CN115115109A - Physical asset wall establishment method, device and terminal equipment - Google Patents

Abstract

The present application is applicable to the technical field of power grid equipment capital investment prediction, and provides a method, device and terminal equipment for establishing a physical asset wall. The method for establishing a physical asset wall includes: acquiring information on decommissioned equipment and equipment in operation; clustering information on decommissioned equipment The analysis shows that the retirement life of the decommissioned equipment has improved significantly; one year is selected as the representative year before and after the significant improvement year, and based on the information of the retired equipment in the representative year, the retirement rate of each year is fitted and corrected, and the actual value of each type of equipment is obtained. Annual decommissioning rate: According to the actual annual decommissioning rate of various types of equipment and the information of the equipment in operation, the number of decommissioned equipment in the future for the equipment in operation in the future is obtained through random simulation. The present application can achieve the effect of cutting peaks and filling valleys on the curve of the number of decommissioning in the future, so that the number of decommissioned equipment is relatively stable every year, so that the funds are relatively stable, which is conducive to the rational allocation of funds.

Description

Physical asset wall establishment method, device and terminal equipment

technical field

The present application belongs to the technical field of power grid equipment capital investment prediction, and in particular relates to a method, device and terminal equipment for establishing a physical asset wall.

Background technique

With the rapid economic development, the scale of physical assets of the power grid continues to increase, and the tasks of maintenance, overhaul and technical transformation of the power grid are becoming more and more 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 economical operation of the power grid.

The asset wall is a visual description of the intensive operation of assets in the historical time range. It is based on historical data arranged in chronological order, and then analyzes the law of its changes with time. Finally, the operation time is taken as the horizontal axis, and the asset scale is taken as the The vertical axis shows that the scale of assets put into operation is in the shape of a "wall", reflecting the scale and amount of existing assets that have been put into operation in different years in history.

In recent years, with the deepening of the research on asset walls, it is unreasonable to only rely on the average lifespan to translate the number of all equipment, which not only ignores the randomness of the retirement life of power grid equipment, but also ignores the huge investment in the future caused by the historical peak period. Technological pressure. These will lead to large fluctuations in the scale of technological transformation in a certain period of time, resulting in unreasonable allocation of funds, which is not conducive to the asset management of power grid enterprises.

SUMMARY OF THE INVENTION

In order to overcome the problems existing in the related art, the embodiments of the present application provide a physical asset wall establishment method, device and terminal device.

This application is achieved through the following technical solutions:

In a first aspect, an embodiment of the present application provides a method for establishing a physical asset wall, including: acquiring information on decommissioned equipment and information on equipment in operation; and performing cluster analysis on the information on decommissioned equipment to obtain an improvement in the decommissioned life of the decommissioned equipment. Significant year; one year is selected as the representative year before and after the significant year, and based on the information of retired equipment in the representative year, the annual decommissioning rate is fitted and corrected to obtain the actual annual decommissioning rate of each type of equipment; according to The actual annual decommissioning rate of the various types of equipment and the information of the equipment in operation are obtained through random simulation to obtain the number of equipment retired each year of the equipment in operation in the future.

Based on the first aspect, in some possible implementations, the decommissioned equipment information includes a commissioning year, a decommissioned year, a service life, and a reason for decommissioning, where the decommissioning reason includes technical modification or overhaul; the The information on the equipment in operation includes the year in which the equipment in operation was put into operation and the number of the equipment in operation each year.

Based on the first aspect, in some possible implementation manners, performing cluster analysis on the retired equipment information to obtain a significantly improved retirement life of the retired equipment includes: performing multi-index clustering based on fisher optimal segmentation method And in line with the time-series division, determine the exact age that has a significant impact due to technological changes, and the exact age is a significant increase in the retirement life of the decommissioned equipment.

Based on the first aspect, in some possible implementations, the year before and after the significant improvement year is selected as a representative year, and based on the retired equipment information in the representative year, the decommissioning rate of each year is fitted and corrected , to obtain the actual annual decommissioning rates of various types of equipment, including: according to preset conditions, select one year from the year before and after the significant improvement year as the representative year, and record it as the first representative year and the second representative year; In the first representative year and the second representative year of a certain type of the decommissioned equipment, a number of sample equipment are randomly selected and recorded as the first sample and the second sample; the first sample and the second sample are counted. The decommissioning life of each device in the sample, and the decommissioning rates of the devices in the first sample and the second sample under different decommissioning lives are calculated respectively; The Weibull parameter fitting is performed on the retirement rates of each service life calculated in the second representative year, and the curve after fitting is used to correct the actual retirement rates of a certain type of decommissioned equipment in each year.

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 the current year has been retired; in the representative year, the equipment put into operation in the current year has been retired; Compared with other years, the number of equipment in the said representative year is more distributed in the different decommissioning years of the equipment put into operation in that year than in other years.

Based on the first aspect, in some possible implementation manners, according to the decommissioning rate and the information of the equipment in operation, the number of decommissioned equipment in the future of the equipment in operation is obtained through random simulation, including: if a certain If the commissioning year of the equipment in operation is before the representative year, stochastic simulation is performed with the decommissioning rate of the first representative year, and conversely, the stochastic simulation is performed with the Weibull-corrected decommissioning rate of the second representative year, Obtain the retirement year of a certain type of equipment in operation, organize and summarize the equipment in operation of all categories, and obtain the equipment in operation to be retired in future years.

Based on the first aspect, in some possible implementations, the sorting and summarizing the equipment in operation of all categories includes: repeatedly obtaining the retirement years of a certain type of the equipment in operation, and taking the average value of the retirement years to eliminate Randomness; the number of the in-service equipment of the same type and of the same voltage level that will be retired in the same year in the future is aggregated to obtain the number of the in-service equipment that will be retired each year in the future.

The above-mentioned physical asset wall establishment method can cut peaks and fill valleys on the curve of the number of decommissioning in the future, so that the number of decommissioned equipment every year is relatively stable, so that the funds are relatively stable, which is conducive to the rational allocation of funds.

In a second aspect, an embodiment of the present application provides an apparatus for establishing a physical asset wall, including: an acquisition module for acquiring information on decommissioned equipment and equipment in operation; a clustering analysis module for clustering the information on decommissioned equipment class analysis, to obtain the significant years of decommissioning life improvement of the decommissioned equipment; the fitting module is used to select one year from each of the years before and after the significant improvement year as the representative years, and based on the information of the decommissioned equipment in the representative years, the Combining and correcting the annual decommissioning rates to obtain the actual annual decommissioning rates of various types of equipment; the stochastic simulation module is used to obtain the future annual decommissioning equipment of the in-operation equipment through random simulation according to the decommissioning rate and the information of the equipment in operation. quantity.

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 a physical asset wall according to any one of the first aspects is implemented.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, implements any one of the first aspect How to build a physical asset wall.

It can be understood that, for the beneficial effects of the foregoing second aspect to the fourth aspect, reference may be made to the relevant descriptions in the foregoing first aspect, and details are not described herein again.

It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the specification.

Description of drawings

In order to illustrate the technical solutions in the embodiments of the present application more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only for the present application. In some embodiments, for those of ordinary skill in the art, other drawings can also be obtained according to these drawings without any creative effort.

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

FIG. 2 is a schematic flowchart of equipment life ratio adjustment in a method for establishing a physical asset wall provided by an embodiment of the present application;

3 is a schematic flowchart of a simulation of the number of decommissioned equipment in a method for establishing a physical asset wall provided by an embodiment of the present application;

4 is a schematic structural diagram of a physical asset wall building device provided by an embodiment of the present application;

FIG. 5 is a schematic structural diagram of a terminal device provided by an embodiment of the present application.

Detailed ways

In the following description, for the purpose of illustration rather than limitation, specific details such as a specific system structure and technology are set forth in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It is to be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described feature, integer, step, operation, element and/or component, but does not exclude one or more other The presence or addition of features, integers, steps, operations, elements, components and/or sets thereof.

It will also be understood that, as used in this specification and the appended claims, the term "and/or" refers to and including any and all possible combinations of one or more of the associated listed items.

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

In addition, in the description of the specification of the present application and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the description, and should not be construed as indicating or implying relative importance.

References in this specification to "one embodiment" or "some embodiments" and the like mean that a particular feature, structure or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in other embodiments," etc. in various places in this specification are not necessarily All refer to the same embodiment, but mean "one or more but not all embodiments" unless specifically emphasized otherwise. The terms "including", "including", "having" and their variants mean "including but not limited to" unless specifically emphasized otherwise.

With the rapid economic development, the scale of physical assets of the power grid continues to rise, and the tasks of maintenance, overhaul and technical transformation of the power grid are becoming more and more 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 economical operation of the power grid. It is of great practical significance for power grid enterprises to improve the level of asset management to carry out research on physical asset management of power grid and build a stable asset wall model.

The asset wall is a visual description of the intensive operation of assets in the historical time range. It is based on historical data arranged in chronological order, and then analyzes the law of its changes with time. Finally, the operation time is taken as the horizontal axis, and the asset scale is taken as the The vertical axis shows that the scale of assets put into operation is in the shape of a "wall", reflecting the scale and amount of existing assets that have been put into operation in different years in history.

Using the asset wall, combined with the translation period, can predict the future technical transformation of the existing assets. The asset wall is established by accumulating statistics of historical assets in operation, and a single type of asset is shifted according to the retirement years of this type of asset to obtain a future technological transformation asset wall, and predict the investment scale and overall investment scale of the selected unit and sub-equipment.

However, in recent years, with the deepening of the research on asset walls, it is unreasonable to only rely on the average lifespan to shift the number of all equipment. Huge technological transformation pressure. These will lead to large fluctuations in the scale of technological transformation in a certain period of time, resulting in unreasonable allocation of funds, which is not conducive to the asset management of power grid enterprises. Therefore, building an appropriate quantity forecasting method is of great significance to the establishment of asset walls.

Based on the above problems, the present application provides a method for establishing a physical asset wall. The method for establishing a physical asset wall of the present application will be described in detail below with reference to FIG. 1 .

1 is a schematic flowchart of a method for establishing a physical asset wall provided by an embodiment of the present application. Referring to FIG. 1 , the detailed description of the method for establishing a physical asset wall is as follows:

In step 101, information on retired equipment and equipment in operation is acquired.

Exemplarily, the information on the decommissioned equipment includes the year of commissioning, the year of decommissioning, the service life and the reason for decommissioning, wherein the reason for the decommissioning includes technical transformation or overhaul; the information on the equipment in operation includes the year in operation and the annual Shipping quantity.

In some embodiments, acquiring the information about the decommissioned equipment and the equipment in operation includes: according to the ERP data of the power grid company, deriving the relevant information of the decommissioned equipment, including the commissioning year of the decommissioned equipment, the decommissioning year of the decommissioned equipment, the service life, and the decommissioned equipment. Reason (technical transformation/overhaul); according to records, also derive the commissioning year of the equipment in operation and the annual commissioning quantity.

In step 102, cluster analysis is performed on the retired equipment information to obtain a significant year increase in the retired lifespan of the retired equipment.

Exemplarily, performing cluster analysis on retired equipment information to obtain a significant increase in the retirement life of the retired equipment includes: performing multi-index clustering based on Fisher's optimal segmentation method and dividing in accordance with time series, and determining the significant impact caused by technological changes. The exact number of years is a significant year increase in the retirement life of the decommissioned equipment.

In some embodiments, based on Fisher's optimal segmentation method, an interval year (taking 2000 as an example) with the most significant increase in the retirement life of the equipment is found, and the retirement life of the retired equipment can be divided into before 2000 and after 2000. Specific steps are as follows:

①Define the segment diameter:

Among them, x _G is the mean vector of the retirement life of the retired equipment; x _(a) is the retirement life of the a-th retired equipment; let the retirement life of the retired equipment included in a class be { _xi , _xi+1 ,. ..,x _j }, denoted G={i,i+1,...,j}, D(i,j) is expressed as the diameter of a class, i and j are the start of a period of years selected in the years start and end.

②Define the classification loss function:

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

③ Solve the classification loss function

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

④Define the classification objective function

Among them, n is the number of ordered samples, k is the number of categories, P(n,k) is a classification method that minimizes the classification loss function L[B(n,k)], and i is the quantile.

⑤ Solve the optimal segmentation:

According to the recursive formula:

Determine the optimal number of splits k:

Take the k value corresponding to the inflection point of the e[P(n,k)]-k curve as the most classified number. It was finally determined to be divided into two categories, and the year 2000 was the year of significant improvement in equipment quality.

In step 103, one year is selected as a representative year from the year before and after the significant improvement year, and based on the retired equipment information in the representative year, the annual retirement rate is fitted and corrected to obtain the actual annual retirement rate of each type of equipment.

Exemplarily, one year is selected as the representative year before and after the significant improvement year, and based on the information of retired equipment in the representative year, the annual retirement rate is fitted and corrected to obtain the actual annual retirement rate of each type of equipment, including: Set the conditions, select one year from the year before and after the significant improvement year as the representative year, and record it as the first representative year and the second representative year; Randomly select a number of sample devices, denoted as the first sample and the second sample; count the retirement life of each device in the first sample and the second sample, and calculate the equipment in the first sample and the second sample respectively. Retirement rates under different retirement lives; by fitting the retirement rates of each service life of a certain type of decommissioned equipment in the first representative year and the second representative year, fitting the Weibull parameters, and using the fitted curve correction to obtain a certain The actual annual decommissioning rate of a class of decommissioned equipment.

Among them, the preset conditions include: in the representative year, more than 80% of the equipment of the same type put into operation in the current year has been retired; in the representative year, the number of equipment put into operation in the current year is larger than that in other years; in the representative year, the investment in the current year The distribution of different types of decommissioning years of the equipment shipped is more than the rest of the years.

In some embodiments, referring to FIG. 2, FIG. 2 shows the equipment life ratio adjustment process, including: analyzing the condition of decommissioned equipment, and selecting a representative year around 2000 according to the following conditions (with year A and year B as the For example, A<2000, B>2000), the selection is based on the following:

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

(2) The number of equipment put into operation in the current year is larger than that in other years.

(3) The distribution range of the decommissioned service life of the equipment put into operation in the current year is relatively large and universal.

Taking X equipment as an example, after finding the years A and B for X equipment, 1000 equipments are randomly sampled from year A and recorded as sample M; 1000 equipments are randomly sampled from year B and recorded as sample N. Calculate the retirement life of each equipment in the M and N samples, and calculate the retirement rate of M and N under each retirement life. The calculation results are shown in Table 1 and Table 2, wherein, Table 1 shows the retirement rate of X equipment M samples, and Table 2 shows the retirement rate of X equipment N samples.

Table 1 Retirement rate of X equipment M sample

Retirement years 1 2 ... ... ... K-1 K Retirement rate p₁ p₂ ... ... ... p_K-1 p_K

Table 2 Retirement rate of X equipment N sample

Retirement years 1 2 ... ... ... D-1 D Retirement rate q₁ q₂ ... ... ... q_D-1 q_D

Among them, theoretically D>K.

In some embodiments, Weibull parameter fitting is performed on each lifetime retirement rate of X equipment samples M, N, including:

①Weibull distribution density function and distribution function

where γ is the position parameter, η is the scale parameter, and β is the shape parameter. Since decommissioning may also occur in the first year of equipment use, γ=0. The three-parameter Weibull distribution degenerates into two parameters.

② Two-parameter fitting of Weibull distribution

According to ①, we can deform the distribution function to get:

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

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

(1) After the structure conversion, we get:

(2)可以表示为：make

(2) can be expressed as:

Y=βx+βlnη (3)

Let β=B, βlnη=A, use 1000 groups of observations (t _(i) , F(t _(i) )) to perform least squares fitting on equation (3):

还原后可求得β，η估计值。get

After reduction, the estimated values of β and η can be obtained.

③ Correct the retirement rate of each year according to the Weibull function

Taking the M sample as an example, the retirement years 1 to K years are respectively brought into the Weibull density function to obtain f(t). As shown in Table 3 and Table 4, wherein, Table 3 shows the retirement rate of X equipment M samples, and Table 4 shows the retirement rate of X equipment N samples.

Table 3 Retirement rate of X equipment M sample

Table 4 X-equipment N sample retirement rate

Retirement years 1 2 ... ... ... D-1 D Retirement rate q₁ q₂ ... ... ... q_D-1 q_D

In step 104, according to the actual annual decommissioning rate of each type of equipment and the information of the equipment in operation, the number of the equipment in operation in the future each year to be retired is obtained through random simulation.

Exemplarily, according to the decommissioning rate and the information of the equipment in operation, through random simulation, the number of retired equipment in each future year of the equipment in operation can be obtained, including: if the commissioning year of a certain type of equipment in operation is before the representative year, the first representative The stochastic simulation is carried out for the retirement rate of the year, otherwise, the Weibull-corrected retirement rate of the second representative year is used for random simulation to obtain the retirement year of a certain type of equipment in operation. equipment in transit.

Among them, sorting and summarizing all types of equipment in operation includes: repeatedly obtaining the retirement year of a certain type of equipment in operation, taking the average value of the retirement year to eliminate randomness; The number of equipment is aggregated to obtain the number of in-service equipment that will be retired each year in the future.

In some embodiments, after obtaining the Weibull-corrected table of retirement rates for each life and the data of the equipment in operation, each in-service equipment is simulated by an improved Monte Carlo stochastic simulation method (the process is shown in Figure 3) , get the retirement year of each equipment, and sort out the data results to get the number of retirements in the future; because the random line of the Monte Carlo method is large, in order to avoid obvious errors caused by large randomness, so Run multiple simulations and then average to remove randomness.

Specifically, the process of the improved Monte Carlo stochastic simulation includes:

(1) Enter the equipment decommissioning life and the corresponding proportion after the Weibull distribution correction. Considering that the time interval of the operating equipment investment year is relatively large, and it is accompanied by the reform and technical improvement of the power grid system, it should be divided into two or more lifespans and corresponding proportions according to the decommissioning life of the existing decommissioned equipment. to analyze;

(2) Stochastic simulation using an improved Monte Carlo model:

为第i年投入的设备，j为第i年投入的第j个设备，例如

代表2008年投入的第12个设备。1. Identify a single device

is the equipment invested in the ith year, j is the jth equipment invested in the ith year, for example

Represents the 12th equipment put into operation in 2008.

取随机数r，r∈[0,1]。如果设备

中i<2000，则r进入表格中第一行循环；i>T,r进入表格中第二个循环。2. Make a cycle judgment, and check the equipment

Take a random number r, r∈[0,1]. if the device

In i<2000, r enters the first loop in the table; i>T, r enters the second loop in the table.

Let the current year be the t-th year, and for the j-th equipment invested in the i-th year:

①If _ti≤x1 :

If 0<r≤p _x1 , then the retirement year of the equipment x=x ₁ ;

m＝1,2,3,4,...,k-1，则设备的退役年x＝x_m+1。if

m=1,2,3,4,...,k-1, then the retirement year of the equipment x=x _m+1 .

②If x _m <ti≤x _m+1 :

Take the remaining life set:

T={x ₍₁₎ ,x ₍₁₎ ,...,x _(k-1-m) |x _m+1 ≥ti,m=1,2,3,4,...,k-1 }

(take the first lifetime x _m+1 = x ₍₁₎ , x _k = x _(k-1-m) ) that satisfies the conditions, and re-weight the lifetime set as follows:

则设备的退役年x＝x₍₁₎；if

Then the retirement year of the equipment x=x ₍₁₎ ;

l＝1,2,...,k-1-m，设备的退役年为x＝x_(1+l)。if

l=1,2,...,k-1-m, and the retirement year of the equipment is x=x _(1+l) .

③If ti>x _k , the equipment should be retired in the current year.

3. Perform random simulation on all equipment, and obtain the distribution of the number of future equipment decommissioning technical renovations.

4. Repeatedly carry out multiple random simulation experiments, after eliminating the randomness of the number r of each equipment, find the average value of the number of retired technical renovations for this equipment in each future year, and draw a graph of the number of asset walls.

In some embodiments, different types of equipment with different voltage levels are simulated, and then the results are sorted and summarized, and the number of the same type of equipment with the same voltage level retired in the same year is summarized to obtain the annual decommissioned equipment in the future. Quantity to construct a scale of decommissioning of different equipment types at each voltage level.

The above-mentioned physical asset wall establishment method can cut peaks and fill valleys on the curve of the number of decommissioning in the future, so that the number of decommissioned equipment every year is relatively stable, so that the funds are relatively stable, which is conducive to the rational allocation of funds.

It should be understood that the size of the sequence numbers of the steps in the above embodiments does not mean the sequence of execution, and the execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

Corresponding to the method for establishing a physical asset wall described in the above embodiment, FIG. 4 shows a structural block diagram of the device for establishing a physical asset wall provided by the embodiment of the present application. part.

Referring to FIG. 4 , the apparatus for establishing a physical asset wall in this embodiment of the present application may include an acquisition module 201 , a cluster analysis module 202 , a fitting module 203 and a random simulation module 204 .

Among them, the acquisition module 201 is used for acquiring information of decommissioned equipment and equipment in operation; the clustering analysis module 202 is used for clustering analysis on the information of decommissioned equipment, so as to obtain a significant year increase in the decommissioning life of the decommissioned equipment; the fitting module 203, It is used to select one year before and after the significant improvement year as a representative year, and based on the retired equipment information in the representative year, fit and correct the annual decommissioning rate to obtain the actual annual decommissioning rate of each type of equipment; the random simulation module 204, using According to the decommissioning rate and the information of the equipment in operation, through random simulation, the number of decommissioned equipment in the future of the equipment in operation can be obtained.

In some embodiments, the obtaining module 201 may be specifically configured to: obtain information on decommissioned equipment and information on equipment in operation, including: the information on decommissioned equipment includes the year of commissioning, the year of decommissioning, the age of use, and the reason for decommissioning, and the reasons for decommissioning include Technical renovation or overhaul; the information of equipment in operation includes the year of operation of the equipment in operation and the number of operations in each year.

In some embodiments, the clustering analysis module 202 can be specifically used to: perform multi-index clustering based on the optimal segmentation method of fisher and conform to the time-series division, and determine the exact age of the significant impact caused by the technical change, and the exact age is the retirement age. The decommissioning life of the equipment has increased significantly by years.

In some embodiments, the fitting module 203 may be specifically configured to: according to preset conditions, select one year from each year before and after the significant improvement year as the representative year, and record it as the first representative year and the second representative year;

Randomly select a certain number of sample equipment from a certain type of decommissioned equipment in the first representative year and the second representative year, denoted as the first sample and the second sample; count 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 under different retirement lives; by calculating the service life of a certain type of decommissioned equipment in the first representative year and the second representative year The decommissioning rate is fitted with Weibull parameters, and the fitted curve is used to correct the actual annual decommissioning rate of a certain type of decommissioned equipment.

Among them, the preset conditions include: in the representative year, more than 80% of the equipment of the same type put into operation in the current year has been retired; in the representative year, the number of equipment put into operation in the current year is larger than that in other years; in the representative year, the investment in the current year The distribution of different types of decommissioning years of the equipment shipped is more than the rest of the years.

In some embodiments, the stochastic simulation module 204 can be specifically used to: obtain, through random simulation, the number of decommissioned equipment in the future in the future according to the decommissioning rate and the information of the equipment in operation, including: if the investment of a certain type of equipment in operation is Before the representative year, the stochastic simulation is carried out with the retirement rate of the first representative year, otherwise, the stochastic simulation is carried out with the Weibull-corrected retirement rate of the second representative year to obtain the retirement year of a certain type of equipment in operation. For the equipment in operation in the category, get the equipment in operation that will be retired in future years.

Among them, sorting and summarizing all types of equipment in operation includes: repeatedly obtaining the retirement year of a certain type of equipment in operation, taking the average value of the retirement year to eliminate randomness; The number of equipment is aggregated to obtain the number of in-service equipment that will be retired each year in the future.

It should be noted that the information exchange, execution process and other contents between the above-mentioned devices/units are based on the same concept as the method embodiments of the present application. For specific functions and technical effects, please refer to the method embodiments section. It is not repeated here.

Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned functions can be allocated to different functional units, Module completion, that is, dividing the internal structure of the device into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated in one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit, and the above-mentioned integrated units may adopt hardware. It can also be realized in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing from each other, and are not used to limit the protection scope of the present application. For the specific working processes of the units and modules in the above-mentioned system, reference may be made to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

An embodiment of the present application further provides a terminal device. Referring to FIG. 5 , the terminal device 300 may include: at least one processor 310 , a memory 320 , and a terminal device stored in the memory 320 and available on the at least one processor 310 The running computer program, when the processor 310 executes the computer program, implements the steps in any of the foregoing method embodiments, for example, steps 101 to 104 in the embodiment shown in FIG. 1 . Alternatively, when the processor 310 executes the computer program, the functions of the modules/units in the foregoing device embodiments, such as the functions of the modules 201 to 204 shown in FIG. 4 , are implemented.

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

Those skilled in the art can understand that FIG. 5 is only an example of a terminal device, and does not constitute a limitation on the terminal device. It may include more or less components than the one shown in the figure, or combine some components, or different components, such as Input and output devices, network access devices, buses, etc.

The processor 310 may be a central processing unit (Central Processing Unit, CPU), and may also be other general-purpose processors, digital signal processors (Digital Signal Processors, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf processors Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 320 may be an internal storage unit of the terminal device, or may be 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 memory card (Flash Card) etc. The memory 320 is used for storing 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 will be output.

The bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, a Peripheral Component (Peripheral Component, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, or the like. The bus can be divided into address bus, data bus, control bus and so on. For convenience of representation, the buses in the drawings of the present application are not limited to only one bus or one type of bus.

The method for establishing a physical asset wall provided by the embodiments of the present application can be applied to terminal devices such as computers, tablet computers, notebook computers, netbooks, personal digital assistants (PDAs), and mobile phones. Type does not impose any restrictions.

Embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the computer program can realize the above-mentioned various embodiments of the physical asset wall establishment method. step.

The embodiments of the present application provide a computer program product, when the computer program product is executed on a mobile terminal, the steps in each of the foregoing embodiments of the method for establishing a physical asset wall can be implemented when the mobile terminal executes the computer program product.

The integrated unit, if implemented in the form of a software functional unit and sold or used as an independent product, may be stored in a computer-readable storage medium. Based on this understanding, the present application realizes all or part of the processes in the methods of the above embodiments, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When executed by a processor, the steps of each of the above method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form, and the like. The computer-readable medium may include at least: any entity or device capable of carrying 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, RandomAccess Memory), electrical carrier signal, telecommunication signal, and software distribution medium. For example, U disk, mobile hard disk, disk or CD, etc.

In the foregoing embodiments, the description of each embodiment has its own emphasis. For parts that are not described or described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of this application.

In the embodiments provided in this application, it should be understood that the disclosed apparatus/network device and method may be implemented in other manners. For example, the apparatus/network device embodiments described above are only 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, such as multiple units. Or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

The above-mentioned embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the above-mentioned embodiments, those of ordinary skill in the art should understand that: it can still be used for the above-mentioned implementations. The technical solutions described in the examples are modified, or some technical features thereof are equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions in the embodiments of the application, and should be included in the within the scope of protection of this application.

Claims (10)

1. A physical asset wall building method is characterized by comprising the following steps:

acquiring retired equipment information and in-transit equipment information;

performing cluster analysis on the decommissioned equipment information to obtain the decommissioned service life of the decommissioned equipment, which is obviously prolonged;

selecting one year from before and after the significant year of promotion as a representative year, fitting and correcting the retirement rate of each year based on the retired equipment information in the representative year, and obtaining the actual retirement rate of each year of each type of equipment;

and obtaining the quantity of the equipment decommissioned every year in the future of the equipment in transit through random simulation according to the actual annual decommissioning rate of each type of equipment and the information of the equipment in transit.

2. The physical asset wall building method according to claim 1, wherein the decommissioned device information includes a year of operation, a year of decommissioning, a service life, and a reason for decommissioning of the decommissioned device, the reasons for decommissioning including technical modification or major repair;

the in-transit device information includes a commissioning year of the in-transit device and a commissioning quantity per year.

3. The method for building the physical asset wall according to claim 1, wherein the step of performing cluster analysis on the decommissioned equipment information to obtain a significant year of life improvement of the decommissioned equipment comprises:

and performing multi-index clustering based on a fisher optimal segmentation method, and determining the exact age of the major influence caused by technical change, wherein the exact age is the retired service life of the retired equipment and is obviously prolonged.

4. The method for building a physical asset wall according to claim 1, wherein the step of fitting and correcting the annual retirement rate based on the retired equipment information in the representative year by selecting one year from before and after the significant year of the promotion as the representative year to obtain the actual annual retirement rate of each type of equipment comprises:

according to preset conditions, selecting one year from before and after the significant year of the promotion as a representative year, and recording the representative year as a first representative year and a second representative year;

randomly extracting a plurality of sample devices from one class of retired devices of the first representative year and the second representative year respectively, and recording the sample devices as a first sample and a second sample;

counting the retired life of each device in the first sample and the second sample, and respectively calculating the retired rates of the devices in the first sample and the second sample under different retired lives;

and performing Weibull parameter fitting on the service life retirement rate of a certain class of retired equipment calculated in the first representative year and the second representative year, and correcting by using a fitted curve to obtain the actual annual retirement rate of the certain class of retired equipment.

5. The physical asset wall building method according to claim 4, wherein the preset conditions include:

over 80% of the same type of equipment that is in operation in the current year has been decommissioned in the representative year;

in the representative year, the number of devices put into operation in the current year is larger compared with other years;

in the representative year, the distribution of the types of different retired years of use of the equipment put into operation in the year is greater than the rest of the year.

6. The method for building the physical asset wall according to claim 4, wherein the obtaining the number of the equipment retired in the future every year of the equipment in transit through stochastic simulation according to the retirement rate and the information of the equipment in transit comprises:

if the commissioning year of a certain type of the in-service equipment is before the representative year, randomly simulating the decommissioning rate of the first representative year, otherwise, randomly simulating the decommissioning rate corrected by Weibull of the second representative year to obtain the decommissioning year of the certain type of the in-service equipment, sorting and summarizing all types of the in-service equipment, and obtaining the in-service equipment decommissioned in the next year.

7. The physical asset wall building method according to claim 6, wherein said collating and summarizing all the categories of said on-board devices comprises:

repeatedly obtaining the retired years of a certain type of the in-service equipment, and averaging the retired years to eliminate randomness;

and summarizing the quantity of the in-service equipment of the same type of the same voltage class retired in the same year in the future to obtain the quantity of the in-service equipment retired in the future every year.

8. A physical asset wall building device, comprising:

the acquisition module is used for acquiring decommissioned equipment information and in-transit equipment information;

the cluster analysis module is used for carrying out cluster analysis on the retired equipment information to obtain the retired service life of the retired equipment, which is obviously prolonged;

the fitting module is used for fitting and correcting the retirement rate of each year from one year before and one year after the significant year of promotion as a representative year based on the retired equipment information in the representative year to obtain the actual retirement rate of each year of each type of equipment;

and the random simulation module is used for obtaining the number of the retired equipment of the in-transit equipment every year in the future through random simulation according to the retirement rate and the in-transit equipment information.

9. A terminal device comprising a memory and a processor, the memory having stored therein a computer program operable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when the computer program is invoked and executed.

10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.

Images