A method, device, equipment, medium and product for determining fault type

Abstract

The present invention discloses a method, device, equipment, medium and product for determining the fault type, including: obtaining the current line information of the transmission line, wherein the current line information includes at least line fault information, line ledger information, line operation and maintenance information, meteorological information and online monitoring information; determining the fault factor matching the current line information, and determining the fault type determination result of the transmission line according to the weight of the fault factor, wherein the fault factor includes a key factor and a regular factor, the regular factor includes a coupling factor and an exclusion factor, and the fault type determination result characterizes the probability that the fault type of the transmission line is a wind deviation fault. The above technical scheme can accurately analyze and locate whether the fault cause of the line is a wind deviation fault, and improve the accuracy and reliability of line fault diagnosis.

Description

Technical Field

[0001] The present invention relates to the field of computer technologies, and in particular, to a method, apparatus, device, medium, and product for determining a fault type. Background Art

[0002] A wind deviation fault of a transmission line refers to a phenomenon in which, under the action of strong wind, a transmission wire deflects or vibrates, resulting in a fault of the transmission line. This kind of fault is usually caused by multiple factors, including strong wind, wire aging, and unstable support structures. According to the severity of the fault, the wind deviation fault can be divided into types such as slight deviation, severe deviation, and fracture. These faults have a significant impact on the safety and reliability of power transmission. Slight wind deviation may lead to increased power loss, while severe wind deviation may even cause wire fracture, resulting in large-scale power outages. Therefore, preventing and promptly handling wind deviation faults of transmission lines is crucial for ensuring the stable operation of the power grid. Correspondingly, there is an urgent need for a method to determine whether the fault type of a transmission line is a wind deviation fault. Summary of the Invention

[0003] The present invention provides a method, apparatus, device, medium, and product for determining a fault type, which can accurately analyze and locate whether the cause of a line fault is a wind deviation fault, and improve the accuracy and reliability of line fault diagnosis.

[0004] In a first aspect, an embodiment of the present disclosure provides a method for determining a fault type, including:

[0005] Obtaining current line information of a transmission line, where the current line information at least includes line fault information, line ledger information, line operation and maintenance information, meteorological information, and online monitoring information;

[0006] Determining a fault factor that matches the current line information, and determining a fault type determination result of the transmission line according to the weight of the fault factor, where the fault factor includes a key factor and a rule factor, the rule factor includes a coupling factor and an exclusion factor, and the fault type determination result represents the probability that the fault type of the transmission line is a wind deviation fault.

[0007] In a second aspect, an embodiment of the present disclosure provides a device for determining a fault type, including:

[0008] A line information acquisition module, configured to obtain current line information of a transmission line, where the current line information at least includes line fault information, line ledger information, line operation and maintenance information, meteorological information, and online monitoring information;

[0009] A fault type determination module, configured to determine a fault factor that matches the current line information, and determine a fault type determination result of the transmission line according to the weight of the fault factor, where the fault factor includes a key factor and a regular factor, the regular factor includes a coupling factor and an exclusion factor, and the fault type determination result represents the probability that the fault type of the transmission line is a wind deviation fault.

[0010] In a third aspect, an embodiment of the present disclosure provides an electronic device, including:

[0011] At least one processor; and

[0012] A memory communicatively connected to the at least one processor; wherein,

[0013] 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 a fault type determination method provided in the first aspect embodiment above.

[0014] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, and the computer-readable storage medium stores computer instructions for causing a processor to implement a fault type determination method provided in the first aspect embodiment above when executed.

[0015] In a fifth aspect, an embodiment of the present disclosure provides a computer program product, the computer program product includes a computer program, and the computer program implements a fault type determination method provided in the first aspect embodiment above when executed by a processor.

[0016] A fault type determination method, apparatus, device, medium and product according to an embodiment of the present invention include obtaining current line information of a transmission line, where the current line information at least includes line fault information, line ledger information, line operation and maintenance information, meteorological information, and on-line monitoring information; determining a fault factor that matches the current line information, and determining a fault type determination result of the transmission line according to the weight of the fault factor, where the fault factor includes a key factor and a regular factor, the regular factor includes a coupling factor and an exclusion factor, and the fault type determination result represents the probability that the fault type of the transmission line is a wind deviation fault.

[0017] The above technical solution accurately analyzes and locates whether the fault cause of the line is a wind deviation fault, and improves the accuracy and reliability of line fault diagnosis.

[0018] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used 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

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0020] Figure 1 is a flowchart of a method for determining a fault type provided in Embodiment 1 of the present invention;

[0021] Figure 2 is a flowchart of a method for determining a fault type provided in Embodiment 2 of the present invention;

[0022] Figure 3 is a logical example diagram of a method for determining a fault type provided in Embodiment 2 of the present invention;

[0023] Figure 4 is a schematic structural diagram of a device for determining a fault type provided in Embodiment 3 of the present invention;

[0024] Figure 5 is a schematic structural diagram of an electronic device provided in Embodiment 4 of the present invention. Detailed Description of the Embodiments

[0025] In order to enable those skilled in the art to better understand the solutions of the present invention, the following clearly and completely describes the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0026] It should be noted that the terms "first", "second", "target", etc. in the specification and claims of the present invention and the above drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily need to be limited to those clearly listed steps or units, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0027] At present, the diagnostic techniques for wind deviation faults in transmission lines mainly include methods such as visual monitoring, acoustic wave detection, and vibration detection. Visual monitoring relies on high-definition cameras to capture the line status in real time and analyzes the wind deviation situation through image recognition technology. Its advantages are intuitiveness and easy understanding, but the disadvantages are high cost and susceptibility to adverse weather conditions. Acoustic wave detection uses the propagation characteristics of specific-frequency acoustic waves on transmission lines to detect wind deviation faults. This method is less affected by environmental interference, but requires complex equipment configuration and high technical support. Vibration detection technology captures vibration signals caused by wind through sensors installed on transmission lines, and then judges the degree of wind deviation. This method has high sensitivity, but the installation and maintenance costs are relatively high, and strict requirements are imposed on data analysis. Each method has its own advantages and disadvantages, and in practical applications, appropriate diagnostic techniques are usually selected according to specific environments and requirements.

[0028] Embodiment 1

[0029] Figure 1 FIG. is a flowchart of a method for determining a fault type provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of determining the probability that the fault cause of a transmission line is a wind deviation fault. This method can be executed by a fault type determination device, and the fault type determination device can be implemented in the form of hardware and / or software.

[0030] As Figure 1 shown, the method includes:

[0031] S101. Obtain the current line information of the transmission line, where the current line information at least includes line fault information, line ledger information, line operation and maintenance information, meteorological information, and online monitoring information.

[0032] In this embodiment, the current line information can be understood as the parameter information of the transmission line at the current moment, at least including line fault information, line ledger information, line operation and maintenance information, meteorological information, and online monitoring information;

[0033] Among them, the line fault information includes at least protection action information and distributed fault information. Among them, the protection action information includes at least fault time (in seconds), fault line, fault phase, reclosing situation, fault location measurement and line span information, fault recording waveform (in milliseconds) and line parameter information. Among them, the reclosing situation includes at least successful reclosing, unsuccessful reclosing and no action. The fault phase includes single-phase ground short circuit (A-phase single-phase ground short circuit, B-phase single-phase ground short circuit, C-phase single-phase ground short circuit), two-phase ground short circuit (AB two-phase ground short circuit, AC two-phase ground short circuit, BC two-phase ground short circuit), two-phase short circuit (AB two-phase short circuit, AC two-phase short circuit, BC two-phase short circuit) and three-phase short circuit (short circuit between ABC). Among them, two-phase short circuit and three-phase short circuit are interphase faults; the distributed fault information includes at least fault time (in milliseconds), fault line, fault phase, reclosing situation, fault tower and distributed fault waveform. Among them, the line fault information also includes that the fault content is tripping. The fault line includes line name and line voltage.

[0034] The line ledger information is obtained from the project management system and includes at least line span information, the location where the tower belongs, line design parameters, tower type, single- and double-circuit information on the same tower, tension and straight information, conductor arrangement method, phase sequence, pole type, insulator string suspension method, insulator material type, insulator operation time, whether to spray anti-pollution flashover material on the insulator, line commissioning time, line rated current, load rate, line parameter information and terrain information. Among them, the insulator string suspension method is the arrangement method of the insulator string on the line tower pole and includes at least single string, double string, I string (I-shaped string), V string (V-shaped string), inverted V string and four strings.

[0035] The line operation and maintenance information is obtained from the project management system and includes at least the line defect library, channel hidden danger library, tower grounding resistance, historical fault information and work ticket maintenance construction plan information.

[0036] The meteorological information is obtained from the power meteorological system and includes at least lightning monitoring data, meteorological disaster warning information, micro-meteorological monitoring data, meteorological station data, weather forecast and environmental thematic maps. Among them, the meteorological disaster warning information includes at least lightning disaster warning information, rainstorm disaster warning information, typhoon disaster warning information, strong wind disaster warning information, severe convective disaster warning information, icing disaster warning information, galloping disaster warning information, fog disaster warning information, geological disaster warning information and mountain fire disaster warning information; both the micro-meteorological monitoring data and the meteorological station data are meteorological monitoring data. The micro-meteorological monitoring data includes at least temperature, relative humidity, air pressure, 1h precipitation, maximum wind and wind direction; the meteorological station data includes at least temperature, humidity, air pressure, wind speed, wind direction and precipitation.

[0037] Online monitoring information is obtained through online monitoring devices on transmission lines, such as high-definition cameras, acoustic wave detectors, and vibration sensors, and at least includes visual alarm information, hidden danger discharge data, conductor icing thickness, conductor and ground wire galloping alarm information, aeolian vibration frequency and amplitude, temperature measurement values of conductors / fittings, leakage current information of insulators, wind deflection angle, and tower inclination alarm information.

[0038] S102. Determine the fault factors that match the current line information, and determine the fault type determination result of the transmission line according to the weights of the fault factors. Among them, the fault factors include key factors and regular factors, and the regular factors include coupling factors and exclusion factors. The fault type determination result represents the probability that the fault type of the transmission line is a wind deflection fault.

[0039] In this embodiment, the fault factors can be understood as fault factors related to wind deflection faults, and each fault factor has its corresponding weight. The fault type determination result can be understood as the determination result for the wind deflection fault type, representing the probability that the fault type of the transmission line is a wind deflection fault. The weights of the fault factors are directly related to the fault type determination result, and the weights of the fault factors are the probabilities that the fault type of the transmission line is a wind deflection fault. The fault factors include key factors and regular factors, and the regular factors include coupling factors and exclusion factors. Among them, the key factor can be understood as a factor that can directly determine that the fault type is a wind deflection fault, and the weight of the key factor is 100%, that is, 1; the regular factor can be understood as a factor that cannot directly determine the fault type determination result, but can obtain the fault type determination result through the interaction of the weights among multiple types of regular factors (weight addition), and the weight of the regular factor is less than 1; the coupling factor can be understood as a factor that has a positive impact on the fault type of wind deflection fault, and the weight of the coupling factor is greater than 0 and less than 1; the exclusion factor can be understood as a factor that has a negative impact on the fault type of wind deflection fault, and the weight of the coupling factor is greater than -1 and less than 0.

[0040] Among them, the key factors include at least one type, for example: meteorological disaster warning information is the first type of warning information + insulator string is I string + reclosing is unsuccessful + wind speed reaches the first preset value; among them, the first type of warning information includes any one of typhoon disaster warning information, severe convective disaster warning information, and strong wind disaster warning information.

[0041] Among them, the first type of warning information can be understood as a type of meteorological disaster warning information, and typhoon, severe convection, and strong wind can all be considered to be included in the first type. The first preset value can be understood as the wind speed preset in advance that can directly indicate that the transmission line has a wind deflection fault, for example, it is 18m / s.

[0042] Specifically, the current line information includes line fault information, line ledger information, line operation and maintenance information, meteorological information, and on-line monitoring information; the meteorological information includes meteorological warning disaster information and meteorological monitoring data, and the meteorological warning disaster information includes disaster warning information corresponding to lightning, heavy rain, typhoon, strong wind, severe convection, icing, galloping, fog, geological disasters, and mountain fires. The meteorological monitoring data includes at least temperature, relative humidity, air pressure, 1h precipitation, wind direction, air pressure, and wind speed; the line ledger information includes the suspension method of insulator strings, and the suspension methods of insulator strings include single string, double string, I string, V string, inverted V string, and four strings; the line fault information includes the reclosing situation, and the reclosing situation includes successful reclosing, unsuccessful reclosing, and no reclosing action.

[0043] When the meteorological warning disaster information is the disaster warning information corresponding to typhoon, severe convection, or strong wind, and the suspension method of the insulator string is I string, and the reclosing situation is unsuccessful reclosing, and the wind speed in the meteorological monitoring data reaches the first preset value, it is determined that the current line information can be matched with the key factor, and the fault type determination result is directly obtained based on the weight of the key factor of 100%, that is, the probability that the fault type of the transmission line is a wind deviation fault is 100%.

[0044] Among them, the coupling factors include at least one of the following:

[0045] a. The insulator string is I string, the reclosing is unsuccessful, and the wind speed reaches the first preset value;

[0046] b. The meteorological disaster warning information is the first type of warning information and the reclosing is unsuccessful;

[0047] c. The meteorological disaster warning information is the first type of warning information and the insulator string is I string;

[0048] d. The meteorological disaster warning information is the second type of warning information, where the second type of warning information includes typhoon disaster warning information or severe convection disaster warning information;

[0049] e. The insulator string is I string;

[0050] f. The reclosing is unsuccessful;

[0051] g. The wind speed reaches the second preset value;

[0052] h. The fault time is in the preset season;

[0053] i. One-hour continuous fault tripping;

[0054] j. The wind deviation angle is greater than the design value.

[0055] Among them, the second type of warning information can be understood as a kind of meteorological disaster warning information, and both typhoons and severe convections can be considered to be included in the second type. The second preset value can be understood as the wind speed preset in advance that can indirectly indicate that the transmission line has a wind deviation fault, such as 15 m / s. The preset season can be understood as the time preset in advance that can indirectly indicate that the transmission line has a wind deviation fault, such as May to September. The design value is the wind deviation angle preset in advance that can indirectly indicate that the transmission line has a wind deviation fault, and the specific angle is determined according to actual needs, and this embodiment does not limit it.

[0056] It can be understood that each type of coupling factor has its corresponding weight. When the current line information matches a certain type of coupling factor, the probability that the transmission line has a wind deviation fault is related to the weight of this type of coupling factor; among them, the weight of the a type of coupling factor is 90%, the weight of the b type of coupling factor is 90%, the weight of the c type of coupling factor is 80%, the weight of the d type of coupling factor is 60%, the weight of the e type of coupling factor is 15%, the weight of the f type of coupling factor is 20%, the weight of the g type of coupling factor is 50%, the weight of the h type of coupling factor is 30%, the weight of the i type of coupling factor is 20%, and the weight of the j type of coupling factor is 20%.

[0057] It can be understood that multiple types of coupling factors can interact with each other. For example, when the current line information simultaneously meets multiple types (at least two types) of coupling factors, further analysis of the fault type determination result is carried out based on the sum of the weights of these at least two types of coupling factors.

[0058] Specifically, if the current line information matches at least one type of coupling factor, further analysis of the wind deviation probability is carried out based on the weight of the coupling factor to determine the fault type determination result of the transmission line.

[0059] Exemplarily, the line fault information in the current line information includes the fault time and the fault content, and the fault content includes at least tripping. Based on the fault time, it can be determined whether the fault time is within the preset season. Based on the fault time and the fault content, it can be determined whether there is a situation of continuous tripping for one hour in the fault of the transmission line. If the current line information simultaneously meets that the fault time is within the preset season and continuous tripping for one hour, further analysis and processing are carried out based on their corresponding weight sum of 50% to obtain the fault type determination result and determine the probability that the fault type of the transmission line is a wind deviation fault.

[0060] Among them, the exclusion factors include at least one of the following:

[0061] k. The insulator string is a V string;

[0062] l. Phase-to-phase fault;

[0063] m. The line voltage is the preset voltage value.

[0064] Among them, the preset season can be understood as the preset wind deviation fault voltage, for example, it can be 1000 kV or ±800 kV.

[0065] It can be understood that each type of exclusion factor has its corresponding weight. When the current line information matches a certain type of exclusion factor, the probability that the transmission line is a wind deviation fault is related to the weight of this type of exclusion factor; among them, the weight of the k-type exclusion factor is -80%, the weight of the l-type exclusion factor is -60%, and the weight of the m-type exclusion factor is -40%.

[0066] It can be understood that multiple types of exclusion factors can interact with each other. For example, when the current line information simultaneously meets multiple types (at least two types) of exclusion factors, further analysis of the fault type determination result is performed based on the sum of the weights of these at least two types of exclusion factors.

[0067] Specifically, if the current line information matches at least one type of exclusion factor, further analysis of the wind deviation probability is performed based on the weight of the exclusion factor to determine the fault type determination result of the transmission line.

[0068] Exemplarily, if at least one of the fault phase in the line fault information in the current line information is an interphase fault, the line voltage corresponding to the fault line is the preset voltage value, and the suspension method of the insulator string is a V-string, it is determined that the current line information matches the exclusion factor.

[0069] It can be understood that the matching analysis of the exclusion factor is after the matching analysis of the coupling factor. That is, first determine whether the current line information matches the key factor. If it matches, directly determine that the fault type of the transmission line is a wind deviation fault. If it does not match, then determine whether the current line information matches the coupling factor. If it matches, based on the weights (or the sum of the weights) of the various matching coupling factors, determine the initial probability that the fault type of the transmission line is a wind deviation fault; then determine whether the current line information matches the exclusion factor. If it does not match, further analyze the fault type determination result for this initial probability. If it matches, take the weights (or the sum of the weights) of the various matching exclusion factors to determine the negative probability that the fault type of the transmission line is a wind deviation fault, calculate the sum value of the initial probability and the negative probability to obtain the intermediate probability, and finally further analyze the fault type determination result for this intermediate probability to obtain the final wind deviation probability (the probability that the fault type of the transmission line is a wind deviation fault).

[0070] A method for determining a fault type provided by an embodiment of the present invention includes obtaining current line information of a transmission line, where the current line information at least includes line fault information, line ledger information, line operation and maintenance information, meteorological information, and on-line monitoring information; determining a fault factor that matches the current line information, and determining a fault type determination result of the transmission line according to the weight of the fault factor, where the fault factor includes a key factor and a regular factor, the regular factor includes a coupling factor and an exclusion factor, and the fault type determination result represents the probability that the fault type of the transmission line is a wind deviation fault. The above technical solution combines the factor correlation rule criterion of the fault type to accurately analyze and locate whether the fault cause of the line is a wind deviation fault, improving the accuracy and reliability of line fault diagnosis.

[0071] As a first alternative embodiment of this embodiment, the method further includes:

[0072] Obtaining historical wind deviation fault information, performing data analysis on the historical wind deviation fault information to obtain key factors, coupling factors, and exclusion factors corresponding to the wind deviation fault, as well as the weights of the key factors, the weights of various coupling factors, and the weights of various exclusion factors.

[0073] In this embodiment, the historical wind deviation fault information can be understood as the information corresponding to the transmission line when a fault occurs and the fault type is wind deviation within the historical time, at least including the historical line information corresponding to the wind deviation fault. It can be understood that the historical line information represents the relevant information of the transmission line within the historical time, which is equivalent to the current line information at the historical moment.

[0074] Specifically, integrating the historical wind deviation fault information, establishing a fault factor library, dividing the historical wind deviation fault information entering the fault factor library through a classification algorithm, sorting out key factors with a weight of 100% that can directly determine the fault type as a wind deviation fault, and regular factors with a weight less than 100% that can indirectly determine the fault type as a wind deviation fault; further analyzing the regular factors to determine the coupling factors that have a positive impact on determining the fault type as a wind deviation fault and their weights, and the exclusion factors that have a negative impact and their weights. Among them, the classification algorithms used include, but are not limited to, the principal component analysis method, the analytic hierarchy process, the entropy weight method, and the regression analysis method. In addition, the weights corresponding to various fault factors are dynamically adjusted and updated based on the multi-modal learning method, further improving the accuracy and reliability of line fault diagnosis.

[0075] Embodiment Two

[0076] Figure 2The figure is a flowchart of a fault type determination method provided in the second embodiment of the present invention. This embodiment is a further optimization of any of the above embodiments and is applicable to the situation of determining the probability that the fault cause of a transmission line is a wind deviation fault. This method can be executed by a fault type determination device, which can be implemented in the form of hardware and / or software.

[0077] As Figure 2 shown, the method includes:

[0078] S201. Obtain the current line information of the transmission line.

[0079] S202. Determine the fault factors that match the current line information.

[0080] S203. If the fault factor that matches the current line information is a key factor, determine that the fault type of the transmission line is a wind deviation fault, and the weight of the key factor is 1.

[0081] In this embodiment, Figure 3 is a logical example diagram of a fault type determination method provided in the second embodiment of the present invention. As Figure 3 shown, if the current line information meets the key factor, or the current line information meets all the fault factors corresponding to the wind deviation fault, it can be directly determined that the fault type of the transmission line is a wind deviation fault, that is, the probability of determining that the fault type of the transmission line is a wind deviation fault is also 100%.

[0082] Exemplarily, if the current line information meets "the meteorological disaster warning information is the first type of warning information, the insulator string is the I string, the reclosing is unsuccessful, and the wind speed reaches the first preset value", it is determined that the current line information matches the key factor, and based on the weight of 100% of the key factor, it is directly determined that the fault type of the transmission line is a wind deviation fault.

[0083] S204. If the fault factor that matches the current line information is a regular factor, obtain a reference factor, and determine the first wind deviation probability according to the weight of the regular factor and the weight of the reference factor, where the weight of the coupling factor in the regular factor is a positive value, and the weight of the exclusion factor in the regular factor is a negative value.

[0084] In this embodiment, the first wind deviation probability can be understood as the probability value of the fault type being a wind deviation fault based on the weights of various regular factors corresponding to the current line information, which is an intermediate probability in the overall fault type determination process. The first wind deviation probability is also the intermediate probability described in step S102 of the above embodiment.

[0085] In this embodiment, since there may be time delays or data loss during the transmission of information on the transmission line, the currently obtained line information for the transmission line may be incomplete information compared to the actual situation on the transmission line. Therefore, it is necessary for the operator to determine this missing part of the information, that is, the reference line information, and match the reference factors corresponding to these reference line information and the weights of the reference factors from the fault factor library. The reference factors and the weights of the reference factors are used as inputs. It can be understood that the reference factors may be coupling factors or negative factors. Correspondingly, their weights may be positive or negative, and the specific situation is determined based on the actual content of the reference factors.

[0086] Specifically, as Figure 3 shown, if the fault factor matched with the current line information is a specific regular factor (coupling factor and / or negative factor), then the reference factor and the weight of the reference factor are obtained. If the matched fault factor only contains coupling factors, then calculate the sum of the weights corresponding to the coupling factors and the weights corresponding to the reference factors, and use this weight sum value as the first wind deflection probability. If the matched fault factor contains both coupling factors and exclusion factors, then calculate the sum of the weights corresponding to the coupling factors and the weights corresponding to the reference factors, and then calculate the sum of this sum value and the weight corresponding to the negative factor, and use this weight sum value as the first wind deflection probability, where the weight of the coupling factor is positive and the weight of the negative factor is negative, and the weight of the reference factor can be positive or negative. If the matched fault factor only contains negative factors, then calculate the sum of the weights corresponding to the reference factors and the weights corresponding to the negative factors, and use this weight sum value as the first wind deflection probability.

[0087] S205. Determine the fault type determination result of the transmission line according to the product of the first wind deflection probability and the second wind deflection probability corresponding to the distributed waveform of the current line information.

[0088] In this embodiment, the second wind deflection probability can be understood as the weight value corresponding to the distributed fault waveform in the current line information.

[0089] Specifically, based on the self-learning diagnosis technology of fault transient traveling wave characteristics, by collecting historical fault information (the historical fault information is the full type of fault information of the transmission line, not limited to the fault information of wind deflection faults), a line fault transient waveform data set is established. Several characteristic parameters of the fault traveling wave are extracted from three aspects: time domain, frequency domain, and time-frequency domain. A fault waveform identification model is established. Based on this model, the current line information is identified, and the type of the distributed fault waveform in the current line information and the weight (second wind deflection probability) corresponding to this type are determined. Then as Figure 3 shown, calculate the product of the first wind deflection probability and the second wind deflection probability to obtain the final probability that the fault type of the transmission line is a wind deflection fault, that is, the fault type determination result.

[0090] Among them, for the content of fault traveling wave extraction, by way of example: a total of 3,415 fault traveling waves are collected, including 994 lightning strikes and 2,421 non-lightning strikes; for the time-frequency domain feature extraction of fault waveforms, it includes 16 time-domain features, 13 frequency-domain features, 6 information fusion (Entropy Weighted Fusion, EWF) component information entropy, weighted energy entropy, EWF4 sample entropy, and EWF1 root mean square value, etc., a total of 38 eigenvalue, and classification and identification research is carried out through traditional binary classification methods, deep learning methods, and combined with the Synthetic Minority Over-sampling Technique (SMOTE) method; for unbalanced sample data, a fault waveform wind deviation identification model based on deep forest and SMOTE algorithms is proposed.

[0091] A fault type determination method provided by an embodiment of the present invention includes obtaining current line information of a transmission line; determining a fault factor matching the current line information; if the fault factor matching the current line information is a key factor, determining that the fault type of the transmission line is a wind deviation fault, and the weight of the key factor is 1; if the fault factor matching the current line information is a regular factor, obtaining a reference factor, and determining a first wind deviation probability according to the weight of the regular factor and the weight of the reference factor, where the weight of the coupling factor in the regular factor is a positive value, and the weight of the exclusion factor in the regular factor is a negative value; determining the fault type determination result of the transmission line according to the product of the first wind deviation probability and the second wind deviation probability of the distributed waveform corresponding to the current line information. The above technical solution combines the wind deviation fault waveform feature data and the factor correlation rule criterion of the fault type to accurately analyze and locate whether the fault cause of the line is a wind deviation fault, improving the accuracy and reliability of line fault diagnosis.

[0092] Embodiment III

[0093] Figure 4 It is a schematic structural diagram of a fault type determination device provided by Embodiment III of the present invention. As Figure 4 shown, the device includes:

[0094] A line information acquisition module 31, configured to acquire current line information of a transmission line, where the current line information at least includes line fault information, line ledger information, line operation and maintenance information, meteorological information, and on-line monitoring information;

[0095] A fault type determination module 32, configured to determine a fault factor that matches the current line information, and determine a fault type determination result of the transmission line according to the weight of the fault factor, where the fault factor includes a key factor and a regular factor, the regular factor includes a coupling factor and an exclusion factor, and the fault type determination result represents the probability that the fault type of the transmission line is a wind deviation fault.

[0096] The fault type determination device adopted in this technical solution can accurately analyze and locate whether the fault cause of the line is a wind deviation fault, improving the accuracy and reliability of line fault diagnosis.

[0097] Optionally, the key factor at least includes:

[0098] The meteorological disaster warning information is the first type of warning information, the insulator string is an I string, the reclosing is unsuccessful and the wind speed reaches a first preset value;

[0099] Wherein, the first type of warning information includes any one of typhoon disaster warning information, severe convective disaster warning information, and strong wind disaster warning information.

[0100] Optionally, the coupling factor includes at least one of the following:

[0101] The insulator string is an I string, the reclosing is unsuccessful and the wind speed reaches a first preset value;

[0102] The meteorological disaster warning information is the first type of warning information and the reclosing is unsuccessful;

[0103] The meteorological disaster warning information is the first type of warning information and the insulator string is an I string;

[0104] The meteorological disaster warning information is the second type of warning information, where the second type of warning information includes typhoon disaster warning information or severe convective disaster warning information;

[0105] The insulator string is an I string;

[0106] The reclosing is unsuccessful;

[0107] The wind speed reaches a second preset value;

[0108] The fault time is in a preset season;

[0109] Continuous fault tripping within one hour;

[0110] The wind deviation angle is greater than the design value.

[0111] Optionally, the exclusion factor includes at least one of the following:

[0112] The insulator string is a V string;

[0113] Phase-to-phase fault;

[0114] The line voltage is a preset voltage value.

[0115] Optionally, the fault type determination module 32 is specifically configured to:

[0116] If the fault factor matching the current line information is a key factor, determine that the fault type of the transmission line is a wind deviation fault, and the weight of the key factor is 1;

[0117] If the fault factor matching the current line information is a regular factor, obtain a reference factor, and determine a first wind deviation probability according to the weight of the regular factor and the weight of the reference factor, where the weight of the coupling factor in the regular factor is a positive value, and the weight of the exclusion factor in the regular factor is a negative value;

[0118] Determine the fault type determination result of the transmission line according to the product of the first wind deviation probability and the second wind deviation probability of the distributed waveform corresponding to the current line information.

[0119] Optionally, the device further includes a fault factor determination module, configured to:

[0120] Obtain historical wind deviation fault information, perform data analysis on the historical wind deviation fault information, and obtain a key factor, a coupling factor, and an exclusion factor corresponding to the wind deviation fault, as well as the weight of the key factor, the weights of various coupling factors, and the weights of various exclusion factors.

[0121] The fault type determination device provided by the embodiments of the present invention can execute the fault type determination method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0122] Embodiment 4

[0123] Figure 5 It is a schematic structural diagram of an electronic device provided by Embodiment 4 of the present invention. 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 processors, 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 only examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0124] Such as Figure 5As shown, the electronic device 40 includes at least one processor 41 and a memory communicatively connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc. Among them, the memory stores a computer program executable by the at least one processor. The processor 41 can execute 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 into 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. The input / output (I / O) interface 45 is also connected to the bus 44.

[0125] Multiple 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 magnetic disk, an optical disc, 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.

[0126] The processor 41 can be various general-purpose and / or special-purpose 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 dedicated 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 fault type determination method.

[0127] In some embodiments, the fault type determination method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed onto 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 fault type determination method described above can be executed. Alternatively, in other embodiments, the processor 41 can be configured to execute the fault type determination method by any other appropriate means (e.g., by means of firmware).

[0128] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), systems on chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0129] The computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0130] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, 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), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0131] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0132] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0133] The computing system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0134] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0135] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for determining a fault type, characterized in that: include: Acquire current line information of the transmission line, wherein the current line information at least includes line fault information, line ledger information, line operation and maintenance information, meteorological information and online monitoring information; Determine a fault factor that matches the current line information, and determine a fault type determination result of the transmission line according to the weight of the fault factor, wherein the fault factor includes a key factor and a regular factor, the regular factor includes a coupling factor and an exclusion factor, and the fault type determination result represents the probability that the fault type of the transmission line is a windage fault; Wherein, determining the result of the fault type of the transmission line according to the weight of the fault factor includes: If the fault factor matching the current line information is a key factor, it is determined that the fault type of the transmission line is a wind deviation fault, and the weight of the key factor is 1; If the fault factor matching the current line information is a regular factor, obtain a reference factor, and determine a first windage probability according to a weight of the regular factor and a weight of the reference factor, wherein the weight of the coupling factor in the regular factor is a positive value, and the weight of the exclusion factor in the regular factor is a negative value; Determine a fault type determination result of the transmission line according to the product of the first wind deviation probability and the second wind deviation probability of the distributed waveform corresponding to the current line information; Wherein, if the fault factor matching the current line information is a regular factor, obtaining a reference factor, and determining a first windage probability according to a weight of the regular factor and a weight of the reference factor include: If the fault factor matching the current line information is a regular factor, then the reference factor and the weight of the reference factor are obtained; If the regularity factor only includes the coupling factor, the sum of the weight corresponding to the coupling factor and the weight corresponding to the reference factor is calculated, and the sum of the weights is used as the first wind deviation probability; If the regularity factor includes both a coupling factor and an exclusion factor, a sum of a weight corresponding to the coupling factor and a weight corresponding to the reference factor is calculated, and then a sum of the sum and the weight corresponding to the exclusion factor is calculated, and the weight sum is used as a first wind deviation probability; If the regularity factor only includes the exclusion factor, the sum of the weight corresponding to the reference factor and the weight corresponding to the exclusion factor is calculated, and the sum of the weights is used as the first wind deviation probability; The key factors include at least: The meteorological disaster warning information is the first type of warning information, the insulator string is I string, the reclosing is unsuccessful, and the wind speed reaches the first preset value; The first type of warning information includes any one of typhoon disaster warning information, severe convective disaster warning information and gale disaster warning information; The coupling factor includes at least one of the following: The insulator string is I string, the reclosing is unsuccessful, and the wind speed reaches a first preset value; The meteorological disaster warning information is the first type of warning information and the reclosing is unsuccessful; The meteorological disaster warning information is the first type of warning information and the insulator string is I string; The meteorological disaster warning information is the second type of warning information, wherein the second type of warning information includes typhoon disaster warning information or severe convective disaster warning information; The insulator string is I string; Reclosing failed; The wind speed reaches a second preset value; The failure time is in the preset season; One hour continuous fault tripping; The wind angle is greater than the design value; The exclusion factors include at least one of the following: The insulator string is a V string; Phase-to-phase fault; The line voltage is the preset voltage value.

2. The method according to claim 1, characterized in that Also includes: Obtain historical windage fault information, perform data analysis on the historical windage fault information, and obtain key factors, coupling factors and exclusion factors corresponding to the windage fault, as well as weights of the key factors, weights of various coupling factors and weights of various exclusion factors.

3. A fault type determination device, characterized in that: include: A line information acquisition module is used to acquire current line information of a transmission line, wherein the current line information at least includes line fault information, line ledger information, line operation and maintenance information, meteorological information, and online monitoring information; A fault type determination module, used to determine a fault factor matching the current line information, and determine a fault type determination result of the transmission line according to the weight of the fault factor, wherein the fault factor includes a key factor and a regular factor, the regular factor includes a coupling factor and an exclusion factor, and the fault type determination result represents the probability that the fault type of the transmission line is a wind deviation fault; Wherein, the fault type determination module is specifically used to: If the fault factor matching the current line information is a key factor, it is determined that the fault type of the transmission line is a wind deviation fault, and the weight of the key factor is 1; If the fault factor matching the current line information is a regular factor, obtain a reference factor, and determine a first windage probability according to a weight of the regular factor and a weight of the reference factor, wherein the weight of the coupling factor in the regular factor is a positive value, and the weight of the exclusion factor in the regular factor is a negative value; Determine a fault type determination result of the transmission line according to the product of the first wind deviation probability and the second wind deviation probability of the distributed waveform corresponding to the current line information; Wherein, if the fault factor matching the current line information is a regular factor, obtaining a reference factor, and determining a first windage probability according to a weight of the regular factor and a weight of the reference factor include: If the fault factor matching the current line information is a regular factor, then the reference factor and the weight of the reference factor are obtained; If the regularity factor only includes the coupling factor, the sum of the weight corresponding to the coupling factor and the weight corresponding to the reference factor is calculated, and the sum of the weights is used as the first wind deviation probability; If the regularity factor includes both a coupling factor and an exclusion factor, a sum of a weight corresponding to the coupling factor and a weight corresponding to the reference factor is calculated, and then a sum of the sum and the weight corresponding to the exclusion factor is calculated, and the weight sum is used as a first wind deviation probability; If the regularity factor only includes the exclusion factor, the sum of the weight corresponding to the reference factor and the weight corresponding to the exclusion factor is calculated, and the sum of the weights is used as the first wind deviation probability; The key factors include at least: The meteorological disaster warning information is the first type of warning information, the insulator string is I string, the reclosing is unsuccessful, and the wind speed reaches the first preset value; The first type of warning information includes any one of typhoon disaster warning information, severe convective disaster warning information and gale disaster warning information; The coupling factor includes at least one of the following: The insulator string is I string, the reclosing is unsuccessful, and the wind speed reaches a first preset value; The meteorological disaster warning information is the first type of warning information and the reclosing is unsuccessful; The meteorological disaster warning information is the first type of warning information and the insulator string is I string; The meteorological disaster warning information is the second type of warning information, wherein the second type of warning information includes typhoon disaster warning information or severe convective disaster warning information; The insulator string is I string; Reclosing failed; The wind speed reaches a second preset value; The failure time is in the preset season; One hour continuous fault tripping; The wind angle is greater than the design value; The exclusion factors include at least one of the following: The insulator string is a V string; Phase-to-phase fault; The line voltage is the preset voltage value.

4. An electronic device, characterized in that: include: at least one processor; as well as 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 a fault type determination method according to any one of claims 1 to 2.

5. 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 a fault type determination method according to any one of claims 1 to 2 when executed.

6. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program implements a fault type determination method according to any one of claims 1-2.

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