CN110956121A - Hidden fault early warning method and device based on protection starting and associated recording analysis - Google Patents
Hidden fault early warning method and device based on protection starting and associated recording analysis Download PDFInfo
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Abstract
The disclosure relates to a hidden fault early warning method and a hidden fault early warning device based on protection starting and associated wave recording analysis, wherein the method comprises the steps of obtaining fault wave recording data; extracting characteristic parameters representing the state of a fault point from the fault recording data; and obtaining a hidden fault early warning result according to the characteristic parameters. In the embodiment of the disclosure, early warning results such as near fault point protection starting early warning, sampling abnormity early warning and main transformer near region fault early warning are obtained through fault recording data; the application range and the application depth of fault recording data are expanded, and hidden faults of the protection device can be found in advance, so that the requirement of operation of the intelligent power grid is met.
Description
Technical Field
The disclosure relates to the technical field of electric power, in particular to a hidden fault early warning method and device based on protection starting and associated wave recording analysis.
Background
In recent years, the large-scale interconnection of power grids has become a trend of global power grid development, which increases the scale of modern power grids and improves the economy, and the requirements for safe and stable operation of power systems are higher and higher. However, since the hidden fault of the protection device is not easy to be discovered in advance, the hidden fault of the relay protection is just a catastrophic mechanism of the power system.
Disclosure of Invention
In view of this, the present disclosure provides a hidden fault early warning method and device based on protection startup and associated recording analysis, which solve the problem that a hidden fault of a protection device is not easy to be found in advance.
According to one aspect of the disclosure, a hidden fault early warning method based on protection starting and associated recording analysis is provided, which includes:
acquiring fault recording data;
extracting characteristic parameters representing the state of a fault point from the fault recording data;
and obtaining a hidden fault early warning result according to the characteristic parameters.
In one possible implementation, the fault recording data includes: protecting fault recording data, and obtaining a hidden fault early warning result according to the characteristic parameters, wherein the hidden fault early warning result comprises the following steps:
according to the fault recording starting signal in the protection fault recording data, obtaining the protection starting state of a near fault point and a far fault point;
under the condition that the protection starting state of the far fault point is started, if the protection starting state of any near fault point is not started, judging the current hidden fault and sending abnormal alarm information;
and the current hidden fault early warning result is a near fault point protection starting abnormity early warning result.
In one possible implementation, the fault recording data includes: protecting fault recording data, and obtaining a hidden fault early warning result according to the characteristic parameters, wherein the hidden fault early warning result comprises the following steps:
according to the fault recording starting signal in the protection fault recording data, obtaining the protection starting states of a first protection device and a second protection device based on double configuration in a near fault point;
under the condition that the protection starting states of the first protection device and the second protection device are different, judging a current hidden fault and sending abnormal alarm information;
and the current hidden fault early warning result is a near fault point protection starting abnormity early warning result.
In one possible implementation, the fault recording data includes: protecting fault recording data and concentrated recording data, and obtaining a hidden fault early warning result according to the characteristic parameters, wherein the hidden fault early warning result comprises the following steps:
and obtaining a hidden fault early warning result by comparing the waveform correlation of the protection fault recording data and the concentrated recording data.
In one possible implementation, the fault recording data includes: protecting fault recording data and concentrated recording data, and obtaining a hidden fault early warning result according to the characteristic parameters, wherein the hidden fault early warning result comprises the following steps:
and obtaining a hidden fault early warning result by comparing the impact current in the protection fault recording data and/or the concentrated recording data with a first preset threshold value.
In a possible implementation manner, the obtaining a hidden fault early warning result by comparing the waveform correlations of the protection fault recording data and the concentrated recording data includes:
acquiring the protection fault recording data and the waveform data of the centralized recording data;
obtaining a correlation coefficient value according to the waveform data;
under the condition that the correlation coefficient value does not exceed a second preset threshold value, judging a current hidden fault and sending out sampling abnormal alarm information;
and the current hidden fault early warning result is a protection sampling abnormity early warning result.
In a possible implementation manner, the obtaining of the hidden fault early warning result by comparing the impact current of the protection fault recording data and/or the centralized recording data includes:
acquiring waveform data of the protection fault recording data and/or the centralized recording data;
obtaining impact current according to the waveform data;
under the condition that the impact current is larger than a first preset threshold value, judging a current hidden fault and sending main transformer near zone fault alarm information;
and the current hidden fault early warning result is a main transformer near zone fault early warning result.
According to another aspect of the present disclosure, a hidden fault early warning device based on protection initiation and associated recording analysis is provided, including:
the fault recording data module is used for acquiring fault recording data;
the characteristic parameter module is used for extracting characteristic parameters representing the state of a fault point from the fault recording data;
and the hidden fault early warning module is used for obtaining a hidden fault early warning result according to the characteristic parameters.
According to another aspect of the present disclosure, a hidden fault early warning device based on protection initiation and associated recording analysis is provided, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to perform the above method.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the above-described method.
In the embodiment of the disclosure, early warning results such as near fault point protection starting early warning, sampling abnormity early warning and main transformer near region fault early warning are obtained through fault recording data; the application range and the application depth of fault recording starting data are expanded, and hidden faults of the protection device can be found in advance, so that the requirement of operation of the intelligent power grid is met.
Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.
Fig. 1 shows a flow chart of a hidden fault early warning method based on protection initiation and associated recording analysis according to an embodiment of the present disclosure;
FIG. 2 illustrates a flow diagram of a near point of failure protection startup warning method according to an embodiment of the present disclosure;
FIG. 3 illustrates a flow diagram of a method of protecting against sample anomaly early warning according to an embodiment of the present disclosure;
FIG. 4 illustrates a schematic graph of a correlation curve of protection fault recording data and centralized recording data according to an embodiment of the present disclosure;
FIG. 5 illustrates a schematic graph of a correlation curve of protection fault recording data and centralized recording data according to an embodiment of the present disclosure;
fig. 6 shows a flow chart of a main transformer near zone fault early warning method according to an embodiment of the present disclosure;
fig. 7 shows a structure diagram of a hidden fault warning device based on protection initiation and associated recording analysis according to an embodiment of the present disclosure;
fig. 8 shows a block diagram of an apparatus for hidden fault warning based on protection initiation and associated recording analysis according to an embodiment of the present disclosure.
Detailed Description
Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.
The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.
Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.
In recent years, the large-scale interconnection of power grids has become a trend of global power grid development, which increases the scale of modern power grids and improves economy, and the demand for safe and stable operation of power systems is higher and higher. However, hidden failures of relay protection are just a catastrophic mechanism in power systems.
Considering that a power grid can generate massive fault recording starting data every year, the application of the fault recording data is only limited to relay protection specialties for fault diagnosis and fault troubleshooting, and the fault recording starting data is small in application range and shallow in application depth and cannot meet the requirements of operation of a smart power grid.
Therefore, the technical scheme of hidden Fault early warning based on protection starting and associated wave recording analysis is provided in the embodiment of the disclosure, and is applied to a power grid of a Fault Information System (FIS) of a protection Information management master station, and the protection starting early warning, the sampling abnormity early warning and the main transformer near-zone Fault early warning of a near Fault point are realized through Fault wave recording data; the application range and the application depth of fault recording starting data are expanded, and hidden faults of the protection device can be found in advance, so that the requirement of operation of the intelligent power grid is met.
Fig. 1 shows a flowchart of a hidden fault early warning method based on protection initiation and associated recording analysis according to an embodiment of the present disclosure. As shown in fig. 1, the method may include the steps of:
and step 30, obtaining a hidden fault early warning result according to the characteristic parameters.
The hidden fault is a defect which may exist in a relay protection system, and when the relay protection device operates normally, the defect cannot interfere with the operation of the system, and when the power grid operates abnormally or internal elements of the protection device change, the defect can be triggered, so that a large-range fault is caused; because the hidden fault has no outside characteristics, the hidden fault has strong hiding performance, so that the hidden fault of the protection device is not easy to discover in advance. In the embodiment of the present disclosure, through fault recording data, hidden faults are timely found and early-warning is performed, and hidden fault early-warning results may include: and the early warning result of the protection starting of the near fault point, the early warning result of the sampling abnormity and the early warning result of the near zone fault of the main transformer.
The fault logging data may include: centralized wave recording data, protection fault wave recording data and other wave recording data; wherein, the centralized wave recording data can be wave recording data obtained by a wave recording acquisition device (such as a wave recorder); the protection fault recording data may be recording data obtained by the protection device. The fault recording data is data for recording characteristic parameters of electric quantity, non-electric quantity, switching value and the like in the power system for representing the state of the power grid; the oscillograph generates fault wave recording data for events such as faults, abnormity and the like in the system by automatically recording and monitoring analog quantity and event quantity in the system, can be stored and transmitted to a main station FIS, and further analyzes and processes the fault wave recording data, so that the fault property, the distance of a fault occurrence point, the severity of the fault and the like are accurately judged.
A protection device (also referred to as a secondary equipment) may refer to equipment that oversees, measures, controls, protects, and regulates primary equipment within a power system. A primary device may refer to a device within a power system that is directly used to produce and use electrical energy. The protection device may collect information of the primary device, including action information, alarm information, self-checking information, and the like, and the number of the protection devices may be one or more, which is not limited in this disclosure.
In one possible implementation, the fault recording data may include: protecting the fault recording data, in step 30, obtaining the hidden fault early warning result according to the characteristic parameters may include: according to the fault recording starting signal in the protection fault recording data, obtaining the protection starting state of a near fault point and a far fault point; under the condition that the protection starting state of the far fault point is started, if the protection starting state of any near fault point is not started, judging the current hidden fault and sending abnormal alarm information; and the current hidden fault early warning result is a near fault point protection starting abnormity early warning result.
Considering that the protection sensitivity of a near fault point is relatively high, if the protection of a far fault point is started and the protection of the near fault point is not started, the hidden fault possibly exists in the protection device, and an alarm needs to be sent out in time so as to check and maintain in time. Therefore, in the embodiment of the disclosure, the fault recording data is used to early warn the protection start abnormality of the near fault point through the start states of the near fault point and the far fault point, so as to find the hidden fault in time. The near fault point and the far fault point may be divided according to specific work tasks in the power grid, which is not limited by the present disclosure.
In one possible implementation, the fault recording data may include: protecting fault recording data, in step 30, obtaining a hidden fault early warning result according to the characteristic parameters, which may further include: according to the fault recording starting signal in the protection fault recording data, obtaining the protection starting states of a first protection device and a second protection device based on double configuration in a near fault point; under the condition that the protection starting states of the first protection device and the second protection device are different, judging a current hidden fault and sending abnormal alarm information; and the current hidden fault early warning result is a near fault point protection starting abnormity early warning result.
Considering the protection of the same equipment in a double configuration (i.e. having two complete, functionally identical, mutually independent protection devices) near a fault point, if one protection device is activated and the other protection device is not activated, the protection device which is not activated has a suspected problem. Therefore, according to the embodiment of the disclosure, the fault recording data is utilized, and the start abnormality early warning is carried out on the protection start abnormality of the near fault point through the start states of the two protection devices which are configured in a dual mode, so that the hidden fault can be found in time.
It should be noted that, when the starting states of the near fault point, the far fault point, and the two sets of protection devices in the near fault point are determined, whether the two sets of protection devices enter the starting state may be determined through fault recording data (e.g., a fault recording starting signal); whether the starting state is entered or not can be judged by protecting the starting signal; further, the fault recording starting signal and the protection starting signal can be used for judging at the same time, the fault recording starting signal and the protection starting signal are mutually verified, and illustratively, when the time difference of the two signals indicating that the protection device enters the starting state is within a certain range, the protection device is judged to be in the starting state.
For example, fig. 2 shows a flowchart of a near fault point protection start-up warning method according to an embodiment of the present disclosure, as shown in fig. 2, a far fault point protection start-up signal or a set of near fault point protection start-up signals is read through a fault information management station FIS; then judging the protection states of all near fault points (comprising two sets of devices configured in a duplex manner); if the protection of all the near fault points is detected to be started, no alarm information is sent; otherwise, sending out abnormal alarm information for protection starting.
In one possible implementation, the fault recording data may include: protecting fault recording data and concentrated recording data, and in step 30, obtaining a hidden fault early warning result according to the characteristic parameters, including: and obtaining a hidden fault early warning result by comparing the waveform correlation of the protection fault recording data and the concentrated recording data.
In the embodiment of the disclosure, whether protection sampling abnormality exists is judged by utilizing protection fault recording data and centralized recording data and by adopting waveform correlation analysis. The correlation analysis is used for analyzing the markers which are really connected in the population, and the main body is used for analyzing the markers with the causal relationship in the population. It is a process of describing the closeness of the relationship between objective things and expressing it with proper statistical indexes. Usually, the correlation coefficient is taken as a measurement index, and the larger the correlation coefficient is, the stronger the correlation is. Illustratively, a pearson correlation coefficient calculation formula is adopted in the embodiment of the present disclosure, as shown in the following formula (1):
wherein r is represented by (X)i，Yi) The standard score mean of the sample points is estimated, n is the number of sample points,
is XiThe average value of the samples is calculated,
is the average value of Yi samples, σXIs XiSample standard deviation, σyIs the standard deviation of Yi sample, XiAnd Yi can be protection fault recording data and centralized recording data respectively.
In a possible implementation manner, the obtaining a hidden fault early warning result by comparing the waveform correlations of the protection fault recording data and the concentrated recording data may include: acquiring the protection fault recording data and the waveform data of the centralized recording data; obtaining a correlation coefficient value according to the waveform data; under the condition that the correlation coefficient value does not exceed a second preset threshold value, judging the hidden fault in the current period and sending sampling abnormal alarm information; and the current hidden fault early warning result is a protection sampling abnormity early warning result.
For example, fig. 3 shows a flowchart of a protection sampling anomaly early warning method according to an embodiment of the present disclosure, as shown in fig. 3, after the start of fault recording, a fault recording start signal and fault recording waveform data are read through a fault information management station FIS, a correlation coefficient value is calculated according to the pearson correlation coefficient formula in combination with the concentrated recording waveform data, and whether an alarm is sent or not is determined according to the magnitude of the correlation coefficient value (i.e., the correlation between the fault recording waveform and the concentrated recording waveform), that is, no alarm is sent when the magnitude is greater than a preset threshold (e.g., the threshold is 0.90), otherwise, an anomaly alarm is sent. The waveform correlation effect of the protection fault recording data and the centralized recording data is shown in fig. 4 and 5, and fig. 4 is a schematic diagram of a correlation curve of the protection fault recording data and the centralized recording data according to an embodiment of the present disclosure; as shown in fig. 4, the curve in the graph shows that the calculated correlation coefficient is large, that is, the effect of small difference between the protection fault recording and the concentrated recording is obtained; FIG. 5 illustrates a schematic graph of a correlation curve between fault recording data and centralized recording data according to an embodiment of the present disclosure; as shown in fig. 5, the curve shows the effect of small calculated correlation coefficient, i.e. large difference between the protection fault recording and the concentrated recording.
In one possible implementation, the fault recording data may include: protecting the fault recording data and the centralized recording data, in step 30, obtaining a hidden fault early warning result according to the characteristic parameters may include: and obtaining a hidden fault early warning result by comparing the impact current in the protection fault recording data and/or the concentrated recording data with a first preset threshold value.
In the embodiment of the disclosure, whether the transformer has hidden danger or not is judged by analyzing whether the impact current is out of limit or not by utilizing the protection fault recording data and the centralized recording data. Wherein, the impact current is far larger than the normal working current. It should be noted that in the embodiment of the present disclosure, the impact current may be obtained through fault recording waveform data, or may be obtained through centralized recording waveform data; the impact current can be obtained through fault recording waveform data and concentrated recording waveform data at the same time, at the moment, the impact current obtained through the fault recording waveform data and the impact current obtained through the concentrated recording waveform data can be compared, and the larger of the two is selected as the impact current.
In a possible implementation manner, the obtaining of the hidden fault early warning result by comparing the impact current of the protection fault recording data and/or the centralized recording data includes: acquiring waveform data of the protection fault recording data and/or the centralized recording data; obtaining impact current according to the waveform data; under the condition that the impact current is larger than a first preset threshold value, judging a current hidden fault and sending main transformer near zone fault alarm information; and the current hidden fault early warning result is a main transformer near zone fault early warning result.
For example, fig. 6 shows a flowchart of a main transformer near-zone fault early warning method according to an embodiment of the present disclosure, and as shown in fig. 6, after the fault recording is started, a fault recording start signal and fault recording waveform data are read through a fault information management station FIS, and a recording current analysis is performed, that is, whether a recording current (impact current) is out of limit is determined, and if the recording current is greater than a certain proportion (for example, 40%) of an operating current, a transformer fault alarm is issued, otherwise, no alarm is issued.
Based on this, in the embodiment of the present disclosure, the obtained early warning result is further displayed, so that relevant personnel can conveniently check early warning information and relevant fault information in real time, and illustratively, 3 main human-machine interfaces of abnormal recording monitoring, protection starting abnormal monitoring and protection sampling abnormal monitoring can be designed and developed by using qt4.8.6distigner and C + + programming languages.
The abnormal recording monitoring method comprises the following steps that abnormal recording information is displayed on an abnormal recording monitoring interface in a mode of combining a geographical map and a table, the main content comprises failure time, failure equipment names, sampling abnormality and recording starting abnormality information, and the structure of an abnormal recording monitoring information table is shown in a table 1;
TABLE 1 abnormal recording monitoring information table structure
| Serial number | Name of field | Means of | |
|
| 1 | fault_time | Time of | datetime | |
| 2 | faultdevid | Faulty device ID | long | |
| 3 | faultdevname | Name of faulty device | char[256] | |
| 4 | absampling | Sampling anomalies | bool | |
| 5 | abrecstartup | Wave recording start up anomaly | bool |
On a protection starting abnormal monitoring interface, displaying information which is required to be started but not started of a near fault point in a mode of combining a geographical diagram and a table, wherein the main content comprises a monitoring station, a non-started wave recording device and a started wave recording device, and the structure of a protection starting abnormal event information table is shown in a table 2;
table 2 protection start exception event information table structure
| Serial number | Name of field | Means of | |
| 1 | stationid | Monitoring plant station ID | long |
| 2 | stationname | Monitoring plant names | char[256] |
| 3 | abrecid | Un-started wave recording device ID | long |
| 4 | abrecname | Name of device without starting recording | char[256] |
| 5 | recordid | Start recorder ID | long |
| 6 | recordname | Starting wave recording device name | char[256] |
And displaying protection sampling abnormal information on a protection starting sampling monitoring interface in a form of combining a table and a curve, wherein the main contents comprise a station, an interval name, a main protection device, a wave recorder name, an abnormal channel name and the like, and the structure of a protection sampling abnormal event information table is shown in a table 3.
Table 3 protection sampling abnormal event information table structure
| Serial number | Name of field | Means of | |
| 1 | stationid | Station ID | long |
| 2 | stationname | Station name | char[256] |
| 3 | bayname | Interval name | char[256] |
| 4 | master1name | Name of master protection device | char[256] |
| 5 | master2name | Name of primary and secondary protection device | char[256] |
| 6 | recordid | Recorder ID | long |
| 7 | recordname | Name of oscillograph | char[256] |
| 8 | abchannelid | Exception channel ID | long |
| 9 | abchannelname | Exception channel name | char[256] |
It should be noted that, although the hidden fault warning method based on protection initiation and associated recording analysis is described above by taking the above embodiment as an example, those skilled in the art can understand that the disclosure should not be limited thereto. In fact, the user can flexibly set each implementation mode according to personal preference and/or actual application scene, as long as the technical scheme of the disclosure is met.
Therefore, in the embodiment of the disclosure, the early warning of the protection starting of the near fault point, the early warning of the sampling abnormity and the early warning of the main transformer near zone fault are realized through the fault recording data; the application range and the application depth of fault recording starting data are expanded, and hidden faults of the protection device can be found in advance, so that the requirement of operation of the intelligent power grid is met.
Fig. 7 shows a structure diagram of a hidden fault warning device based on protection initiation and associated recording analysis according to an embodiment of the present disclosure; as shown in fig. 7, the apparatus may include: the fault recording data module 41 is used for acquiring fault recording data; a characteristic parameter module 42, configured to extract a characteristic parameter representing a state of a fault point from the fault recording data; and the hidden fault early warning module 43 is configured to obtain a hidden fault early warning result according to the characteristic parameter.
In one possible implementation, the fault recording data includes: protecting fault recording data, obtaining a hidden fault early warning result according to the characteristic parameters, wherein the hidden fault early warning module can comprise: the first near fault point protection starting early warning unit is used for obtaining the protection starting states of a near fault point and a far fault point according to a fault recording starting signal in the protection fault recording data; under the condition that the protection starting state of the far fault point is started, if the protection starting state of any near fault point is not started, judging the current hidden fault and sending abnormal alarm information; and the current hidden fault early warning result is a near fault point protection starting abnormity early warning result.
In one possible implementation, the fault recording data includes: protect trouble record ripples data, hide trouble early warning module can include: the second near fault point protection starting early warning unit is used for obtaining protection starting states of the first protection device and the second protection device based on the duplex configuration in the near fault point according to the fault recording starting signal in the protection fault recording data; under the condition that the protection starting states of the first protection device and the second protection device are different, judging a current hidden fault and sending abnormal alarm information; and the current hidden fault early warning result is a near fault point protection starting abnormity early warning result.
In one possible implementation, the fault recording data includes: protect trouble record ripples data and concentrate record ripples data, hide trouble early warning module can include: and the sampling abnormity early warning unit is used for obtaining a hidden fault early warning result by comparing the waveform correlation of the protection fault recording data and the concentrated recording data.
In one possible implementation, the fault recording data includes: protect trouble record ripples data and concentrate record ripples data, hide trouble early warning module can include: and the main transformer near-region fault early warning unit is used for obtaining a hidden fault early warning result by comparing the impact current in the protection fault recording data and/or the concentrated recording data with a first preset threshold value.
In a possible implementation manner, the sampling anomaly early-warning unit is specifically configured to: acquiring the protection fault recording data and the waveform data of the centralized recording data; obtaining a correlation coefficient value according to the waveform data; under the condition that the correlation coefficient value does not exceed a second preset threshold value, judging a current hidden fault and sending out sampling abnormal alarm information; and the current hidden fault early warning result is a protection sampling abnormity early warning result.
In a possible implementation manner, the main transformer near zone fault early warning unit is specifically configured to: acquiring waveform data of the protection fault recording data and/or the centralized recording data; obtaining impact current according to the waveform data; under the condition that the impact current is larger than a first preset threshold value, judging a current hidden fault and sending main transformer near zone fault alarm information; and the current hidden fault early warning result is a main transformer near zone fault early warning result.
It should be noted that, although the hidden fault warning apparatus based on protection initiation and associated recording analysis is described above by taking the above embodiment as an example, those skilled in the art can understand that the disclosure should not be limited thereto. In fact, the user can flexibly set each implementation mode according to personal preference and/or actual application scene, as long as the technical scheme of the disclosure is met.
Therefore, in the embodiment of the disclosure, the early warning of the protection starting of the near fault point, the early warning of the sampling abnormity and the early warning of the main transformer near zone fault are realized through the fault recording data; the application range and the application depth of fault recording starting data are expanded, and hidden faults of the protection device can be found in advance, so that the requirement of operation of the intelligent power grid is met.
Fig. 8 shows a block diagram of an apparatus 1900 for hidden fault warning based on protection initiation and associated recording analysis according to an embodiment of the present disclosure. For example, the apparatus 1900 may be provided as a server. Referring to FIG. 8, the device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by the processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.
The device 1900 may also include a power component 1926 configured to perform power management of the device 1900, a wired or wireless network interface 1950 configured to connect the device 1900 to a network, and an input/output (I/O) interface 1958. The device 1900 may operate based on an operating system stored in memory 1932, such as Windows Server, MacOS XTM, UnixTM, LinuxTM, FreeBSDTM, or the like.
In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 1932, is also provided that includes computer program instructions executable by the processing component 1922 of the apparatus 1900 to perform the above-described methods.
The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the 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 the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A hidden fault early warning method based on protection starting and associated recording analysis is characterized by comprising the following steps:
acquiring fault recording data;
extracting characteristic parameters representing the state of a fault point from the fault recording data;
and obtaining a hidden fault early warning result according to the characteristic parameters.
2. The method of claim 1, wherein the fault logging data comprises: protecting fault recording data, and obtaining a hidden fault early warning result according to the characteristic parameters, wherein the hidden fault early warning result comprises the following steps:
according to the fault recording starting signal in the protection fault recording data, obtaining the protection starting state of a near fault point and a far fault point;
under the condition that the protection starting state of the far fault point is started, if the protection starting state of any near fault point is not started, judging the current hidden fault and sending abnormal alarm information;
and the current hidden fault early warning result is a near fault point protection starting abnormity early warning result.
3. The method of claim 1, wherein the fault logging data comprises: protecting fault recording data, and obtaining a hidden fault early warning result according to the characteristic parameters, wherein the hidden fault early warning result comprises the following steps:
according to the fault recording starting signal in the protection fault recording data, obtaining the protection starting states of a first protection device and a second protection device based on double configuration in a near fault point;
under the condition that the protection starting states of the first protection device and the second protection device are different, judging a current hidden fault and sending abnormal alarm information;
and the current hidden fault early warning result is a near fault point protection starting abnormity early warning result.
4. The method of claim 1, wherein the fault logging data comprises: protecting fault recording data and concentrated recording data, and obtaining a hidden fault early warning result according to the characteristic parameters, wherein the hidden fault early warning result comprises the following steps:
and obtaining a hidden fault early warning result by comparing the waveform correlation of the protection fault recording data and the concentrated recording data.
5. The method of claim 1, wherein the fault logging data comprises: protecting fault recording data and concentrated recording data, and obtaining a hidden fault early warning result according to the characteristic parameters, wherein the hidden fault early warning result comprises the following steps:
and obtaining a hidden fault early warning result by comparing the impact current in the protection fault recording data and/or the concentrated recording data with a first preset threshold value.
6. The method of claim 4, wherein the comparing the waveform correlation of the protection fault recording data and the centralized recording data to obtain the hidden fault warning result comprises:
acquiring the protection fault recording data and the waveform data of the centralized recording data;
obtaining a correlation coefficient value according to the waveform data;
under the condition that the correlation coefficient value does not exceed a second preset threshold value, judging a current hidden fault and sending out sampling abnormal alarm information;
and the current hidden fault early warning result is a protection sampling abnormity early warning result.
7. The method according to claim 5, wherein the step of obtaining the hidden fault early warning result by comparing the magnitude of the impact current of the protection fault recording data and/or the centralized recording data comprises:
acquiring waveform data of the protection fault recording data and/or the centralized recording data;
obtaining impact current according to the waveform data;
under the condition that the impact current is larger than a first preset threshold value, judging a current hidden fault and sending main transformer near zone fault alarm information;
and the current hidden fault early warning result is a main transformer near zone fault early warning result.
8. The utility model provides a hide trouble early warning device based on protection is started and is correlated with record wave analysis which characterized in that includes:
the fault recording data module is used for acquiring fault recording data;
the characteristic parameter module is used for extracting characteristic parameters representing the state of a fault point from the fault recording data;
and the hidden fault early warning module is used for obtaining a hidden fault early warning result according to the characteristic parameters.
9. The utility model provides a hide trouble early warning device based on protection is started and is correlated with record wave analysis which characterized in that includes:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to implement the method of any one of claim 1 to claim 7 when executing the memory-stored executable instructions.
10. A non-transitory computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the method of any of claims 1 to 7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112285464A (en) * | 2020-10-13 | 2021-01-29 | 国网安徽省电力有限公司 | Power grid fault diagnosis method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012189392A (en) * | 2011-03-09 | 2012-10-04 | Hokkaido Electric Power Co Inc:The | Waveform recorder and fault point locating system |
| CN106950450A (en) * | 2017-04-18 | 2017-07-14 | 国家电网公司 | The method for early warning and equipment of protective relaying device secondary circuit failure |
| CN109655692A (en) * | 2018-12-28 | 2019-04-19 | 中国南方电网有限责任公司 | A kind of transient state same source data comparison method based on recorded wave file |
| CN110082614A (en) * | 2019-04-19 | 2019-08-02 | 中国南方电网有限责任公司超高压输电公司南宁局 | A kind of abnormal intelligent monitoring method of relay protection secondary circuit |
| US20190243735A1 (en) * | 2018-02-05 | 2019-08-08 | Wuhan University | Deep belief network feature extraction-based analogue circuit fault diagnosis method |
-
2019
- 2019-11-27 CN CN201911181546.0A patent/CN110956121A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012189392A (en) * | 2011-03-09 | 2012-10-04 | Hokkaido Electric Power Co Inc:The | Waveform recorder and fault point locating system |
| CN106950450A (en) * | 2017-04-18 | 2017-07-14 | 国家电网公司 | The method for early warning and equipment of protective relaying device secondary circuit failure |
| US20190243735A1 (en) * | 2018-02-05 | 2019-08-08 | Wuhan University | Deep belief network feature extraction-based analogue circuit fault diagnosis method |
| CN109655692A (en) * | 2018-12-28 | 2019-04-19 | 中国南方电网有限责任公司 | A kind of transient state same source data comparison method based on recorded wave file |
| CN110082614A (en) * | 2019-04-19 | 2019-08-02 | 中国南方电网有限责任公司超高压输电公司南宁局 | A kind of abnormal intelligent monitoring method of relay protection secondary circuit |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112285464A (en) * | 2020-10-13 | 2021-01-29 | 国网安徽省电力有限公司 | Power grid fault diagnosis method and system |
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