for:

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

[0037] In a third aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the recursive filtering parallel partial discharge detection method based on time-frequency characteristics as provided in the first aspect above is implemented.

[0038] In a fourth aspect, the present invention provides a storage medium comprising computer executable instructions, wherein the computer executable instructions are executed by a computer processor to implement the recursive filtering parallel partial discharge detection method based on time-frequency characteristics as provided in the first aspect above.

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

[0040] The present invention provides a recursive filtering parallel partial discharge detection method, system, computer equipment and storage medium based on time-frequency characteristics. According to the time-frequency characteristics of the partial discharge signal, after a series of acquisition, conversion, filtering, detection and analysis operations are performed, the method can automatically realize efficient identification and positioning of the partial discharge. The method is suitable for general detection of various partial discharges, has good adaptability and high reliability.

[0041] The present invention has other features and advantages, which will be apparent from or will be described in detail in the accompanying drawings and the following detailed description incorporated herein, which together serve to explain the specific principles of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative work.

[0043] Figure 1 It is a flow chart of a recursive filtering parallel partial discharge detection method based on time-frequency characteristics provided in the first embodiment of the present invention;

[0044] Figure 2 This is an example diagram of non-periodic partial discharge in the laboratory;

[0045] Figure 3 This is an example diagram of partial discharge from field data;

[0046] Figure 4 is the original signal and the corresponding filtered signal graph;

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

[0048] Figure 6 This is an example diagram of corona type partial discharge detection results;

[0049] Figure 7This is an example diagram of significant partial discharge detection results;

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

[0051] Fig. 9 It is a structural diagram of a computer device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0052] In order to explain in detail the possible application scenarios, technical principles, specific schemes that can be implemented, and the purposes and effects that can be achieved, the following is a detailed description of the specific embodiments listed in conjunction with the accompanying drawings. The embodiments described herein are only used to more clearly illustrate the technical solutions of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0053] Reference to "embodiment" herein means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present application. The term "embodiment" appearing in various places in the specification does not necessarily refer to the same embodiment, nor does it particularly limit its independence or association with other embodiments. In principle, in the present application, as long as there is no technical contradiction or conflict, the various technical features mentioned in the embodiments can be combined in any way to form a corresponding implementable technical solution.

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

[0055] In the description of this application, the term "and / or" is an expression used to describe the logical relationship between objects, indicating that three relationships may exist, for example, A and / or B, which means: A exists, B exists, and A and B exist at the same time. In addition, the character " / " in this article generally indicates that the objects before and after are in an "or" logical relationship.

[0056] In the present application, terms such as “first” and “second” are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship of quantity, priority or sequence between these entities or operations.

[0057] Without further limitations, in this application, the words "include", "comprises", "has" or other similar expressions used in the sentences are intended to cover non-exclusive inclusion. These expressions do not exclude the presence of additional elements in the process, method or product including the elements, so that the process, method or product including a series of elements may include not only those limited elements, but also other elements not explicitly listed, or also include elements inherent to such process, method or product.

[0058] In the present application, expressions such as "greater than", "less than", "exceed" and the like are understood to exclude the number itself; expressions such as "above", "below", "within" and the like are understood to include the number itself. In addition, in the description of the embodiments of the present application, "multiple" means more than two (including two), and similar expressions related to "multiple" are also understood in this way, such as "multiple groups", "multiple times", etc., unless otherwise clearly and specifically limited.

[0059] In the description of the embodiments of the present application, space-related expressions used, such as "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "vertical", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicate the orientation or position relationship based on the orientation or position relationship shown in the specific embodiments or drawings, and are only for the convenience of describing the specific embodiments of the present application or facilitating the reader's understanding, and do not indicate or imply that the referred 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 expressly specified or limited, in the description of the embodiments of the present application, the terms such as "install", "connect", "connect", "fix", "set", etc. used should be understood in a broad sense. For example, the "connection" can be a fixed connection, a detachable connection, or an integrated setting; it can be a mechanical connection, an electrical connection, or a communication connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium; it can be the internal connection of two elements or the interaction relationship between two elements. For technicians in the technical field to which the present application belongs, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0061] Embodiment 1

[0062] In view of the defects of the above-mentioned prior art, the applicant, based on many years of rich practical experience and professional knowledge in this field, and in conjunction with the application of theory, actively conducts research and innovation in the hope of creating a technology that can solve the defects of the prior art. After continuous research and design, and after repeated trial production and improvement, the present invention with real practical value was finally created.

[0063] Please refer to Figure 1 , is a flow chart of a recursive filtering parallel partial discharge detection method based on time-frequency characteristics provided in Embodiment 1 of the present invention. The method specifically comprises the following steps:

[0064] S101, collecting analog voltage signals on electrical equipment and converting them into digital signals.

[0065] It should be noted that this step is to accurately collect analog voltage signals from 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 an implementation of this embodiment, the step S101 may be further refined to include the following contents:

[0067] Using the voltage sensing principle, collect analog voltage signals on electrical equipment;

[0068] The collected analog voltage signal is converted into a digital signal through a high sampling rate analog-to-digital converter.

[0069] It should be noted that, first of all, by using the voltage induction principle, voltage sensors are carefully placed at key locations of electrical equipment, so as to accurately and correctly collect the analog voltage signals generated by 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, so as to ensure that the collected analog voltage signals can truly reflect the operating status of the electrical equipment.

[0070] Next, the analog voltage signal collected carefully is efficiently and accurately converted to digital form through an analog-to-digital converter (ADC) equipped with a high sampling rate. In this process, the selection of a high sampling rate is crucial, as it ensures that the detailed information of the signal during the conversion process is fully preserved, providing a high-quality data foundation for subsequent digital signal processing. At the same time, the performance of the analog-to-digital converter must also meet the corresponding standards to ensure the accuracy and stability of the conversion process and avoid introducing additional noise or errors.

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

[0072] S102: performing band-pass filtering on the digital signal to eliminate noise and extract signal components related to partial discharge.

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

[0074] In one implementation of this embodiment, a clear frequency range is set for the bandpass filtering step to ensure that the signal components related to partial discharge can be accurately extracted. Specifically, the frequency range of the bandpass filtering is set to 400 kHz to 1.5 MHz.

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

[0076] In addition, the setting of the frequency range also takes into account the actual operating environment and signal transmission characteristics of electrical equipment. In the complex and changeable operating environment of electrical equipment, the signal may be interfered and affected by various factors, and 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 is achieved, providing strong support for subsequent signal analysis, detection and positioning.

[0078] From a signal processing perspective, there are several types of partial discharges, which vary in discharge duration, rising edge slope, and overall shape. Choosing the right sensor to capture the oscillatory partial discharge response from field data shows that when moving from laboratory data to field data, additional low-frequency and high-frequency noise can be noticed in the signal. Figure 2 This is an example diagram of non-periodic partial discharge in the laboratory. Figure 3 The following is an example of partial discharge from field data. Partial discharge only manifests itself as different local properties of signal oscillation. Use a suitable bandpass filter to separate the required frequency band and remove other high-frequency and low-frequency noise components to retain the frequency band that best represents the partial discharge response signal. Figure 4The original signal and the corresponding filtered signal are shown in Figure 2. The results of bandpass filtering are shown in Figure 2. Figure 4 The partial discharge response is very clear after filtering, while it is barely visible in the original signal.

[0079] S103: Perform initial detection 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 a preliminary basis for subsequent detailed detection. Although the accuracy in time, i.e. the frequency, will be lower and important data may be lost, the basic changes can be identified.

[0081] S104 , calculating two auxiliary signals, Aux1 and Aux2 , from the bandpass filtered signal to meet the needs of initial detection and refined 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 signal after bandpass filtering. The generation of these two auxiliary signals is to meet the diverse needs of the initial detection stage and the subsequent detailed detection stage to ensure the accuracy and comprehensiveness of the detection process.

[0083] S105 , analyzing the Aux1 and Aux2 , detecting the non-steady-state components in the filtered signal, and storing the results in a 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-steady-state components in the filtered signal, which are crucial for determining the precise timing and characteristics of partial discharge. After the analysis is completed, the results are properly stored in the spatial pool for subsequent processing.

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

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

[0087] S107 , refining and determining the time of discharge start according to the local maximum time of Aux2 , that is, finding the precise time point before and after the initial detection time.

[0088] It should be noted that this step further utilizes the local maximum time of the Aux2 signal to refine the time of discharge start. Through this step, the key time points before and after the initial detection time can be accurately found, thereby accurately capturing the moment of partial discharge.

[0089] exist Figure 5 In the figure, the red asterisk in auxiliary signal 1 indicates the initial detection time of partial discharge. The black asterisk in auxiliary signal 2 indicates the refined detection time. Figure 5 This time is also indicated by the blue asterisk in the original signal in the second figure. It can be clearly seen that the algorithm is able to determine the arrival moment of the partial discharge very accurately.

[0090] Figure 6 The first example in Figure 1 shows a corona-type partial discharge. The results of the automatic partial discharge detection algorithm are indicated by blue asterisks. It can be seen that the results are exactly at the beginning of each corona pulse. Corona discharge is characterized by a large number of pulses in rapid succession, so the dead time of the detection algorithm must be as short as possible. Otherwise, the algorithm is likely to miss some pulses and give inaccurate results.

[0091] Figure 7 The second example in Figure 1 shows a clear non-periodic PD response superimposed on the noise floor. It can be seen that the determined detection time corresponds exactly to the start of the PD rising edge. It is important to note that the location of this measurement is different from the previous one, but the detection method still provides correct results. In fact, the only thing that changes is the frequency band of the bandpass filter, which is related to the measurement location.

[0092] S108. Separate the frequency spectrum portion related to 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 spectrum part directly related to partial discharge from the voltage signal stored in the space pool. The completion of this step indicates that the time-frequency characteristic analysis of partial discharge signals has been fully launched, providing detailed data support for subsequent analysis and diagnosis.

[0094] In a specific implementation of this embodiment, in addition to the steps described above, we also add an important step after step S108, namely, outputting the detection result. The specific content of this step is as follows:

[0095] After completing all signal acquisition, conversion, filtering, detection and analysis operations, the system will output detailed detection results. These results include partial discharge detection signals, which are obtained after precise processing and identification, and can clearly reflect the characteristics and status of partial discharge. At the same time, the detection results also include positioning information, that is, the specific location of partial discharge in electrical equipment. This information is obtained through time-frequency analysis, feature extraction and matching of the signal, and is highly accurate and reliable.

[0096] There are many ways to output the test results, such as displaying the test results in real time on a display screen, or printing the test results in the form of a report for technical personnel to refer to and analyze. In addition, the test results can also be remotely transmitted and shared through communication means such as the Internet, so that further analysis and processing can be carried out at different locations and times.

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

[0098] Although the terms such as time-frequency, filtering, and signal are used more frequently in this application, the possibility of using other terms is not excluded. These terms are used only to more conveniently describe and explain the essence of the present invention; interpreting them as any additional restrictions is contrary to the spirit of the present invention.

[0099] An embodiment of the present invention provides a recursive filtering parallel partial discharge detection method based on time-frequency characteristics. According to the time-frequency characteristics of the partial discharge signal, after a series of acquisition, conversion, filtering, detection and analysis operations, the method can automatically realize efficient identification and positioning of partial discharge. The method is not only suitable for various general detection scenarios of partial discharge, but also exhibits excellent adaptability and high reliability, providing strong technical support for fault diagnosis and maintenance of electrical equipment.

[0100] Embodiment 2

[0101] Please refer to Figure 8 Embodiment 2 of the present invention provides a recursive filtering parallel partial discharge detection system based on time-frequency characteristics, the system comprising:

[0102] The signal acquisition module 201 is used to collect analog voltage signals on electrical equipment and convert them into digital signals;

[0103] A signal filtering module 202, configured to perform bandpass filtering on the digital signal to eliminate noise and extract signal components related to partial discharge;

[0104] A discharge identification module 203, used to perform initial detection to identify partial discharge events;

[0105] Auxiliary signal module 204, used to calculate two auxiliary signals, Aux1 and Aux2, from the bandpass filtered signal to meet the needs of initial detection and refined detection;

[0106] An analysis and storage module 205 is used to analyze the Aux1 and Aux2, detect the non-steady-state components in the filtered signal, and store the results in a spatial pool;

[0107] An initial time module 206, configured to determine an initial detection time of partial discharge according to the time when Aux1 exceeds a set threshold;

[0108] The precise time module 207 is used to refine the time of discharge start according to the local maximum time of Aux2, that is, to find the precise time point before and after the initial detection time;

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

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

[0111] Using the voltage sensing principle, collect analog voltage signals on electrical equipment;

[0112] The collected analog voltage signal is converted into a digital signal through a high sampling rate analog-to-digital converter.

[0113] Preferably, the frequency range of the bandpass filter is set to 400 kHz to 1.5 MHz.

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

[0115] Output the detection results, including the detection signal and positioning information of partial discharge.

[0116] The embodiment of the present invention provides a recursive filtering parallel partial discharge detection system based on time-frequency characteristics. According to the time-frequency characteristics of the partial discharge signal, after a series of acquisition, conversion, filtering, detection and analysis operations are performed, the system can automatically realize efficient identification and positioning of partial discharge. The system 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 invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0118] Embodiment 3

[0119] Fig. 9 A schematic diagram of the structure of a computer device provided in Embodiment 3 of the present invention. Fig. 9 A block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention is shown. Fig. 9 The computer device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0120] like Fig. 9 As shown, the computer device 12 is in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0121] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0122] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0123] The system memory 28 may 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 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Fig. 9 not shown, usually called a "hard drive"). Although Fig. 9 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0124] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in the memory 28, such program modules 42 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0125] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface 22. In addition, the computer device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with the other modules of the computer device 12 via a bus 18. It should be understood that although Fig. 9 Not shown, other hardware and / or software modules may be used in conjunction 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 backup storage systems.

[0126] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing the recursive filtering parallel partial discharge detection method based on time-frequency characteristics provided in an embodiment of the present invention.

[0127] Embodiment 4

[0128] Embodiment 4 of the present invention provides a computer-readable storage medium having computer-executable instructions stored thereon. When the instructions are executed by a processor, the recursive filtering parallel partial discharge detection method based on time-frequency characteristics provided in all the embodiments of the present application is implemented.

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

[0130] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0131] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

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

[0133] Finally, it should be noted that although the above embodiments have been described in the specification and drawings of this application, this does not limit the scope of patent protection of this application. All technical solutions generated by replacing or modifying equivalent structures or equivalent processes based on the essential concept of this application using the contents recorded in the specification and drawings of this application, as well as directly or indirectly implementing the technical solutions of the above embodiments in other related technical fields, are included in the scope of patent protection of this application.

Claims

1. A recursive filtering parallel partial discharge detection method based on time-frequency characteristics, characterized in that: The method comprises: Collect analog voltage signals from electrical equipment and convert them into digital signals; Performing bandpass filtering on the digital signal to eliminate noise and extract signal components related to partial discharge; Perform initial testing to identify partial discharge events; Two auxiliary signals, Aux1 and Aux2, are calculated from the bandpass filtered signal to meet the needs of initial detection and refined detection; Analyze the Aux1 and Aux2, detect the non-steady-state components in the filtered signal, and store the results in a spatial pool; Determine the initial detection time of partial discharge according to the time when Aux1 exceeds the set threshold; Refining the time of discharge start according to the local maximum time of Aux2, that is, finding the precise time point before and after the initial detection time; The spectral portion related to partial discharge is separated from the voltage signal stored in the spatial pool.

2. The recursive filtering parallel partial discharge detection method based on time-frequency characteristics according to claim 1 is characterized in that: The step of collecting the analog voltage signal on the electrical device and converting it into a digital signal comprises: Using the voltage sensing principle, collect analog voltage signals on electrical equipment; The collected analog voltage signal is converted into a digital signal through a high sampling rate analog-to-digital converter.

3. The recursive filtering parallel partial discharge detection method based on time-frequency characteristics according to claim 1 is characterized in that: In the step of performing band-pass filtering on 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.

4. The recursive filtering parallel partial discharge detection method based on time-frequency characteristics according to claim 1 is characterized in that: The method further comprises: Output the detection results, including the detection signal and positioning information of partial discharge.

5. A recursive filtering parallel partial discharge detection system based on time-frequency characteristics, characterized in that: The system comprises: A signal acquisition module is used to collect analog voltage signals on electrical equipment and convert them into digital signals; A signal filtering module, used for performing bandpass filtering on the digital signal to eliminate noise and extract signal components related to partial discharge; A discharge identification module for performing initial detection to identify partial discharge events; Auxiliary signal module, used to calculate two auxiliary signals, Aux1 and Aux2, from the bandpass filtered signal to meet the needs of initial detection and refined detection; An analysis and storage module, used for analyzing the Aux1 and Aux2, detecting the non-steady-state components in the filtered signal, and storing the results in a spatial pool; An initial time module, used to determine the initial detection time of partial discharge according to the time when Aux1 exceeds a set threshold; A precise time module, used to refine the time of discharge start according to the local maximum time of Aux2, that is, to find the precise time point before and after the initial detection time; The signal separation module is used to separate the frequency spectrum part related to partial discharge from the voltage signal stored in the spatial pool.

6. The recursive filtering parallel partial discharge detection system based on time-frequency characteristics according to claim 5 is characterized in that: The signal acquisition module is specifically used for: Using the voltage sensing principle, collect analog voltage signals on electrical equipment; The collected analog voltage signal is converted into a digital signal through a high sampling rate analog-to-digital converter.

7. The recursive filtering parallel partial discharge detection system based on time-frequency characteristics according to claim 5, characterized in that: The frequency range of the bandpass filter is set from 400 kHz to 1.5 MHz.

8. The recursive filtering parallel partial discharge detection system based on time-frequency characteristics according to claim 5, characterized in that: The system also includes a result output module, which is used to: Output the detection results, including the detection signal and positioning information of partial discharge.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the recursive filtering parallel partial discharge detection method based on time-frequency characteristics as described in any one of claims 1 to 4 is implemented.

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

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