CN113591013A - Service life estimation method and system for traction substation equipment and storage medium - Google Patents
Service life estimation method and system for traction substation equipment and storage medium Download PDFInfo
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Abstract
本申请提供了一种牵引变电所设备寿命估算方法、估算系统及存储介质，估算方法包括：采集牵引变电所中关键设备的数据；从采集的牵引变电所中关键设备的数据中获取寿命估算所需数据；根据设备的寿命估算所需数据对设备的寿命进行估算，设备的估算寿命为：设备的估算寿命＝设备的理论剩余寿命年*寿命估算系数，设备的理论剩余寿命年为：设备的理论剩余寿命年＝(出厂设定的设备属性分合总次数‑设备的总动作次数)/出厂设定的设备属性分合总次数*设备出厂寿命年限；设备的总动作次数为：总动作次数＝分合次数‑分闸失败次数+电流速断跳闸次数×预设系数。本申请能够结合设备的真实数据对牵引变电所设备的寿命进行准确地估算。
The present application provides a method, an estimation system and a storage medium for estimating equipment life of a traction substation. The estimation method includes: collecting data of key equipment in the traction substation; obtaining data from the collected data of the key equipment in the traction substation The data required for life estimation; estimate the life of the equipment according to the data required for the life estimation of the equipment. The estimated life of the equipment is: the estimated life of the equipment = the theoretical remaining life years of the equipment * the life estimation coefficient, and the theoretical remaining life years of the equipment is : Theoretical remaining life years of the equipment = (the total number of times of opening and closing of the equipment attributes set by the factory - the total number of actions of the equipment) / the total times of opening and closing of the equipment attributes set by the factory * the life of the equipment leaving the factory; the total number of times of the equipment operation is: The total number of actions = the number of opening and closing - the number of failures to open + the number of current quick-break trips × preset coefficient. The present application can accurately estimate the service life of the traction substation equipment in combination with the real data of the equipment.
Description
Technical Field
The application belongs to the technical field of power substations, and particularly relates to a traction substation equipment life estimation method, an estimation system and a storage medium.
Background
With the rapid development of high-speed railways, at present, the high-speed railways in China gradually enter an operation maintenance period from a construction period, and the safety and the stability become new concerns of people for high-speed rails. As operating time increases, the performance of high-speed rail traction power units will tend to decline. One of the problems that has to be faced after the development of the climax of the electrified railway is the problem of remaining life of all the equipment supporting the operation of the substation. Equipment faults, equipment aging and other problems can occur to the substation every year, cost and economic benefits are involved when equipment is replaced, and therefore the service life of equipment in the traction substation needs to be estimated in advance to prevent accidents and improve the operation safety of the electrified railway.
At present, service life estimation and analysis of substation equipment are generally based on theoretical estimated service life given by manufacturers, real data are not monitored and analyzed in operation management of the substation, the real data are often judged through empirical values, or temporary processing is performed when the equipment really has problems in the use process, and the residual service life of the equipment is not estimated in advance. Therefore, the problem of estimating the service life of the power transformation equipment is still in the germination stage, and no mature product can be used as a reference object.
Disclosure of Invention
To overcome at least some of the problems in the related art, the present application provides a method, a system and a storage medium for estimating the service life of a traction substation device.
According to a first aspect of embodiments of the present application, there is provided a method for estimating a service life of a traction substation device, including:
collecting data of key equipment in a traction substation, wherein the key equipment comprises a circuit breaker and a disconnecting switch;
acquiring data required by life estimation from the acquired data of key equipment in the traction substation; the data required by the life estimation comprise the type of the equipment, the number of the equipment and the action of the equipment;
estimating the service life of the equipment according to the data required by the service life estimation of the equipment, wherein the estimated service life of the equipment is as follows:
the estimated life of the equipment is the theoretical residual life year of the equipment, and the estimated life coefficient of the equipment is shown as follows:
the theoretical remaining life year of the equipment is (total times of equipment attribute integration and separation-total times of equipment action) set by a factory/total times of equipment attribute integration and separation-total times of equipment factory life year;
in the formula, the total action times of the equipment is as follows:
the total action times is the opening and closing times, the opening failure times and the current quick-break tripping times multiplied by a preset coefficient.
In the method for estimating the service life of the equipment in the traction substation, the process of acquiring the data of the key equipment in the traction substation is as follows:
extracting historical data of key equipment from a background database of a traction substation, wherein the historical data of the key equipment comprises historical data of breaker opening and closing, historical data of breaker tripping and historical data of disconnector opening and closing;
the recorded data of key equipment in equipment attribute, equipment fault, equipment maintenance and technical specification is manually input.
Further, the specific process of acquiring the data required by the life estimation from the collected data of the key equipment in the traction substation is as follows:
reading historical data of key equipment and recorded data of the key equipment;
capturing data containing the keyword in the currently read data according to the preset keyword, and storing the captured data into an analysis database; the preset keywords comprise an equipment type keyword, an equipment number keyword and an equipment event keyword;
and obtaining the data required by the life estimation according to the captured data.
In the method for estimating the service life of the traction substation equipment, the service life estimation coefficient is updated by adopting a machine learning algorithm.
The method for estimating the service life of the traction substation equipment further comprises the following steps:
drawing a life evaluation chart of the equipment according to the historical data of the key equipment and the individual data of the key equipment;
the individual data of the key equipment comprises equipment model, manufacturer, use date, main parameters, design life and equipment pictures;
the service life evaluation chart of the equipment comprises an equipment information summary table and an individual equipment information table;
the equipment information summary table comprises circuit breakers of the substation pavilions, equipment types of the disconnecting switch equipment, equipment numbers, design life surplus and life estimation surplus;
the individual equipment information table comprises the equipment model, the manufacturer, the use date, the main parameters, the design life, the switching-off times, the switching-on times, the tripping-off times and the failure times of certain equipment.
According to a second aspect of the embodiments of the present application, the present application further provides a service life estimation system for a traction power transformer, which includes a data extraction module, a manual input module, a data acquisition module, and a service life estimation module;
the data extraction module is used for extracting historical data of key equipment from a background database of the traction substation; the historical data of the key equipment comprises breaker opening and closing historical data, breaker tripping historical data and disconnecting and closing historical data of a disconnecting switch;
the manual input module is used for manually inputting the record data of key equipment in the equipment attribute, equipment fault, equipment maintenance and technical specification;
the data acquisition module is used for acquiring data required by life estimation from historical data of the key equipment and recorded data of the key equipment;
and the service life estimation module is used for obtaining the estimated service life of the equipment according to the data required by service life estimation and the service life estimation coefficient.
The service life estimation system of the traction substation equipment further comprises a coefficient correction module, wherein the coefficient correction module updates the service life estimation coefficient by adopting a machine learning algorithm.
The service life estimation system of the traction substation equipment further comprises a chart drawing module, wherein the chart drawing module is used for drawing a service life estimation chart of the equipment according to historical data of the key equipment and individual data of the key equipment.
According to a third aspect of embodiments of the present application, there is also provided a computer storage medium having a computer program stored thereon, where the computer program is executed by a processor to implement any one of the methods for estimating the lifetime of a traction substation device.
According to the above embodiments of the present application, at least the following advantages are obtained: the service life of the traction substation equipment can be accurately estimated by combining the real data of the equipment.
The off-line data acquisition mode is adopted when this application carries out the data acquisition of pulling key equipment in the electric substation, also accessible off-line data package form when system analysis backstage data to do not influence the operation of backstage software, guarantee the security. The method and the device can rotate to extract effective data, and can automatically capture and classify the data according to preset extraction rules. The method and the device can automatically analyze data and automatically correct the life estimation coefficient in real time according to the real-time data. The data can be intelligently extracted, so that the labor intensity is greatly reduced, the time is saved, and the efficiency is improved; the normal use of the equipment is not influenced when the data are extracted, and the method is safe and reliable; huge data are extracted and refined, and finally a chart is formed and visually presented, so that time is saved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the scope of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of the specification of the application, illustrate embodiments of the application and together with the description, serve to explain the principles of the application.
Fig. 1 is a flowchart of a method for estimating a lifetime of traction substation equipment according to an embodiment of the present application.
Fig. 2 is a block diagram of a life estimation system of a traction power transformer according to an embodiment of the present disclosure.
Description of reference numerals:
1. a data extraction module; 2. a manual input module; 3. a data acquisition module; 4. a life estimation module; 5. a coefficient correction module; 6. and a chart drawing module.
Detailed Description
For the purpose of promoting a clear understanding of the objects, aspects and advantages of the embodiments of the present application, reference will now be made to the accompanying drawings and detailed description, wherein like reference numerals refer to like elements throughout.
The illustrative embodiments and descriptions of the present application are provided to explain the present application and not to limit the present application. Additionally, the same or similar numbered elements/components used in the drawings and the embodiments are used to represent the same or similar parts.
As used herein, "first," "second," …, etc., are not specifically intended to mean in a sequential or chronological order, nor are they intended to limit the application, but merely to distinguish between elements or operations described in the same technical language.
With respect to directional terminology used herein, for example: up, down, left, right, front or rear, etc., are simply directions with reference to the drawings. Accordingly, the directional terminology used is intended to be illustrative and is not intended to be limiting of the present teachings.
As used herein, the terms "comprising," "including," "having," "containing," and the like are open-ended terms that mean including, but not limited to.
As used herein, "and/or" includes any and all combinations of the described items.
References to "plurality" herein include "two" and "more than two"; reference to "multiple sets" herein includes "two sets" and "more than two sets".
Certain words used to describe the present application are discussed below or elsewhere in this specification to provide additional guidance to those skilled in the art in describing the present application.
Fig. 1 is a flowchart of a method for estimating a lifetime of traction substation equipment according to an embodiment of the present application.
As shown in fig. 1, a method for estimating a lifetime of traction substation equipment provided in an embodiment of the present application includes the following steps:
s1, collecting data of key equipment in the traction substation, wherein the key equipment comprises a circuit breaker and a disconnecting switch, and the key equipment specifically comprises:
and S11, extracting historical data of the key equipment from the existing background database of the traction substation.
Specifically, the db data file can be extracted from a background database of the electric railway telecontrol system software NK6000 of the traction substation.
The off-line data extraction mode does not directly interact with the electrified railway telecontrol system software NK6000 of the traction substation, and the operation of the electrified railway telecontrol system software NK6000 is not influenced.
The historical data of the key equipment can be extracted from the annual test report of the high-voltage test of the traction substation. Historical data for key devices may also be extracted from the SO event report data.
The historical data of the key equipment comprises breaker opening and closing historical data, breaker tripping historical data, disconnecting and closing historical data of a disconnecting switch and the like.
And S12, manually inputting the recorded data of the key equipment in the equipment attribute, the equipment fault, the equipment maintenance and the technical specification.
S2, acquiring data required by life estimation from the acquired data of the key equipment in the traction substation, wherein the specific process comprises the following steps:
and S21, reading the historical data of the key equipment and the recorded data of the key equipment.
And S22, capturing data containing the keyword in the currently read data according to the preset keyword, and storing the captured data in an analysis database.
The preset keywords include device type keywords, device number keywords, device event keywords, and the like. For example, the device type keyword may be a circuit breaker, a disconnector, etc. The device number key may be 101, 102, 201, 202, 211, 212, 1011, 1021, 2011, 2021, 2111, etc. The device event keywords can be position-opening, position-closing, tripping, action, current quick-break, brake-opening failure and the like.
And S23, obtaining the data required by the life estimation according to the captured data.
The device type can be determined according to the device type key word, and the device number can be determined according to the device number key word. Which device is determined according to the device type and the device number.
The action taken by the device may be determined from the device event keywords.
And obtaining data required by the service life estimation of the equipment according to the equipment type, the equipment number and the action of the equipment. Specifically, the data required for life estimation may include the number of times of switching on and off of the device, the number of times of failure of switching off, the number of times of current snap-off tripping, and the like.
S3, estimating the service life of the equipment according to the data required by the service life estimation of the equipment, wherein the specific process is as follows:
and S31, calculating the total action times of the equipment according to the data required by the life estimation of the equipment.
The total action times are the opening and closing times, the opening failure times, the current quick-break tripping times and a preset coefficient. Specifically, the preset coefficient may be set to 1.2.
And S32, calculating the theoretical residual life year of the equipment according to the recorded data of the manually input key equipment.
The theoretical remaining life of the device is (total number of times of division of device attributes set by factory-total number of times of operation of the device)/total number of times of division of device attributes set by factory-factory life of the device.
And S33, obtaining the estimated life of the equipment according to the theoretical residual life years and the life estimation coefficient of the equipment.
The estimated life of the device is the theoretical remaining life year of the device.
It should be noted that, in the present application, the life estimation coefficient is continuously updated by using a machine learning algorithm. Specifically, the machine learning algorithm may be a least square method, a clustering algorithm, a singular value decomposition algorithm, or the like.
When a certain device is scrapped or replaced, the date of the device which is changed needs to be recorded, the device is analyzed and determined to reach the end point of the service life, the switching-on and switching-off times, the current quick-break tripping times and the service life year of factory design are analyzed, the service life estimation coefficient is automatically corrected, and weighting balance is carried out. And recording the data into an estimation system of the equipment of the type as an estimation basis of subsequent equipment of the same type.
With the increase of the service life and the continuous increase of the number of the recorded switch equipment, the number of the scrapped equipment is continuously increased, the recorded correction data is continuously increased, the coefficient can be automatically corrected, and the more the data of the recorded switch equipment is, the longer the time is, the more the correction times are, the more accurate the data is.
The method for estimating the service life of the traction substation equipment further comprises the following steps:
and S4, drawing a life evaluation chart of the equipment according to the historical data of the key equipment and the individual data of the key equipment.
The individual data of the key equipment comprises equipment model, manufacturer, use date, main parameters, design life, equipment pictures and the like.
The lifetime evaluation chart of the device may include a device information summary table and an individual device information table. The equipment information summary table comprises circuit breakers of the substation pavilions, equipment types of the disconnecting switch equipment, equipment numbers, design life remaining (years) and life estimation remaining (years).
The individual device information table may include a device model, a manufacturer, a use date, main parameters, a design life, switching-off times, switching-on times, tripping times, failure times, and the like of a certain device.
Fig. 2 is a block diagram of a life estimation system of a traction power transformer according to an embodiment of the present disclosure.
As shown in fig. 2, based on the method for estimating the service life of the traction substation equipment provided by the present application, the present application further provides a system for estimating the service life of the traction substation equipment, which includes a data extraction module 1, a manual input module 2, a data acquisition module 3, and a service life estimation module 4.
The data extraction module 1 is used for extracting historical data of key equipment from a background database of the traction substation. The historical data of the key equipment comprises breaker opening and closing historical data, breaker tripping historical data, disconnecting and closing historical data of a disconnecting switch and the like.
The manual input module 2 is used for manually inputting the record data of key equipment in the equipment attribute, equipment fault, equipment maintenance and technical specification.
The data acquisition module 3 is used for acquiring data required by life estimation from historical data of the key equipment and recorded data of the key equipment.
The life estimation module 4 is used for obtaining the estimated life of the equipment according to the data required by life estimation and the life estimation coefficient.
The service life estimation system of the traction power transformer equipment further comprises a coefficient correction module 5, wherein the coefficient correction module 5 adopts a machine learning algorithm to continuously update the service life estimation coefficient, so that the estimated service life of the obtained equipment is more accurate.
The service life estimation system of the traction power transformation equipment further comprises a chart drawing module 6, wherein the chart drawing module 6 is used for drawing a service life estimation chart of the equipment according to historical data of the key equipment and individual data of the key equipment, so that huge data can be extracted and refined, the service life estimation chart of the equipment can be obtained, and visual display can be carried out.
In an exemplary embodiment, the present application further provides a service life estimation apparatus for a traction substation device, which includes a memory and a processor coupled to the memory, where the processor is configured to execute a service life estimation method for the traction substation device in any embodiment of the present application based on instructions stored in the memory.
The memory may be a system memory, a fixed nonvolatile storage medium, or the like, and the system memory may store an operating system, an application program, a boot loader, a database, other programs, and the like.
In an exemplary embodiment, the present application further provides a computer storage medium, which is a computer readable storage medium, for example, a memory including a computer program, which is executable by a processor to perform the method for estimating the service life of a traction substation device in any of the embodiments of the present application.
The service life estimation system for the traction substation equipment, provided by the embodiment of the application, extracts historical data of key equipment from a background software database of the traction substation in an off-line mode, does not affect the operation of background software, and can ensure the safety of the background software. According to the service life estimation system of the traction power transformation equipment, the data acquisition module intelligently extracts data from huge data volume, so that the labor force can be greatly reduced, the time can be saved, and the efficiency can be improved.
The analysis of the use condition of the traction substation equipment is a weak link in China at present and does not bring sufficient attention. Whether the theoretical life of the equipment is consistent with the actual service life of the equipment or not can cause great difference of the service life of the equipment due to the difference of the operating frequency and the fault frequency of each equipment in the using process. Through the equipment life estimation system for the traction power transformer, the service condition of the equipment can be recorded and analyzed every year, the end point of the service life of the equipment is judged in advance, and a theoretical basis is provided for determining the time point of equipment replacement in advance.
By analyzing the service life of the equipment, the economic benefit of the equipment can be further judged, and the quality degree of each brand of equipment can be judged by analyzing the service life and the cost, so that a basis is provided for purchasing decision. The service life estimation system for the traction substation equipment has wide application prospect and can provide powerful technical support for development of electric railways in China.
The foregoing is merely an illustrative embodiment of the present application, and any equivalent changes and modifications made by those skilled in the art without departing from the spirit and principles of the present application shall fall within the protection scope of the present application.
Claims (9)
1. A service life estimation method for traction substation equipment is characterized by comprising the following steps:
collecting data of key equipment in a traction substation, wherein the key equipment comprises a circuit breaker and a disconnecting switch;
acquiring data required by life estimation from the acquired data of key equipment in the traction substation; the data required by the life estimation comprise the type of the equipment, the number of the equipment and the action of the equipment;
estimating the service life of the equipment according to the data required by the service life estimation of the equipment, wherein the estimated service life of the equipment is as follows:
the estimated life of the equipment is the theoretical residual life year of the equipment, and the estimated life coefficient of the equipment is shown as follows:
the theoretical remaining life year of the equipment is (total times of equipment attribute integration and separation-total times of equipment action) set by a factory/total times of equipment attribute integration and separation-total times of equipment factory life year;
in the formula, the total action times of the equipment is as follows:
the total action times is the opening and closing times, the opening failure times and the current quick-break tripping times multiplied by a preset coefficient.
2. The method for estimating the service life of the traction substation equipment according to claim 1, wherein the process of collecting data of the key equipment in the traction substation is as follows:
extracting historical data of key equipment from a background database of a traction substation, wherein the historical data of the key equipment comprises historical data of breaker opening and closing, historical data of breaker tripping and historical data of disconnector opening and closing;
the recorded data of key equipment in equipment attribute, equipment fault, equipment maintenance and technical specification is manually input.
3. The method for estimating the service life of the equipment of the traction substation according to claim 2, wherein the specific process of acquiring the data required for estimating the service life from the collected data of the key equipment in the traction substation is as follows:
reading historical data of key equipment and recorded data of the key equipment;
capturing data containing the keyword in the currently read data according to the preset keyword, and storing the captured data into an analysis database; the preset keywords comprise an equipment type keyword, an equipment number keyword and an equipment event keyword;
and obtaining the data required by the life estimation according to the captured data.
4. The traction substation equipment life estimation method according to claim 1, wherein the life estimation coefficient is updated using a machine learning algorithm.
5. The traction substation equipment life estimation method according to claim 1, characterized by further comprising the steps of:
drawing a life evaluation chart of the equipment according to the historical data of the key equipment and the individual data of the key equipment;
the individual data of the key equipment comprises equipment model, manufacturer, use date, main parameters, design life and equipment pictures;
the service life evaluation chart of the equipment comprises an equipment information summary table and an individual equipment information table;
the equipment information summary table comprises circuit breakers of the substation pavilions, equipment types of the disconnecting switch equipment, equipment numbers, design life surplus and life estimation surplus;
the individual equipment information table comprises the equipment model, the manufacturer, the use date, the main parameters, the design life, the switching-off times, the switching-on times, the tripping-off times and the failure times of certain equipment.
6. A service life estimation system of a traction power transformer is characterized by comprising a data extraction module, a manual input module, a data acquisition module and a service life estimation module;
the data extraction module is used for extracting historical data of key equipment from a background database of the traction substation; the historical data of the key equipment comprises breaker opening and closing historical data, breaker tripping historical data and disconnecting and closing historical data of a disconnecting switch;
the manual input module is used for manually inputting the record data of key equipment in the equipment attribute, equipment fault, equipment maintenance and technical specification;
the data acquisition module is used for acquiring data required by life estimation from historical data of the key equipment and recorded data of the key equipment;
and the service life estimation module is used for obtaining the estimated service life of the equipment according to the data required by service life estimation and the service life estimation coefficient.
7. The traction substation equipment life estimation system of claim 6, further comprising a coefficient correction module, wherein the coefficient correction module updates the life estimation coefficient using a machine learning algorithm.
8. The traction substation equipment life estimation system of claim 6, further comprising a graph plotting module for plotting a life estimation graph of the equipment according to historical data of the critical equipment and individual data of the critical equipment.
9. A computer storage medium, having a computer program stored thereon, which, when executed by a processor, implements the traction substation equipment life estimation method of any of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110707163.3A CN113591013A (en) | 2021-06-25 | 2021-06-25 | Service life estimation method and system for traction substation equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110707163.3A CN113591013A (en) | 2021-06-25 | 2021-06-25 | Service life estimation method and system for traction substation equipment and storage medium |
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| JP2000097815A (en) * | 1998-09-22 | 2000-04-07 | Toshiba Corp | Plant remaining life management device |
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| CN111104342A (en) * | 2018-10-29 | 2020-05-05 | 伊姆西Ip控股有限责任公司 | Method, electronic device and computer program product for storage |
| CN112668840A (en) * | 2020-12-11 | 2021-04-16 | 广州致新电力科技有限公司 | Method for evaluating service life of high-voltage electrical equipment of rail transit |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP2000097815A (en) * | 1998-09-22 | 2000-04-07 | Toshiba Corp | Plant remaining life management device |
| CN107656200A (en) * | 2017-11-09 | 2018-02-02 | 北京长城华冠汽车技术开发有限公司 | A kind of battery relay life estimate device and evaluation method |
| CN111104342A (en) * | 2018-10-29 | 2020-05-05 | 伊姆西Ip控股有限责任公司 | Method, electronic device and computer program product for storage |
| CN112668840A (en) * | 2020-12-11 | 2021-04-16 | 广州致新电力科技有限公司 | Method for evaluating service life of high-voltage electrical equipment of rail transit |
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