CN113516400A - Equipment management method and system - Google Patents

Equipment management method and system Download PDF

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CN113516400A
CN113516400A CN202110845918.6A CN202110845918A CN113516400A CN 113516400 A CN113516400 A CN 113516400A CN 202110845918 A CN202110845918 A CN 202110845918A CN 113516400 A CN113516400 A CN 113516400A
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importance
equipment
multidimensional
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judgment matrix
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吴建国
马东森
甘晓晶
张华东
于信波
杨春
孙鹏
刘士方
孙广庆
张敬
吴立星
邵帅
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Beijing Bicotest Tech Co ltd
Huaneng Shandong Power Generation Co Ltd
Huaneng Weihai Power Generation Co Ltd
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Huaneng Shandong Power Generation Co Ltd
Huaneng Weihai Power Generation Co Ltd
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Abstract

The invention provides a device management method and a system, wherein the method comprises the following steps: acquiring a multidimensional judgment matrix of equipment; the multi-dimensional judgment matrix is used for describing the correlation among a plurality of importance indexes of the same equipment; calculating the importance of the equipment according to the multidimensional judgment matrix; determining the importance level of the equipment according to the importance of the equipment; and maintaining the equipment according to the importance level of the equipment. The invention can carry out quantitative processing on the importance degrees of different devices in a factory, and adopts different modes to manage according to different importance degrees of the devices, thereby improving the management precision and efficiency of the devices.

Description

Equipment management method and system
Technical Field
The present invention relates to the field of device management technologies, and in particular, to a device management method and system.
Background
With the development of science and technology, the demand of industry, agriculture and residents on electric energy is higher and higher, in order to meet the power consumption demand of various industries, the scale of a power plant is continuously enlarged, the electric energy storage capacity of a power grid is also continuously enlarged, and under the background, the equipment of the power plant needs to be updated in time to ensure the safe and reliable operation of the power grid, so that the maintenance and management of the equipment of the power plant are particularly important. The traditional equipment management mainly depends on manual recording management, and the management mode has many defects, such as procedure redundancy, low efficiency, easy error, and incapability of timely feeding back the use and maintenance conditions of equipment. Meanwhile, the repeated labor causes waste of manpower, financial resources and material resources to gradually increase.
Disclosure of Invention
The invention aims to provide a device management method and a device management system, which are used for quantizing the importance degrees of different devices in a factory, and managing the devices in different modes according to different importance degrees of the devices, so that the precision and the efficiency of device management are improved.
In order to achieve the purpose, the invention provides the following scheme:
a device management method, comprising:
acquiring a multidimensional judgment matrix of equipment; the multi-dimensional judgment matrix is used for describing the correlation among a plurality of importance indexes of the same equipment;
calculating the importance of the equipment according to the multidimensional judgment matrix;
determining the importance level of the equipment according to the importance of the equipment;
and maintaining the equipment according to the importance level of the equipment.
Optionally, the importance index includes one or more or all of safety impact, impact of failure on the system, equipment failure frequency, maintenance cost, outage loss, monitorability, outage time, and ease of maintenance.
Optionally, the obtaining the multidimensional determination matrix of the device specifically includes:
determining a plurality of importance indexes of the same equipment;
constructing a multidimensional judgment matrix according to a plurality of importance indexes;
using formulas
Figure BDA0003180759450000021
Calculating the random consistency ratio of the multidimensional judgment matrix;
judging whether the random consistency ratio of the multidimensional judgment matrix is smaller than a consistency ratio threshold value or not to obtain a first judgment result;
if the first judgment result is negative, updating the multidimensional judgment matrix, and executing the step of utilizing a formula
Figure BDA0003180759450000022
Calculating a random consistency ratio of the multi-dimensional decision matrix;
wherein, CRRandom consistency ratio for multi-dimensional decision matrix, CIFor a general consistency index of the multi-dimensional decision matrix,
Figure BDA0003180759450000023
λmaxfor the maximum eigenvalue of the multi-dimensional decision matrix, N is the total number of importance indicators, RIAnd the average random consistency index of the multidimensional judgment matrix.
Optionally, the calculating the importance of the device according to the multidimensional determination matrix specifically includes:
determining the weight of each importance index by using a feature vector method according to the multidimensional judgment matrix;
acquiring the factor score of each importance index;
using a formula according to the factor score and weight of each importance index
Figure BDA0003180759450000024
Calculating the importance of the equipment;
where Index is the importance of the equipment, AnThe factor score, α, for the nth importance indicatornIs the weight of the nth importance indicator.
Optionally, the determining, according to the multidimensional determination matrix, the weight of each importance index by using a feature vector method specifically includes:
carrying out normalization processing on the multidimensional judgment matrix to obtain a normalized multidimensional judgment matrix;
and determining the average number of elements in each row in the normalized multi-dimensional judgment matrix as the weight of the corresponding importance index of each row.
Optionally, the importance levels of the device include: key equipment, important equipment, general equipment and maintenance-free equipment; wherein, the importance degree corresponding to the key equipment, the important equipment, the general equipment and the maintenance-free equipment is reduced in sequence; the maintenance intensity of key equipment, important equipment, general equipment and maintenance-free equipment is reduced in sequence.
A device management system, comprising:
the multidimensional judgment matrix acquisition module is used for acquiring a multidimensional judgment matrix of the equipment; the multi-dimensional judgment matrix is used for describing the correlation among a plurality of importance indexes of the same equipment;
the importance calculation module is used for calculating the importance of the equipment according to the multidimensional judgment matrix;
the importance level determining module is used for determining the importance level of the equipment according to the importance level of the equipment;
and the equipment maintenance module is used for maintaining the equipment according to the importance level of the equipment.
Optionally, the importance index includes one or more or all of safety impact, impact of failure on the system, equipment failure frequency, maintenance cost, outage loss, monitorability, outage time, and ease of maintenance.
Optionally, the multidimensional determination matrix obtaining module specifically includes:
an importance index determination unit configured to determine a plurality of importance indexes of the same device;
the multidimensional judgment matrix construction unit is used for constructing a multidimensional judgment matrix according to the importance indexes;
a random consistency ratio calculation unit for using a formula
Figure BDA0003180759450000031
Calculating the random consistency ratio of the multi-dimensional judgment matrix;
the judging unit is used for judging whether the random consistency ratio of the multidimensional judging matrix is smaller than a consistency ratio threshold value or not to obtain a first judging result; if the first judgment result is negative, calling a multidimensional judgment matrix updating unit;
a multidimensional judgment matrix updating unit for updating the multidimensional judgment matrix and calling the random consistency ratio calculating unit;
wherein, CRRandom consistency ratio for multi-dimensional decision matrix, CIFor one of a multi-dimensional decision matrixThe general index of consistency is that,
Figure BDA0003180759450000032
λmaxfor the maximum eigenvalue of the multi-dimensional decision matrix, N is the total number of importance indicators, RIAnd the average random consistency index of the multidimensional judgment matrix.
Optionally, the importance calculating module specifically includes:
the weight determining unit is used for determining the weight of each importance index by using a characteristic vector method according to the multidimensional judgment matrix;
a factor score acquisition unit for acquiring a factor score of each importance index;
an importance calculating unit for calculating importance by using a formula according to the factor score and weight of each importance index
Figure BDA0003180759450000033
Calculating the importance of the equipment;
where Index is the importance of the equipment, AnThe factor score, α, for the nth importance indicatornIs the weight of the nth importance indicator.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a device management method and a system, wherein the method comprises the following steps: acquiring a multidimensional judgment matrix of equipment; the multi-dimensional judgment matrix is used for describing the correlation among a plurality of importance indexes of the same equipment; calculating the importance of the equipment according to the multidimensional judgment matrix; determining the importance level of the equipment according to the importance of the equipment; and maintaining the equipment according to the importance level of the equipment. The invention can carry out quantitative processing on the importance degrees of different devices in a factory, and adopts different modes to manage according to different importance degrees of the devices, thereby improving the precision and efficiency of device management.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a flow chart of a device management method according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating a multi-dimensional decision matrix according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating factor scores according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a device management system in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a device management method and a device management system, which are used for quantizing the importance degrees of different devices in a factory, and managing the devices in different modes according to different importance degrees of the devices, so that the precision and the efficiency of device management are improved.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a flowchart of a device management method in an embodiment of the present invention, and as shown in the drawing, the present invention provides a device management method, including:
step 101: acquiring a multidimensional judgment matrix of equipment; the multi-dimensional judgment matrix is used for describing the correlation among a plurality of importance indexes of the same equipment; the specific data of the multidimensional decision matrix is shown in fig. 2.
Step 102: calculating the importance of the equipment according to the multidimensional judgment matrix;
step 103: determining the importance level of the equipment according to the importance of the equipment;
step 104: and maintaining the equipment according to the importance level of the equipment.
Wherein the importance indicators include any or all of security impact, impact of failure on the system, frequency of equipment failure, maintenance costs, outage losses, monitorability, outage time, and ease of maintenance.
Step 101, specifically comprising:
determining a plurality of importance indexes of the same equipment;
constructing a multidimensional judgment matrix according to the multiple importance indexes;
using formulas
Figure BDA0003180759450000051
Calculating the random consistency ratio of the multidimensional judgment matrix;
judging whether the random consistency ratio of the multidimensional judgment matrix is smaller than a consistency ratio threshold value or not to obtain a first judgment result;
if the first judgment result is negative, updating the multidimensional judgment matrix, and executing the step of utilizing the formula
Figure BDA0003180759450000052
Calculating a random consistency ratio of the multidimensional judgment matrix;
wherein, CRRandom consistency ratio for multi-dimensional decision matrix, CIFor a general consistency index of the multi-dimensional decision matrix,
Figure BDA0003180759450000053
λmaxfor the maximum eigenvalue of the multi-dimensional decision matrix, N is the total number of importance indicators, RIAnd the average random consistency index of the multidimensional judgment matrix.
Step 102, specifically comprising:
determining the weight of each importance index by using a feature vector method according to the multidimensional judgment matrix;
acquiring the factor score of each importance index; the factor score is shown schematically in FIG. 3.
Using a formula according to the factor score and weight of each importance index
Figure BDA0003180759450000054
Calculating the importance of the device;
where Index is the importance of the equipment, AnThe factor score, α, for the nth importance indicatornIs the weight of the nth importance indicator.
Specifically, determining the weight of each importance index by using a feature vector method according to the multidimensional judgment matrix specifically comprises:
carrying out normalization processing on the multidimensional judgment matrix to obtain a normalized multidimensional judgment matrix;
and determining the average number of elements in each row in the normalized multi-dimensional judgment matrix as the weight of the corresponding importance index of each row.
Specifically, the importance levels of the device include: key equipment, important equipment, general equipment and maintenance-free equipment; wherein, the corresponding importance of the key equipment, the important equipment, the general equipment and the maintenance-free equipment is reduced in sequence; the maintenance intensity of key equipment, important equipment, general equipment and maintenance-free equipment is reduced in sequence.
The equipment management method provided by the invention comprises the following specific steps:
the method comprises the following steps: an evaluation dimension (importance indicator) is selected.
The equipment importance degree is evaluated according to 8 dimensions, including: safety impact (SA), impact of failure on the System (SF), equipment Failure Frequency (FF), Maintenance Cost (MC), outage loss (OC), monitorability (DE), outage time (DT), and ease of maintenance. The evaluation dimension of the importance of the same power plant equipment is consistent.
Step two: evaluation of relative importance
(1) A decision matrix (multidimensional) is established.
Selecting N dimensions from a dimension library influencing the importance of the equipment to form an N-N matrix, analyzing the correlation among the dimensions by using a feature vector technology in a mathematical model, and calculating the weight of each dimension on the importance of the equipment.
Next, the invention selects 7 dimensions from 8 dimensions for correlation analysis, and fills in U according to the sequence in FIG. 2ijA 7-dimensional judgment matrix is obtained,
Uijrepresents the correlation of the ith importance index to the jth importance index, UjiThe correlation of the jth importance index to the ith importance index is represented, and the value of the correlation is UijThe reciprocal of (a); if the data of the second row and the second column is number 2, the data of the corresponding second row and the first column is 0.5, i.e. Uij*U ji1, another UiiThe diagonal of the decision matrix has a value of 1. Specifically, the correlation criteria of the two importance indicators are shown in table 1.
TABLE 1 two importance index correlation criteria
Correlation data Means of
1 Of equal importance
3 Of slight importance
5 Of considerable importance
7 Is very important
9 Of extreme importance
2，4，6，8 Situation between the above classes
(2) And (5) random consistency check.
The consistency check formula is as follows:
Figure BDA0003180759450000071
wherein, CRRandom consistency ratio for multi-dimensional decision matrix, CIFor a general consistency index of the multi-dimensional decision matrix,
Figure BDA0003180759450000072
λmaxfor the maximum eigenvalue of the multi-dimensional decision matrix, N is the total number of importance indicators, RIAnd the average random consistency index of the multidimensional judgment matrix. RIThe relationship between the value range of (a) and the dimension of the judgment matrix is shown in table 2.
TABLE 2RIValue range of (2) and judgment matrix dimension relation
n 1 2 3 4 5 6 7 8 9
RI 0.00 0.00 0.58 0.90 1.12 1.24 1.32 1.41 1.46
As can be seen from Table 2, the present invention takes a 7 × 7 matrix as an example, so R is usedIConsistency check is performed at 1.32, if 8 x 8 matrices are selected, then RI＝1.41。
When C is presentR<When the weight distribution is 0.1, the judgment matrix is considered to have satisfactory consistency, and the weight distribution is reasonable, namely, the relevant mathematical model is also reasonable; if C of 7-7 matrixR>0.1, the values of the elements in the judgment matrix need to be modified until CRThe matrix model can be judged to be reasonably constructed within 0.1.
(3) Calculating a weight coefficient
The invention utilizes the characteristic vector and the Fourier transform technology to calculate the importance of equipment, calculates the priority vector through the characteristic vector, adopts Fourier transform to express a certain function meeting certain conditions as a trigonometric function (sine and/or cosine function) or the linear combination of the integrals of the trigonometric function and/or cosine function, the calculation process of the weight coefficient is to calculate the characteristic vector corresponding to the maximum characteristic root, and the lower graph is an example for calculating the characteristic value.
Calculation of the priority vector:
a normalized feature vector is determined. The elements of the decision matrix of the present invention are shown in Table 3
TABLE 3 decision matrix
Figure BDA0003180759450000081
The sums are summed for each column of the decision matrix, and the result is shown in table 4, where SVM represents the sum.
TABLE 4 decision matrix after summation
Figure BDA0003180759450000082
Then, each element of the judgment matrix is divided by the sum of the columns of the judgment matrix, so that a normalized judgment matrix can be obtained, and the sum of each column is 1. The normalized decision matrix is shown in table 5.
TABLE 5 normalized decision matrix
Figure BDA0003180759450000083
The normalized eigenvectors (the weight of each importance indicator) are obtained by averaging the rows, and the formula is as follows:
Figure BDA0003180759450000091
weights occupied by SA, SF, FF, MC, OC, DE and DT are obtained as 0.2758, 0.2297, 0.1566, 0.0544, 0.0520, 0.0835 and 0.1611 respectively; the sum of the weights occupied by SA, SF, FF, MC, OC, DE and DT is 1.
The maximum eigenvalue of the multidimensional decision matrix is the sum of the products of the reciprocal of the element on the diagonal of the matrix in table 5 and the weights occupied by SA, SF, FF, MC, OC, DE, and DT, respectively:
λmax＝91/30*0.2758+297/60*0.2297+43/4*0.1566+21*0.0544+37/2*0.052+ 89/6*0.0835+797/60*0.1611＝8.452
the priority vector shows the relative weights between the judgment things. For example, the safety impact (SA) accounts for 27.582% when judging the relative importance of one coal mill; the impact of failure on the System (SF) is 22.967%.
(4) Obtaining factor scores
Each importance index corresponds to a factor score, and the factor scores of the importance indexes are as follows:
4.1 Medium (Security impact) -SA in devices
The influence of equipment failure on personnel and environment can be evaluated according to media and safety influence results, but the evaluation indexes of the same power plant are consistent, and the evaluation standard is shown in table 6.
TABLE 6 SA evaluation criteria
Serial number Type of media Score of
1 Inflammable and explosive 10
2 High temperature and high pressure 8
3 Toxic and corrosive 6
4 Non-toxic and harmless 1
And the evaluation can also be carried out according to the safety influence consequence, but the evaluation indexes of the same power plant are consistent.
4.2 Effect of failure on System function-SF
The influence on the system function after equipment failure in the production process is mainly considered, and the existence of standby is considered. The evaluation criteria are shown in table 7.
TABLE 7 SF evaluation criteria
Figure BDA0003180759450000101
4.3 probability of failure of device-FF
The MTBF value of the equipment can be obtained by performing field operation and correction by a maintainer according to an equipment operation history (for the equipment which has been operated for a period of Time) or a related equipment reliability database (for the equipment which is just put into operation). The evaluation criteria are shown in Table 8.
TABLE 8 FF evaluation criteria
Figure BDA0003180759450000102
Figure BDA0003180759450000111
4.4 maintenance costs-MC
This factor comprehensively considers the complexity of the equipment, the cost of spare parts, etc., which mainly refers to the cost of spare parts. The evaluation criteria are shown in Table 9.
TABLE 9 MC evaluation criteria
Serial number Maintenance cost/dollar Score of
1 >＝50000 10
2 10000—50000 6
3 1000—10000 4
4 <1000 1
4.5 outage losses-OC
The OC includes economic losses due to changes in system operation caused by equipment outages, standby equipment commissioning and even outages. The evaluation criteria are shown in table 10.
TABLE 10 OC evaluation criteria
Figure BDA0003180759450000112
4.6 monitorability-DE
DE primarily considers monitoring costs and requirements for monitoring technology. The evaluation criteria are shown in Table 11.
TABLE 11 DE evaluation criteria
Figure BDA0003180759450000113
Figure BDA0003180759450000121
4.7 downtime-DT
DT includes the duration from the shutdown of the plant to the startup of the plant, and the evaluation criteria are shown in table 12.
TABLE 12 DT evaluation criteria
Figure BDA0003180759450000122
4.8 ease of maintenance-DM
DM relates to the ease of access of the equipment (including altitude, ambient conditions, maintenance measures, safety measures, etc.), the complexity of the equipment, and the availability of spare parts, with specific scores determined by the field maintenance.
(5) Importance scoring
Using a formula according to the factor score and weight of each importance index
Figure BDA0003180759450000123
Calculating the importance of the device;
where Index is the importance of the equipment, AnThe factor score, α, for the nth importance indicatornIs the weight of the nth importance indicator.
(6) device Key rankings
According to the importance of the equipment, the equipment is classified into four classes of AA, A, B and C, the equipment with different classes is managed in a classified mode, the management difficulty of the equipment is reduced, the class classification standard is shown in a table 13, and the maintenance standard of each class of the equipment is shown in a table 14.
TABLE 13 Equipment Classification criteria
Figure BDA0003180759450000124
Figure BDA0003180759450000131
TABLE 14 maintenance standards for various classes of equipment
Figure BDA0003180759450000132
Figure BDA0003180759450000141
Fig. 4 is a schematic structural diagram of a device management system in an embodiment of the present invention, and as shown in fig. 4, the present invention further provides a device management system, which includes:
a multidimensional determination matrix obtaining module 401, configured to obtain a multidimensional determination matrix of a device; the multi-dimensional judgment matrix is used for describing the correlation among a plurality of importance indexes of the same equipment;
an importance calculating module 402, configured to calculate an importance of the device according to the multidimensional determination matrix;
an importance level determining module 403, configured to determine an importance level of the device according to the importance level of the device;
and an equipment maintenance module 404, configured to maintain the equipment according to the importance level of the equipment.
Wherein the importance indicators include any or all of security impact, impact of failure on the system, frequency of equipment failure, maintenance costs, outage losses, monitorability, outage time, and ease of maintenance.
The multidimensional determination matrix obtaining module 401 specifically includes:
an importance index determination unit configured to determine a plurality of importance indexes of the same device;
the multidimensional judgment matrix construction unit is used for constructing a multidimensional judgment matrix according to the importance indexes;
a random consistency ratio calculation unit for using a formula
Figure BDA0003180759450000151
Calculating the random consistency ratio of the multidimensional judgment matrix;
the judgment unit is used for judging whether the random consistency ratio of the multidimensional judgment matrix is smaller than a consistency ratio threshold value or not to obtain a first judgment result; if the first judgment result is negative, calling a multidimensional judgment matrix updating unit;
the multidimensional judgment matrix updating unit is used for updating the multidimensional judgment matrix and calling the random consistency ratio calculating unit;
wherein, CRRandom consistency ratio for multi-dimensional decision matrix, CIFor a general consistency index of the multi-dimensional decision matrix,
Figure BDA0003180759450000152
λmaxfor the maximum eigenvalue of the multi-dimensional decision matrix, N is the total number of importance indicators, RIAnd the average random consistency index of the multidimensional judgment matrix.
The importance calculating module 402 specifically includes:
the weight determining unit is used for determining the weight of each importance index by using a characteristic vector method according to the multidimensional judgment matrix;
a factor score acquisition unit for acquiring a factor score of each importance index;
an importance calculating unit for calculating importance by using a formula according to the factor score and weight of each importance index
Figure BDA0003180759450000153
Calculating the importance of the device;
where Index is the importance of the equipment, AnThe factor score, α, for the nth importance indicatornIs the weight of the nth importance indicator.
Specifically, the weight determining unit specifically includes:
the normalization subunit is used for performing normalization processing on the multidimensional judgment matrix to obtain a normalized multidimensional judgment matrix;
and the weight determining subunit is used for determining the average number of the elements in each row in the normalized multi-dimensional judgment matrix as the weight of the corresponding importance index in each row.
Wherein the importance levels of the devices include: key equipment, important equipment, general equipment and maintenance-free equipment; wherein, the importance degree corresponding to the key equipment, the important equipment, the general equipment and the maintenance-free equipment is reduced in turn; the maintenance intensity of key equipment, important equipment, general equipment and maintenance-free equipment is reduced in turn.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principle and the implementation of the present invention are explained herein by using specific examples, and the above description of the embodiments is only used to help understand the method and the core idea of the present invention; also, for those skilled in the art, there may be variations to the specific embodiments and applications of the present invention based on the concepts of the present invention. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (10)

1. A device management method, the method comprising:
acquiring a multidimensional judgment matrix of equipment; the multi-dimensional judgment matrix is used for describing the correlation among a plurality of importance indexes of the same equipment;
calculating the importance of the equipment according to the multidimensional judgment matrix;
determining the importance level of the equipment according to the importance of the equipment;
and maintaining the equipment according to the importance level of the equipment.
2. The equipment management method according to claim 1, wherein the importance index includes one or all of a security impact, an impact of failure on a system, an equipment failure frequency, a maintenance cost, a outage loss, monitorability, an outage time, and a maintenance difficulty level.
3. The device management method according to claim 1, wherein the obtaining the multidimensional determination matrix of the device specifically includes:
determining a plurality of importance indexes of the same equipment;
constructing a multidimensional judgment matrix according to a plurality of importance indexes;
using formulas
Figure FDA0003180759440000011
Calculating the random consistency ratio of the multidimensional judgment matrix;
judging whether the random consistency ratio of the multidimensional judgment matrix is smaller than a consistency ratio threshold value or not to obtain a first judgment result;
if the first judgment result is negative, updating the multidimensional judgment matrix, and executing the step of utilizing a formula
Figure FDA0003180759440000012
Calculating a random consistency ratio of the multi-dimensional decision matrix;
wherein, CRRandom consistency ratio for multi-dimensional decision matrix, CIFor multi-dimensional decision matricesThe general consistency index of (a) is,
Figure FDA0003180759440000013
λmaxfor the maximum eigenvalue of the multi-dimensional decision matrix, N is the total number of importance indicators, RIAnd the average random consistency index of the multidimensional judgment matrix.
4. The device management method according to claim 3, wherein the calculating the importance of the device according to the multidimensional determination matrix specifically includes:
determining the weight of each importance index by using a feature vector method according to the multidimensional judgment matrix;
acquiring the factor score of each importance index;
using a formula according to the factor score and weight of each importance index
Figure FDA0003180759440000014
Calculating the importance of the equipment;
where Index is the importance of the equipment, AnThe factor score, α, for the nth importance indicatornIs the weight of the nth importance indicator.
5. The device management method according to claim 4, wherein the determining the weight of each importance indicator by using a feature vector method according to the multidimensional determination matrix specifically comprises:
carrying out normalization processing on the multidimensional judgment matrix to obtain a normalized multidimensional judgment matrix;
and determining the average number of elements in each row in the normalized multi-dimensional judgment matrix as the weight of the corresponding importance index of each row.
6. The device management method according to claim 1, wherein the importance level of the device comprises: key equipment, important equipment, general equipment and maintenance-free equipment; wherein, the corresponding importance of the key equipment, the important equipment, the general equipment and the maintenance-free equipment is reduced in sequence; the maintenance intensity of key equipment, important equipment, general equipment and maintenance-free equipment is reduced in sequence.
7. A device management system, the system comprising:
the multidimensional judgment matrix acquisition module is used for acquiring a multidimensional judgment matrix of the equipment; the multi-dimensional judgment matrix is used for describing the correlation among a plurality of importance indexes of the same equipment;
the importance calculation module is used for calculating the importance of the equipment according to the multidimensional judgment matrix;
the importance level determining module is used for determining the importance level of the equipment according to the importance level of the equipment;
and the equipment maintenance module is used for maintaining the equipment according to the importance level of the equipment.
8. The equipment management system of claim 7 wherein the importance indicators include more or all of security impact, impact of failure on the system, frequency of equipment failure, maintenance costs, outage loss, monitorability, outage time, and ease of maintenance.
9. The device management system according to claim 7, wherein the multidimensional determination matrix obtaining module specifically includes:
an importance index determination unit configured to determine a plurality of importance indexes of the same device;
the multidimensional judgment matrix construction unit is used for constructing a multidimensional judgment matrix according to the importance indexes;
a random consistency ratio calculation unit for using a formula
Figure FDA0003180759440000021
Calculating the random consistency ratio of the multidimensional judgment matrix;
the judging unit is used for judging whether the random consistency ratio of the multidimensional judging matrix is smaller than a consistency ratio threshold value or not to obtain a first judging result; if the first judgment result is negative, calling a multidimensional judgment matrix updating unit;
a multidimensional judgment matrix updating unit for updating the multidimensional judgment matrix and calling the random consistency ratio calculating unit;
wherein, CRRandom consistency ratio for multi-dimensional decision matrix, CIFor a general consistency index of the multi-dimensional decision matrix,
Figure FDA0003180759440000031
λmaxfor the maximum eigenvalue of the multi-dimensional decision matrix, N is the total number of importance indicators, RIAnd the average random consistency index of the multidimensional judgment matrix.
10. The device management system according to claim 9, wherein the importance calculating module specifically includes:
the weight determining unit is used for determining the weight of each importance index by using a characteristic vector method according to the multidimensional judgment matrix;
a factor score acquisition unit for acquiring a factor score of each importance index;
an importance calculating unit for calculating importance by using a formula according to the factor score and weight of each importance index
Figure FDA0003180759440000032
Calculating the importance of the equipment;
where Index is the importance of the equipment, AnThe factor score, α, for the nth importance indicatornIs the weight of the nth importance indicator.
CN202110845918.6A 2021-07-26 2021-07-26 Equipment management method and system Pending CN113516400A (en)

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