Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention 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 invention 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.
First, in order to facilitate understanding of the embodiments of the present invention, some terms or nouns referred to in the present invention will be explained below:
akaike information criterion (AIC criterion): the method is a standard for measuring the fitting superiority of a statistical model, is established on the basis of the concept of entropy, and can balance the complexity of an estimated model and the superiority of fitting data of the model.
Bayesian Information Criterion (BIC Information Criterion): under incomplete intelligence, the subjective probability of a part of unknown states is estimated, then the occurrence probability is corrected by a Bayesian formula, and finally an optimal decision is made by using an expected value and the correction probability.
Example 1
According to an embodiment of the present invention, there is provided an embodiment of a method for lifetime assessment of a power transmission line, it is noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
Fig. 1 is a schematic flow chart of a method for evaluating the lifetime of a power transmission line according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, generating the degeneration quantity sample data of the power transmission line according to the acquired degeneration quantity data of the power transmission line;
step S104, determining a performance degradation model of the power transmission line based on the sample data of the degradation amount, wherein the performance degradation model is generated based on a random process;
step S106, determining a service life distribution function of the power transmission line based on the performance degradation model and a preset failure threshold value;
and S108, estimating the target characteristic parameters of the service life distribution function based on a target estimation method to obtain a service life evaluation result of the power transmission line.
Optionally, when at least one of the characteristic performance parameters exceeds the failure threshold, the power transmission line is degraded and failed; when the performance degradation model reaches the failure threshold value for the first time, the power transmission line is degraded and failed; the target estimation method at least comprises a maximum likelihood estimation method and a Bayesian estimation method; the target characteristic parameters at least include: the average life and the reliable life of the power transmission line are prolonged.
In the embodiment of the invention, by adopting a service life evaluation mode of the power transmission line, the degradation amount sample data of the power transmission line is generated according to the obtained degradation amount data of the power transmission line; determining a performance degradation model of the power transmission line based on the sample data of the degradation amount, wherein the performance degradation model is generated based on a random process; determining a life distribution function of the power transmission line based on the performance degradation model and a preset failure threshold value; the target characteristic parameters of the service life distribution function are estimated based on a target estimation method to obtain a service life estimation result of the power transmission line, so that the purpose of quickly and accurately selecting a service life estimation model of the power transmission line is achieved, the technical effect of accurately estimating the service life of the power transmission line is achieved, and the technical problems of low service life estimation efficiency and large estimation error of the power transmission line caused by inaccurate selection of the service life estimation model of the power transmission line are solved.
In an optional embodiment, before generating degradation sample data of the power transmission line according to the obtained degradation amount data of the power transmission line, the method further includes:
step S202, determining a characteristic performance parameter of the power transmission line based on the parameter characteristic of the power transmission line, wherein the parameter characteristic of the power transmission line includes: time sensitivity, trend, volatility;
and step S204, determining the degradation data of the power transmission line according to the characteristic performance parameters.
Optionally, the characteristic performance parameter of the power transmission line is a main technical performance index capable of reflecting the health state of the power transmission line, and the characteristic performance parameter of the power transmission line must have two conditions: (1) the performance index as a characteristic performance parameter must be accurately defined and can be measured; (2) along with the extension of the working or testing time of the product, the characteristic performance parameters have obvious trend changes, and the performance state of the product can be objectively reflected.
As an optional embodiment, fig. 2 is a schematic flow chart of optional determination of characteristic performance parameters of a power transmission line according to an embodiment of the present invention, and as shown in fig. 2, determining the characteristic performance parameters of the power transmission line based on the parameter characteristics of the power transmission line includes:
step S302, when the ratio of the standard deviation to the mean value of the characteristic performance parameters is larger than a preset value, determining that the characteristic performance parameters belong to time-sensitive parameters;
step S304, when the mean value and the standard deviation of the unit time degradation sequence of the characteristic performance parameters meet preset conditions, determining that the characteristic performance parameters belong to trend type parameters;
step S306, when the range sequence of the characteristic performance parameter is a time-sensitive parameter, determining that the characteristic performance parameter belongs to a fluctuation type parameter.
Optionally, whether the measured parameter is approximate to a horizontal line is determined by calculating a range and a standard deviation of the measured data, and whether the parameter is a time-sensitive parameter is specifically: setting the measured value of the characteristic performance parameter as
Wherein x is
iCharacteristic performance parameter at time t
iTime degradation data, calculating the range E for the above
1=max{x
i}-min{x
i}, calculating
If it is
If not, determining the characteristic performance parameter as a time sensitive parameter; calculating the standard deviation
If it is
The characteristic performance parameter belongs to a time insensitive parameter, otherwise, the characteristic is determinedThe performance parameter is a time sensitive parameter. In the case of the time-insensitive parameter, since the parameter does not change with time, it is not considered in the lifetime evaluation.
Optionally, the time-sensitive parameters are further divided into trend-type parameters and fluctuation-type parameters according to whether the measured values of the characteristic performance parameters have obvious variation trends (increase or decrease). The trend type parameters show increasing or decreasing trend along with the test time, and the fluctuation type parameters show fluctuation change along with the test time without obvious increasing or decreasing trend. Let X { (t) be the measured value of the characteristic parameter
i,x
i) I 1,2, …, n, constructing a degradation increment sequence per unit time according to the measured data sequence
The mean μ and standard deviation σ of the above sequence degeneration increment sequence Y were calculated. The criteria are shown in the following table:
serial number
|
Basis of discrimination
|
Type of parameter
|
1
|
μ≈0,μ-σ<0,μ+σ>0
|
Wave motion type
|
2
|
μ>0,μ-σ<0
|
Increasing trend type (weak trend)
|
3
|
μ>0,μ-σ>0,μ-2σ<0
|
Increasing trend type
|
4
|
μ>0,μ-2σ>0,μ-3σ<0
|
Increasing trend type
|
5
|
μ>0,μ-3σ>0
|
Increasing trend type
|
6
|
μ>0,μ+σ>0
|
Descending trend type (weak trend)
|
7
|
μ<0,μ+σ<0,μ+2σ>0
|
Descending trend type
|
8
|
μ<0,μ+2σ<0,μ+3σ>0
|
Descending trend type
|
9
|
μ<0,μ+3σ<0
|
Descending trend type |
Optionally, whether the fluctuation type parameter has a degradation trend or not is judged, and a range is usually adopted as a main basis for analyzing a change rule of the fluctuation type parameter. The range is divided into a full fluctuation type parameter and a degraded fluctuation type parameter according to whether the range changes with time or not. Wherein the range of the complete fluctuation type parameter does not change with time, and the degraded fluctuation type parameterThe range of the number varies with time, specifically: and constructing a range sequence. Let X { (t) be the measured value of the characteristic parameteri,xi) And i is 1,2, …, n }, a range sequence can be constructed:
E={ei|ei=maxk=1,2,…i(xk)-mink=1,2,…i(xk) I ═ 1,2, …, n }; if the range sequence is a time-sensitive sequence, the characteristic performance parameter is considered to be a fluctuation degradation parameter.
In an optional embodiment, determining degradation data of the power transmission line according to the characteristic performance parameter includes:
step S402, when detecting that the data of the characteristic performance parameters has null values, filling the null values; when an abnormal value exists in the data of the characteristic performance parameters, the abnormal value is corrected to obtain the processed characteristic performance parameters;
step S404, smoothing the processed data of the characteristic performance parameter based on a data smoothing technique to obtain the degradation amount data.
Optionally, when a null value is detected in the data of the characteristic performance parameter, a data interpolation method, for example, a method of directly deleting tuples, filling an average value, and the like, is used to fill the null value. When an abnormal value is detected in the data of the characteristic performance parameter, the abnormal value is corrected, specifically, the abnormal value is determined, corrected and interpolated.
In an optional embodiment, determining the characteristic performance parameter of the power transmission line based on the parameter characteristic of the power transmission line comprises determining the performance degradation model as a degraded orbit model when the degradation time of the power transmission line is within a preset range; when the degradation time of the power transmission line exceeds the preset range, judging whether the degradation process of the degradation sample data is a continuous degradation process; if the degradation process of the degradation amount sample data is the continuous degradation process, determining the performance degradation model as a degradation model based on a wiener function; and if the degradation process of the degradation amount sample data is not the continuous degradation process, judging the use damage accumulation value of the power transmission line, and determining the performance degradation model to be a gamma function-based degradation model when the damage accumulation value reaches a preset accumulation value.
As an optional embodiment, fig. 3 is a schematic flow chart of determining an optional transmission line characteristic performance degradation model according to an embodiment of the present invention, and as shown in fig. 3, determining the performance degradation model of the transmission line based on the sample data of the degradation amount includes: judging whether the degradation time of the sample data of the degradation amount of the power transmission line is within a preset range or not, and if the degradation time of the power transmission line is within the preset range, determining that the performance degradation model is a degraded track model; otherwise, judging whether the degradation process of the degradation amount sample data is a continuous degradation process or not, and if the degradation process of the degradation amount sample data is the continuous degradation process, determining the performance degradation model as a degradation model based on a wiener function; otherwise, judging a tiny damage accumulation value caused by the continuous use of the power transmission line, and determining the performance degradation model as a gamma function-based degradation model when the damage accumulation value reaches a preset accumulation value. And after the characteristic performance degradation model of the power transmission line is selected, the excellence of the characteristic performance degradation model of the power transmission line is checked.
In an optional embodiment, after determining the performance degradation model of the power transmission line based on the degradation amount sample data, the method includes:
step S502, evaluating the goodness of fit of the performance degradation model based on a target information criterion and a target evaluation model;
and step S504, when the goodness of fit is lower than a preset value, performing optimization training on the performance degradation model to obtain an optimized performance degradation model.
Optionally, the information criterion may be, but not limited to, bayesian information criterion and akachi pool information criterion; the target evaluation model may directly evaluate the goodness of fit of the performance degradation model by, but not limited to, a mean square error method.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts or the sequence of acts described, as some steps may be performed in other orders or concurrently according to the present invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
Example 2
According to an embodiment of the present invention, there is further provided a system embodiment for implementing the method for estimating the lifetime of the power transmission line, and fig. 4 is a schematic structural diagram of a system for estimating the lifetime of the power transmission line according to an embodiment of the present invention, and as shown in fig. 4, the system for estimating the lifetime of the power transmission line includes: data acquisition device 60, model construction and life evaluation device 62, display device 64, wherein:
the data acquisition device 60 is configured to generate degradation amount sample data of the power transmission line according to the obtained degradation amount data of the power transmission line; the model construction and life evaluation device 62 is connected to the data acquisition device and is used for determining a performance degradation model of the power transmission line based on the degradation amount sample data, wherein the performance degradation model is generated based on a random process; determining a life distribution function of the power transmission line based on the performance degradation model and a preset failure threshold value; estimating the target characteristic parameters of the service life distribution function based on a target estimation method to obtain a service life evaluation result of the power transmission line; the display device 64 is connected to the data acquisition device and the model building and life evaluating device, and is configured to display a data acquisition result and a life evaluating result of the power transmission line.
It should be noted that the specific structure of the service life evaluation system of the power transmission line shown in fig. 4 in the present application is only an illustration, and in a specific application, the service life evaluation of the power transmission line in the present application may have more or less structures than the data acquisition device 60, the model building and service life evaluation device 62, and the display device 64 shown in fig. 4.
It should be noted that any optional or preferred method for estimating the lifetime of the power transmission line in embodiment 1 above may be implemented or realized in the system for estimating the lifetime of the power transmission line provided in this embodiment.
In addition, it should be noted that, for alternative or preferred embodiments of the present embodiment, reference may be made to the relevant description in embodiment 1, and details are not described herein again.
Example 3
According to an embodiment of the present invention, an embodiment of an apparatus for implementing the method for estimating lifetime of a power transmission line is further provided, and fig. 5 is a schematic structural diagram of an apparatus for estimating lifetime of a power transmission line according to an embodiment of the present invention, as shown in fig. 5, the apparatus for estimating lifetime of a power transmission line includes: a generation module 70, a first determination module 72, a second determination module 74, an estimation module 76, wherein:
the generating module 70 is configured to generate degradation amount sample data of the power transmission line according to the obtained degradation amount data of the power transmission line; the first determining module 72 is configured to determine a performance degradation model of the power transmission line based on the sample data of the degradation amount, where the performance degradation model is a performance degradation model generated based on a random process; the second determining module 74 is configured to determine a life distribution function of the power transmission line based on the performance degradation model and a preset failure threshold; the estimation module 76 is configured to estimate the target characteristic parameter of the life distribution function based on a target estimation method, so as to obtain a life evaluation result of the power transmission line.
It should be noted that the above modules may be implemented by software or hardware, for example, for the latter, the following may be implemented: the modules can be located in the same processor; alternatively, the modules may be located in different processors in any combination.
It should be noted here that the generating module 70, the first determining module 72, the second determining module 74, and the estimating module 76 correspond to steps S102 to S108 in embodiment 1, and the modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the disclosure in embodiment 1. It should be noted that the modules described above may be implemented in a computer terminal as part of an apparatus.
It should be noted that, reference may be made to the relevant description in embodiment 1 for alternative or preferred embodiments of this embodiment, and details are not described here.
The life evaluation device of the power transmission line may further include a processor and a memory, where the generating module 70, the first determining module 72, the second determining module 74, the estimating module 76, and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions.
The processor comprises a kernel, and the kernel calls a corresponding program unit from the memory, wherein one or more than one kernel can be arranged. The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.
According to an embodiment of the present application, there is also provided an embodiment of a non-volatile storage medium. Optionally, in this embodiment, the nonvolatile storage medium includes a stored program, and when the program runs, the apparatus where the nonvolatile storage medium is located is controlled to execute the method for estimating the lifetime of any one of the power transmission lines.
Optionally, in this embodiment, the nonvolatile storage medium may be located in any one of a group of computer terminals in a computer network or any one of a group of mobile terminals, and the nonvolatile storage medium includes a stored program.
Optionally, the apparatus in which the non-volatile storage medium is controlled to perform the following functions when the program is executed: generating the degeneration amount sample data of the power transmission line according to the acquired degeneration amount data of the power transmission line; determining a performance degradation model of the power transmission line based on the sample data of the degradation amount, wherein the performance degradation model is generated based on a random process; determining a service life distribution function of the power transmission line based on the performance degradation model and a preset failure threshold value; and estimating the target characteristic parameters of the service life distribution function based on a target estimation method to obtain a service life evaluation result of the power transmission line.
According to an embodiment of the present application, there is also provided an embodiment of a processor. Optionally, in this embodiment, the processor is configured to execute a program, where the program executes the method for estimating the lifetime of any one of the power transmission lines.
According to an embodiment of the present application, there is further provided an embodiment of a computer program product, which is adapted to execute a program initializing the steps of the method for estimating lifetime of a power transmission line according to any one of the above.
Optionally, the computer program product described above, when being executed on a data processing device, is adapted to perform a program initialized with the method steps of: generating degradation amount sample data of the power transmission line according to the obtained degradation amount data of the power transmission line; determining a performance degradation model of the power transmission line based on the sample data of the degradation amount, wherein the performance degradation model is generated based on a random process; determining a service life distribution function of the power transmission line based on the performance degradation model and a preset failure threshold value; and estimating the target characteristic parameters of the service life distribution function based on a target estimation method to obtain a service life estimation result of the power transmission line.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, 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 invention 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 non-volatile storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a non-volatile storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned nonvolatile 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 invention, and it should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be construed as the protection scope of the present invention.