CN115619098A - Intelligent electric power material data processing method based on grading monitoring and early warning - Google Patents

Intelligent electric power material data processing method based on grading monitoring and early warning Download PDF

Info

Publication number
CN115619098A
CN115619098A CN202211328480.5A CN202211328480A CN115619098A CN 115619098 A CN115619098 A CN 115619098A CN 202211328480 A CN202211328480 A CN 202211328480A CN 115619098 A CN115619098 A CN 115619098A
Authority
CN
China
Prior art keywords
life
electric power
coefficient
depreciation
early warning
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202211328480.5A
Other languages
Chinese (zh)
Inventor
王骊
程栋
张旭阳
王延海
张莹
王征
周华
邓文
翁慧颖
胡晓哲
俞晨玺
马骏
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Zhejiang Electric Power Co Ltd Shengzhou Power Supply Co
State Grid Zhejiang Zhedian Tendering Consulting Co ltd
Shaoxing Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Materials Branch of State Grid Zhejiang Electric Power Co Ltd
Original Assignee
State Grid Zhejiang Electric Power Co Ltd Shengzhou Power Supply Co
State Grid Zhejiang Zhedian Tendering Consulting Co ltd
Shaoxing Power Supply Co of State Grid Zhejiang Electric Power Co Ltd
Materials Branch of State Grid Zhejiang Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by State Grid Zhejiang Electric Power Co Ltd Shengzhou Power Supply Co, State Grid Zhejiang Zhedian Tendering Consulting Co ltd, Shaoxing Power Supply Co of State Grid Zhejiang Electric Power Co Ltd, Materials Branch of State Grid Zhejiang Electric Power Co Ltd filed Critical State Grid Zhejiang Electric Power Co Ltd Shengzhou Power Supply Co
Priority to CN202211328480.5A priority Critical patent/CN115619098A/en
Publication of CN115619098A publication Critical patent/CN115619098A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2474—Sequence data queries, e.g. querying versioned data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06315—Needs-based resource requirements planning or analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Human Resources & Organizations (AREA)
  • Economics (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Strategic Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • General Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • Development Economics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Educational Administration (AREA)
  • Game Theory and Decision Science (AREA)
  • Health & Medical Sciences (AREA)
  • Fuzzy Systems (AREA)
  • Databases & Information Systems (AREA)
  • Mathematical Physics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Software Systems (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Finance (AREA)
  • General Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Public Health (AREA)
  • Water Supply & Treatment (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Remote Monitoring And Control Of Power-Distribution Networks (AREA)

Abstract

The invention relates to an intelligent electric power material data processing method based on grading monitoring and early warning, which comprises the following steps: step S1, setting standard service life and life breakage coefficient of the electric power materials according to historical use records of the electric power materials; s2, monitoring actual use data of the electric power materials, calculating the depreciated life of the electric power materials according to the actual use data and the life depreciation coefficient, and calculating the residual life rate of the electric power materials according to the standard service life and the depreciated life; and S3, constructing a grading monitoring early warning signal according to the residual life rate of the electric power material, and managing the electric power material according to the grading monitoring early warning signal. The method and the device judge the residual working capacity of the electric power materials by taking the service life of the electric power materials as an index, and timely carry out grading early warning when the residual working capacity of the electric power materials possibly influences the operation of an electric power network, thereby effectively improving the management effect of the electric power materials.

Description

Intelligent electric power material data processing method based on grading monitoring and early warning
Technical Field
The invention relates to the technical field of power system material management, in particular to an intelligent power material data processing method based on grading monitoring and early warning.
Background
The electric power is the basic pillar industry of national economy, the development of each industry and the growth of national economy are closely related to the electric power, once an accident occurs in a transformer substation and a power transmission and distribution line, the stability of a power grid is influenced, large-area power failure is formed, the power supply reliability is influenced, and huge loss is caused to users, so that the normal construction and operation of the power grid are the basis for ensuring the normal life of people and the normal activities of the country.
Electric power materials are basic guarantees in the process of power grid construction, the material quality of the electric power materials is closely related to safe operation of a power grid, a relatively perfect material information management system is established, but the current situations of material data fragmentation, material storage mechanization and subject responsibility fuzzification of the current material management work show enable the current power grid material related management data fragmentation and operation data islanding to directly influence the goal of material management work refinement. Chinese patent CN110443413B discloses a power material demand prediction system and a method for constructing a power material demand model, the method comprising: s1, acquiring the whole process data of the electric power material; s2, constructing a prediction model for forming the multi-level comprehensive power material demand by using the whole process data of the power material acquired in the S1 and adopting a mode of combining a least square support vector machine, an echo state network and a regularization limit learning machine, wherein the prediction model comprises the following steps: s21, establishing a sample database; s22, predicting the demand of the electric power materials by adopting a least square support vector machine; s23, predicting the demand of the electric power materials by adopting an echo state network; s24, predicting the demand of the electric power materials by adopting a regularization extreme learning machine; s25, the final prediction result of the electric power material demand is obtained by combining the prediction results in a weighting mode.
Disclosure of Invention
Therefore, the invention provides an intelligent electric power material data processing method based on grading monitoring and early warning, which has the beneficial effects of effectively improving the management effect of electric power materials and solving the problem that the management effect of the electric power materials cannot be effectively improved in the prior art by predicting the residual service life of the electric power materials according to the electric power material data and carrying out grading early warning according to the prediction result.
In order to achieve the purpose, the invention provides an intelligent electric power material data processing method based on grading monitoring and early warning, which comprises the following steps:
the method comprises the following steps of S1, setting the standard service life and the life breaking coefficient of the electric power materials according to the historical use records of the electric power materials, wherein the life breaking coefficient comprises a normal use breaking coefficient, a use environment breaking coefficient and a damaged breaking coefficient;
s2, monitoring actual use data of the electric power materials, wherein the actual use data comprises use time, use environment indexes, damage reasons and damage times of the electric power materials, calculating the broken life of the electric power materials according to the actual use data and the life breaking coefficient, and calculating the residual life rate of the electric power materials according to the standard use life and the broken life;
and S3, constructing a graded monitoring early warning signal according to the residual life rate of the electric power materials, managing the electric power materials according to the graded monitoring early warning signal, monitoring the working running state of the electric power materials to judge whether the life breaking coefficient meets a preset standard, and correcting the life breaking coefficient of the electric power materials when the life breaking coefficient does not meet the preset standard.
Further, when the standard service life of the electric power material is set according to the historical use records of the electric power material, the service life data in the historical use records of the electric power material are screened, the mode of the service life data is calculated to be set as credible service life data, the average value of the credible service life data is calculated to be set as the standard service life, and meanwhile, the historical use records in which the credible service life data are recorded are set as credible use records.
Furthermore, when a life depreciation coefficient is set according to the historical use record of the electric power material, the credible use data in the credible use record of the electric power material is analyzed, the credible use data comprises credible use duration, credible use environment indexes, credible damage reasons and credible damage times, the use environment depreciation coefficient is respectively set according to n types of environment factors which reduce the service life of the electric power material in the credible use environment indexes, the 1 st type environment depreciation coefficient of the 1 st type environment factor with the historical occurrence times of W10 is k21, the 2 nd type environment depreciation coefficient of the 2 nd type environment factor with the historical occurrence times of W20 is k22, and so on, the nth type environment depreciation coefficient of the n type environment factor with the historical occurrence times of Wn0 is k2n, damage factors are respectively set according to m types of damage factors of the credible damage factors, the 1 st type damage factor of the 1 st type damage factor with the historical occurrence frequency of D10 is k31, the 2 nd type damage factor of the 2 nd type damage factor with the historical occurrence frequency of D20 is k32, and the like, the m type damage factor of the m type damage factor with the historical occurrence frequency of Dm0 is k3m, and the normal use damage factors k1 and k1= [ T0- (k 21 xW 10+ k22 xW 20+ … + k2n xWn 0) - (k 31 xD 10+ k32 xD 20+ … + k3m xDm 0) ] T0 are set according to the standard service life T0, the credible use time length T0, the environmental damage factor and the damage factors.
Further, when the depreciated life Tu of the electric power material is calculated according to the actual usage data and the life depreciation coefficient, tu = Tu1+ Tu2+ Tu3, where Tu1 is the normal usage depreciation life, tu1= k1 × t, t is the usage duration, tu2 is the environmental factor depreciation life, tu2= k21 × W1+ k22 × W2+ … + k2n × Wn, W1 is the number of occurrences of the type 1 environmental factor, W2 is the number of occurrences of the type 2 environmental factor, and so on, wn is the number of occurrences of the type n environmental factor, tu3 is the depreciation life of the damage factor, tu3= k31 × D1+ k32 × D2+ … + k3m × Dm, D1 is the number of occurrences of the type 1 damage factor, D2 is the type 2 damage factor, and so on.
Further, when calculating the remaining life rate Q of the electric power material according to the standard service life and the broken life, Q = [ (T0-Tu)/T0 ] × 100%, wherein T0 is the standard service life, a graded monitoring early warning signal is constructed according to the remaining life rate of the electric power material, when constructing the graded monitoring early warning signal according to the remaining life rate of the electric power material, a primary alarm life rate, a secondary alarm life rate and a tertiary alarm life rate are set, wherein the primary alarm life rate is greater than the secondary alarm life rate and is greater than the tertiary alarm life rate,
when the residual life rate is greater than the first-level alarm life rate, constructing a zero-level monitoring early warning signal for the electric power materials;
when the first-stage alarm life rate is greater than or equal to the residual life rate and greater than the second-stage alarm life rate, constructing a first-stage monitoring early warning signal for the electric power materials;
when the secondary alarm life rate is greater than or equal to the residual life rate and is greater than the tertiary alarm life rate, constructing a secondary monitoring early warning signal for the electric power materials;
and when the third-level alarm life rate is greater than or equal to the residual life rate, constructing a third-level monitoring early warning signal for the electric power materials.
Further, when the electric power materials are managed according to the grading monitoring early warning signal,
if a zero-level monitoring early warning signal is constructed for the electric power materials, acquiring actual use data of the electric power materials;
if a primary monitoring early warning signal is constructed for the electric power materials, monitoring the normal use depreciation life, the environmental factor depreciation life and the damage factor depreciation life in the actual use data of the electric power materials;
if a secondary monitoring early warning signal is constructed for the electric power materials, calculating the normal use depreciation life, the environmental factor depreciation life and the proportion of the damaged factor depreciation life in the actual use data of the electric power materials in the depreciation life respectively, constructing a monitoring material use signal when the normal use depreciation life proportion is maximum, constructing a reinforced material protection signal when the environmental factor depreciation life proportion is maximum, and constructing a material replacement signal when the damaged factor depreciation life proportion is maximum;
if a three-level monitoring early warning signal is constructed for the electric power materials, the electric power materials are replaced emergently.
Further, when judging whether the life break coefficient meets the preset standard according to the working running state of the electric power material, judging whether the life break coefficient meets the preset standard according to the actual service life and the standard service life of the electric power material,
when the actual service life is more than or equal to 0.9 multiplied by the standard service life, judging that the life loss coefficient meets the preset standard;
when the actual service life is less than 0.9 multiplied by the standard service life, the service life loss coefficient is judged not to accord with the preset standard, the normal service loss life, the environmental factor loss life and the proportion of the damaged factor loss life in the actual service life of the power material are respectively calculated, the normal service loss coefficient is adjusted when the proportion of the normal service loss life is maximum, the service environment loss coefficient is adjusted when the proportion of the environmental factor loss life is maximum, and the damaged factor loss coefficient is adjusted when the proportion of the damaged factor loss life is maximum.
Further, when the normal use discount coefficient is adjusted, a first adjustment coefficient L1 is set for adjusting the normal use discount coefficient k1 to k1', k1' = k1 × (1 + L1), where L1= (0.9 × T0-T)/T, and T is the actual service life.
Further, when the usage environment depreciation coefficient is adjusted, a second adjustment coefficient L2 is set for adjusting the usage environment depreciation coefficient k2 to k2', k2' = k2 × (1 + l2), where L2= (0.9 × T0-T)/T.
Further, when adjusting the damaged breakage coefficient, a third adjustment coefficient L3 is set for adjusting the damaged breakage coefficient k3 to k3', k3' = k3 × (1 + l3), where L3= (0.9 × T0-T)/T.
Compared with the prior art, the invention has the advantages that the standard service life of the electric power materials is set according to the historical use records of the electric power materials, the life breaking coefficient is set according to the historical use records of the electric power materials, the actual use data of the electric power materials is monitored, the broken life of the electric power materials is calculated according to the actual use data and the life breaking coefficient, the residual life rate of the electric power materials is calculated according to the standard service life and the broken life, the grading monitoring early warning signal is constructed according to the residual life rate of the electric power materials, the electric power materials are managed according to the grading monitoring early warning signal, the working running state of the electric power materials is monitored to judge whether the life breaking coefficient meets the preset standard, when the life breaking coefficient does not meet the preset standard, the life breaking coefficient of the electric power materials is corrected, the residual working capacity of the electric power materials is preliminarily judged by taking the service life of the electric power materials as an index, the future working capacity of the electric power materials is predicted, the working running state of the electric power materials is monitored, and the residual working capacity of the electric power materials is effectively utilized before the electric power management is carried out.
Particularly, the mode in the service life data is screened, the average value of the mode is calculated again to be set as the standard service life, the set value of the standard service life is ensured to be in accordance with the historical actual service life of the electric power materials, the reliable reference standard is set in the subsequent monitoring data processing method, and the problems that the electric power materials are not completely used and replaced due to the fact that the set value of the standard service life is too small or the use data of the electric power materials are monitored inaccurately due to the fact that the set value of the standard service life is too small and the management level of the electric power materials is reduced are avoided, so that the management effect of the electric power materials is effectively improved.
Particularly, by analyzing the credible use duration, the credible use environment index, the credible damage reason and the credible damage times in the credible use data in the credible use record of the electric power materials, the use environment damage coefficient is respectively set according to various environment factors which reduce the service life of the electric power materials in the credible use environment index, the damage coefficient is respectively set according to various damage reasons of the credible damage reason, the normal use damage coefficient is set according to the standard use life, the credible use duration, the environment damage coefficient and the damage coefficient, the normal use damage coefficient, the use environment damage coefficient and the damage coefficient are ensured to be set to be in accordance with the historical use data of the electric power materials, and then the subsequent damaged life calculated by the normal use damage coefficient, the use environment damage coefficient and the damage coefficient is ensured to be in accordance with the preset standard, so that the management effect of the electric power materials is effectively improved.
Particularly, the depreciated life of the electric power materials is calculated according to the actual use data and the life depreciation coefficient, the normal use depreciation life is set to be the product of the use duration and the normal use depreciation coefficient, the environmental factor depreciation life is the sum of the product of the occurrence times of various environmental factors and the corresponding respective use environment depreciation coefficient, the damage factor depreciation life is the sum of the product of the occurrence times of various damage reasons and the corresponding respective damage depreciation coefficient, the calculated depreciated life is guaranteed to accord with the preset standard, and therefore the management effect of the electric power materials is effectively improved.
Particularly, when a graded monitoring early warning signal is constructed according to the residual life rate of the electric power material, a first-grade alarm life rate, a second-grade alarm life rate and a third-grade alarm life rate are set, when the residual life rate is greater than the first-grade alarm life rate, a zero-grade monitoring early warning signal is constructed for the electric power material, when the first-grade alarm life rate is greater than or equal to the residual life rate and greater than the second-grade alarm life rate, the first-grade monitoring early warning signal is constructed for the electric power material, when the second-grade alarm life rate is greater than or equal to the residual life rate and greater than the third-grade alarm life rate, the second-grade monitoring early warning signal is constructed for the electric power material, when the third-grade alarm life rate is greater than or equal to the residual life rate, the graded early warning is timely carried out when the residual working capacity of the electric power material possibly influences the operation of the electric power network, the material management operation is carried out before the electric power material damage, the full utilization of the electric power material is realized, and the management effect of the electric power material is effectively improved.
Particularly, when electric power materials are managed according to the graded monitoring early warning signals, the actual use data of the electric power materials are collected when a zero-grade monitoring early warning signal is constructed for the electric power materials, the normal use depreciation life, the environmental factor depreciation life and the damaged factor depreciation life in the actual use data of the electric power materials are monitored when a first-grade monitoring early warning signal is constructed for the electric power materials, the normal use depreciation life, the environmental factor depreciation life and the damaged factor depreciation life in the actual use data of the electric power materials are respectively calculated when a second-grade monitoring early warning signal is constructed for the electric power materials, the monitoring material use signal is constructed when the normal use depreciation life is maximum, a reinforced material protection signal is constructed when the environmental factor depreciation life is maximum, a material replacement signal is constructed when the damaged factor depreciation life is maximum, the electric power materials are emergently replaced when a third-grade monitoring early warning signal is constructed for the electric power materials, the future working capacity of the electric power materials is realized, the working condition of the electric power materials is monitored, the working capacity of the electric power materials is changed, and the residual materials are effectively utilized in a graded operation, and the network is possible operation effect of the residual material management is improved before the operation is realized when the electric power management is effectively.
Particularly, whether the life depreciation coefficient accords with a preset standard or not is judged according to the actual service life and the standard service life of the electric power material, and the actual service life does not accord with the preset standard, the life depreciation coefficient does not accord with the preset standard, the normal service depreciation life, the environmental factor depreciation life and the damaged factor depreciation life of the electric power material in the actual service life are respectively calculated, the normal service depreciation coefficient is adjusted when the normal service depreciation life accounts for the maximum, the service environment depreciation coefficient is adjusted when the environmental factor depreciation life accounts for the maximum, the damaged depreciation coefficient is adjusted when the damaged factor depreciation life accounts for the maximum, the set values of the normal service depreciation coefficient, the service environment depreciation coefficient and the damaged depreciation coefficient accord with the preset standard, the calculated depreciation life is accurate and reliable according to the normal service depreciation coefficient, the service environment depreciation coefficient and the damaged depreciation coefficient, the future working capacity of the electric power material can be effectively managed before the electric power material is effectively managed when the residual working capacity of the electric power material possibly affects the electric power network.
Particularly, when the normal use depreciation coefficient is adjusted, a first adjustment parameter is set according to the actual service life and the standard service life so as to adjust the set value of the normal use depreciation coefficient, the adjustment range of the set value of the normal use depreciation coefficient is related to the difference value between the actual service life and the preset standard, when the difference value between the actual service life and the preset standard is larger, the adjustment range of the normal use depreciation coefficient is larger, when the difference value between the actual service life and the preset standard is smaller, the adjustment range of the normal use depreciation coefficient is smaller, the setting of the normal use depreciation coefficient is ensured to accord with the preset standard, the calculated depreciation life is ensured to be accurate and credible according to the normal use depreciation coefficient, the future working capacity of the electric power material is realized, the working condition of the electric power material is monitored, and the grading early warning is timely performed when the residual working capacity of the electric power material possibly influences the operation, so that the damage of the electric power material is performed before the full utilization of the electric power material is realized, and the effective management effect of the electric power material is improved.
Particularly, when the use environment depreciation coefficient is adjusted, a second adjustment parameter is set according to the actual service life and the standard service life so as to adjust the set value of the use environment depreciation coefficient, the adjustment range of the set value of the use environment depreciation coefficient is related to the difference value between the actual service life and the preset standard, when the difference value between the actual service life and the preset standard is larger, the adjustment range of the use environment depreciation coefficient is larger, when the difference value between the actual service life and the preset standard is smaller, the adjustment range of the use environment depreciation coefficient is smaller, the setting of the use environment depreciation coefficient is ensured to accord with the preset standard, the calculated depreciation life is ensured to be accurate and credible according to the normal use depreciation coefficient, the future working capacity of the electric power material is realized, the working operation condition of the electric power material is monitored, and the grading early warning is timely performed when the residual working capacity of the electric power material possibly influences the operation, so that the damage of the electric power material is performed before the full utilization of the electric power material is realized, and the effective management effect of the electric power material is improved.
Particularly, when the damaged breaking coefficient is adjusted, a third adjustment parameter is set according to the actual service life and the standard service life, so that the set value of the damaged breaking coefficient is adjusted, the adjustment range of the set value of the damaged breaking coefficient is related to the difference between the actual service life and the preset standard, when the difference between the actual service life and the preset standard is larger, the adjustment range of the damaged breaking coefficient is larger, when the difference between the actual service life and the preset standard is smaller, the adjustment range of the damaged breaking coefficient is smaller, the set of the damaged breaking coefficient is ensured to accord with the preset standard, the damaged life calculated according to the normal use breaking coefficient, the use environment breaking coefficient and the damaged breaking coefficient is ensured to be accurate and credible, the future working capacity of the electric power materials is realized, the working operation condition of the electric power materials is monitored, and the grading early warning is timely carried out when the residual working capacity of the electric power materials possibly influences the operation of the electric power network, so that the material management operation is carried out before the damage of the electric power materials is realized, and the full utilization of the electric power materials is effectively improved.
Drawings
Fig. 1 is a schematic flow chart of an intelligent electric power material data processing method based on hierarchical monitoring and early warning according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an intelligent electric power material data processing system in the intelligent electric power material data processing method based on hierarchical monitoring and early warning according to the embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described below with reference to examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principles of the present invention, and do not limit the scope of the present invention.
It should be noted that in the description of the present invention, the terms of direction or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, which are only for convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1, an embodiment of the invention provides an intelligent electric power material data processing method based on hierarchical monitoring and early warning, which includes:
the method comprises the following steps that S1, the standard service life and the life breaking coefficient of the electric power materials are set according to historical use records of the electric power materials, wherein the life breaking coefficient comprises a normal use breaking coefficient, a use environment breaking coefficient and a damaged breaking coefficient;
s2, monitoring actual use data of the electric power materials, wherein the actual use data comprises use time, use environment indexes, damage reasons and damage times of the electric power materials, calculating the damaged life of the electric power materials according to the actual use data and the life damage coefficient, and calculating the residual life rate of the electric power materials according to the standard service life and the damaged life;
and S3, constructing a graded monitoring early warning signal according to the residual life rate of the electric power materials, managing the electric power materials according to the graded monitoring early warning signal, monitoring the working running state of the electric power materials to judge whether the life breaking coefficient meets a preset standard, and correcting the life breaking coefficient of the electric power materials when the life breaking coefficient does not meet the preset standard.
The standard service life of the electric power materials is set according to the historical service records of the electric power materials, the life breaking coefficient is set according to the historical service records of the electric power materials, the actual service data of the electric power materials are monitored, the broken life of the electric power materials is calculated according to the actual service data and the life breaking coefficient, the residual life rate of the electric power materials is calculated according to the standard service life and the broken life, a graded monitoring early warning signal is constructed according to the residual life rate of the electric power materials, the electric power materials are managed according to the graded monitoring early warning signal, meanwhile, the working operation state of the electric power materials is monitored so as to judge whether the life breaking coefficient meets the preset standard, when the life breaking coefficient does not meet the preset standard, the life breaking coefficient of the electric power materials is corrected, the residual working capacity of the electric power materials is preliminarily judged by taking the service life of the electric power materials as an index, the future working capacity of the electric power materials is looked forward, the working operation state of the electric power materials is monitored, the residual working capacity of the electric power materials is timely influenced, the effective management is realized, and the effective utilization of the electric power materials is fully improved.
Specifically, when the standard service life of the electric power material is set according to the historical use record of the electric power material, the service life data in the historical use record of the electric power material is screened, the mode of the service life data is calculated to be set as credible life data, the average value of the credible life data is calculated to be set as the standard service life, and meanwhile, the historical use record in which the credible life data is recorded is set as the credible use record.
The mode in the service life data is screened, the average value of the mode is calculated again to be set as the standard service life, the set value of the standard service life is guaranteed to be in accordance with the historical actual service life of the electric power material, the follow-up monitoring data processing method is provided with a reliable reference standard, the problems that the electric power material is not completely used and is replaced due to the fact that the set value of the standard service life is too small, or the use data of the electric power material is monitored inaccurately due to the fact that the set value of the standard service life is too small, the management level of the electric power material is reduced are solved, and therefore the management effect of the electric power material is effectively improved.
Specifically, when a life depreciation coefficient is set according to a historical use record of the electric power materials, credible use data in the credible use record of the electric power materials are analyzed, the credible use data comprise credible use duration, credible use environment indexes, credible damage reasons and credible damage times, the use environment depreciation coefficient is respectively set according to n types of environment factors which reduce the service life of the electric power materials in the credible use environment indexes, the 1 st type environment depreciation coefficient of the 1 st type environment factor with the historical occurrence times of W10 is k21, the 2 nd type environment depreciation coefficient of the 2 nd type environment factor with the historical occurrence times of W20 is k22, and so on, the nth type environment depreciation coefficient of the n type environment factor with the historical occurrence times of Wn0 is k2n, damage factors are respectively set according to m types of damage factors of the credible damage factors, the 1 st type damage factor of the 1 st type damage factor with the historical occurrence frequency of D10 is k31, the 2 nd type damage factor of the 2 nd type damage factor with the historical occurrence frequency of D20 is k32, and the like, the m type damage factor of the m type damage factor with the historical occurrence frequency of Dm0 is k3m, and the normal use damage factors k1 and k1= [ T0- (k 21 xW 10+ k22 xW 20+ … + k2n xWn 0) - (k 31 xD 10+ k32 xD 20+ … + k3m xDm 0) ] T0 are set according to the standard service life T0, the credible use time length T0, the environmental damage factor and the damage factors.
Specifically, when the depreciated life Tu of the electric power material is calculated according to the actual usage data and the life depreciation coefficient, tu = Tu1+ Tu2+ Tu3, where Tu1 is the normal usage depreciation life, tu1= k1 × t, t is the usage duration, tu2 is the environmental factor depreciation life, tu2= k21 × W1+ k22 × W2+ … + k2n × Wn, W1 is the number of occurrences of the type 1 environmental factor, W2 is the number of occurrences of the type 2 environmental factor, and so on, wn is the number of occurrences of the type n environmental factor, tu3 is the depreciation life of the damage factor, tu3= k31 × D1+ k32 × D2+ … + k3m × Dm, D1 is the number of occurrences of the type 1 damage cause, D2 is the number of occurrences of the type 2 damage cause, and so on.
For the service life of the power material, the components of the power material include the normal service life and the damage life of normal use loss caused by normal use under normal use conditions, the damage life of environmental factors and the damage life of damage factors caused by environmental loss caused by inappropriate use environment and damage loss caused by accidental damage, for example, for the power cable, the service life of the power cable can be potentially reduced by environmental factors such as high-temperature environmental factors, low-temperature environmental factors and strong wind environmental factors, and the damage factors such as electric shock, lightning stroke and animal damage can greatly influence the service life of the power cable.
The method comprises the steps of analyzing the credible use duration, the credible use environment index, the credible damage reason and the credible damage times in the credible use data in the credible use record of the electric power materials, respectively setting the use environment damage coefficient according to various environment factors reducing the service life of the electric power materials in the credible use environment index, respectively setting the damage coefficient according to various damage reasons of the credible damage reason, respectively setting the normal use damage coefficient according to the standard use life, the credible use duration, the environment damage coefficient and the damage coefficient, ensuring that the normal use damage coefficient, the use environment damage coefficient and the damage coefficient are set to accord with the historical use data of the electric power materials, further ensuring that the subsequent damaged life calculated by the normal use damage coefficient, the use environment damage coefficient and the damage coefficient accords with the preset standard, and effectively improving the management effect of the electric power materials.
The depreciated life of the electric power materials is calculated according to actual use data and the life depreciation coefficient, the normal use depreciation life is set to be the product of the use duration and the normal use depreciation coefficient, the environment factor depreciation life is the sum of the product of the occurrence times of various environment factors and the corresponding respective use environment depreciation coefficient, the damage factor depreciation life is the sum of the product of the occurrence times of various damage reasons and the corresponding respective damage depreciation coefficient, the calculated depreciated life is guaranteed to accord with the preset standard, and the management effect of the electric power materials is effectively improved.
Specifically, when the remaining life rate Q of the electric power material is calculated according to the standard service life and the broken life, Q = [ (T0-Tu)/T0 ] × 100%, wherein T0 is the standard service life, a hierarchical monitoring early warning signal is constructed according to the remaining life rate of the electric power material, when the hierarchical monitoring early warning signal is constructed according to the remaining life rate of the electric power material, a primary alarm life rate, a secondary alarm life rate and a tertiary alarm life rate are set, wherein the primary alarm life rate is greater than the secondary alarm life rate and is greater than the tertiary alarm life rate,
when the residual life rate is greater than the first-level alarm life rate, constructing a zero-level monitoring early warning signal for the electric power materials;
when the first-stage alarm life rate is greater than or equal to the residual life rate and greater than the second-stage alarm life rate, constructing a first-stage monitoring early warning signal for the electric power materials;
when the secondary alarm life rate is greater than or equal to the residual life rate and is greater than the tertiary alarm life rate, constructing a secondary monitoring early warning signal for the electric power materials;
and when the third-level alarm life rate is greater than or equal to the residual life rate, constructing a third-level monitoring early warning signal for the electric power materials.
When the residual service life rate of the electric power materials is larger than the first-level alarm service life rate, a zero-level monitoring early warning signal is constructed for the electric power materials, when the first-level alarm service life rate is larger than the second-level alarm service life rate, the first-level monitoring early warning signal is constructed for the electric power materials, when the second-level alarm service life rate is larger than or equal to the residual service life rate, the second-level monitoring early warning signal is constructed for the electric power materials, when the third-level alarm service life rate is larger than or equal to the residual service life rate, the third-level monitoring early warning signal is constructed for the electric power materials, when the residual working capacity of the electric power materials possibly influences the operation of an electric power network, grading early warning is timely carried out, the material management operation is carried out before the damage of the electric power materials, the full utilization of the electric power materials is realized, and the management effect of the electric power materials is effectively improved.
Specifically, when the electric power materials are managed according to the grading monitoring early warning signal,
if a zero-level monitoring early warning signal is constructed for the electric power materials, acquiring actual use data of the electric power materials;
if a primary monitoring early warning signal is constructed for the electric power materials, monitoring the normal use depreciation life, the environmental factor depreciation life and the damaged factor depreciation life in the actual use data of the electric power materials;
if a secondary monitoring early warning signal is constructed for the electric power materials, calculating the normal use depreciation life, the environmental factor depreciation life and the proportion of the damaged factor depreciation life in the actual use data of the electric power materials in the depreciation life respectively, constructing a monitoring material use signal when the normal use depreciation life proportion is maximum, constructing a reinforced material protection signal when the environmental factor depreciation life proportion is maximum, and constructing a material replacement signal when the damaged factor depreciation life proportion is maximum;
if a three-level monitoring early warning signal is constructed for the electric power materials, the electric power materials are replaced emergently.
When the electric power materials are managed according to the grading monitoring early warning signals, the actual use data of the electric power materials are collected when zero-level monitoring early warning signals are constructed for the electric power materials, the normal use depreciation life, the environmental factor depreciation life and the damaged factor depreciation life in the actual use data of the electric power materials are monitored when first-level monitoring early warning signals are constructed for the electric power materials, the normal use depreciation life, the environmental factor depreciation life and the damaged factor depreciation life in the depreciation life of the electric power materials are respectively calculated when second-level monitoring early warning signals are constructed for the electric power materials, the monitoring material use signals are constructed when the normal use depreciation life is maximum, the reinforced material protection signals are constructed when the environmental factor depreciation life is maximum, the replacement material signals are constructed when the damaged factor depreciation life is maximum, the electric power materials are emergently replaced when third-level monitoring early warning signals are constructed for the electric power materials, the prospective working capacity of the electric power materials is monitored, the working condition of the electric power materials is monitored, and the working capacity of the electric power materials is effectively utilized in a grading management network, and the possible damage of the electric power materials is effectively utilized.
Specifically, when the service life breaking coefficient is judged to meet the preset standard according to the working running state of the electric power material, whether the service life breaking coefficient meets the preset standard is judged according to the actual service life and the standard service life of the electric power material,
when the actual service life is more than or equal to 0.9 multiplied by the standard service life, judging that the life loss coefficient meets the preset standard;
when the actual service life is less than 0.9 multiplied by the standard service life, the service life loss coefficient is judged not to accord with the preset standard, the normal service loss life, the environmental factor loss life and the proportion of the damaged factor loss life in the actual service life of the power material are respectively calculated, the normal service loss coefficient is adjusted when the proportion of the normal service loss life is maximum, the service environment loss coefficient is adjusted when the proportion of the environmental factor loss life is maximum, and the damaged factor loss coefficient is adjusted when the proportion of the damaged factor loss life is maximum.
Whether the life depreciation coefficient accords with a preset standard or not is judged according to the actual service life and the standard service life of the electric power material, and the actual service life does not accord with the preset standard, the life depreciation coefficient does not accord with the preset standard, the normal service depreciation life, the environmental factor depreciation life and the damaged factor depreciation life of the electric power material in the actual service life are respectively calculated, the normal service depreciation coefficient is adjusted when the normal service depreciation life ratio is maximum, the service environment depreciation coefficient is adjusted when the environmental factor depreciation life ratio is maximum, the damaged depreciation coefficient is adjusted when the damaged factor depreciation life ratio is maximum, the normal service depreciation coefficient, the service environment depreciation coefficient and the damaged depreciation coefficient are enabled to accord with the preset standard, the calculated depreciation life is accurate and reliable according to the normal service depreciation coefficient, the service environment depreciation coefficient and the damaged depreciation coefficient, the future working capacity of the electric power material is enabled to be calculated to be in time, the effective management and the damage of the electric power material is enabled to be fully utilized, and the early warning is realized when the remaining working capacity of the electric power material possibly affects the network operation.
Specifically, when the normal use discount coefficient is adjusted, a first adjustment coefficient L1 is set for adjusting the normal use discount coefficient k1 to k1', k1' = k1 × (1 + L1), where L1= (0.9 × T0-T)/T, and T is the actual service life.
When the normal use depreciation coefficient is adjusted, a first adjustment parameter is set according to the actual service life and the standard service life so as to adjust the set value of the normal use depreciation coefficient, the adjustment range of the set value of the normal use depreciation coefficient is related to the difference value between the actual service life and the preset standard, when the difference value between the actual service life and the preset standard is larger, the adjustment range of the normal use depreciation coefficient is larger, when the difference value between the actual service life and the preset standard is smaller, the adjustment range of the normal use depreciation coefficient is smaller, the setting of the normal use depreciation coefficient is ensured to accord with the preset standard, the calculated depreciation life is ensured to be accurate according to the normal use depreciation coefficient, the use environment depreciation coefficient and the damaged depreciation coefficient, the future working capacity of the electric power material is realized, the working condition of the electric power material is monitored, and the grading early warning is timely carried out when the residual working capacity of the electric power material possibly influences the operation, so that the damage of the electric power material is carried out before the full utilization of the electric power material is realized, and the effective management effect of the electric power material is improved.
Specifically, when the usage environment depreciation coefficient is adjusted, a second adjustment coefficient L2 is set for adjusting the usage environment depreciation coefficient k2 to k2', k2' = k2 × (1 + l2), where L2= (0.9 × T0-T)/T.
When the use environment depreciation coefficient is adjusted, a second adjustment parameter is set according to the actual service life and the standard service life, so that the set value of the use environment depreciation coefficient is adjusted, the adjustment range of the set value of the use environment depreciation coefficient is related to the difference between the actual service life and the preset standard, when the difference between the actual service life and the preset standard is large, the adjustment range of the use environment depreciation coefficient is large, when the difference between the actual service life and the preset standard is small, the adjustment range of the use environment depreciation coefficient is small, the setting of the use environment depreciation coefficient is ensured to accord with the preset standard, the calculated depreciation life is accurate according to the normal use depreciation coefficient, the use environment depreciation coefficient and the damaged depreciation coefficient, the future working capacity of the electric power material is realized, the working condition of the electric power material is monitored, and the grading early warning is timely carried out when the residual working capacity of the electric power material possibly influences the operation, the electric power material damage is carried out before the electric power material damage, the full utilization of the electric power material is realized, and the management effect of the electric power material is effectively improved.
Specifically, when the damaged breakage coefficient is adjusted, a third adjustment coefficient L3 is set for adjusting the damaged breakage coefficient k3 to k3', k3' = k3 × (1 + l3), where L3= (0.9 × T0-T)/T.
When the damaged breaking coefficient is adjusted, a third adjustment parameter is set according to the actual service life and the standard service life, so that the set value of the damaged breaking coefficient is adjusted, the adjustment range of the set value of the damaged breaking coefficient is related to the difference between the actual service life and the preset standard, when the difference between the actual service life and the preset standard is large, the adjustment range of the damaged breaking coefficient is large, when the difference between the actual service life and the preset standard is small, the adjustment range of the damaged breaking coefficient is small, the set of the damaged breaking coefficient is ensured to accord with the preset standard, the broken life calculated according to the normal use breaking coefficient, the use environment breaking coefficient and the damaged breaking coefficient is ensured to be accurate and reliable, the future working capacity of the electric power material is looked forward, the working operation condition of the electric power material is monitored, and grading early warning is timely performed when the residual working capacity of the electric power material possibly influences the operation of an electric power network, the material management operation is performed before the electric power material is damaged, and the full utilization of the electric power material is realized, and the management effect of the electric power material is effectively improved.
Referring to fig. 2, a schematic structural diagram of an intelligent power material data processing system in an intelligent power material data processing method based on hierarchical monitoring and early warning according to an embodiment of the present invention includes:
the monitoring module 1 is used for monitoring and collecting historical use data and actual use data of electric power materials; the service life calculating module 2 is used for calculating the residual service life rate of the electric power materials according to the preset standard service life, the service life breakage coefficient and the actual use data; the central control module 3 is used for setting a standard service life and a life loss coefficient according to historical use data, constructing a graded early warning monitoring signal according to the residual life rate and correcting the life loss coefficient; and the material allocation module 4 is used for allocating electric power materials according to the grading early warning monitoring signals, and the modules are in communication connection.
In the process of managing the electric power materials of the high-voltage power equipment, the specific implementation process of the intelligent electric power material data processing method based on the grading monitoring and early warning provided by the embodiment of the invention is as follows:
when the materials of the power cables in the high-voltage power equipment are managed, the monitoring module retrieves the historical use data of the power cables of the same type, the central control module sets the standard service life and the service life breaking coefficient of the power cables according to the historical use data, wherein the standard service life is 7300 days, when the service life breaking coefficient is set according to the historical use record of the power materials, the service environment breaking coefficient is respectively set according to various environment factors which reduce the service life of the power materials in the credible use environment indexes, the abnormal temperature environment breaking coefficient k21 of the abnormal temperature environment factor with the historical occurrence frequency of 156 is 0.05, the abnormal humidity environment breaking coefficient k22 of the abnormal humidity environment factor with the historical occurrence frequency of 83 is 0.03, damage factors are respectively set according to various damage causes of credible damage causes, the impact damage factor k31 of the impact damage cause with the historical occurrence number of 6 is 0.20, the electric shock damage factor k32 of the electric shock damage cause with the historical occurrence number of 2 is 0.37, and the normal use damage factor k1, k1= [ T0- (k 21 xW 10+ k22 xW 20+ … + k2n xWn 0) - (k 31 xD 10+ k32 xD 20+ … + k3m x Dm0 ]/T0= [7300- (0.05 x 156+0.03 x 83) - (0.20 x 6 x 7000 0.37 x 2) ]/T0= (7300-10.29-1.94)/7000.04 are set according to the standard service life 7300, the credible use duration 7000, each environmental damage factor and each damage factor. After the power cable is put into use, the monitoring module collects actual use data of the power cable such as the service life, the service environment humidity, the service environment temperature, the number of times of electric shock and the number of times of impact, the service life calculating module calculates the residual service life rate of the power cable according to preset standard service life, a life breaking coefficient and the actual use data, wherein when the broken service life Tu of the power material is calculated according to the actual use data and the life breaking coefficient, tu1 is the normal service breaking life, the service life is T =6000 days, tu1= k1 × T =1.04 × 6000=6240, tu2 is the depreciation life of the environmental factor, the frequency W1 of the occurrence of the abnormal temperature environmental factor is 225, the frequency W2 of the occurrence of the abnormal humidity environmental factor is 124, tu2= k21 × W1+ k22 × W2=0.05 × 225+0.03 × 124=14.97, tu3 is the depreciation life of the damage factor, the frequency D1 of the occurrence of the impact damage factor is 4, the frequency D2 of the occurrence of the electric shock damage factor is 5, tu3= k31 × D1+ k32 × D2=0.20 × 4+0.37 × 5=2.65, tu = Tu1+ Tu2+ Tu3=6240+14.97+2.65=6257.62, the remaining life ratio Q, Q = Q [ (T0-Tu =)/T0 ] = 100% = (7300-8978 × 8900 × 28.0 wt%; the method comprises the steps that a central control module constructs a graded early warning monitoring signal according to the residual life rate of a power cable, when the graded early warning signal is constructed according to the residual life rate of the power cable, the central control module sets a first-level alarm life rate of 30%, a second-level alarm life rate of 20% and a third-level alarm life rate of 10%, when the residual life rate is larger than 30%, the central control module constructs a zero-level monitoring early warning signal for the power cable, and the monitoring module continues to acquire actual use data of the power cable; when the residual life rate is more than or equal to 30% and more than 20%, the central control module constructs a primary monitoring early warning signal for the power cable, and the monitoring module monitors the normal use breaking life, the environmental factor breaking life and the damage factor breaking life in the actual use data of the power materials; when the 20% residual life rate is more than or equal to 10%, the central control module constructs a secondary monitoring early warning signal for the power cable, the life calculation module respectively calculates the normal use depreciation life, the environmental factor depreciation life and the proportion of the damaged factor depreciation life in the actual use data of the power cable in the depreciation life, constructs a monitoring material use signal when the normal use depreciation life proportion is maximum, constructs a reinforced material protection signal when the environmental factor depreciation life proportion is maximum, and constructs a material replacement signal when the damaged factor depreciation life proportion is maximum; when the residual service life rate is more than or equal to 10%, the central control module constructs a three-level monitoring early warning signal for the power cable, and the material allocation module performs emergency allocation and replacement on power materials; according to the data, the residual service life rate of the power cable is 14.28%, the central control module constructs a secondary monitoring early warning signal for the power cable, the service life calculation module respectively calculates the proportion of the normal service loss service life, the environmental factor loss service life and the damage factor loss service life in the actual service data of the power cable in the damaged service life, the proportion of the normal service loss service life is determined to be the maximum, a monitoring material service signal is constructed, and the actual service data of the power cable is monitored.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.

Claims (10)

1. An intelligent electric power material data processing method based on grading monitoring and early warning is characterized by comprising the following steps:
the method comprises the following steps that S1, the standard service life and the life breaking coefficient of the electric power materials are set according to historical use records of the electric power materials, wherein the life breaking coefficient comprises a normal use breaking coefficient, a use environment breaking coefficient and a damaged breaking coefficient;
s2, monitoring actual use data of the electric power materials, wherein the actual use data comprises use time, use environment indexes, damage reasons and damage times of the electric power materials, calculating the damaged life of the electric power materials according to the actual use data and the life damage coefficient, and calculating the residual life rate of the electric power materials according to the standard service life and the damaged life;
and S3, constructing a graded monitoring early warning signal according to the residual life rate of the electric power materials, managing the electric power materials according to the graded monitoring early warning signal, monitoring the working running state of the electric power materials to judge whether the life breaking coefficient meets a preset standard, and correcting the life breaking coefficient of the electric power materials when the life breaking coefficient does not meet the preset standard.
2. The intelligent electric power material data processing method based on graded monitoring and early warning as claimed in claim 1, wherein when the standard service life of the electric power material is set according to the historical usage record of the electric power material, the service life data in the historical usage record of the electric power material is screened, the mode of the service life data is calculated and set as credible life data, the average value of the calculated credible life data is set as the standard service life, and meanwhile, the historical usage record of the recorded credible life data is set as the credible usage record.
3. The intelligent electric power material data processing method based on graded monitoring and early warning as claimed in claim 2, characterized in that when a life depreciation coefficient is set according to a historical use record of electric power materials, credible use data in the credible use record of the electric power materials is analyzed, the credible use data comprises credible use duration, credible use environment index, credible damage reason and credible damage times, the use environment depreciation coefficient is respectively set according to n types of environment factors reducing the service life of the electric power materials in the credible use environment index, the class 1 environment depreciation coefficient of the class 1 environment factor with the historical occurrence times of W10 is k21, the class 2 environment depreciation coefficient of the class 2 environment factor with the historical occurrence times of W20 is k22, and so on, the nth type environment depreciation coefficient of the nth type environment factors with the historical occurrence frequency Wn0 is k2n, the damage depreciation coefficients are respectively set according to the m types of damage reasons of the credible damage reasons, the 1 st type damage coefficient of the 1 st type damage reason with the historical occurrence frequency D10 is k31, the 2 nd type damage coefficient of the 2 nd type damage reason with the historical occurrence frequency D20 is k32, and by analogy, the mth type damage coefficient of the mth type damage reason with the historical occurrence frequency Dm0 is k3m, the normal use depreciation coefficient k1 is set according to the standard service life T0, the credible use duration T0, the environment depreciation coefficient and the damage depreciation coefficient, and k1= [ T0- (k 21 xW 10+ k22 xW 20+ … + k2n xWn 0) - (k 31 xD 10+ k32 xD 20+ 3262 z3262 zdMxDm 0/T0) ].
4. The intelligent power material data processing method based on grading monitoring and early warning as claimed in claim 3, wherein Tu = Tu1+ Tu2+ Tu3 when the depreciated lifetime Tu of the power material is calculated according to the actual usage data and the lifetime depreciation coefficient, where Tu1 is the normal usage depreciation lifetime, tu1= k1 × t, t is the usage duration, tu2 is the environmental factor depreciation lifetime, tu2= k21 × W1+ k22 × W2+ … + k2n × Wn, W1 is the number of occurrences of the type 1 environmental factor, W2 is the number of occurrences of the type 2 environmental factor, and so on, wn is the number of occurrences of the type n environmental factor, tu3 is the depreciation lifetime of the damage factor, tu3= k31 × D1+ k32 × D2+ … + k3m × Dm, D1 is the number of occurrences of the type n environmental factor, D2 is the number of occurrences of the type 2, and so on.
5. The intelligent power material data processing method based on the grading monitoring and early warning as claimed in claim 4, wherein when the remaining life rate Q of the power material is calculated according to the standard service life and the damaged life, Q = [ (T0-Tu)/T0 ] x 100%, wherein T0 is the standard service life, the grading monitoring and early warning signal is constructed according to the remaining life rate of the power material, and when the grading monitoring and early warning signal is constructed according to the remaining life rate of the power material, a primary alarm life rate, a secondary alarm life rate and a tertiary alarm life rate are set, wherein the primary alarm life rate is greater than the secondary alarm life rate and is greater than the tertiary alarm life rate,
when the residual life rate is greater than the first-level alarm life rate, constructing a zero-level monitoring early warning signal for the electric power materials;
when the first-stage alarm life rate is greater than or equal to the residual life rate and greater than the second-stage alarm life rate, constructing a first-stage monitoring early warning signal for the electric power materials;
when the secondary alarm life rate is greater than or equal to the residual life rate and is greater than the tertiary alarm life rate, constructing a secondary monitoring early warning signal for the electric power materials;
and when the third-level alarm life rate is greater than or equal to the residual life rate, constructing a third-level monitoring early warning signal for the electric power materials.
6. The intelligent electric power material data processing method based on the grading monitoring and early warning as claimed in claim 5, wherein when the electric power material is managed according to the grading monitoring and early warning signal,
if a zero-level monitoring early warning signal is constructed for the electric power materials, acquiring actual use data of the electric power materials;
if a primary monitoring early warning signal is constructed for the electric power materials, monitoring the normal use depreciation life, the environmental factor depreciation life and the damage factor depreciation life in the actual use data of the electric power materials;
if a secondary monitoring early warning signal is constructed for the electric power materials, calculating the normal use depreciation life, the environmental factor depreciation life and the proportion of the damaged factor depreciation life in the actual use data of the electric power materials in the depreciation life respectively, constructing a monitoring material use signal when the normal use depreciation life proportion is maximum, constructing a reinforced material protection signal when the environmental factor depreciation life proportion is maximum, and constructing a material replacement signal when the damaged factor depreciation life proportion is maximum;
if a three-level monitoring early warning signal is constructed for the electric power materials, the electric power materials are replaced emergently.
7. The intelligent electric power material data processing method based on grading monitoring and early warning as claimed in claim 6, wherein when judging whether the life break coefficient meets the preset standard according to the working operation state of the electric power material, judging whether the life break coefficient meets the preset standard according to the actual service life and the standard service life of the electric power material,
when the actual service life is more than or equal to 0.9 multiplied by the standard service life, judging that the life loss coefficient meets the preset standard;
when the actual service life is less than 0.9 multiplied by the standard service life, the service life loss coefficient is judged not to accord with the preset standard, the normal service loss life, the environmental factor loss life and the proportion of the damaged factor loss life in the actual service life of the power material are respectively calculated, the normal service loss coefficient is adjusted when the proportion of the normal service loss life is maximum, the service environment loss coefficient is adjusted when the proportion of the environmental factor loss life is maximum, and the damaged factor loss coefficient is adjusted when the proportion of the damaged factor loss life is maximum.
8. The intelligent power material data processing method based on graded monitoring and early warning as claimed in claim 7, wherein when the normal usage breakage coefficient is adjusted, a first adjustment coefficient L1 is set for adjusting the normal usage breakage coefficient k1 to k1', k1' = k1 x (1 + L1), where L1= (0.9 × T0-T)/T, and T is the actual service life.
9. The intelligent power material data processing method based on graded monitoring and early warning as claimed in claim 8, wherein when the usage environment depreciation coefficient is adjusted, a second adjustment coefficient L2 is set for adjusting the usage environment depreciation coefficient k2 to k2', k2' = k2 x (1 + L2), wherein L2= (0.9 × T0-T)/T.
10. The intelligent power material data processing method based on graded monitoring and early warning as claimed in claim 9, wherein when the damaged breakage coefficient is adjusted, a third adjustment coefficient L3 is set for adjusting the damaged breakage coefficient k3 to k3', k3' = k3 x (1 + l3), wherein L3= (0.9 × T0-T)/T.
CN202211328480.5A 2022-10-26 2022-10-26 Intelligent electric power material data processing method based on grading monitoring and early warning Pending CN115619098A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202211328480.5A CN115619098A (en) 2022-10-26 2022-10-26 Intelligent electric power material data processing method based on grading monitoring and early warning

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202211328480.5A CN115619098A (en) 2022-10-26 2022-10-26 Intelligent electric power material data processing method based on grading monitoring and early warning

Publications (1)

Publication Number Publication Date
CN115619098A true CN115619098A (en) 2023-01-17

Family

ID=84876928

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202211328480.5A Pending CN115619098A (en) 2022-10-26 2022-10-26 Intelligent electric power material data processing method based on grading monitoring and early warning

Country Status (1)

Country Link
CN (1) CN115619098A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117528287A (en) * 2023-09-11 2024-02-06 国网浙江省电力有限公司物资分公司 Hierarchical early warning system based on electric power material data monitoring

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080059082A1 (en) * 2004-07-02 2008-03-06 Australasian Steel Products Pty Ltd Hose Assembly Analysis Apparatus and Methods
CN109255524A (en) * 2018-08-16 2019-01-22 广西电网有限责任公司电力科学研究院 A kind of measuring equipment data analyzing evaluation method and system
CN110443413A (en) * 2019-07-23 2019-11-12 华南理工大学 The construction method of Power Material demand forecast system and Power Material demand model
US20190392360A1 (en) * 2017-04-04 2019-12-26 Korea Electric Power Corporation Power transformer asset management device and method therefor
CN112379198A (en) * 2020-11-05 2021-02-19 华润电力技术研究院有限公司 Method and system for evaluating residual life of equipment
CN114488996A (en) * 2021-12-27 2022-05-13 山东浪潮工业互联网产业股份有限公司 Equipment health monitoring and early warning method and system

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080059082A1 (en) * 2004-07-02 2008-03-06 Australasian Steel Products Pty Ltd Hose Assembly Analysis Apparatus and Methods
US20190392360A1 (en) * 2017-04-04 2019-12-26 Korea Electric Power Corporation Power transformer asset management device and method therefor
CN109255524A (en) * 2018-08-16 2019-01-22 广西电网有限责任公司电力科学研究院 A kind of measuring equipment data analyzing evaluation method and system
CN110443413A (en) * 2019-07-23 2019-11-12 华南理工大学 The construction method of Power Material demand forecast system and Power Material demand model
CN112379198A (en) * 2020-11-05 2021-02-19 华润电力技术研究院有限公司 Method and system for evaluating residual life of equipment
CN114488996A (en) * 2021-12-27 2022-05-13 山东浪潮工业互联网产业股份有限公司 Equipment health monitoring and early warning method and system

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117528287A (en) * 2023-09-11 2024-02-06 国网浙江省电力有限公司物资分公司 Hierarchical early warning system based on electric power material data monitoring
CN117528287B (en) * 2023-09-11 2024-05-14 国网浙江省电力有限公司物资分公司 Hierarchical early warning system based on electric power material data monitoring

Similar Documents

Publication Publication Date Title
CN111010084B (en) Photovoltaic power station intelligent monitoring analysis platform and method
CN106655522B (en) A kind of main station system suitable for electric grid secondary equipment operation management
CN105245185B (en) A kind of area distribution formula photovoltaic fault diagnosis system and method for accessing power distribution network
CN116014741B (en) Flexible controller and power distribution network operation adaptation system and method based on data processing
CN105678467A (en) Regulation and control integrated data analysis and aid decision making system and method under ultrahigh-voltage alternating current and direct current networking
CN114928171A (en) Electric power secondary equipment comprehensive monitoring system based on Internet of things
CN110363326B (en) Power grid 110kV line short-term load curve prediction method
CN110569997A (en) charging station operation maintenance method based on multi-dimensional data system
CN115619098A (en) Intelligent electric power material data processing method based on grading monitoring and early warning
CN112255560A (en) Battery core health degree prediction method
CN103559580A (en) Power distribution network analysis system and method
CN115603459A (en) Digital twin technology-based power distribution network key station monitoring method and system
CN116820014A (en) Intelligent monitoring and early warning method and system for traffic electromechanical equipment
CN117614137A (en) Power distribution network optimization system based on multi-source data fusion
CN116308306B (en) New energy station intelligent management system and method based on 5G
CN115238957A (en) Early warning method and system for power transmission line corridor
CN114693186A (en) Method and system for analyzing and processing multiple fault events of differentiated combined type transformer substation
CN114696467A (en) Method and system for analyzing and processing fault tripping event of high-voltage transmission long line
CN115224684A (en) Intelligent power distribution network risk state identification method and system based on immune hazard theory
CN114236306A (en) Distribution line interval insulation degradation degree evaluation method and system based on distribution main station
CN112862249A (en) Lean management method and system for intelligent power distribution equipment
CN112039436B (en) Method for analyzing power station state by integrating working state and real-time data of photovoltaic inverter
CN115374965A (en) Equipment maintenance method based on power dispatching maintenance background maintenance data
CN117596209B (en) High-low voltage distribution environment operation parameter real-time supervision early warning system
CN116316586B (en) Method for tracing power jump in power system by adopting jump analysis method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20230117

RJ01 Rejection of invention patent application after publication