Homologous data comparison method, intelligent fault recording device, equipment and storage medium

Abstract

The invention discloses a homologous data comparison method, an intelligent fault recording device, equipment and a storage medium, and relates to the technical field of power system automation. The method comprises the following steps: acquiring two first homologous data files acquired by two different acquisition devices for the same transformer substation; wherein the types of the electrical parameters recorded by the two first homologous data files are the same; performing consistency alignment processing on the two first homologous data files to obtain two aligned second homologous data files; wherein the sampling frequencies of the electrical parameters in the two aligned second homologous data files are consistent, and the signal waveforms are consistent; and performing homologous data comparison processing on the two second homologous data files based on an improved dynamic time warping algorithm to obtain a data comparison result, and performing debugging, state evaluation and fault analysis on the transformer substation according to the data comparison result. And the self-diagnosis, self-verification and intelligent analysis capabilities of the power system can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system automation, and in particular to a same-source data comparison method, an intelligent fault recording device, equipment and a storage medium. BACKGROUND

[0002] A power system is composed of five parts, i.e., power generation, power transmission, power transformation, power distribution and power consumption, and is a key infrastructure supporting the operation of the national economy. With the expansion of the system scale and the complication of the system structure, it is particularly important to ensure the safe, stable and continuous operation of the power system. For this reason, the secondary system of a substation plays a core role in the entire power grid and undertakes tasks such as measurement, control, protection, communication and monitoring. Among them, fault recording, as an important part of the secondary system, is a key means to record the system disturbance and fault process and to support post-analysis and diagnosis, and provides important data support for power grid dispatching, maintenance and technical improvement. With the large-scale access of new energy, the gradual establishment of multi-regional interconnected power grids and the proposal of the "double carbon" target, the operation environment and control mode of the power grid have undergone profound changes, and the uncertainty of system operation has significantly increased, which puts forward higher requirements for information perception and rapid response capability. At the same time, the construction of digital substations is rapidly advancing, and communication protocols such as IEC 61850, GOOSE and MMS are widely used, which promotes the evolution of the secondary system towards networked and intelligent direction. Under this background, the traditional fault recording device is difficult to meet the new requirements of high reliability, high adaptability and intelligence development, and it is urgent to have an intelligent fault recording device and data processing method with stronger compatibility, higher precision and intelligent analysis capability as support to improve the self-diagnosis, self-checking and intelligent analysis capability of the power system. SUMMARY

[0003] The present application aims to at least solve one of the technical problems existing in the prior art. To this end, the present application provides a same-source data comparison method, an intelligent fault recording device, equipment and a storage medium, which can automatically realize reliable and accurate same-source data comparison to obtain a data comparison result, provide a reliable reference for subsequent debugging, state evaluation and fault analysis of a substation, and help to improve the self-diagnosis, self-checking and intelligent analysis capability of the power system.

[0004] In a first aspect, an embodiment of the present application provides a same-source data comparison method applied to an intelligent fault recording device, wherein the intelligent fault recording device is electrically connected with a substation and a plurality of protection devices corresponding to the same substation; and the method comprises: obtaining two first same-source data files collected by two different collection devices for the same substation; wherein the types of electrical parameters recorded by the two first same-source data files are the same; and the two different collection devices are the intelligent fault recording device and one of the protection devices; The two first homologous data files are subjected to consistency alignment processing to obtain two second aligned homologous data files; wherein the sampling frequencies of the electrical parameters in the two second aligned homologous data files are consistent and the signal waveforms are consistent. The two second homologous data files are subjected to homologous data comparison processing based on an improved dynamic time warping algorithm to obtain a data comparison result, so as to debug, state evaluate and analyze faults of the transformer substation according to the data comparison result.

[0005] In a second aspect, an embodiment of the present application provides an intelligent fault recording device, comprising: A data acquisition module is configured to acquire two first homologous data files collected by two different collection devices for a same transformer substation; wherein the types of electrical parameters recorded by the two first homologous data files are the same; the two different collection devices are the intelligent fault recording device and one of the protection devices. A consistency alignment module is configured to subject the two first homologous data files to consistency alignment processing to obtain two second aligned homologous data files; wherein the sampling frequencies of the electrical parameters in the two second aligned homologous data files are consistent and the signal waveforms are consistent. A data comparison module is configured to subject the two second homologous data files to homologous data comparison processing based on an improved dynamic time warping algorithm to obtain a data comparison result, so as to debug, state evaluate and analyze faults of the transformer substation according to the data comparison result.

[0006] In a third aspect, an embodiment of the present application provides an electronic device, comprising at least one processor and a memory connected with the at least one processor in communication; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the homologous data comparison method according to any one of the embodiments of the first aspect.

[0007] In a fourth aspect, a computer readable storage medium stores computer executable instructions for causing a computer to execute the homologous data comparison method according to any one of the embodiments of the first aspect.

[0008] The embodiment of the application comprises: an intelligent fault recording device and a transformer substation, and a plurality of protection devices corresponding to the same transformer substation are electrically connected; in the process of working of the intelligent fault recording device, first, two first homologous data files collected by two different collection devices for the same transformer substation are acquired; wherein the types of the electrical parameters recorded in the two first homologous data files are the same; the two different collection devices are the intelligent fault recording device and one of the protection devices; then, consistency alignment processing is performed on the two first homologous data files, and two second homologous data files after alignment are obtained; wherein the sampling frequencies of the electrical parameters in the two second homologous data files after alignment are consistent and the signal waveforms are consistent; the two second homologous data files after alignment obtained after data collection and consistency alignment processing lay a data foundation for subsequent data comparison; finally, homologous data comparison processing is performed on the two second homologous data files based on an improved dynamic time warping algorithm, and a data comparison result is obtained, so that the transformer substation is debugged, state evaluated and fault analyzed according to the data comparison result; reliable and accurate homologous data comparison is realized to obtain the data comparison result, which improves reliable reference for subsequent debugging, state evaluation and fault analysis of the transformer substation; that is, the embodiment of the application can automatically realize reliable and accurate homologous data comparison to obtain the data comparison result, which improves reliable reference for subsequent debugging, state evaluation and fault analysis of the transformer substation, and is beneficial to improving self-diagnosis, self-checking and intelligent analysis capabilities of the power system.

[0009] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and attained by particularly pointed out in the description and claims. BRIEF DESCRIPTION OF DRAWINGS

[0010] Figure 1 is a schematic diagram of a system architecture for performing a homologous data comparison method provided by an embodiment of the application; Figure 2 is a flowchart of a homologous data comparison method provided by an embodiment of the application; Figure 3 is a functional module schematic diagram of an intelligent fault recording device provided by an embodiment of the application; Figure 4 is a hardware structure schematic diagram of an electronic device provided by an embodiment of the application. DETAILED DESCRIPTION

[0011] In order to make the purpose, technical scheme and advantages of the present application more clear, the present application is further described in detail below with reference to the drawings and embodiments.

[0012] It should be noted that although the logical order is shown in the flowchart in the description of the present application, in some cases, the steps shown or described can be performed in an order different from that in the flowchart. In the description of the present application, several meanings are one or more, and multiple meanings are two or more. The description of "first", "second" is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features or the sequence of indicated technical features.

[0013] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0014] The present application provides a homologous data comparison method, an intelligent fault recording device, an electronic device and a computer readable storage medium, which relates to the technical field of power system automation. The method comprises: acquiring two first homologous data files collected by two different acquisition devices for a same transformer substation; wherein the types of the electrical parameters recorded by the two first homologous data files are the same; performing consistency alignment processing on the two first homologous data files to obtain two aligned second homologous data files; wherein the sampling frequencies of the electrical parameters in the two aligned second homologous data files are consistent and the signal waveforms are consistent; performing homologous data comparison processing on the two second homologous data files based on an improved dynamic time warping algorithm to obtain a data comparison result, so as to debug, state evaluate and fault analyze the transformer substation according to the data comparison result. It can be beneficial to improve the self-diagnosis, self-checking and intelligent analysis capabilities of the power system.

[0015] The embodiments of the present application will be further described below with reference to the accompanying drawings.

[0016] As shown in Figure 1 , Figure 1 is a schematic diagram of a system architecture for performing a homologous data comparison method provided by an embodiment of the present application; the system architecture comprises: an intelligent fault recording device 100, a plurality of protection devices 200 arranged corresponding to a same transformer substation 300; the intelligent fault recording device 100 is electrically connected with the protection devices 200; the protection devices 200 are electrically connected with the transformer substation 300, and different protection devices 200 are used to collect and transmit the electrical parameters of the transformer substation 300 through different channels or protocols, and the intelligent fault recording device 100 is also used to collect the electrical parameters of the transformer substation 300 to generate a fault recording file, and receive the data uploaded by the different protection devices 200 to form a fault recording file.

[0017] It can be understood that the intelligent fault recording device 100 is one of the core units of the new generation of digital substation, integrates functions such as high-speed sampling, multi-source information fusion, intelligent triggering, edge analysis, remote transmission, and can realize accurate recording and intelligent diagnosis of the whole process of fault. Compared with the traditional fault recorder, the intelligent fault recording device 100 not only has the ability to collect analog quantities, but also can receive and process network communication information such as sampling values (SV), GOOSE, MMS, etc., to improve the breadth and depth of system perception. As the "black box" of power grid operation events and an important support device for intelligent operation and maintenance, the intelligent fault recording device 100 plays an irreplaceable role in improving the self-diagnosis, self-recovery, and self-management capabilities of the power grid.

[0018] It can be understood that in the intelligent substation, the same electrical parameter is often collected and transmitted by multiple devices through different channels or protocols. In order to ensure data consistency, judge the correctness of the wiring, and verify the clock synchronization, the same source data comparison algorithm emerges as the times require. The intelligent fault recording device 100 can realize functions such as wiring consistency check, time synchronization error detection, data integrity check, and recording accuracy verification by comparing waveform data of the same electrical parameter (such as voltage, current, etc.) from different sources, which provides important technical support for device debugging, system operation state evaluation, and fault cause analysis. The same source data comparison algorithm of the present application is one of the key intelligent capabilities of the intelligent fault recording device to realize "self-diagnosis, self-checking, and self-analysis".

[0019] It should be noted that there are multiple protection devices 200, and the number of protection devices is not specifically limited in the present application.

[0020] In the embodiments of the present application, the intelligent fault recording device 100 can cooperate with the protection device 200 to realize the same source data comparison method provided by the present application, automatically realize reliable and accurate same source data comparison to obtain a data comparison result, and provide a reliable reference for subsequent debugging, state evaluation, and fault analysis of the substation, which is beneficial to improve the self-diagnosis, self-checking, and intelligent analysis capabilities of the power system.

[0021] Those skilled in the art can understand that the system structure shown in the figure does not constitute a limitation on the embodiments of the present application, and can include more or fewer components than the figure, or combine certain components, or different component arrangements.

[0022] The system embodiments described above are only schematic, and the units described as separate components can or can not be physically separated, that is, they can be located in one place, or distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments.

[0023] Those skilled in the art can understand that the system architecture and application scenarios described in the embodiments of the present application are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of system architecture and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0024] Based on the above system structure, the following embodiments of the homologous data comparison method of the present application are proposed.

[0025] As shown in Figure 2 , the homologous data comparison method can be applied to the intelligent fault recording device as shown in Figure 1 , the intelligent fault recording device is electrically connected with the substation and a plurality of protection devices corresponding to the same substation; the homologous data comparison method can include but is not limited to steps S100 to S300.

[0026] Step S100: acquiring two first homologous data files collected by two different collection devices for the same substation; wherein the types of the electrical parameters recorded by the two first homologous data files are the same; the two different collection devices are the intelligent fault recording device and one of the protection devices.

[0027] Further explanation of step S100. The electrical parameter can be voltage, or current, etc. The type of the electrical parameter is not specifically limited in the present application.

[0028] Specifically, both of the two first homologous data files are fault recording files.

[0029] It can be understood that the intelligent fault recording device receives more fault recording files, and needs to further determine the first homologous data file. When determining the first homologous data file, some methods need to be used to compare the fault recording files collected by the intelligent fault recording device and the protection devices to determine which two fault recording files belong to the homologous data file. The existing method is the homologous recording data searching strategy based on the mutation variable.

[0030] Through step S100, two first homologous data files to be compared are collected, laying a data foundation for subsequent processing.

[0031] Step S200: performing consistency alignment processing on the two first homologous data files to obtain two aligned second homologous data files; wherein the sampling frequencies of the electrical parameters in the two aligned second homologous data files are consistent and the signal waveforms are consistent.

[0032] Specifically, the consistency alignment processing includes frequency comparison processing, waveform comparison processing, and data alignment processing performed when the sampling frequencies and / or the signal waveforms are inconsistent.

[0033] According to some embodiments of the present application, the step S200 provided by the embodiments of the present application is further explained as follows: the step S200 is to perform consistency alignment processing on the two first homologous data files to obtain two aligned second homologous data files, and includes but is not limited to steps S210 to S220.

[0034] The step S210 is to perform frequency comparison processing on the sampling frequencies of the two first homologous data files to obtain a frequency comparison result, and perform waveform comparison processing on the signal waveforms of the two first homologous data files to obtain a waveform comparison result.

[0035] Specifically, in this step, the frequency comparison processing refers to checking whether the sampling frequencies of the two first homologous data files to be compared are consistent, and the obtained frequency comparison result has two kinds: the sampling frequencies are consistent, or the sampling frequencies are inconsistent.

[0036] Specifically, in this step, the waveform comparison processing refers to checking whether the signal waveforms of the two first homologous data files to be compared are consistent, and the obtained waveform comparison result has two kinds: the signal waveforms are consistent, or the signal waveforms are inconsistent.

[0037] The step S220 is to perform data alignment processing on the two first homologous data files in the case that the frequency comparison result represents that the sampling frequencies are inconsistent and / or the waveform comparison result represents that the signal waveforms are inconsistent, to obtain two aligned second homologous data files.

[0038] It can be understood that in the case that the sampling frequencies and / or the signal waveforms are inconsistent, the first homologous data files need to be aligned for the next homologous data comparison processing. The specific processes of the data alignment processing performed next are different according to the frequency comparison result and the waveform comparison result. The specific explanations are as follows.

[0039] According to some embodiments of the present application, the data alignment processing includes frequency conversion processing. Embodiment one for further explaining the step S220 is as follows: the step S220 is to perform data alignment processing on the two first homologous data files to obtain two aligned second homologous data files, and includes but is not limited to the step S221: in the case that the frequency comparison result represents that the sampling frequencies are inconsistent and the waveform comparison result represents that the signal waveforms are consistent, performing frequency conversion processing on the two first homologous data files based on a Lagrange interpolation resampling technique to obtain two aligned second homologous data files.

[0040] Specifically, the Lagrange interpolation resampling technique is a signal processing method based on polynomial interpolation, mainly through a Lagrange interpolation polynomial to estimate new sampling values between original sampling points, so as to realize sampling rate conversion of any multiple.

[0041] According to some embodiments of the present application, the data alignment processing includes waveform alignment processing; further to step S220, embodiment two: performing data alignment processing on the two first homologous data files to obtain the two second homologous data files, including but not limited to step S222: in the case that the frequency comparison result represents that the sampling frequencies are consistent and the waveform comparison result represents that the signal waveforms are inconsistent, performing waveform alignment processing on the two first homologous data files based on the Euclidean distance to obtain the two second homologous data files.

[0042] Specifically, the waveform alignment processing based on the Euclidean distance refers to: by sliding one wave recording data, calculating the Euclidean distance between the slid wave recording data and another reference wave recording data at each possible time offset. The Euclidean distance measures the overall difference of the corresponding points of the waveforms. When the shapes of the two waveforms completely match on the time axis, the Euclidean distance is the smallest. Therefore, finding the offset corresponding to the smallest Euclidean distance is the best alignment position, thereby completing the time synchronization of the waveforms.

[0043] According to some embodiments of the present application, the data alignment processing includes frequency alignment processing and waveform alignment processing, further to step S220, embodiment three: performing data alignment processing on the two first homologous data files to obtain the two second homologous data files, including but not limited to steps S223 to S224.

[0044] Step S223: in the case that the frequency comparison result represents that the sampling frequencies are inconsistent and the waveform comparison result represents that the signal waveforms are inconsistent, performing frequency conversion processing on the two first homologous data files based on the Lagrange interpolation resampling technique to obtain the two first homologous data files with aligned sampling frequencies.

[0045] Step S224: performing waveform alignment processing on the two first homologous data files with aligned sampling frequencies based on the Euclidean distance to obtain the two second homologous data files.

[0046] Specifically, in the case that the sampling frequencies are inconsistent and the signal waveforms are inconsistent, the frequency conversion processing and the waveform alignment processing need to be performed in sequence. The frequency conversion processing of step S223 is the same as the frequency conversion processing of step S221; the waveform alignment processing of step S224 is the same as the waveform alignment processing of step S222.

[0047] According to some embodiments of the present application, the homologous data comparison method further comprises Embodiment Four: after obtaining the frequency comparison result and the waveform comparison result, in the case that the frequency comparison result represents that the sampling frequencies are consistent and the waveform comparison result represents that the signal waveforms are consistent, the two first homologous data files are determined as two aligned second homologous data files.

[0048] It can be understood that, based on the actual frequency comparison result and the waveform comparison result, Embodiment One or Embodiment Two or Embodiment Three or Embodiment Four described above is executed to obtain the two aligned second homologous data files, which lays a data foundation for subsequent data comparison.

[0049] The embodiment of the present application obtains the two aligned second homologous data files through the step S200 after data acquisition and consistency alignment processing, which lays a data foundation for subsequent data comparison.

[0050] Step S300: performing homologous data comparison processing on the two second homologous data files based on the improved dynamic time warping algorithm to obtain a data comparison result, so as to debug, state evaluate and analyze the fault of the transformer substation according to the data comparison result.

[0051] Specifically, the dynamic time warping algorithm (DTW) is introduced into the homologous data comparison method due to its robustness to time axis misalignment, and is used to compare similar but not completely time-aligned waveform signals in multiple wave recording channels. The DTW has the disadvantages of high calculation complexity (O(N²)), sensitivity to amplitude anomaly and phase error, and non-intuitive physical meaning of comparison result, which limits its application in online comparison of high sampling rate and large-scale wave recording data. In addition, the DTW algorithm lacks engineering interpretability in processing typical power problems such as phasor deviation, polarity error and synchronization offset, so the present application proposes a homologous data comparison algorithm based on the improved DTW algorithm.

[0052] According to some embodiments of the present application, step S300 is further illustrated as follows: step S300: performing homologous data comparison processing on the two second homologous data files based on the improved dynamic time warping algorithm to obtain a data comparison result, which includes but is not limited to steps S310 to S330.

[0053] Step S310: performing first effective value calculation processing on the second homologous data file from the intelligent fault wave recording device to obtain a first effective value.

[0054] Specifically, the first effective value will be used as a reference value in the subsequent.

[0055] Specifically, the first effective value calculation processing refers to effective value calculation on the recording wave data, which is a calculation mode of converting the instantaneous alternating current waveform into a direct current flow representing the energy size of the instantaneous alternating current waveform. The calculation is mainly performed by a sliding time window (usually one power frequency period) on the instantaneous sampling values in the window, and the calculation is performed by squaring, averaging, and taking the square root. The result is an effective value sequence that changes smoothly with time, which filters out high-frequency oscillations and noise, and more stably reflects the actual amplitude level and change trend of the current / voltage, and provides stable and reliable characteristic quantities for subsequent data comparison and analysis.

[0056] Step S320: performing second effective value calculation processing on the second homologous data file from the protection device to obtain a second effective value.

[0057] It can be understood that the specific process of the second effective value calculation processing is the same as that of the first effective value calculation processing.

[0058] Step S330: based on the improved dynamic time warping algorithm, taking the first effective value as a reference, and comparing the second effective value point by point to obtain a data comparison result; the improved dynamic time warping algorithm includes pre-filtering processing, path search range limiting processing, and multi-thread parallel processing.

[0059] Specifically, the path search range limiting processing refers to the Sakoe-Chiba Band (also known as: global path limiting window) mode, which limits the search range of the DTW path, thereby reducing the time and space complexity and improving the calculation efficiency.

[0060] Specifically, the pre-filtering processing refers to the Lower Bound (i.e. lower bound filtering) mode, which is a fast pre-filtering technology; and is used for fast pre-filtering before calculating the time sequence similarity using the DTW algorithm, so as to speed up the nearest neighbor search or batch matching.

[0061] Specifically, the multi-thread parallel processing refers to using GPU or multi-thread optimization, so that the calculation in the improved DTW algorithm can be completed in parallel on the row or diagonal line, thereby improving the processing efficiency.

[0062] It can be understood that the improved dynamic time warping algorithm of the embodiment of the present application is improved on the basis of the traditional DTW algorithm, and a balance between algorithm effectiveness and time is achieved by limiting the parallel calculation range, parallel filtering, and parallel calculation when performing multi-sequence batch matching.

[0063] Specifically, in the embodiments of the present application, the improved dynamic time warping algorithm is based on the traditional dynamic time warping (DTW), combined with Sakoe-Chiba Band method, Lower Bound filtering method and multi-thread parallel method, to improve the calculation efficiency and accuracy of data comparison. Among them, the Sakoe-Chiba Band method limits the path search range, reduces unnecessary calculation, maintains high comparison accuracy while speeding up the processing speed; the Lower Bound filtering method estimates the lower bound of the distance before calculation, quickly excludes dissimilar samples, and further reduces the calculation burden; and the multi-thread parallel method enables fast data comparison in a multi-core environment in the case of high channel number and high sampling rate. These optimizations have greatly improved the real-time processing capability of the improved dynamic time warping algorithm of the present application, and can meet the large and high-frequency data processing needs in complex power systems.

[0064] In the process of working of the intelligent fault recording device, two first same-source data files collected by two different collection devices for the same substation are first obtained in steps S100 to S300; the types of the electrical parameters recorded in the two first same-source data files are the same; the two different collection devices are the intelligent fault recording device and one of the protection devices; then, the two first same-source data files are subjected to consistency alignment processing to obtain two aligned second same-source data files; the sampling frequencies of the electrical parameters in the two aligned second same-source data files are consistent and the signal waveforms are consistent; the two aligned second same-source data files obtained after data collection and consistency alignment processing lay a data foundation for subsequent data comparison; finally, the two second same-source data files are subjected to same-source data comparison processing based on the improved dynamic time warping algorithm to obtain a data comparison result, so as to debug, state evaluate and analyze the fault of the substation according to the data comparison result; reliable and accurate same-source data comparison is realized to obtain the data comparison result, which improves the reliable reference for subsequent debugging, state evaluation and fault analysis of the substation; that is, the embodiments of the present application can automatically realize reliable and accurate same-source data comparison to obtain the data comparison result, which improves the reliable reference for subsequent debugging, state evaluation and fault analysis of the substation, and is beneficial to improving the self-diagnosis, self-checking and intelligent analysis capability of the power system.

[0065] As Figure 3 shown, Figure 3 is a functional module schematic diagram of the intelligent fault recording device provided by the embodiments of the present application. The intelligent fault recording device 100 comprises a data acquisition module 101, a consistency alignment module 102 and a data comparison module 103.

[0066] The data acquisition module 101 is configured to acquire two first homologous data files collected by two different collection devices for a same transformer substation, wherein the two first homologous data files record the same type of electrical parameters, and the two different collection devices are an intelligent fault recording device and one of the protection devices.

[0067] The consistency alignment module 102 is configured to perform consistency alignment processing on the two first homologous data files to obtain two second homologous data files after alignment, wherein the sampling frequencies of the electrical parameters in the two second homologous data files after alignment are consistent and the signal waveforms are consistent.

[0068] The data comparison module 103 is configured to perform homologous data comparison processing on the two second homologous data files based on the improved dynamic time warping algorithm to obtain a data comparison result, and to perform debugging, state evaluation and fault analysis on the transformer substation according to the data comparison result.

[0069] The intelligent fault recording device provided in the embodiments of the present application implements the homologous data comparison method of the embodiments of the present application, and can provide reliable reference for subsequent debugging, state evaluation and fault analysis of the transformer substation. In the intelligent fault recording device provided in the embodiments of the present application, the improved dynamic time warping algorithm is applied to the homologous data comparison algorithm, that is, the fault recording files of the same electrical parameters (such as current, voltage, etc.) collected by two devices are compared and analyzed. In some embodiments, the fault recording files of the same electrical parameters (such as current, voltage, etc.) collected by multiple devices can also be compared and analyzed. Through the improved dynamic time warping algorithm, the intelligent recording device can efficiently identify and align the signal offset caused by synchronization error, delay, wiring problem, etc., and accurately evaluate the consistency of the signal. Not only can it help to judge the common problems such as clock synchronization, data loss, wiring polarity in the system, but also can provide accurate data support for fault location, device diagnosis and system operation and maintenance, greatly improving the self-diagnosis, self-checking and intelligent analysis capability of the power system.

[0070] As shown in Figure 4 The present application further provides an electronic device, which comprises: The processor 401 can be implemented in a general-purpose central processing unit (CPU), a microprocessor, an application specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present application. The memory 402 can be implemented in the form of a Read Only Memory (ROM), a static storage device, a dynamic storage device, or a Random Access Memory (RAM), etc. The memory 402 can store an operating system and other application programs, and when the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the related program codes are stored in the memory 402 and are called and executed by the processor 401 to perform the same-origin data comparison method of the embodiments of the present application; The input / output interface 403 is configured to realize information input and output. The communication interface 404 is configured to realize the communication interaction between the device and other devices, and can realize the communication through a wired manner (for example, a USB, a network cable, etc.) or a wireless manner (for example, a mobile network, WIFI, Bluetooth, etc.). The bus 405 is configured to transmit information between various components (for example, the processor 401, the memory 402, the input / output interface 403, and the communication interface 404) of the device. The processor 401, the memory 402, the input / output interface 403, and the communication interface 404 are connected to each other through the bus 405 to realize the communication connection between the device.

[0071] The embodiments of the present application also provide a storage medium, which is a computer readable storage medium, and the storage medium stores a computer program. The computer program is executed by a processor to implement the same-origin data comparison method.

[0072] The memory is a non-transitory computer readable storage medium, which can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof. The above-described device embodiments are only schematic, and the units described as separate components can be or can not be physically separated, and can be implemented in one place or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments.

[0073] As will be appreciated by one of ordinary skill in the art, all or some steps, systems of the above-disclosed methods can be implemented as software, firmware, hardware, or any suitable combination thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application- specific integrated circuit. Such software can be distributed on computer readable media, which can comprise computer storage media (or non-transitory media) and communication media (or transitory media). As is well known to those of ordinary skill in the art, computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Further, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery media.

[0074] The above description is that of the preferred embodiments of the present application. Various modifications and changes can be made thereto without departing from the spirit of the application, which is defined by the appended claims.

Claims

1. A method for comparing data from the same source, characterized in that, The method is applied to an intelligent fault recording device, which is electrically connected to a substation and multiple protection devices installed corresponding to the same substation; the method includes: Two first source data files collected by two different acquisition devices for the same substation are obtained; wherein the electrical parameters recorded in the two first source data files are of the same type; the two different acquisition devices are the intelligent fault recording device and one of the protection devices. The two first source data files are subjected to consistency alignment processing to obtain two aligned second source data files; wherein the sampling frequency of the electrical parameters in the two aligned second source data files is consistent and the signal waveform is consistent. Based on the improved dynamic time warping algorithm, the two second source data files are compared to obtain the data comparison results, which are then used to perform commissioning, status assessment and fault analysis on the substation.

2. The method for comparing data from the same source according to claim 1, characterized in that, The step of performing consistency alignment processing on the two first source data files to obtain two aligned second source data files includes: Frequency comparison is performed on the sampling frequencies of the two first source data files to obtain frequency comparison results, and waveform comparison is performed on the signal waveforms of the two first source data files to obtain waveform comparison results. If the frequency comparison result indicates that the sampling frequency is inconsistent and / or the waveform comparison result indicates that the signal waveform is inconsistent, the two first source data files are subjected to data alignment processing to obtain two aligned second source data files.

3. The method for comparing data from the same source according to claim 2, characterized in that, The data alignment process includes: frequency conversion processing; the data alignment process of the two first homogeneous data files to obtain two aligned second homogeneous data files includes: When the frequency comparison result indicates that the sampling frequencies are inconsistent and the waveform comparison result indicates that the signal waveforms are consistent, frequency conversion processing is performed on the two first source data files based on the Lagrange interpolation resampling technique to obtain two aligned second source data files.

4. The method for comparing data from the same source according to claim 2, characterized in that, The data alignment process includes: waveform alignment processing; the step of performing data alignment processing on the two first source data files to obtain two aligned second source data files includes: When the frequency comparison result indicates that the sampling frequencies are consistent and the waveform comparison result indicates that the signal waveforms are inconsistent, waveform alignment processing is performed on the two first source data files based on Euclidean distance to obtain two aligned second source data files.

5. The method for comparing data from the same source according to claim 2, characterized in that, The data alignment process includes frequency alignment and waveform alignment. The step of performing data alignment on the two first source data files to obtain two aligned second source data files includes: When the frequency comparison result indicates that the sampling frequencies are inconsistent and the waveform comparison result indicates that the signal waveforms are inconsistent, the two first source data files are frequency converted based on the Lagrange interpolation resampling technique to obtain two first source data files with the sampling frequencies aligned. Based on Euclidean distance, waveform alignment processing is performed on the two first source data files with the sampling frequency aligned to obtain two second source data files with the same alignment.

6. The method for comparing data from the same source according to claim 2, characterized in that, The method further includes: After obtaining the frequency comparison result and the waveform comparison result, if the frequency comparison result indicates that the sampling frequency is consistent and the waveform comparison result indicates that the signal waveform is consistent, the two first source data files are determined as two aligned second source data files.

7. The method for comparing data from the same source according to claim 1, characterized in that, The improved dynamic time warping algorithm is used to perform source data comparison processing on the two second source data files to obtain data comparison results, including: The first effective value is obtained by performing a first effective value calculation on the second source data file originating from the intelligent fault recording device. The second valid value is obtained by performing a second valid value calculation on the second source data file originating from the protection device; Based on the improved dynamic time warping algorithm, the data comparison result is obtained by comparing the first valid value with the second valid value point by point, with the first valid value as the benchmark; the improved dynamic time warping algorithm includes: pre-filtering processing, path search range limitation processing and multi-threaded parallel processing.

8. An intelligent fault recording device, characterized in that, include: The data acquisition module is used to acquire two first source data files collected by two different acquisition devices for the same substation; wherein the electrical parameters recorded in the two first source data files are of the same type; the two different acquisition devices are the intelligent fault recording device and one of the protection devices. The consistency alignment module is used to perform consistency alignment processing on the two first source data files to obtain two aligned second source data files; wherein the sampling frequency of the electrical parameters in the two aligned second source data files is consistent and the signal waveform is consistent. The data comparison module is used to perform source data comparison processing on two second source data files based on an improved dynamic time warping algorithm to obtain data comparison results, so as to perform commissioning, status assessment and fault analysis on the substation based on the data comparison results.

9. An electronic device, characterized in that, It includes at least one processor and a memory for communicatively connecting to the at least one processor; the memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to perform the same-source data comparison method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform the same-source data comparison method as described in any one of claims 1 to 7.

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