Method, apparatus and terminal device for establishing physical asset wall

Abstract

This application is applicable to the technical field of predicting capital investment in power grid equipment, and provides a method, device and terminal device for establishing a physical asset wall. The method for establishing the physical asset wall includes: obtaining information on retired equipment and in-service equipment; performing cluster analysis on the information of retired equipment to obtain the significant years of improved retired life of the retired equipment; selecting one year each before and after the significant years as representative years, and based on the information of retired equipment in the representative years, fitting and correcting the annual retirement rates of each type of equipment to obtain the actual annual retirement rates of each type of equipment; according to the actual annual retirement rates of each type of equipment and the information of in-service equipment, through random simulation, obtaining the number of retired equipment of in-service equipment in each future year. This application can play a role in flattening the peak and filling the valley of the curve of future retirement quantities, making the number of retired equipment relatively stable each year, so that the funds are also relatively stable, which is conducive to reasonable fund allocation.

Description

Technical Field

[0001] This application belongs to the technical field of power grid equipment capital investment prediction, and particularly relates to a method, device, and terminal device for establishing a physical asset wall. Background Art

[0002] With the rapid development of the economy, the scale of physical assets of the power grid continues to rise, and the tasks of power grid maintenance, overhaul, and technological transformation are becoming increasingly severe. How to scientifically plan the construction of the power grid and reasonably and orderly carry out asset transformation is the basis and guarantee for the safe, stable, efficient, and economic operation of the power grid.

[0003] The asset wall is an intuitive description of the intensive commissioning situation of assets within the historical time range. After arranging the historical data in chronological order, analyzing its changing pattern over time, and finally using the commissioning time as the horizontal axis and the asset scale as the vertical axis, the scale of commissioned assets shows the shape of a "wall", reflecting the scale of existing assets commissioned in different years in history.

[0004] In recent years, with the in-depth research on the asset wall, it is unreasonable to simply shift the quantity of all equipment based on the average service life, which not only ignores the randomness of the retirement life of power grid equipment but also neglects the huge technological transformation pressure caused by the investment during the historical peak period. These will lead to large fluctuations in the scale of technological transformation in a certain period, resulting in unreasonable capital allocation and being unfavorable to the asset management of power grid enterprises. Summary of the Invention

[0005] To overcome the problems existing in the related technologies, the embodiments of this application provide a method, device, and terminal device for establishing a physical asset wall.

[0006] This application is implemented through the following technical solutions:

[0007] In a first aspect, the embodiments of this application provide a method for establishing a physical asset wall, including: obtaining information on retired equipment and information on in-service equipment; performing clustering analysis on the information on retired equipment to obtain the years with significant improvement in the retirement life of the retired equipment; selecting one year before and one year after the significant improvement year as representative years, and based on the information on retired equipment in the representative years, fitting and correcting the annual retirement rates of each type of equipment to obtain the actual annual retirement rates of each type of equipment; and through random simulation based on the actual annual retirement rates of each type of equipment and the information on in-service equipment, obtaining the number of retired equipment of the in-service equipment in each future year.

[0008] Based on the first aspect, in some possible implementation manners, the information on retired equipment includes the commissioning year, retirement year, service life, and reasons for retirement of the retired equipment, and the reasons for retirement include technological transformation or overhaul; the information on in-service equipment includes the commissioning year of the in-service equipment and the annual commissioning quantity.

[0009] Based on the first aspect, in some possible implementation manners, the steps of performing clustering analysis on the retired equipment information to obtain the significant years for improving the retired life of the retired equipment include: performing multi-index clustering based on the fisher optimal segmentation method and making a division that conforms to the time sequence, and determining the exact years that have a significant impact due to technological changes, where the exact years are the significant years for improving the retired life of the retired equipment.

[0010] Based on the first aspect, in some possible implementation manners, the steps of selecting one year before and after the significant year as representative years respectively, and fitting and correcting the annual retirement rate based on the retired equipment information in the representative years to obtain the actual annual retirement rate of each type of equipment include: according to preset conditions, selecting one year before and after the significant year as representative years respectively, denoted as the first representative year and the second representative year; randomly selecting a certain number of sample equipment from a certain type of the retired equipment in the first representative year and the second representative year respectively, denoted as the first sample and the second sample; counting the retired life of each equipment in the first sample and the second sample, and respectively calculating the retirement rate of the equipment in the first sample and the second sample at different retired lives; performing Weibull parameter fitting on the retirement rates of each service life of a certain type of the retired equipment calculated in the first representative year and the second representative year, and using the fitted curve for correction to obtain the actual annual retirement rate of a certain type of the retired equipment.

[0011] Based on the first aspect, in some possible implementation manners, the preset conditions include: in the representative year, more than 80% of the equipment of the same type put into operation in that year has been retired; in the representative year, the number of equipment put into operation in that year is relatively large compared with other years; in the representative year, the distribution of the types of different retired service years of the equipment put into operation in that year is more than that in the remaining years.

[0012] Based on the first aspect, in some possible implementation manners, the steps of obtaining the number of retired equipment of the in-service equipment in each future year through random simulation according to the retirement rate and the in-service equipment information include: if the commissioning year of a certain type of the in-service equipment is before the representative year, performing random simulation with the retirement rate of the first representative year, and vice versa, performing random simulation with the Weibull-corrected retirement rate of the second representative year to obtain the retirement year of a certain type of the in-service equipment, and sorting and summarizing all types of the in-service equipment to obtain the in-service equipment retired in each future year.

[0013] Based on the first aspect, in some possible implementation manners, the process of sorting and summarizing all categories of the in-service devices includes: repeatedly calculating the retirement year of a certain category of the in-service devices, taking the average value of the retirement years to eliminate randomness; summarizing the number of the in-service devices of the same type with the same voltage level that will retire in the same future year to obtain the number of the in-service devices that will retire each year in the future.

[0014] The above method for establishing the physical asset wall can play a role in flattening the peak and filling the valley of the curve of the future retirement quantity, making the number of retired devices each year relatively stable, so that the funds are also relatively stable, which is beneficial to the reasonable allocation of funds.

[0015] In a second aspect, an embodiment of the present application provides a physical asset wall establishment device, including: an acquisition module, configured to acquire retired device information and in-service device information; a clustering analysis module, configured to perform clustering analysis on the retired device information to obtain the years with significant improvement in the retirement life of the retired devices; a fitting module, configured to select one year before and one year after the significant improvement year as representative years, and based on the retired device information in the representative years, fit and correct the retirement rate of each year to obtain the actual retirement rate of each type of device for each year; a random simulation module, configured to obtain the number of retired devices of the in-service devices in each future year through random simulation according to the retirement rate and the in-service device information.

[0016] In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for establishing the physical asset wall according to any item of the first aspect is implemented.

[0017] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the method for establishing the physical asset wall according to any item of the first aspect is implemented.

[0018] It can be understood that the beneficial effects of the above second aspect to the fourth aspect can refer to the relevant descriptions in the first aspect above, and will not be elaborated here.

[0019] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this specification. Description of the Drawings

[0020] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the accompanying drawings required for use in the embodiments or the description of the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0021] Figure 1 is a schematic flowchart of a method for establishing a physical asset wall provided by an embodiment of the present application;

[0022] Figure 2 is a schematic flowchart of the equipment life ratio adjustment process in the method for establishing a physical asset wall provided by an embodiment of the present application;

[0023] Figure 3 is a schematic flowchart of the equipment retirement quantity simulation in the method for establishing a physical asset wall provided by an embodiment of the present application;

[0024] Figure 4 is a schematic structural diagram of a physical asset wall establishment device provided by an embodiment of the present application;

[0025] Figure 5 is a schematic structural diagram of a terminal device provided by an embodiment of the present application. Detailed implementation manners

[0026] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are put forward in order to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, the detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0027] It should be understood that when used in the specification and the appended claims of the present application, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0028] It should also be understood that the term " / and" as used in the specification and the appended claims of the present application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0029] As used in the specification and the appended claims of this application, the term "if" may be construed, depending on the context, as "when", "once", "in response to determining", or "in response to detecting". Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be construed, depending on the context, to mean "once determined", "in response to determining", "once [the described condition or event] is detected", or "in response to detecting [the described condition or event]".

[0030] In addition, in the description of the specification and the appended claims of this application, the terms "first", "second", "third", etc. are used only for distinguishing descriptions and cannot be construed as indicating or implying relative importance.

[0031] Reference to "one embodiment" or "some embodiments" or the like described in the specification of this application means that a specific feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of this application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in another way. The terms "comprising", "including", "having", and their variants all mean "including but not limited to", unless otherwise specifically emphasized in another way.

[0032] With the rapid development of the economy, the scale of physical assets of the power grid continues to rise, and the tasks of power grid maintenance, overhaul, and technological transformation are becoming increasingly severe. How to scientifically plan the construction of the power grid and carry out asset transformation in a reasonable and orderly manner is the basis and guarantee for the safe, stable, efficient, and economic operation of the power grid. Conducting research on the physical asset management of the power grid and constructing a stable asset wall model have important practical significance for power grid enterprises to improve their asset management level.

[0033] The asset wall is an image description of the intensive commissioning situation of assets within the historical time range. After arranging historical data in chronological order, analyzing its changing pattern over time, and finally using the commissioning time as the horizontal axis and the asset scale as the vertical axis, the commissioning asset scale shows the shape of a "wall", reflecting the scale of existing assets commissioned in different years in history.

[0034] By using the asset wall and combining the translation years, the future technological transformation situation of some existing assets can be predicted. An asset wall is established through cumulative statistics of historical commissioned assets. The single-category assets are translated according to the retirement years of this category of assets to obtain the future technological transformation asset wall, and the investment scale of the selected unit's sub-equipment and the overall investment scale are predicted.

[0035] However, in recent years, with the in-depth research on the asset wall, it is unreasonable to simply shift all equipment quantities based on the average life. This not only ignores the randomness of the retirement life of power grid equipment but also neglects the huge technical renovation pressure on the future caused by the investment during the historical peak period. These will lead to large fluctuations in the scale of technical renovation during a certain period, resulting in unreasonable capital allocation and being unfavorable to the asset management of power grid enterprises. Therefore, constructing a suitable quantity prediction method is of great significance for the establishment of the asset wall.

[0036] Based on the above problems, the present application provides a method for establishing a physical asset wall. The following will Figure 1 describe the method for establishing the physical asset wall of the present application in detail.

[0037] Figure 1 is a schematic flowchart of the method for establishing a physical asset wall provided by an embodiment of the present application. Referring to Figure 1 the following will describe the method for establishing the physical asset wall in detail:

[0038] In step 101, obtain the information of retired equipment and the information of in-service equipment.

[0039] Exemplarily, the information of retired equipment includes the commissioning year, retirement year, service life, and retirement reason of the retired equipment, where the retirement reason includes technical renovation or overhaul; the information of in-service equipment includes the commissioning year of the in-service equipment and the annual commissioning quantity.

[0040] In some embodiments, obtaining the information of retired equipment and the information of in-service equipment includes: according to the ERP data of the power grid company, export the relevant information of the retired equipment, including the commissioning year, retirement year, service life, and retirement reason (technical renovation / overhaul) of the retired equipment; according to the records, also export the commissioning year of the in-service equipment and the annual commissioning quantity.

[0041] In step 102, perform cluster analysis on the information of retired equipment to obtain the significant years for the improvement of the retirement life of retired equipment.

[0042] Exemplarily, performing cluster analysis on the information of retired equipment to obtain the significant years for the improvement of the retirement life of retired equipment includes: performing multi-index clustering based on the Fisher optimal segmentation method and making a division that conforms to the time sequence to determine the exact years that have a significant impact due to technological changes, and the exact years are the significant years for the improvement of the retirement life of retired equipment.

[0043] In some embodiments, based on the Fisher optimal segmentation method, find the interval years with the most significant improvement in the retirement years of equipment (taking 2000 as an example). The retirement life situation of retired equipment can be divided into before 2000 and after 2000. The specific steps are as follows:

[0044] ① Define the sectional diameter:

[0045]

[0046] Among them, x G is the mean vector of the retirement life of retired equipment; x (a) is the retirement life of the a-th retired equipment; assume that the retirement lives of the retired equipment included in a class are {x i , x i+1 ,..., x j}, denote G = {i, i + 1,..., j}, D(i, j) represents the diameter of a class, and i and j are the start and end of a selected number of years in the time limit.

[0047] ② Define the classification loss function:

[0048]

[0049] Among them, L[B(n, k)] is the classification loss function; t represents the summation variable, summing from 1 to the k-th classification; k is the number of classifications, and i represents the quantile 1 = i 1 <i 2 <... <i k <n = i k+1 -1

[0050] ③ Solve the classification loss function

[0051]

[0052]

[0053] Among them, b(n, k) represents a way of dividing n retirement lives into k classes; j is a variable, which represents a certain value from 2 to n in the first formula and a certain value from k to n in the second formula.

[0054] ④ Define the classification objective function

[0055]

[0056] Among them, n is the number of ordered samples, k is the number of classes, P(n, k) is a way of dividing that makes the classification loss function L[B(n, k)] reach the minimum, and i is the quantile.

[0057] ⑤ Solve the optimal segmentation:

[0058] According to the recurrence formula:

[0059]

[0060]

[0061] Determine the optimal number of segments \(k\):

[0062] Take the value of \(k\) corresponding to the inflection point of the \(e[P(n,k)] - k\) curve as the optimal classification number. Finally, it is determined to be divided into 2 categories, and the year 2000 is the year when the equipment quality has been significantly improved.

[0063] In step 103, select one year before and one year after the significant improvement year as representative years respectively. Based on the information of retired equipment in the representative years, fit and correct the annual retirement rates of each year to obtain the actual annual retirement rates of each type of equipment.

[0064] Exemplarily, select one year before and one year after the significant improvement year as representative years respectively. Based on the information of retired equipment in the representative years, fit and correct the annual retirement rates of each year to obtain the actual annual retirement rates of each type of equipment, including: according to the preset conditions, select one year before and one year after the significant improvement year as representative years, denoted as the first representative year and the second representative year; randomly select a certain number of sample equipment from a certain type of retired equipment in the first representative year and the second representative year respectively, denoted as the first sample and the second sample; count the retirement lives of each equipment in the first sample and the second sample, and calculate the retirement rates of the equipment in the first sample and the second sample at different retirement lives respectively; through Weibull parameter fitting of the retirement rates of each service life calculated for a certain type of retired equipment in the first representative year and the second representative year, and using the fitted curve for correction, obtain the actual annual retirement rates of a certain type of retired equipment.

[0065] Among them, the preset conditions include: in the representative year, more than 80% of the same type of equipment put into operation in that year has been retired; in the representative year, the number of equipment put into operation in that year is relatively large compared with other years; in the representative year, the distribution of different retirement service years of the equipment put into operation in that year is more diverse than in other years.

[0066] In some embodiments, refer to Figure 2 , Figure 2 shows the equipment life ratio adjustment process, including: analyzing the situation of retired equipment, and selecting a representative year before and after 2000 respectively according to the following conditions (taking year A and year B as examples, \(A \lt 2000\), \(B \gt 2000\)), and the selection basis is as follows:

[0067] (1) Most of the same type of equipment put into operation in that year has been retired.

[0068] (2) The number of equipment put into operation in that year is relatively large compared with other years.

[0069] (3) The distribution range of the retirement service years of the equipment put into operation in that year is relatively large and has universality.

[0070] Taking the X device as an example, for the X device, after A and B years, 1000 devices are randomly sampled from year A and denoted as sample M; 1000 devices are randomly sampled from year B and denoted as sample N. The retirement lifetimes of each device in samples M and N are statistically counted, and the retirement rates of M and N at each retirement lifetime are calculated respectively. The calculation results are shown in Table 1 and Table 2, where Table 1 shows the retirement rate of sample M of the X device, and Table 2 shows the retirement rate of sample N of the X device.

[0071] Table 1 Retirement Rate of Sample M of X Device

[0072] Retirement age 1 2 ... ... ... K-1 K Retirement rate <![CDATA[p 1 > <![CDATA[p 2 > ... ... ... <![CDATA[p K-1 > <![CDATA[p K >

[0073] Table 2 Retirement Rate of Sample N of X Device

[0074] Retirement age 1 2 ... ... ... D-1 D Retirement rate <![CDATA[q 1 > <![CDATA[q 2 > ... ... ... <![CDATA[q D-1 > <![CDATA[q D >

[0075] Among them, theoretically D > K.

[0076] In some embodiments, Weibull parameter fitting is performed on the retirement rates of each life of samples M and N of the X device, including:

[0077] ① Weibull distribution density function and distribution function

[0078]

[0079]

[0080] Among them, γ is the location parameter, η is the scale parameter, and β is the shape parameter. Since the device may also be retired in the first year of use, so γ = 0. The three-parameter Weibull distribution degenerates into a two-parameter one.

[0081] ② Two-parameter Weibull distribution fitting

[0082] According to ①, we can transform the distribution function to get:

[0083]

[0084] Taking M as an example, the 1000 data are arranged according to the retirement lifetime length, a total of 1000, defined as the sample with serial number i in sample M, and is the retirement lifetime length of the i-th sample. Substitute it into formula (1):

[0085]

[0086] Among them, F(t (i) ) is the median rank, and the calculation formula is:

[0087] (1) After structural transformation, we get:

[0088]

[0089] Let (2) can be expressed as:

[0090] Y = βx + βlnη (3)

[0091] Let β = B and βlnη = A. Using 1000 sets of observed values (t (i) , F(t (i) )) to perform least squares fitting on equation (3):

[0092]

[0093]

[0094] Obtain After restoration, the estimated values of β and η can be obtained.

[0095] ③ Modify the annual retirement rate of each year according to the Weibull function

[0096] Taking the M sample as an example, substitute the retirement years from 1 to K into the Weibull density function respectively to obtain f(t). As shown in Tables 3 and 4, where Table 3 shows the retirement rate of the M sample of equipment X, and Table 4 shows the retirement rate of the N sample of equipment X.

[0097] Table 3 Retirement rate of the M sample of equipment X

[0098]

[0099]

[0100] Table 4 Retirement rate of the N sample of equipment X

[0101] Retirement age 1 2 ... ... ... D-1 D Retirement rate <![CDATA[q 1 > <![CDATA[q 2 > ... ... ... <![CDATA[q D-1 > <![CDATA[q D >

[0102] In step 104, according to the actual annual retirement rate of each type of equipment and the information of the in-service equipment, the number of in-service equipment retired each year in the future is obtained through random simulation.

[0103] Exemplarily, according to the retirement rate and the information of the in-service equipment, the number of in-service equipment retired each year in the future is obtained through random simulation, including: if the commissioning year of a certain type of in-service equipment is before the representative year, random simulation is performed at the retirement rate of the first representative year, and vice versa, random simulation is performed at the Weibull-corrected retirement rate of the second representative year to obtain the retirement year of a certain type of in-service equipment. Collate and summarize all types of in-service equipment to obtain the in-service equipment retired in each future year.

[0104] Among them, sorting and summarizing the in-service equipment of all categories includes: repeatedly obtaining the retirement year of a certain category of in-service equipment and taking the average value of the retirement year to eliminate randomness; summarizing the number of in-service equipment of the same type with the same voltage level that will retire in the same future year to obtain the number of in-service equipment that will retire each year in the future.

[0105] In some embodiments, after obtaining the Weibull-corrected life retirement rate tables and the data of the in-service equipment, each in-service equipment is simulated by an improved Monte Carlo random simulation method (the process is as Figure 3 shown), the retirement year of each equipment is obtained, and the data results are sorted to obtain the number of retirements in each future year; because the randomness of the Monte Carlo method is relatively large, in order to avoid obvious errors caused by large randomness, multiple simulations are performed, and then the average value is taken to eliminate randomness.

[0106] Specifically, the process of the improved Monte Carlo random simulation includes:

[0107] (1) Input the retirement life of the equipment corrected by the Weibull distribution and the corresponding ratio. Considering that the time intervals for the commissioning years of in-service equipment are relatively large and are accompanied by the reform and technological improvement of the power grid system, the retirement life conditions of existing retired equipment should be divided into two or more life and corresponding ratio situations for analysis;

[0108] (2) Perform random simulation using the improved Monte Carlo model:

[0109] 1. Determine a single equipment as the equipment put into use in the i-th year, and j is the j-th equipment put into use in the i-th year. For example, represents the 12th equipment put into use in 2008.

[0110] 2. Perform a loop judgment. For the equipment take a random number r, r ∈ [0, 1]. If for the equipment i < 2000, then r enters the first row loop in the table; i > T, r enters the second loop in the table.

[0111] Let the current year be the t-th year. For the j-th equipment put into use in the i-th year:

[0112] ① If t - i ≤ x 1 :

[0113] If 0 < r ≤ p x1 , then the retirement year x of the equipment = x 1 ;

[0114] If m = 1, 2, 3, 4,..., k - 1, then the retirement year x of the equipment = x m+1 .

[0115] ② If x m <t - i ≤ x m+1 :

[0116] Take the remaining life set:

[0117] T = {x (1) , x (1) ,..., x (k-1-m) |x m+1 ≥ t - i, m = 1, 2, 3, 4,..., k - 1}

[0118] (Take the first life x that meets the condition m+1 = x (1) , x k = x (k-1-m) ), and re - weight the life set as follows:

[0119]

[0120]

[0121] If then the retirement year x of the device = x (1) ;

[0122] If l = 1, 2,..., k - 1 - m, the retirement year of the device is x = x (1+l) .

[0123] ③ If t - i > x k , retire the device in that year.

[0124] 3. Conduct random simulations on all devices to obtain the future distribution of the number of retired and technically improved devices.

[0125] 4. Repeat the random simulation experiment multiple times. After eliminating the randomness of the number r taken for each device, calculate the mean value of the number of retired and technically improved devices for each device in future years, and draw the asset wall quantity graph.

[0126] In some embodiments, simulate different types of devices with different voltage levels, then organize and summarize the results. Aggregate the number of devices of the same type with the same voltage level that will be retired in the same year to obtain the number of retired devices each year in the future, and construct the quantity scale of retired devices of different types under each voltage level.

[0127] The above - mentioned physical asset wall establishment method can play a role in flattening the peak and filling the valley of the future retirement quantity curve, making the number of retired devices relatively stable each year, and thus making the funds relatively stable, which is conducive to reasonable fund allocation.

[0128] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0129] Corresponding to the physical asset wall establishment method described in the above embodiments, Figure 4 The structural block diagram of the physical asset wall establishment device provided by the embodiments of the present application is shown. For the sake of convenience of description, only the parts related to the embodiments of the present application are shown.

[0130] See Figure 4 , the physical asset wall establishment device in the embodiments of the present application may include an acquisition module 201, a clustering analysis module 202, a fitting module 203, and a stochastic simulation module 204.

[0131] Among them, the acquisition module 201 is used to acquire retired equipment information and in-service equipment information; the clustering analysis module 202 is used to perform clustering analysis on the retired equipment information to obtain the significant years of retired life improvement of the retired equipment; the fitting module 203 is used to select one year each before and after the significant improvement year as representative years, and based on the retired equipment information in the representative years, fit and correct the annual retirement rates of each year to obtain the actual annual retirement rates of each type of equipment; the stochastic simulation module 204 is used to obtain the number of retired equipment of in-service equipment in each future year through stochastic simulation according to the retirement rate and the in-service equipment information.

[0132] In some embodiments, the acquisition module 201 may specifically be used to: acquire retired equipment information and in-service equipment information, including: the retired equipment information includes the commissioning year, retirement year, service life, and retirement reasons of the retired equipment, and the retirement reasons include technical transformation or major overhaul; the in-service equipment information includes the commissioning year of the in-service equipment and the annual commissioning quantity.

[0133] In some embodiments, the clustering analysis module 202 may specifically be used to: perform multi-index clustering and time-sequence-compliant partitioning based on the fisher optimal segmentation method to determine the exact years with significant impacts caused by technological changes, and the exact years are the significant years of retired life improvement of the retired equipment.

[0134] In some embodiments, the fitting module 203 may specifically be used to: according to preset conditions, select one year each before and after the significant improvement year as representative years, denoted as the first representative year and the second representative year;

[0135] Randomly select a certain number of sample devices from a certain type of retired equipment in the first representative year and the second representative year, denoted as the first sample and the second sample; count the retirement lifetimes of each device in the first sample and the second sample, and calculate the retirement rates of the devices in the first sample and the second sample at different retirement lifetimes respectively; through Weibull parameter fitting for the retirement rates of each service life calculated for a certain type of retired equipment in the first representative year and the second representative year, and using the fitted curve for correction, obtain the actual annual retirement rates of a certain type of retired equipment.

[0136] Among them, the preset conditions include: in the representative year, more than 80% of the same type of equipment put into operation in that year has been retired; in the representative year, the number of equipment put into operation in that year is relatively large compared with other years; in the representative year, the distribution of the types of different retirement service lives of the equipment put into operation in that year is more than that in the remaining years.

[0137] In some embodiments, the random simulation module 204 can specifically be used to: according to the retirement rate and the information of the in-service equipment, through random simulation, obtain the number of retired equipment of the in-service equipment in each future year, including: if the commissioning year of a certain type of in-service equipment is before the representative year, perform random simulation with the retirement rate of the first representative year, and vice versa, perform random simulation with the Weibull-corrected retirement rate of the second representative year to obtain the retirement year of a certain type of in-service equipment, and collate and summarize all types of in-service equipment to obtain the in-service equipment retired in each future year.

[0138] Among them, collating and summarizing all types of in-service equipment includes: repeatedly obtaining the retirement year of a certain type of in-service equipment, taking the mean of the retirement years to eliminate randomness; aggregating the number of the same type of in-service equipment with the same voltage level retired in the same future year to obtain the number of in-service equipment retired in each future year.

[0139] It should be noted that the content such as the information interaction and execution process between the above-mentioned devices / units, due to being based on the same concept as the method embodiment of the present application, for its specific functions and the technical effects brought, reference can be specifically made to the method embodiment part, and details are not described here again.

[0140] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment and will not be elaborated here.

[0141] An embodiment of this application also provides a terminal device. Refer to Figure 5 , the terminal device 300 may include: at least one processor 310, a memory 320, and a computer program stored in the memory 320 and executable on the at least one processor 310. When the processor 310 executes the computer program, it implements the steps in any of the foregoing method embodiments, such as Figure 1 the steps 101 to 104 in the illustrated embodiment. Alternatively, when the processor 310 executes the computer program, it implements the functions of each module / unit in the foregoing device embodiments, such as Figure 4 the functions of the illustrated modules 201 to 204.

[0142] Exemplarily, the computer program can be divided into one or more modules / units. One or more modules / units are stored in the memory 320 and executed by the processor 310 to complete this application. The one or more modules / units can be a series of computer program segments capable of completing specific functions, and these program segments are used to describe the execution process of the computer program in the terminal device 300.

[0143] Those skilled in the art can understand that Figure 5 this is only an example of a terminal device and does not constitute a limitation on the terminal device. It may include more or fewer components than shown in the figure, or combine some components, or different components, such as input / output devices, network access devices, buses, etc.

[0144] The processor 310 may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0145] The memory 320 may be an internal storage unit of the terminal device or an external storage device of the terminal device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. The memory 320 is used to store the computer program and other programs and data required by the terminal device. The memory 320 may also be used to temporarily store data that has been output or is to be output.

[0146] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the buses in the drawings of the present application are not limited to only one bus or one type of bus.

[0147] The physical asset wall building method provided by the embodiments of the present application can be applied to terminal devices such as computers, tablet computers, laptop computers, netbooks, personal digital assistants (PDAs), mobile phones, etc. The embodiments of the present application do not impose any restrictions on the specific types of terminal devices.

[0148] The embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the various embodiments of the above-mentioned physical asset wall building method can be implemented.

[0149] An embodiment of the present application provides a computer program product. When the computer program product runs on a mobile terminal, it enables the mobile terminal to execute the steps in each of the above-described embodiments of the method for establishing a physical asset wall when executed.

[0150] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above-described embodiment methods of the present application, a computer program can be used to instruct relevant hardware to complete. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the photographing device / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc, etc.

[0151] In the above embodiments, the descriptions of each embodiment have their own emphases. For parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0152] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. A professional technician can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0153] In the embodiments provided by the present application, it should be understood that the disclosed device / network device and method can be implemented in other ways. For example, the device / network device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical, mechanical, or other form.

[0154] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0155] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for establishing a physical asset wall, characterized in that, it includes: Obtain retired equipment information and in-service equipment information; Conduct cluster analysis on the retired equipment information to obtain the significant years for improving the retired life of the retired equipment; Select one year each before and after the significant year as representative years, and based on the retired equipment information in the representative years, fit and correct the annual retirement rates to obtain the actual annual retirement rates of each type of equipment; According to the actual annual retirement rates of each type of equipment and the in-service equipment information, through random simulation, obtain the number of retired equipment of the in-service equipment in each future year; The conducting cluster analysis on the retired equipment information to obtain the significant years for improving the retired life of the retired equipment includes: Based on the fisher optimal segmentation method for multi-index clustering and chronological division, determine the exact years with significant impacts caused by technological changes, and the exact years are the significant years for improving the retired life of the retired equipment.

2. The method for establishing a physical asset wall according to claim 1, characterized in that, the retired equipment information includes the commissioning year, retirement year, service life, and retirement reasons of the retired equipment, and the retirement reasons include technological transformation or major overhaul; the in-service equipment information includes the commissioning year of the in-service equipment and the annual commissioning quantity.

3. The method for establishing a physical asset wall according to claim 1, characterized in that, the selecting one year each before and after the significant year as representative years, and based on the retired equipment information in the representative years, fit and correct the annual retirement rates to obtain the actual annual retirement rates of each type of equipment includes: According to preset conditions, select one year each before and after the significant year as representative years, denoted as the first representative year and the second representative year; Randomly select a certain number of sample equipment from a certain type of the retired equipment in the first representative year and the second representative year respectively, denoted as the first sample and the second sample; Statistically analyze the retired life of each equipment in the first sample and the second sample, and calculate the retirement rates of the equipment in the first sample and the second sample at different retired lives respectively; Through Weibull parameter fitting for the retirement rates of each service life calculated for a certain type of the retired equipment in the first representative year and the second representative year, and using the fitted curve for correction, obtain the actual annual retirement rates of a certain type of retired equipment.

4. The method for establishing a physical asset wall according to claim 3, characterized in that, the preset conditions include: In the representative year, more than 80% of the equipment of the same type commissioned in the current year has been retired; In the representative year, the quantity of equipment commissioned in the current year is relatively large compared with other years; In the representative year, the distribution of different retired service life types of the equipment commissioned in the current year is more than that in other years.

5. The method for establishing a physical asset wall according to claim 3, characterized in that, the obtaining the number of retired equipment of the in-service equipment in each future year through random simulation according to the retirement rate and the in-service equipment information includes: If the commissioning year of a certain type of the in-service equipment is before the representative year, perform random simulation with the retirement rate of the first representative year; otherwise, perform random simulation with the Weibull-corrected retirement rate of the second representative year to obtain the retirement year of a certain type of the in-service equipment. Collate and summarize all types of the in-service equipment to obtain the in-service equipment retired in each future year.

6. The method for establishing a physical asset wall according to claim 5, wherein, the collating and summarizing all types of the in-service equipment includes: repeatedly obtaining the retirement year of a certain type of the in-service equipment and taking the mean of the retirement years to eliminate randomness; summarize the quantity of the in-service equipment of the same type with the same voltage level retired in the same future year to obtain the quantity of the in-service equipment retired each year in the future.

7. A device for establishing a physical asset wall, wherein, it includes: an acquisition module, configured to acquire retired equipment information and in-service equipment information; a clustering analysis module, configured to perform clustering analysis on the retired equipment information to obtain the significant years for the improvement of the retirement life of the retired equipment; a fitting module, configured to select one year before and one year after the significant year as representative years, and based on the retired equipment information in the representative years, fit and correct the retirement rate of each year to obtain the actual retirement rate of each type of equipment for each year; a random simulation module, configured to obtain the quantity of the in-service equipment retired each year in the future through random simulation according to the retirement rate and the in-service equipment information; the clustering analysis module is specifically configured to: perform multi-index clustering and time-sequence-compliant partitioning based on the fisher optimal segmentation method to determine the exact years with significant impacts caused by technological changes, and the exact years are the significant years for the improvement of the retirement life of the retired equipment.

8. A terminal device, including a memory and a processor, and a computer program that can run on the processor is stored in the memory, wherein, when the processor calls and executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, and a computer program is stored in the computer-readable storage medium, wherein, when the computer program is executed by the processor, the method according to any one of claims 1 to 6 is implemented.

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