Bird damage fault diagnosis method, device and equipment and storage medium

Abstract

The invention discloses a bird damage fault diagnosis method and device, equipment and a storage medium. The method comprises the steps that fault associated information is determined, and the fault associated information comprises a plurality of first fault factors associated with bird damage fault occurrence; according to the current state of the first fault factor and a corresponding first preset weight, determining a to-be-determined bird damage fault probability; and if the to-be-determined bird damage fault probability is smaller than a preset threshold value, determining a target bird damage fault probability according to a current fault traveling wave and the to-be-determined bird damage fault probability. According to the technical scheme of the embodiment of the invention, the probability of the current bird trouble fault is accurately researched and judged, a large amount of economic cost does not need to be invested, and the method is less limited by weather and terrains.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission, and in particular to a bird damage fault diagnosis method, device, equipment and storage medium. Background Art

[0002] Currently, power transmission lines are facing a serious problem of bird damage. Birds such as magpies and crows often inhabit transmission lines. They not only build nests on the wires, but can also cause short circuit accidents. These birds damage transmission lines in a variety of ways, including pecking off the insulation of the wires and causing short circuits with the bird carcasses.

[0003] The installation of physical isolation facilities such as bird-proof spikes and bird-proof nets often has limitations and cannot completely solve the problem of bird damage. At present, common methods include visual inspection, infrared thermal imaging, and acoustic monitoring. Visual inspection relies on manual or drone line inspections, which can directly detect faults caused by bird nests or dead birds. Infrared thermal imaging technology is used to detect abnormal hot spots in the line to identify bird damage problems, which is suitable for inspections at night or in bad weather. The acoustic monitoring system can capture the sound of bird activities in real time and analyze its impact on power transmission equipment. It is efficient and all-weather.

[0004] However, visual inspection is inefficient and is subject to weather and terrain restrictions, infrared thermal imaging technology is expensive, and acoustic monitoring systems are expensive to install and maintain in the early stages. These methods all have their own limitations. Summary of the invention

[0005] The present invention provides a bird damage fault diagnosis method, device, equipment and storage medium to solve the limitations of traditional bird damage diagnosis methods.

[0006] In a first aspect, the present invention provides a method for diagnosing bird damage faults, comprising:

[0007] Determining fault association information, wherein the fault association information includes a plurality of first fault factors associated with the bird damage fault;

[0008] Determine the probability of a bird damage failure to be determined according to the current state of the first fault factor and the corresponding first preset weight;

[0009] If the to-be-determined bird damage fault probability is less than a preset threshold, the target bird damage fault probability is determined according to the current fault traveling wave and the to-be-determined bird damage fault probability.

[0010] In a second aspect, the present invention provides a bird damage fault diagnosis device, comprising:

[0011] A fault-related information determination module, used to determine fault-related information, wherein the fault-related information includes a plurality of first fault factors associated with the bird damage fault;

[0012] A failure probability determination module to be determined, used to determine the failure probability of bird damage to be determined according to the current state of the first failure factor and the corresponding first preset weight;

[0013] The target fault probability determination module is used to determine the target bird damage fault probability according to the current fault traveling wave and the bird damage fault probability to be determined if the to-be-determined bird damage fault probability is less than a preset threshold.

[0014] In a third aspect, the present invention provides an electronic device, the electronic device comprising:

[0015] at least one processor;

[0016] and a memory communicatively coupled to the at least one processor;

[0017] The memory stores a computer program executable by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the bird damage fault diagnosis method of the first aspect.

[0018] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer instructions, which are used to implement the bird damage fault diagnosis method of the first aspect when executed by a processor.

[0019] The bird damage fault diagnosis scheme provided by the present invention determines fault association information, wherein the fault association information includes multiple first fault factors associated with the occurrence of bird damage faults, and determines the probability of the bird damage fault to be determined according to the current state of the first fault factor and the corresponding first preset weight. If the probability of the bird damage fault to be determined is less than the preset threshold, the target bird damage fault probability is determined according to the current fault traveling wave and the probability of the bird damage fault to be determined. By adopting the above technical scheme, the probability of the current occurrence of the bird damage fault is preliminarily determined by using the factors associated with the occurrence of the bird damage fault that are mined. When the probability is small, the probability of the current occurrence of the bird damage fault is accurately determined according to the characteristics of the fault traveling wave and the probability, without investing a large amount of economic cost, and is less restricted by weather and terrain.

[0020] It should be understood that the content described in this section is not intended to identify the key or important features of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 is a flow chart of a bird damage fault diagnosis method provided according to Embodiment 1 of the present invention;

[0023] Figure 2 is a flow chart of a bird damage fault diagnosis method provided according to Embodiment 2 of the present invention;

[0024] Figure 3 is a structural schematic diagram of a bird damage fault diagnosis device provided according to Embodiment 3 of the present invention;

[0025] Figure 4 It is a schematic diagram of the structure of an electronic device provided according to Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In the description of the present invention, unless otherwise specified, "multiple" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] Embodiment 1

[0029] Figure 1 A flowchart of a bird damage fault diagnosis method is provided for the first embodiment of the present invention. This embodiment can be applied to determine the probability of a bird damage fault occurring in a transmission line. The method can be executed by a bird damage fault diagnosis device. The bird damage fault diagnosis device can be implemented in the form of hardware and / or software. The bird damage fault diagnosis device can be configured in an electronic device. The electronic device can be composed of two or more physical entities or one physical entity.

[0030] like Figure 1 As shown, the bird damage fault diagnosis method provided by the first embodiment of the present invention specifically includes the following steps:

[0031] S101. Determine fault association information, wherein the fault association information includes a plurality of first fault factors associated with a bird damage fault.

[0032] In this embodiment, the causes of bird damage failures and the characteristics after bird damage failures occur can be studied in advance, and factors associated with bird damage failures, i.e., first fault factors, can be mined based on expert experience or prior knowledge. For example, weather conditions and bird distribution in the current area, etc. The first fault factors include the cause factors that easily cause bird damage failures and the characteristic factors after bird damage failures occur.

[0033] S102: Determine a to-be-determined bird damage fault probability according to the current state of the first fault factor and the corresponding first preset weight.

[0034] In this embodiment, corresponding weights may be set in advance for different states of the first fault factor, that is, first preset weights may be set. Then, the probability of bird damage failure to be determined may be calculated based on the current state of each first fault factor and the preset weight corresponding to each state. For example, the values ​​of these weights may be added together, and the result obtained is the probability of bird damage failure to be determined. The first preset weight is usually less than 1.

[0035] S103: If the to-be-determined bird damage fault probability is less than a preset threshold, determine a target bird damage fault probability according to the current fault traveling wave and the to-be-determined bird damage fault probability.

[0036] In this embodiment, if the probability of bird damage failure to be determined is less than the preset threshold, it means that the state of the first fault factor does not meet the state that should be present when the bird damage failure occurs. The target bird damage failure probability can be determined based on the current fault traveling wave and the probability of bird damage failure to be determined. For example, the probability of bird damage failure can be predicted based on the current fault traveling wave, and then the predicted probability and the probability of bird damage failure to be determined are processed to obtain the target bird damage failure probability. For example, the predicted probability and the probability of bird damage failure to be determined are weighted and summed to obtain the target bird damage failure probability.

[0037] The bird damage fault diagnosis method provided by the embodiment of the present invention determines fault association information, wherein the fault association information includes multiple first fault factors associated with the occurrence of bird damage faults, and determines the probability of the bird damage fault to be determined according to the current state of the first fault factor and the corresponding first preset weight. If the probability of the bird damage fault to be determined is less than the preset threshold, the target bird damage fault probability is determined according to the current fault traveling wave and the probability of the bird damage fault to be determined. The technical solution of the embodiment of the present invention uses the factors associated with the occurrence of bird damage faults that have been mined to preliminarily determine the probability of the current occurrence of bird damage faults. When the probability is small, the probability of the current occurrence of bird damage faults is accurately determined based on the characteristics of the fault traveling wave and the probability, without investing a large amount of economic cost, and is less restricted by weather and terrain.

[0038] Optionally, before determining the probability of a bird damage fault to be determined based on the current state of the first fault factor and the corresponding first preset weight, it also includes: obtaining the current state of the first fault factor, and determining whether the state is invalid and / or missing; if so, receiving input information, and using the input information to correct and / or supplement the state to obtain an updated current state of the first fault factor, wherein the input information includes invalid and / or missing states.

[0039] Specifically, when the state of the first fault factor is invalid and / or missing, manually inputted entry information may be accepted to complete and / or correct the state of the first fault factor.

[0040] Optionally, the first fault factor in the fault-related information includes time, post-fault reclosing information, transmission line phase fault information, visualization information, preset bird damage level in the current area, meteorological information and line voltage level; wherein the preset bird damage level in the current area is the risk level of bird damage faults occurring in the current area, and the visualization information is the bird situation in the current area.

[0041] Specifically, through statistics and analysis, we can find that:

[0042] 1) Due to the habits of birds, bird damage failures frequently occur during certain time periods.

[0043] 2) After a bird-damaged fault occurs, there is a certain regularity in the reclosing of the transmission line.

[0044] 3) Under bird damage faults, there are certain regularities in the fault conditions of different transmission line phases.

[0045] 4) Bird damage is prone to occur under certain specific meteorological conditions, such as when there is no typhoon, heavy rain or strong wind and the weather is good.

[0046] 5) Lines of certain voltage levels are prone to bird damage.

[0047] 6) Areas with a large number of birds usually have a higher risk level of bird damage failures and are more likely to experience bird damage failures.

[0048] 7) When bird nests or other bird conditions are photographed around power transmission lines, bird damage is likely to occur.

[0049] Therefore, the current time, the reclosing situation after the current fault occurs, the fault conditions of different transmission lines, the visual information collected by the camera, the preset bird damage level in the area where the transmission line tower is located, the meteorological conditions and the voltage level of the transmission line are all related to whether the bird damage fault occurs.

[0050] Embodiment 2

[0051] Figure 2 This is a flow chart of a bird damage fault diagnosis method provided in the second embodiment of the present invention. The technical solution of the embodiment of the present invention is further optimized on the basis of the above-mentioned optional technical solutions, and a specific method for judging bird damage fault is given.

[0052] Optionally, the determining of the probability of a bird damage fault to be determined based on the current state of the first fault factor and the corresponding first preset weight includes: determining a first sum value of the first preset weight corresponding to the current state of the first fault factor, and determining fault elimination information, wherein the fault elimination information includes a plurality of second fault factors associated with eliminating bird damage faults; determining a second sum value of the second preset weight corresponding to the current state of the second fault factor, and determining the sum of the first sum value and the second sum value as the probability of a bird damage fault to be determined. The advantage of such a setting is that the probability of a bird damage fault (i.e., the first sum value) determined according to the weight of the fault association information is corrected using the fault elimination information, further ensuring the accuracy and reliability of line fault diagnosis.

[0053] Optionally, the determining of the target bird damage fault probability according to the current fault traveling wave and the to-be-determined bird damage fault probability includes: outputting the predicted bird damage fault probability according to the current fault traveling wave using a preset bird damage fault waveform identification model; and obtaining the target bird damage fault probability by performing a preset operation on the predicted bird damage fault probability and the to-be-determined bird damage fault probability. The advantage of such a setting is that the predicted bird damage fault probability under the current fault traveling wave is quickly predicted using the preset bird damage fault waveform identification model, and the probability of a bird damage fault occurring on the current line is accurately analyzed in combination with the to-be-determined bird damage fault probability.

[0054] Optionally, after determining the probability of bird damage failure to be determined based on the current state of the first fault factor and the corresponding first preset weight, it includes: if the probability of bird damage failure to be determined is greater than or equal to a preset threshold, determining the probability of bird damage failure to be determined as the target bird damage failure probability.

[0055] like Figure 2 As shown, a bird damage fault diagnosis method provided by Embodiment 2 of the present invention specifically includes the following steps:

[0056] S201. Determine fault-related information, wherein the fault-related information includes time, post-fault reclosing information, transmission line phase fault information, visualization information, preset bird damage level in the current area, meteorological information, and line voltage level.

[0057] The preset bird damage level of the current area is the risk level of bird damage failure in the current area, and the visualization information is the bird situation in the current area.

[0058] S202, obtaining the current state of the first fault factor, and determining whether the state is invalid and / or missing, if so, executing step 203, if not, executing step 204.

[0059] S203, receiving input information, and using the input information to correct and / or supplement the state to obtain an updated current state of the first fault factor, wherein the input information includes a failure and / or missing state.

[0060] S204: Determine a first sum value of a first preset weight corresponding to the current state of the first fault factor, and determine fault elimination information, wherein the fault elimination information includes a plurality of second fault factors associated with eliminating the bird damage fault.

[0061] Exemplarily, if the state of the first fault factor is:

[0062] The fault time is between 4 and 8 o'clock or between 17 o'clock and 22 o'clock, the reclosing is successful, the faulty transmission line phase is the upper phase or the middle phase, the visual information indicates that there is a bird or no abnormality, the faulty tower is located in the second-level or above bird-damaged area, there is no typhoon, rainstorm and strong wind disaster at present, and the faulty transmission line is not at the voltage level of ±800kV or ±1000kV. The first preset weight corresponding to "the fault time is between 4 and 8 o'clock or between 17 o'clock and 22 o'clock" is a, the first preset weight corresponding to "the reclosing is successful" is b, the first preset weight corresponding to "the faulty transmission line phase is the upper phase or the middle phase" is c, the first preset weight corresponding to "the visual information indicates that there is a bird or no abnormality" is d, the first preset weight corresponding to "the faulty tower is located in the second-level or above bird-damaged area" is e, the first preset weight corresponding to "there is no typhoon, rainstorm and strong wind disaster at present" is f, and the first preset weight corresponding to "the faulty transmission line is not at the voltage level of ±800kV or ±1000kV" is g. If a+b+c+d+e+f=X%, then the first sum is X%. The second fault factor in the fault elimination information may include line voltage level, meteorological information, post-fault reclosing information, phase-to-phase fault information, and high-resistance fault information.

[0063] S205: Determine a second sum value of a second preset weight corresponding to the current state of the second fault factor, and determine the sum of the first sum value and the second sum value as the to-be-determined bird damage fault probability.

[0064] Specifically, the preset weight corresponding to the state of the fault factor is usually a negative number.

[0065] Exemplarily, if the state of the second fault factor is at least one of the following:

[0066] The voltage level of the fault line is ±800kV or ±1000kV, a typhoon, heavy rain or strong wind disaster occurs, the reclosing fails, a phase-to-phase fault occurs, and a high-resistance fault occurs. If the second preset weight corresponding to "the voltage level of the fault line is ±800kV or ±1000kV" is A, the second preset weight corresponding to "a typhoon, heavy rain or strong wind disaster occurs" is B, the second preset weight corresponding to "reclosing fails" is C, the second preset weight corresponding to "a phase-to-phase fault occurs" is D, and the second preset weight corresponding to "a high-resistance fault occurs" is E. Among them, if A+B+C+D+E=-Y%<0, the second sum is -Y%. If the first sum is Z%, the probability of bird damage failure to be determined is Z%-Y%.

[0067] S206 , judging whether the to-be-determined bird damage failure probability is less than a preset threshold value, if so, executing step 207 , if not, executing step 209 .

[0068] Exemplarily, the preset threshold may be X% as mentioned above.

[0069] S207: Output a predicted probability of bird damage fault according to the current fault traveling wave using a preset bird damage fault waveform identification model.

[0070] Specifically, the current fault traveling wave may be input into a preset bird damage fault waveform identification model to obtain a predicted bird damage fault probability.

[0071] S208: Obtain a target bird damage failure probability by performing a preset operation on the predicted bird damage failure probability and the to-be-determined bird damage failure probability.

[0072] Exemplarily, a preset operation such as weighted summation, direct summation or averaging may be performed on the predicted bird damage failure probability and the bird damage failure probability to obtain a target bird damage failure probability.

[0073] Optionally, the method for determining the preset bird damage fault waveform identification model includes:

[0074] Acquire historical power grid fault data, wherein the historical power grid fault data includes time domain feature data and frequency domain feature data of bird damage fault traveling waves under multiple bird damage fault types; use oversampling technology to supplement the historical power grid fault data to obtain balanced training sample data; use the balanced training sample data and the deep forest algorithm to train the initial deep learning model to obtain a preset bird damage fault waveform recognition model.

[0075] Specifically, historical fault information can be collected first, and the information can be used to establish a line fault transient waveform database. Multiple characteristic parameters of fault traveling waves are extracted from the time domain and frequency domain, and these parameters are used to establish a bird damage fault waveform recognition model. The time domain characteristic data and frequency domain characteristic data of bird damage fault traveling waves under multiple bird damage fault types contained in the historical power grid fault data may be unbalanced data. Therefore, the SMOTE oversampling technology can be used to supplement the historical power grid fault data to obtain balanced training sample data. The initial deep learning model can be a multi-granularity cascade forest model. The multi-granularity cascade forest model includes multi-granularity scanning and cascade forest. The multi-granularity scanning part screens features to generate feature quantities that are more closely related to classification. The role of the cascade forest is to process sample features layer by layer to enhance the accuracy of the algorithm's pattern recognition. Each layer is equipped with one random forest and one completely random forest. The input data of the first layer of the cascade forest is a multi-dimensional vector spliced ​​by a multi-dimensional class vector of the random forest and a multi-dimensional vector of the completely random forest. After classification processing, two two-dimensional category vectors are obtained. Then, these two-dimensional category vectors are concatenated with the multidimensional initial feature vector to form a new multidimensional feature vector as the input of the second layer, and the same method is used. Finally, the category vectors output by the Nth layer are averaged, and the maximum value of the average value is output, which is the output predicted bird damage failure probability.

[0076] S209: Determine the to-be-determined bird damage failure probability as a target bird damage failure probability.

[0077] Exemplarily, when the to-be-determined bird damage failure probability = X%, it means that the state of the first fault factor satisfies the state when the bird damage failure occurs, and therefore the to-be-determined bird damage failure probability can be directly determined as the target bird damage failure probability.

[0078] The bird damage fault diagnosis method provided in the embodiment of the present invention uses the fault elimination information to correct the bird damage fault probability determined according to the weight of the fault association information, further ensuring the accuracy and reliability of the line fault diagnosis. When the probability is small, the preset bird damage fault waveform recognition model is used to quickly predict the predicted bird damage fault probability under the current fault traveling wave, and combined with the bird damage fault probability to be determined, the probability of the bird damage fault occurring in the current line is accurately analyzed.

[0079] Embodiment 3

[0080] Figure 3 This is a schematic diagram of the structure of a bird damage fault diagnosis device provided by Embodiment 3 of the present invention. Figure 3 As shown, the device includes: a fault association information determination module 301, a to-be-determined fault probability determination module 302, and a target fault probability determination module 303, wherein:

[0081] A fault-related information determination module, used to determine fault-related information, wherein the fault-related information includes a plurality of first fault factors associated with the bird damage fault;

[0082] A failure probability determination module to be determined, used to determine the failure probability of bird damage to be determined according to the current state of the first failure factor and the corresponding first preset weight;

[0083] The target fault probability determination module is used to determine the target bird damage fault probability according to the current fault traveling wave and the bird damage fault probability to be determined if the to-be-determined bird damage fault probability is less than a preset threshold.

[0084] The bird damage fault diagnosis device provided in the embodiment of the present invention uses the factors associated with the occurrence of bird damage faults to preliminarily determine the probability of the current bird damage fault occurring. When the probability is small, the probability of the current bird damage fault occurring is accurately determined based on the characteristics of the fault traveling wave and the probability, without investing a large amount of economic cost and with less restrictions on weather and terrain.

[0085] Optionally, the module for determining the failure probability to be determined includes:

[0086] A summing and elimination information determination unit, configured to determine a first sum value of a first preset weight corresponding to the current state of the first fault factor, and determine fault elimination information, wherein the fault elimination information includes a plurality of second fault factors associated with eliminating the bird damage fault;

[0087] The to-be-determined fault probability determination unit is used to determine a second sum value of a second preset weight corresponding to the current state of the second fault factor, and determine the sum of the first sum value and the second sum value as the to-be-determined bird damage fault probability.

[0088] Optionally, the device further comprises:

[0089] A judgment module, used for obtaining the current state of the first fault factor and judging whether the state is invalid and / or missing before determining the probability of bird damage fault to be determined according to the current state of the first fault factor and the corresponding first preset weight;

[0090] An update module is used to receive input information if the information returned by the judgment module is yes, and use the input information to correct and / or supplement the state to obtain an updated current state of the first fault factor, wherein the input information includes a failed and / or missing state.

[0091] Optionally, the target failure probability determination module includes:

[0092] A probability output unit is used to output a predicted probability of bird damage fault according to the current fault traveling wave by using a preset bird damage fault waveform identification model;

[0093] The target fault probability determination unit is used to obtain a target bird damage fault probability by performing a preset operation on the predicted bird damage fault probability and the to-be-determined bird damage fault probability.

[0094] Furthermore, the method for determining the preset bird damage fault waveform identification model includes: obtaining historical power grid fault data, wherein the historical power grid fault data includes time domain feature data and frequency domain feature data of bird damage fault traveling waves under multiple bird damage fault types; using oversampling technology to supplement the historical power grid fault data to obtain balanced training sample data; using balanced training sample data and deep forest algorithm to train the initial deep learning model to obtain the preset bird damage fault waveform identification model.

[0095] Furthermore, the first fault factor in the fault-related information includes time, post-fault reclosing information, transmission line phase fault information, visualization information, preset bird damage level of the current area, meteorological information and line voltage level; wherein the preset bird damage level of the current area is the risk level of bird damage faults occurring in the current area, and the visualization information is the bird situation in the current area.

[0096] Optionally, the device further comprises:

[0097] The bird damage fault probability determination module is used to determine the bird damage fault probability to be determined as the target bird damage fault probability after determining the bird damage fault probability to be determined according to the current state of the first fault factor and the corresponding first preset weight, if the bird damage fault probability to be determined is greater than or equal to a preset threshold.

[0098] The bird damage fault diagnosis device provided in the embodiment of the present invention can execute the bird damage fault diagnosis method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0099] Embodiment 4

[0100] Figure 4 A schematic diagram of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0101] like Figure 4 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0102] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0103] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as the bird damage fault diagnosis method.

[0104] In some embodiments, the bird damage fault diagnosis method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the bird damage fault diagnosis method described above can be performed. Alternatively, in other embodiments, the processor 41 can be configured to perform the bird damage fault diagnosis method in any other appropriate manner (for example, by means of firmware).

[0105] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0106] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0107] The computer device provided above can be used to execute the bird damage fault diagnosis method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0108] Embodiment 5

[0109] In the context of the present invention, a computer readable storage medium may be a tangible medium, wherein the computer executable instructions, when executed by a computer processor, are used to perform a bird damage fault diagnosis method, the method comprising:

[0110] Determining fault association information, wherein the fault association information includes a plurality of first fault factors associated with the bird damage fault;

[0111] Determine the probability of a bird damage failure to be determined according to the current state of the first fault factor and the corresponding first preset weight;

[0112] If the to-be-determined bird damage fault probability is less than a preset threshold, the target bird damage fault probability is determined according to the current fault traveling wave and the to-be-determined bird damage fault probability.

[0113] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or with an instruction execution system, device, or equipment or used in combination with an instruction execution system, device, or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0114] The computer device provided above can be used to execute the bird damage fault diagnosis method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0115] It is worth noting that in the above-mentioned embodiment of the bird damage fault diagnosis device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0116] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A bird damage fault diagnosis method, characterized in that: include: Determining fault association information, wherein the fault association information includes a plurality of first fault factors associated with whether a bird damage fault occurs; Determine the probability of a bird damage failure to be determined according to the current state of the first fault factor and the corresponding first preset weight; If the to-be-determined bird damage fault probability is less than a preset threshold, the target bird damage fault probability is determined according to the current fault traveling wave and the to-be-determined bird damage fault probability.

2. The method according to claim 1, characterized in that: The determining of the to-be-determined bird damage failure probability according to the current state of the first fault factor and the corresponding first preset weight includes: Determine a first sum value of a first preset weight corresponding to the current state of the first fault factor, and determine fault elimination information, wherein the fault elimination information includes a plurality of second fault factors associated with eliminating the bird damage fault; A second sum value of a second preset weight corresponding to the current state of the second fault factor is determined, and a sum value of the first sum value and the second sum value is determined as the bird damage fault probability to be determined.

3. The method according to claim 1, characterized in that Before determining the to-be-determined probability of bird damage failure according to the current state of the first fault factor and the corresponding first preset weight, the method further includes: Obtaining the current state of the first fault factor, and determining whether the state is invalid and / or missing; If so, receiving input information, and using the input information to correct and / or supplement the state to obtain an updated current state of the first fault factor, wherein the input information includes a failed and / or missing state.

4. The method according to any one of claims 1 to 3, characterized in that The step of determining the target bird damage fault probability according to the current fault traveling wave and the to-be-determined bird damage fault probability includes: The preset bird damage fault waveform identification model is used to output the predicted probability of bird damage fault according to the current fault traveling wave; By performing a preset operation on the predicted bird damage failure probability and the to-be-determined bird damage failure probability, a target bird damage failure probability is obtained.

5. The method according to claim 4, characterized in that The method for determining the preset bird damage fault waveform identification model includes: Acquire historical power grid fault data, wherein the historical power grid fault data includes time domain characteristic data and frequency domain characteristic data of bird damage fault traveling waves under multiple bird damage fault types; Using oversampling technology to supplement the historical power grid fault data to obtain balanced training sample data; The initial deep learning model is trained using balanced training sample data and the deep forest algorithm to obtain a preset bird damage fault waveform recognition model.

6. The method according to claim 1, characterized in that The first fault factor in the fault-related information includes time, post-fault reclosing information, transmission line phase fault information, visualization information, preset bird damage level in the current area, meteorological information and line voltage level; The preset bird damage level of the current area is the risk level of bird damage failure in the current area, and the visualization information is the bird situation in the current area.

7. The method according to claim 1, characterized in that After determining the probability of bird damage failure to be determined according to the current state of the first fault factor and the corresponding first preset weight, the method includes: If the to-be-determined bird damage failure probability is greater than or equal to a preset threshold, the to-be-determined bird damage failure probability is determined as a target bird damage failure probability.

8. A bird damage fault diagnosis device, characterized in that: include: A fault-related information determination module, used to determine fault-related information, wherein the fault-related information includes a plurality of first fault factors associated with the bird damage fault; A failure probability determination module to be determined, used to determine the failure probability of bird damage to be determined according to the current state of the first failure factor and the corresponding first preset weight; The target fault probability determination module is used to determine the target bird damage fault probability according to the current fault traveling wave and the bird damage fault probability to be determined if the to-be-determined bird damage fault probability is less than a preset threshold.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the bird damage fault diagnosis method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the bird damage fault diagnosis method according to any one of claims 1 to 7 when executed.

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