CN113298389A - Method and device for evaluating cable running state - Google Patents
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Abstract
The application discloses a method and a device for evaluating a cable running state. Wherein, the method comprises the following steps: acquiring data related to the running state of the cable; determining target data belonging to a time-dependent covariate type in the data; determining an evaluation index for evaluating the cable running state according to the target data, wherein the evaluation index comprises at least one of the following: reliability of operation or failure coefficient; and evaluating the running state of the cable according to the evaluation index. The method and the device solve the technical problem that the analysis result and the actual condition have large deviation because the related technology analyzes the cable running state based on the monitoring data of single time or single equipment.
Description
Technical Field
The application relates to the field of electric power, in particular to a method and a device for evaluating a running state of a cable.
Background
At present, cable run's fortune dimension is overhauld with the manual work and is looked round, state detection and on-line monitoring are leading, data discretization, islanding, fortune dimension personnel can't be patrolled or overhaul the in-process and effectively assess and master cable run state, also can't obtain circuit operation and state information data through system's platform, it receives certain restriction to patrol and examine efficiency, the data dispersion that the inspection was looked round in all kinds of check out equipment, data form or monitor platform, the form lacks unity standardization, be difficult to realize the information interaction, and it is complicated to type storage work flow. Based on the existing data condition of cable professional management and operation and inspection service, data such as ledgers, completions, inspection patrols, perception monitoring, maintenance records, professional management and the like exist in polymorphic images, texts and numbers, cross-data type analysis technology is less, the existing conditions mainly comprise centralized detection and monitoring data analysis, correlation analysis and mining capacity among state quantities is insufficient, a large amount of research at the present stage mainly comprises single-state data analysis with knowledge and logic as the main part, the application of ledgers and inspection data and data trend characteristics is less, the cross-domain, multi-dimensional and long-time data comprehensive analysis and study capacity is weak, and in the application aspects such as fault early warning study and study of similar equipment, cable aging state evaluation and diagnosis, operation reliability analysis and assessment and the like, the data are detected/monitored according to the single-time or single-equipment field state in the related technology, the cable equipment transverse study and judgment or longitudinal study and judgment based on historical overhaul and development trend under the same type and the same working condition are lacked, so that the analysis conclusion is usually greatly deviated from the actual condition, and the practicability is extremely low.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the application provides a method and a device for evaluating a cable running state, so as to at least solve the technical problem that a larger deviation exists between an analysis result and an actual situation caused by analyzing the cable running state based on monitoring data of a single moment or a single device in the related art.
According to an aspect of an embodiment of the present application, there is provided a method of evaluating an operating state of a cable, including: acquiring data related to the running state of the cable; determining target data belonging to a time-dependent covariate type in the data; determining an evaluation index for evaluating the cable running state according to the target data, wherein the evaluation index comprises at least one of the following: reliability of operation or failure coefficient; and evaluating the running state of the cable according to the evaluation index.
Optionally, the data related to the operating state of the cable, including the temperature, the circulation, the partial discharge size, the dielectric loss, the air humidity of the cable, and the construction unit, the length, and the manufacturer corresponding to the cable, determines the target data belonging to the time-dependent covariate type in the data, and includes: and determining the target data of the temperature, the circulation, the partial discharge size, the dielectric loss and the air humidity of the cable, wherein the target data belong to time-dependent covariate types.
Optionally, determining an evaluation index for evaluating the cable running state according to the target data includes: according to the target data, an evaluation index for evaluating the operation state of the cable is determined by a Weibull model.
Optionally, the weibull model comprises: a first Weibull model and a second Weibull model; the first Weibull model is used for determining a fault coefficient, and the second Weibull model is used for determining the operation reliability.
Alternatively,
the first Weibull model is
Wherein, XjIs the jth time-dependent covariate, γjIs XjCorresponding regression coefficients, wherein n is the number of jth time-dependent covariates, t is the running time of the cable, beta is a Weibull distribution shape parameter, and eta is a Weibull scale parameter;
the second Weibull model is
Wherein, X is a time-dependent covariate, and alpha is a regression parameter corresponding to the time-dependent covariate.
Optionally, after determining the evaluation index for evaluating the cable running state by the Weibull model, the method further comprises: and obtaining a fault probability density function according to the first Weibull model and the second Weibull model, wherein the fault probability density function is f (t, X) ═ h (t, X) · R (t, X).
According to another aspect of the present application, there is also provided an apparatus for evaluating an operating state of a cable, including: the acquisition module is used for acquiring data related to the running state of the cable; the first determining module is used for determining target data which belong to a time-dependent covariate type in the data; the second determination module is used for determining an evaluation index for evaluating the cable running state according to the target data, wherein the evaluation index comprises at least one of the following: reliability of operation or failure coefficient; and the evaluation module is used for evaluating the running state of the cable according to the evaluation index.
Optionally, the second determining module includes: and the determining unit is used for determining an evaluation index for evaluating the running state of the cable through a Weibull model according to the target data.
According to another aspect of the present application, there is also provided a non-volatile storage medium including a stored program, wherein the apparatus in which the non-volatile storage medium is controlled to perform any one of the methods of evaluating the cable running status while the program is running.
According to another aspect of the present application, there is also provided a processor for executing a program, wherein the program executes any one of the methods for evaluating the operating state of a cable.
In the embodiment of the application, a cable running state is determined by adopting a time-dependent covariate type-based target data, and the target data belonging to the time-dependent covariate type in the data is determined by acquiring data related to the cable running state; and determining an evaluation index for evaluating the cable running state according to the target data, wherein the evaluation index comprises at least one of the following: reliability of operation or failure coefficient; and finally, evaluating the running state of the cable according to the evaluation index, and achieving the purpose of determining the running state of the cable through a plurality of time-coordinated type monitoring data, thereby realizing the technical effect of determining the running state of the cable based on the plurality of time-coordinated type monitoring data, and further solving the technical problem that the analysis result has larger deviation with the actual condition due to the fact that the related technology analyzes the running state of the cable based on the monitoring data of a single moment or a single device.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a schematic flow chart diagram of an alternative method of assessing cable operational status according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating an alternative process for normalizing data associated with cable operating conditions according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an alternative apparatus for evaluating an operating state of a cable according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In accordance with an embodiment of the present application, there is provided an embodiment of a method for assessing the operational status of a cable, where the steps illustrated in the flowchart of the figure may be performed in a computer system such as a set of computer-executable instructions, and where the logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than that illustrated herein.
Fig. 1 is a method for evaluating an operating state of a cable according to an embodiment of the present application, as shown in fig. 1, the method including the steps of:
s102, acquiring data related to a cable running state;
s104, determining target data belonging to a time-dependent covariate type in the data;
s106, determining an evaluation index for evaluating the cable running state according to the target data, wherein the evaluation index comprises at least one of the following: reliability of operation or failure coefficient;
and S108, evaluating the running state of the cable according to the evaluation index.
In the method for evaluating the cable running state, firstly, data related to the cable running state can be acquired, then target data belonging to a time-dependent covariate type in the data is determined, and an evaluation index for evaluating the cable running state is determined according to the target data, wherein the evaluation index comprises at least one of the following: reliability of operation or failure coefficient; finally, the running state of the cable is evaluated according to the evaluation index, and the purpose of determining the running state of the cable through a plurality of time-coordinated type monitoring data is achieved, so that the technical effect of determining the running state of the cable based on the plurality of time-coordinated type monitoring data is achieved, and the technical problem that the analysis result has larger deviation with the actual situation due to the fact that the related technology analyzes the running state of the cable based on the monitoring data of a single moment or a single device is solved.
It should be noted that after acquiring data related to the cable running state, a fingerprint library may be established according to the data, specifically:
1. the method comprises the steps of dividing cable line defects and faults into different state parameters of a cable body and accessories for Analysis, analyzing main defect Correlation of the body and the accessories in detail, analyzing Correlation between every two state quantities, namely a CCA Correlation coefficient rho based on typical Correlation Analysis (CCA), and aiming at two groups of random variables x and y with dimensions p and q respectively. Note the book
The goal of CCA is to find the correlation coefficient of two sets of data.
If | ρ | > 1, indicating a linear correlation between X and Y, this condition can be relaxed in engineering applications to | ρ | > 0.9. However, for the random variable nonlinear correlation, a single correlation coefficient cannot be characterized.
2. If | ρ | is less than or equal to 0.9, cross-domain typical Correlation Analysis (CCADD: statistical Correlation Analysis across differences Domains), (mixed) probability typical Correlation Analysis ((Mix) PCCA: spatial of statistical Correlation Analysis), Coupula function model and other methods are used for researching Correlation rules among variables, calculating a data weight rule, a data weight/probability rule and a sequence direction anisotropy rule, and finding out the change rule of parameters such as the maximum weight/probability, thereby obtaining the cable line and channel operation state quantity data quantization risk factor fingerprint.
3. And establishing cable line fault representation data groups to which different equipment faults point by screening parameters such as the weight/probability of the maximum occurrence.
4. In the process of extracting the defect severity evaluation parameters, constructing an original multi-source evaluation parameter set describing the defect development process, introducing new variables such as mutual information, maximum information coefficients and the like to measure the incidence relation between characteristic information and the defect severity, adopting weighting factors to measure the importance of redundancy and correlation, carrying out feature selection by taking the maximum correlation and minimum redundancy as a criterion, and finally preferably selecting the characteristic parameters capable of most representing the defect severity.
5. Establishing a characteristic quantity set and a state evaluation mapping relation of the operation states of the cable lines and the tunnels through the analysis of the accuracy and reliability of the existing state monitoring quantity in the representation of the operation states of the cable lines and the tunnels;
6. finally, a cable line defect, fault and state characteristic characterization data fingerprint database is formed.
It should be noted that, the data related to the cable running state, including but not limited to the temperature, circulation, partial discharge size, dielectric loss, air humidity of the cable, and the construction unit, length, and manufacturer corresponding to the cable, determines the target data belonging to the time-dependent covariate type in the data, including: and determining the target data of the temperature, the circulation, the partial discharge size, the dielectric loss and the air humidity of the cable, wherein the target data belong to time-dependent covariate types.
In some optional embodiments of the present application, an evaluation index for evaluating an operating state of the cable is determined according to the target data, specifically: according to the target data, an evaluation index for evaluating the operation state of the cable is determined by a Weibull model.
It should be noted that the weibull model includes, but is not limited to: a first Weibull model and a second Weibull model; it will be appreciated that a first weibull model is used to determine the fault coefficients and a second weibull model is used to determine the operational reliability.
Specifically, the first Weibull model is
Wherein, XjIs the jth time-dependent covariate, γjIs XjCorresponding regressionThe coefficient, n is the number of the jth time-dependent covariate, t is the running time of the cable, beta is a Weibull distribution shape parameter, and eta is a Weibull scale parameter;
in particular, the second Weibull model is
Wherein, X is a time-dependent covariate, and alpha is a regression parameter corresponding to the time-dependent covariate.
In some optional embodiments of the present application, after determining the evaluation index for evaluating the cable operating state by the Weibull model, the fault probability density function may be obtained by: and obtaining a fault probability density function according to the first Weibull model and the second Weibull model, wherein the fault probability density function is f (t, X) ═ h (t, X) · R (t, X).
In some optional embodiments of the present application, after obtaining the failure probability density function, a likelihood function of the failure probability density function may be constructed, and shape parameters of the Weibull model are obtained through the likelihood function, where the likelihood function is:
wherein n is the total number of data, m is the number of fault data, and n-m represents the number of tail data.
It can be understood that the shape parameters of the Weibull distribution can be obtained by solving the likelihood function, and the reliability, i.e., the reliability and the fault coefficient, can be obtained according to the Weibull distribution.
It should be noted that, according to the data fingerprint library and the weight/probability coefficient thereof, data related to the cable running state may be classified and normalized, a time-dependent covariate and non-time-dependent covariate probability correlation and a probability rule are established, and the Weibull model is simplified to reduce the computational complexity, fig. 2 is a schematic flow chart of the optional classification and normalization of the data related to the cable running state in the present application, and as shown in fig. 2, the flow includes normalization of the data related to the cable running state, for example, data such as insulation resistance, partial discharge (partial discharge size), low-frequency medium, and the like. In addition, it can be understood that the fault data and the state data of the cable are analyzed simultaneously, the state decision curve of the cable is drawn by solving the parameters of the Weibull model, the state of the cable can be divided into three types of normal work, critical zone and maintenance according to the reliability, and meanwhile the residual service life of the cable can be predicted.
Fig. 3 is an apparatus for evaluating an operating state of a cable according to the present application, as shown in fig. 3, the apparatus comprising:
an obtaining module 40, configured to obtain data related to a cable running state;
a first determining module 42, configured to determine target data belonging to a time-dependent covariate type in the data;
a second determining module 44, configured to determine an evaluation index for evaluating the cable running state according to the target data, where the evaluation index includes at least one of: reliability of operation or failure coefficient;
and the evaluation module 46 is used for evaluating the running state of the cable according to the evaluation index.
In the device, an obtaining module 40 is used for obtaining data related to the running state of the cable; a first determining module 42, configured to determine target data belonging to a time-dependent covariate type in the data; a second determining module 44, configured to determine an evaluation index for evaluating the cable running state according to the target data, where the evaluation index includes at least one of: reliability of operation or failure coefficient; the evaluation module 46 is configured to evaluate the operation state of the cable according to the evaluation index, so as to achieve a purpose of determining the operation state of the cable according to the multiple time-coordinated type monitoring data, thereby achieving a technical effect of determining the operation state of the cable based on the multiple time-coordinated type monitoring data, and further solving a technical problem that a larger deviation exists between an analysis result and an actual situation due to analysis of the operation state of the cable based on the single-time or single-device monitoring data in the related art.
It should be noted that, the second determining module further includes: and the determining unit is used for determining an evaluation index for evaluating the running state of the cable through a Weibull model according to the target data.
According to another aspect of the present application, there is also provided a non-volatile storage medium including a stored program, wherein the apparatus in which the non-volatile storage medium is controlled to perform any one of the methods of evaluating the cable running status while the program is running.
Specifically, the nonvolatile storage medium is used for storing program instructions for executing the following functions, namely acquiring data related to the running state of the cable; determining target data belonging to a time-dependent covariate type in the data; determining an evaluation index for evaluating the cable running state according to the target data, wherein the evaluation index comprises at least one of the following: reliability of operation or failure coefficient; and evaluating the running state of the cable according to the evaluation index.
According to another aspect of the present application, there is also provided a processor for executing a program, wherein the program executes any one of the methods for evaluating the operating state of a cable.
Specifically, the processor is configured to call a program instruction in the memory, and implement the following functions: acquiring data related to the running state of the cable; determining target data belonging to a time-dependent covariate type in the data; determining an evaluation index for evaluating the cable running state according to the target data, wherein the evaluation index comprises at least one of the following: reliability of operation or failure coefficient; and evaluating the running state of the cable according to the evaluation index.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (10)
1. A method of assessing the operational status of a cable, comprising:
acquiring data related to the running state of the cable;
determining target data belonging to a time-dependent covariate type in the data;
determining an evaluation index for evaluating the cable running state according to the target data, wherein the evaluation index comprises at least one of the following: reliability of operation or failure coefficient;
and evaluating the running state of the cable according to the evaluation index.
2. The method as claimed in claim 1, wherein the data related to the cable running state, including the temperature, circulation, partial discharge size, dielectric loss, air humidity of the cable, and the construction unit, length and manufacturer corresponding to the cable, determines the target data belonging to the time-dependent covariate type in the data, and comprises:
and determining the target data of the temperature, the circulation, the partial discharge size, the dielectric loss and the air humidity of the cable, wherein the target data belong to time-dependent covariate types.
3. The method of claim 1, wherein determining an evaluation index for evaluating the cable operational status based on the target data comprises:
and determining an evaluation index for evaluating the running state of the cable by a Weibull model according to the target data.
4. The method of claim 3, wherein the Weibull model comprises: a first Weibull model and a second Weibull model; wherein the first Weibull model is used to determine the fault coefficients and the second Weibull model is used to determine the operational reliability.
5. The method of claim 4,
the first Weibull model is
Wherein, XjIs the jth time-dependent covariate, γjIs XjCorresponding regression coefficients, wherein n is the number of jth time-dependent covariates, t is the running time of the cable, beta is a Weibull distribution shape parameter, and eta is a Weibull scale parameter;
the second Weibull model is
Wherein, X is a time-dependent covariate, and alpha is a regression parameter corresponding to the time-dependent covariate.
6. The method of claim 5, wherein after determining an evaluation index for evaluating the cable operating condition by a Weibull model, the method further comprises:
and obtaining a fault probability density function according to the first Weibull model and the second Weibull model, wherein the fault probability density function is f (t, X) ═ h (t, X) · R (t, X).
7. An apparatus for evaluating an operational status of a cable, comprising:
the acquisition module is used for acquiring data related to the running state of the cable;
the first determining module is used for determining target data which belong to a time-dependent covariate type in the data;
a second determination module, configured to determine an evaluation index for evaluating the cable running state according to the target data, where the evaluation index includes at least one of: reliability of operation or failure coefficient;
and the evaluation module is used for evaluating the running state of the cable according to the evaluation index.
8. The apparatus of claim 7, wherein the second determining module comprises:
and the determining unit is used for determining an evaluation index for evaluating the running state of the cable through a Weibull model according to the target data.
9. A non-volatile storage medium, comprising a stored program, wherein the program, when executed, controls a device in which the non-volatile storage medium is located to perform the method for evaluating a cable status operation state according to any one of claims 1 to 6.
10. A processor for executing a program, wherein the program executes the method for assessing a cable status operation state according to any one of claims 1 to 6.
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